<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.182100.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Determining The Prevalence of Low Bone Health Conditions and Related Factors Using Multisite Quantitative Ultrasound Technique in Young Indian Women: An Epidemiological Community-Based Study</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Chawla</surname>
                        <given-names>Jasmine Kaur</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-8281-6166</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Shenoy</surname>
                        <given-names>Shweta</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Gupta</surname>
                        <given-names>Swati</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sandhu</surname>
                        <given-names>Jaspal Singh</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Hazari</surname>
                        <given-names>Animesh</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-3936-5029</uri>
                    <xref ref-type="corresp" rid="c2">b</xref>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Kandakurti</surname>
                        <given-names>Praveen Kumar</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-2669-4488</uri>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>School Of Allied Health Sciences, Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, India</aff>
                <aff id="a2">
                    <label>2</label>Faculty of Sports Medicine and Physiotherapy, Guru Nanak Dev University, Amritsar, Punjab, India</aff>
                <aff id="a3">
                    <label>3</label>Nutrition, Smt. Parvati Devi Hospital, Amritsar, Punjab, India</aff>
                <aff id="a4">
                    <label>4</label>College of Health Sciences, Gulf Medical University, Ajman, Ajman, United Arab Emirates</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:jasminekaur.sahs@mriu.edu.in">jasminekaur.sahs@mriu.edu.in</email>
                </corresp>
                <corresp id="c2">
                    <label>b</label>
                    <email xlink:href="mailto:dr.animesh@gmu.ac.ae">dr.animesh@gmu.ac.ae</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>4</day>
                <month>6</month>
                <year>2026</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2026</year>
            </pub-date>
            <volume>15</volume>
            <elocation-id>872</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>19</day>
                    <month>5</month>
                    <year>2026</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Chawla JK et al.</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/15-872/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>Premenopausal osteoporosis is a condition where increased bone loss is seen in young women. Dietary Nutrition, lack of physical activity and other factors related to women health can be related to this condition.</p>
                </sec>
                <sec>
                    <title>Objective</title>
                    <p>The main objective of the study was to find the prevalence and related risk factors of low bone mineral density conditions in Indian women aged 20&#x2013;40&#x00a0;years.</p>
                </sec>
                <sec>
                    <title>Methodology</title>
                    <p>1176 women were enrolled from Amritsar. Women were divided in three categories. Dietary nutrition was assessed using 24-hour dietary questionnaire and Bone health status was measured using a multisite quantitative ultrasound bone densitometer by Omnisense targeted over two sites: radius and tibia.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>There were 1,176 women in a cohort of 20&#x2013;40&#x00a0;years of age. The prevalence of low bone mineral density (BMD), corresponding to z -score&#x00a0;&lt;&#x00a0;&#x2212;2.0 to z -score-3.0 was 22.6, and the prevalence of very low BMD (z -score-3.0- z -score) was 8.1. BMD was lower or very low among women who had a later age of menarche and those with a history of previous pregnancies, with low calcium intake, less sun exposure, and managed to perceive increased stress. Delayed menarche (adjusted odds ratio&#x00a0;=&#x00a0;4.73; 95% confidence interval&#x00a0;=&#x00a0;2.06&#x2013;10.82), hypothyroid status (adjusted odds ratio&#x00a0;=&#x00a0;3.84; 95% confidence interval&#x00a0;=&#x00a0;0.89&#x2013;16.49), and limited sun exposure (adjusted odds ratio&#x00a0;=&#x00a0;2.87; 95% confidence interval&#x00a0;=&#x00a0;1.61&#x2013;5.12) were found to be statistically significant predictors by multinomial logistic regression.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>There is a significant percentage of young Indian females with low bone mineral density (BMD). Skeletal health risks can be mitigated through early detection through community-based screening and prior intentional lifestyle modifications.</p>
                </sec>
                <sec>
                    <title>Clinical Trial Registration Status</title>
                    <p>The study has been registered in the Clinical Trial Registry of India, CTRI/2015/10/006240.</p>
                    <p>The manuscript is available as a preprint on the Research Square platform.
                        <sup>
                            <xref ref-type="bibr" rid="ref37">37</xref>
                        </sup>
                    </p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>low bone mineral density</kwd>
                <kwd>Indian women</kwd>
                <kwd>nutrition</kwd>
                <kwd>multi-site quantitative ultrasound.</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>Department of Science and Technology, Ministry of Science and Technology, New Delhi-110026.</funding-source>
                    <award-id>DSTRefno:SSD/WD/012/2010/GNDU.</award-id>
                </award-group>
                <funding-statement>The study results are a part of a major research community-based project entitled &#x201c;Nutrition and Bone Health in Punjab: A Community Study,&#x201d; funded by the Department of Science and Technology, Ministry of Science and Technology, New Delhi-110026. DST Ref no: SSD/WD/012/2010/GNDU.</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec7" sec-type="intro">
            <title>Introduction</title>
            <p>Osteoporosis is recognised as a disease of mainly postmenopausal women, but decreased bone mineral density (BMD) and rapid bone loss can also occur in young adulthood, a disease often referred to as premenopausal osteoporosis.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> Attainment of peak bone mass in early adulthood represents a key factor in subsequent fracture risk, and inadequate skeletal development at this critical period could be a risk factor for osteoporosis later in life.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> A constellation of biological and lifestyle factors, including poor nutrition, sedentary behaviour, endocrine dysregulation, menstrual irregularities, gestational influences, and inadequate sun exposure, has been implicated in the diminution of BMD among young women.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> In clinical practice, a Z-score of &#x2212;2.0 or lower is generally considered low for pre-menopausal women, especially when used in combination with other risk determinants.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> Recent epidemiological studies show that low BMD is becoming more common in young women, especially in Asian populations; the prevalence of reduced BMD in young Asian women between the ages of 20&#x2013;40&#x00a0;years may already reach 15&#x2013;30 percent.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> These findings highlight the increasing public health concern of early skeletal health evaluation and the need for the identification of modifiable determinants during the peak bone building period.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> Quantitative ultrasound (QUS) has become a pragmatic, cost-effective and radiation-free modality for community-based skeletal screening, particularly in resource-constrained settings.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> Multisite instruments, for instance, the Omnisense, assess bone properties at peripheral skeletal sites and show reasonable concordance with dual-energy X-ray absorptiometry in identifying persons with decreased BMD.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>,
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> Although QUS is not a replacement for diagnostic imaging, it is sufficiently portable and feasible to be used for large-scale epidemiological studies and early risk identification.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>,
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> Moreover, community and cohort data from South Asia today show that women at reproductive age often have low BMD with the associated high rate of vitamin D insufficiency and inadequate calcium intake, which may impair peak bone mass and increase the risk of long-term fracture.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> Consequently, multisite QUS has been gradually used in field-based epidemiological screening, due to its portability, affordability, and acceptable concordance with conventional densitometric methods, but has been defined as a screening rather than a diagnostic tool.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> In spite of the growing body of evidence from around the world, community-based studies on low BMD in young Indian women are still limited, particularly those that incorporate nutritional, reproductive, lifestyle and psycho-social determinants in a coherent analytical framework.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>,
                    <xref ref-type="bibr" rid="ref10">10</xref>,
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> Existing research in India has mainly focused on postmenopausal cohorts or reference BMD databases, without comprehensive risk factor evaluations in younger women.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>,
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
            </p>
            <p>Therefore, the present study was conducted to determine the prevalence of low bone mineral density and identify its associated risk factors among Indian women aged 20&#x2013;40&#x00a0;years using multisite quantitative ultrasound in a community-based cross-sectional design.</p>
        </sec>
        <sec id="sec8">
            <title>Materials and methods</title>
            <sec id="sec9">
                <title>Study settings, design, and sampling</title>
                <p>The study was conducted at Guru Nanak Dev University, Amritsar, India. The current study design was population-based and cross-sectional in nature. The study started on October 15
                    <sup>th</sup>, 2015, and was completed on July 17
                    <sup>th</sup>, 2025. A cluster randomized sampling method was adopted, using the probabilities proportional to size (PPS) criteria to collect samples. The studied sample population comprised both rural and urban women of different socio-economic categories, belonging to the age group of 20&#x2013;40&#x00a0;years.</p>
            </sec>
            <sec id="sec10">
                <title>Ethical approval, consent, and registration</title>
                <p>The study was approved by the Institutional Ethics Committee, Faculty of Sports Medicine and Physiotherapy, Guru Nanak Dev University, Amritsar, India (No-1319/SMP). The protocol was carried out in accordance with the relevant guidelines and regulations from the &#x201c;Declaration of Helsinki&#x201d;. A written informed consent explaining the purpose and procedure of the study, translated both in Hindi and Punjabi, was obtained from each participant. The consent for the study was drafted as per the Indian Council of Medical Research (ICMR) guidelines. This study was registered in the Clinical Trial Registry of India (CTRI/2015/10/006240) on October 6
                    <sup>th</sup>, 2015.</p>
            </sec>
            <sec id="sec11">
                <title>Sample size</title>
                <p>The sample size was calculated to estimate the prevalence of low bone mineral density (BMD) in young Indian women. Based on previous Indian studies indicating a prevalence of approximately 10%, and using a 95% confidence level with a relative precision of &#x00b1;25%, the initial required sample was 540. Considering that data were collected across nearly 50 clusters, a design effect of 2.0 was applied to account for potential intra-cluster correlation, increasing the target to 1,080 participants. Ultimately, 1,176 women were recruited, exceeding the minimum requirement. This extended recruitment ensured adequate representation across age groups and geographic clusters, enhanced the precision of prevalence estimates, and strengthened the statistical power and generalizability of the findings.</p>
            </sec>
            <sec id="sec12">
                <title>Inclusion, exclusion criteria</title>
                <p>Physically able women aged 20&#x2013;40&#x00a0;years were included in the study. Pregnant and lactating women were excluded from the study. Women with a minimum gap of 6&#x2013;9&#x00a0;months from the last delivery and lactation period were part of the study. Those who consented to participate were enrolled in the study.</p>
            </sec>
            <sec id="sec13">
                <title>Questionnaires and interview procedure</title>
                <p>The study methodology was precisely carried out as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Physical activity, a 24-hour dietary and self-designed questionnaire encompassing the anthropometric and socio-economic strata were collected. The self-designed questionnaire contained information related to factors that affect bone health.
                    <sup>
                        <xref ref-type="bibr" rid="ref11">11</xref>
                    </sup> The questionnaire contained medical histories which included the questions on whether the participant was currently experiencing the following conditions: hyperparathyroidism, hypothyroidism, renal disease, diabetes mellitus, rheumatoid arthritis, eating disorders, medications that elevate bone density, history of back pain or not, and the question about whether the participant is or was undergoing glucocorticoids and/or thyroid hormone treatment. Another area explored by the interviewer was the obstetric and gynecological history of the participant, which included age at menarche and menopause (assuming it occurred), incidence of amenorrhea, number of offspring and pregnancies, length of breastfeeding, and whether the participant had undergone any surgical events or procedures, including oophorectomy or hysterectomy. There was also an investigation into the use of oral contraceptive pills and/or hormone replacement therapy. The next five questionnaires were used to collect information on socioeconomic status, family occupation, living expenditure, lifelong occupation, and educational attainment. Data on recreational activities and weight-bearing exercises were documented using a validated and translated Punjabi International Physical Activity Questionnaire (IPAQ). Perceived stress was measured using a local translation of a validated and translated Cohen Perceived Stress Scale (PSS-10) using the Punjabi local language. Each respondent was asked to give the time they spent under the sun every day, and a sun-exposure index was calculated according to the approach of Barger-Lux and Heaney (2002).
                    <sup>
                        <xref ref-type="bibr" rid="ref3">3</xref>
                    </sup> The respondents also indicated their eating patterns through the 24-hour dietary recall technique.
                    <sup>
                        <xref ref-type="bibr" rid="ref11">11</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec14">
                <title>Outcome variable and measures: bone health quantification &amp; quantitative ultrasound (qus) measurement protocol</title>
                <p>Bone health was assessed using a portable multisite quantitative ultrasound (QUS) device, the Sunlight Omnisense&#x2122; 7000S (BeamMed Ltd., Israel). Speed of Sound (SOS) measurements were taken at two peripheral skeletal sites, the distal one-third radius of the non-dominant arm and the mid-shaft tibia, after procedures to match those described by Shenoy et al. (2017).
                    <sup>
                        <xref ref-type="bibr" rid="ref11">11</xref>
                    </sup> To ensure accuracy, measurements reproducible within a range of &#x2212;2% of the expected calibration range were accepted daily to calibrate the device. The participants were sitting in a comfortable position as the palpation of the anatomical landmarks was carried out manually. Three successive readings were taken at each site, and the average of the three readings was taken to obtain the value of this mean or the average of the three values as near to the true value as possible. This multisite QUS protocol presented a viable and sound method of characterizing bone qualities in young adult women.
                    <sup>
                        <xref ref-type="bibr" rid="ref11">11</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec15">
                <title>Operator training and reliability</title>
                <p>Two physiotherapists, who had received structured training in the presence of an experienced supervisor, were used to carry out all QUS measurements. Their competence was first put to a pilot sample of 30 people. Inter-operator reliability was high, and the coefficient of variation was 1.8% at the radius and 2.1% at the tibia. Only those operators who passed a training stage and received more than 95 percent agreement in the training phase could carry out measurements during data collection to ensure consistency and accuracy.</p>
            </sec>
            <sec id="sec16">
                <title>Z-Score classification</title>
                <p>The device automatically produced Z-scores based on sex- and age-specific reference data based on several populations of Asians. In line with the recommendations of the International Society of Clinical Densitometry (ISCD), a Z-score less than &#x2212;2.0 was considered as low bone mineral density, whereas a Z-score below &#x2212;3.0 was regarded as very low bone mineral density. The reason behind the choice of these cut-offs is to enhance the sensitivity of screening in women of the target age group of the present study, i.e., between 20 and 40&#x00a0;years.</p>
            </sec>
            <sec id="sec17">
                <title>Data management and quality control</title>
                <p>Data was collected with a pre-established quality-control protocol that included daily checks of calibration, monitoring of signal quality indicators, and verification of the correct positioning of the anatomy during each scan. The entire data was entered in a two-entry procedure to reduce transcription errors. An automated check was used to find outliers, incomplete entries, or inconsistent responses. Records where anthropometric, QUS, or questionnaire data were missing were categorized as missing and were not included in statistical analyses.</p>
            </sec>
            <sec id="sec18">
                <title>Statistical analysis</title>
                <p>The descriptive statistics in the study have been evaluated using the exact binomial method. For the multinomial logistic regression analysis, bone mineral density (BMD) was divided into three categories based on z-score values: (1) normal BMD (z-score&#x00a0;&#x2265;&#x00a0;&#x2212;2.0), (2) low BMD (z-score between &#x2212;2.0 and&#x00a0;&#x2212;&#x00a0;3.0), and (3) very low BMD (z-score&#x00a0;&#x2264;&#x00a0;&#x2212;3.0). These thresholds are aligned with the recommendations of the International Society of Clinical Densitometry (ISCD) for premenopausal women and have been widely used in population-based studies to assess skeletal risk in younger adults. Categorizing BMD in this way allowed us to capture the gradual decline in bone health while ensuring sufficient sample sizes in each group to produce robust and meaningful statistical results. To analyze the relationship of categorical variables (PSS score, obstetrics and gynecological, categories of socio-economic status, physical activity level, nutrition variables, medical history, and anthropometric characteristics) with low bone mineral density, the chi-square test with Bonferroni&#x2019;s correction was used. Bonferroni&#x2019;s correction, p-value &lt;0.025, was considered significant. To evaluate the baseline characteristics among different groups, one-way ANOVA with Tukey&#x2019;s post hoc adjustment was used. Additionally, one-way ANOVA was used to draw a comparative analysis of the average mean of all nutrient variables among three groups. The Levene&#x2019;s test was applied to check the homogeneity of variances for all variables across groups; when the test was significant, the Welch correction was used. Post-hoc comparisons were conducted using Tukey&#x2019;s test when variances were equal, and Dunnett T3 when they were unequal. In addition, a multinomial logistic regression analysis using the force-entry method was performed to examine the independent association of various factors with reduced bone mineral density, with the normal BMD group serving as the reference category. To minimize model overfitting, the predictors entered into the model were selected based on biological relevance, bivariate correlations with p&#x00a0;&lt;&#x00a0;0.20, and prior evidence from young female cohorts. The final model included age at menarche, gravidity, hypothyroid status, perceived stress, socioeconomic status, daily sun exposure, and dietary calcium intake. Model fit was evaluated using the Hosmer&#x2013;Lemeshow test, and multicollinearity was assessed through variance inflation factors (VIF&#x00a0;&lt;&#x00a0;2.5 considered acceptable). To reduce the likelihood of type I error, multiple comparisons were adjusted using the Bonferroni correction. Adjusted odds ratios (ORs) with 95% confidence intervals were reported, and a p-value &lt;0.05 was considered statistically significant. All analyses were carried out using IBM SPSS Statistics version 26.0.</p>
            </sec>
        </sec>
        <sec id="sec19" sec-type="results">
            <title>Results</title>
            <p>A total of 1,350 women were screened, of whom 1,176 participants met the inclusion criteria and were retained in the final analysis to find the prevalence of low bone mineral density conditions in the age group of 20&#x2013;40-year-old women in the population of Punjab (
                <xref ref-type="fig" rid="f1">
Figure 1</xref>).</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>
Figure 1. </label>
                <caption>
                    <title>CONSORT flowchart.</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/201005/a08b8298-64c8-4ff6-be3e-f7b7a6d4cf11_figure1.gif"/>
            </fig>
            <p>For statistical analysis, the participants were categorized into three groups: normal (z score&#x00a0;&#x2265;&#x00a0;&#x2212;2.0), z score&#x00a0;&lt;&#x00a0;&#x2212;2.0 and&#x00a0;&#x2265;&#x00a0;&#x2212;3.0, and z score&#x00a0;&lt;&#x00a0;&#x2212;3.0.</p>
            <p>
                <xref ref-type="table" rid="T1">
Table 1</xref> shows the baseline characteristics of the women participants. Both z-score categories had similar mean ages (~33&#x00a0;years). The mean values of anthropometric covariates (weight, waist circumference, waist: hip ratio) were higher in women having a z-score&#x00a0;&lt;&#x00a0;&#x2212;3.0. Further, in terms of obstetrics and gynecological covariates, the average menarche age was almost similar (~13&#x00a0;years) in all three groups. Significantly greater number of pregnancies (3.94), children (2.39), and prolonged duration of breastfeeding (14.41&#x00a0;months) was reported from women belonging to the z-score below &#x2212;3.0 category in comparison to the normal group. In addition, significantly low mean physical activity level (488.41 METS-min/week), low sun exposure index (0.83), and high perceived stress (PSS) (25.67) were reported from women in the category of z score below &#x2212;3.0 (p&#x00a0;&lt;&#x00a0;0.025). Moreover, women in the category of z score below &#x2212;3.0 had significantly low mean SOS values of radius (3743.65&#x00a0;m/s) and tibia (3903.18&#x00a0;m/s), and low SES when compared to the mean values of the normal group (p&#x00a0;&lt;&#x00a0;0.025).</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>
Table 1. </label>
                <caption>
                    <title>Comparison of baseline characteristics of normal, osteopenic and osteoporotic participants in the age category of 20&#x2013;40&#x00a0;years old women participants.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">Normal (1) N&#x00a0;=&#x00a0;815 Mean  (SD)</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">Low BMD (2)  (z score&#x00a0;&lt;&#x00a0;&#x2212;2 &amp; &#x2265;3) N&#x00a0;=&#x00a0;266 Mean  (SD)</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">Very low BMD (3)  (z score&#x00a0;&lt;&#x00a0;&#x2212;3) N&#x00a0;=&#x00a0;95 Mean  (SD)</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">One way-ANOVA 
 (Post hoc Tukey&#x2019;s test)</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">p value (1 vs 2)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">p value (1 vs 3)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
Age (years)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">31.25 (6.17)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33.23 (5.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33.41 (6.2)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.008*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Weight (kg)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">61.02 (11.63)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">63.29 (13.46)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">64 (13.38)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.008*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.02*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Height (cm)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">157.63 (5.59)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">157.96 (4.89)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">156.92 (5.76)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.024*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.064</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>BMI (kg/m</bold>
                                <sup>

                                    <bold>2</bold>
                                </sup>
                                <bold>)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">24.58 (4.64)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25.37 (5.35)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25.98 (5.2)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.053</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.021*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Waist circumference (cm)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">81.06 (12.18)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">83.63 (14.59)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">83.95 (13.51)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.004*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.156</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Hip circumference (cm)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">92.82 (11.85)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">97.09 (14.38)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">95.42 (12.34)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.125</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Waist hip ratio</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.88 (0.31)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.87 (0.15)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.88 (0.1)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.791</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.971</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Wrist circumference (cm)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.55 (1.11)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.44 (1.38)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.43 (1.35)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.414</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.996</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Menarche age (years)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12.69 (1.16)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14.98 (1.11)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15.02 (1.19)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Number of pregnancies</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.06 (1.43)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.91 (1.91)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.94 (2.26)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Number of children</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.73 (1.13)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.05 (1.31)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.39 (1.41)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.001*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Breast-feed (months)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13.02 (9.97)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14.41 (8.99)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14.57 (9.43)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.064</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.386</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Physical activity  (METS-min/week)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">829.98 (286.05)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">535.05 (38.74)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">488.41 (59.36)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Sun exposure index</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.25 (0.44)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.99 (0.26)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.83 (0.2)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Perceived stress score  (PSS)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19.52 (5.6)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23.96 (3.85)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25.67 (4.2)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Socio economic status  (SES)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">35.3 (15.81)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27.87 (13.54)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">22.87 (11.76)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Z score radius</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2212;0.67 (1.31)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2212;2.6 (0.97)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2212;3.85 (1.2)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Z score tibia</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.44 (1.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2212;2.2 (0.84)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2212;3.02 (0.73)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>SOS radius</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4082.51 (142.45)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3903.18 (140.22)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3743.65 (133.87)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>SOS tibia</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3955.75 (137.02)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3730.16 (117.31)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3574.23 (103.7)</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                            <td align="char" char="." colspan="1" rowspan="1" valign="top">0.000*</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Note: BMD&#x00a0;=&#x00a0;bone mineral density; BMI&#x00a0;=&#x00a0;body mass index; MET&#x00a0;=&#x00a0;metabolic equivalent of task; SOS&#x00a0;=&#x00a0;speed of sound; SD&#x00a0;=&#x00a0;standard deviation. p&#x00a0;&lt;&#x00a0;0.025* is statistically significant.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>The results in 
                <xref ref-type="table" rid="T2">
Table 2</xref> revealed that 83.9% of the participants had high waist circumference. 32.48% of the women from the total sample population had a complaint of low back pain. Out of 1176 women studied, 13 women had undergone the oophorectomy procedure; of them, 53.84% of the women had a z-score below &#x2212;3.0. No woman had reported having undergone hormonal therapy. Only 0.5% of the women mentioned the history of osteoporosis as their medical history. 7.57% of the women reported rheumatoid arthritis as their medical history; of them, 71.15% of the women had z scores less than &#x2212;2.0. 27.72% of the total sample population reported having more than 3 children, of which 41.71% of the women had a z-score&#x00a0;&lt;&#x00a0;&#x2212;2.0. Further, 9.27% of the women surveyed reported having consumed calcium supplements (minimum 2&#x00a0;months continuously); of them, 77.98% were in the normal category (Table-2).</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>
Table 2. </label>
                <caption>
                    <title>Frequency distribution (by percentage) of anthropometry, medical, obstetrics and gynecological covariates of 20&#x2013;40&#x00a0;years old adult women participants.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Categories</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Normal (1) N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Low BMD (2) (z score&#x00a0;&lt;&#x00a0;&#x2212;2 &amp;-&#x00a0;&#x2265;&#x00a0;3) N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Very low BMD (3) (z score&#x00a0;&lt;&#x00a0;&#x2212;3) N (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Chi square p value 1 vs 2</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Chi square p value 1 vs 3</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>BMI (kg/m2)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;23</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">658 (55.95)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">479 (72.79)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">137 (20.80)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">42 (6.38)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">4.32, p&#x00a0;&lt;&#x00a0;0.05</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">7.32, p&#x00a0;&lt;&#x00a0;0.001*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&gt;23</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">518 (44.04)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">336 (64.86)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">129 (24.90)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">53 (10.23)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Waist circumference  (WC) (cm)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;80 non obese</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">189 (16.07)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">102 (53.96)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">53 (28.04)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">34 (17.91)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.0028*</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">&lt;0.0001*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&gt;80 obese</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">987 (83.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">713 (72.23)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">213 (21.58)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">61 (6.18)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Waist hip ratio  (WHR)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;0.81 non obese</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">222 (18.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">146 (65.76)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">58 (26.13)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18 (8.11)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.167</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.434</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&gt;0.81 obese</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">954 (81.12)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">669 (70.12)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">208 (21.80)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">77 (8.07)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="top">
                                <bold>Wrist circumference  (WrC) (cm)</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Small</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">38 (3.23)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">28 (73.68)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8 (21.05)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2 (5.26)</td>
                            <td align="left" colspan="1" rowspan="3" valign="top">0.76, p&#x00a0;&gt;&#x00a0;0.05</td>
                            <td align="left" colspan="1" rowspan="3" valign="top">0.5, p&#x00a0;&gt;&#x00a0;0.05*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Medium</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">31 (2.63)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20 (64.51)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9 (29.03)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2 (6.45)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Large</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1107 (94.13)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">767 (69.28)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">249 (22.49)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">91 (8.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Marital status</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Married</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">970 (82.48)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">657 (67.73)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">230 (23.71)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">83 (87.37)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.009*</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.109</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Unmarried</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">206 (17.51)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">158 (76.69)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">36 (17.475)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12 (12.63)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Back pain</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">382 (32.48)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">253 (66.23)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">97 (25.39)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">32 (8.37)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.65</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.1001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">794 (67.52)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">562 (70.7)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">169 (21.28)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">63 (7.93)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Oophorectomy</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13 (1.105)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1 (7.69)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5 (38.46)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7 (53.84)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.168</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">&lt;0.001*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1163 (98.89)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">814 (69.22)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">261 (22.44)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">88 (7.48)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Amenorrhea</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15 (1.27)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2 (13.33)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12 (80)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1 (6.67)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.19</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1161 (98.72)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">813 (70.025)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">254 (21.87)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">94 (8.09)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Hormone replacement therapy</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1176 (100)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">815 (69.30)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">266 (22.61)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">95 (8.07)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Family history of Osteoporosis</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6 (0.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2 (33.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3 (50)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1 (16.67)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.16</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.06</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1170 (99.5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">813 (69.48)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">263 (22.47)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">94 (8.03)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>History of any fracture</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">125 (10.63)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">53 (42.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">72 (57.6)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">-</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">-</td>
                        </tr>
                        <tr>
                            <td colspan="1" rowspan="1"/>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1051 (89.37)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">815 (77.54)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">213 (20.27)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23 (2.19)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Rheumatoid arthritis</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">89 (7.57)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">52 (4.42)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23 (44.23)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14 (26.92)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.057</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">&lt;0.0001*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1087 (92.43)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1124 (95.57)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">792 (70.46)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">252 (22.41)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Number of children</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">850 (72.27)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">625 (73.52)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">177 (20.82)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">48 (5.64)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">&lt;0.0001*</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">&lt;0.0001*</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&gt;3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">326 (27.72)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">190 (58.28)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">89 (27.300)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">47 (14.41)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>Calcium supplement</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">109 (9.27)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">85 (77.98)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">17 (15.59)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7 (6.42)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.05</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.34</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1067 (90.73)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">730 (68.41)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">249 (23.33)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">88 (8.24)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Note: BMD categories were defined as Normal  (Z&#x00a0;&gt;&#x00a0;&#x2212;2.0), Low BMD  (Z&#x00a0;&#x2212;&#x00a0;2.0 to &#x2212;3.0), and Very-Low BMD  (Z&#x00a0;&lt;&#x00a0;&#x2212;3.0). WC&#x00a0;&gt;&#x00a0;80&#x00a0;cm and WHR&#x00a0;&gt;&#x00a0;0.81 were classified as central obesity. Group comparisons were performed using &#x03c7;
                        <sup>2</sup> tests. &#x201c;&#x2013;&#x201d; indicates statistical comparison could not be conducted because of sparse or zero-frequency cells. Significant at p&#x00a0;&lt;&#x00a0;0.025* after Bonferroni correction.</p>
                </table-wrap-foot>
            </table-wrap>
            <sec id="sec20">
                <title>Prevalence of low bone spectrum</title>
                <p>The crude prevalence of low bone mineral density conditions: z score below &#x2212;2.0) and z score below-3.0 was found to be 22.6% (95% CI, 20.3&#x2013;25.1), and 8.1% (95% CI, 6.6&#x2013;9.8), respectively.</p>
            </sec>
            <sec id="sec21">
                <title>Percentage distribution of dietary practices by low z-score categories</title>
                <p>
                    <xref ref-type="table" rid="T3">
Table 3</xref> presents the distribution of bone mineral density (BMD) categories among the 1,176 women who participated in the study. Most women (69.30%) were classified as having normal BMD, indicating generally healthy bone status in this age group. Even so, a considerable number showed reduced bone density. About 22.61% fell into the low BMD range (Z-score&#x00a0;&#x2212;&#x00a0;2 to &#x2212;3), suggesting early deterioration in bone strength. An additional 8.07% had very low BMD (Z-score&#x00a0;&lt;&#x00a0;&#x2212;3), placing them at the greatest risk for osteoporosis-related issues.</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>
Table 3. </label>
                    <caption>
                        <title>Distribution of bone mineral density (BMD) categories among 20&#x2013;40-year-old women participants (N&#x00a0;=&#x00a0;1176).</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">BMD Category</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Percentage (%)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Normal (z&#x00a0;&#x2265;&#x00a0;&#x2212;2)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">815</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69.30%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Low BMD (z&#x00a0;&lt;&#x00a0;&#x2212;2 to&#x00a0;&#x2265;&#x00a0;&#x2212;3)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">266</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22.61%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Very Low BMD (z&#x00a0;&lt;&#x00a0;&#x2212;3)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">95</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.07%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1176</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>100%</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Note: BMD&#x00a0;=&#x00a0;bone mineral density.</p>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec56">
                <title>Distribution and mean comparison of micro- and macronutrient intake across BMD categories</title>
                <p>
                    <xref ref-type="table" rid="T4">
Table 4</xref> highlights noticeable differences in dietary intake across the three BMD groups. Women with normal BMD were much more likely to fulfil their daily calcium requirements, and this relationship was statistically significant. This suggests that sufficient calcium intake plays an important role in maintaining healthier bone density. A similar trend was seen for energy intake, where women with very low BMD were less likely to meet the recommended calorie levels.</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>
Table 4. </label>
                    <caption>
                        <title>Nutrient intake status and mean differences across BMD groups (n&#x00a0;=&#x00a0;1176).</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Nutrient Variable</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Category/Mean 
(SD) [95% CI]</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Normal BMD (n&#x00a0;=&#x00a0;815)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Low-BMD (z score&#x00a0;&lt;&#x00a0;&#x2212;2 
&amp;-&#x00a0;&#x2265;&#x00a0;3) (n&#x00a0;=&#x00a0;266)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Very-Low BMD (z&#x00a0;&lt;&#x00a0;&#x2212;3) (n&#x00a0;=&#x00a0;95)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Chi-Square/ 
F-test p-value</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="3" valign="top">
                                    <bold>Calcium (g)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">591 (97.2%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12 (1.97%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (0.82%)</td>
                                <td align="left" colspan="1" rowspan="3" valign="top">&lt;0.0001*(&#x03c7;
                                    <sup>2</sup>) /&lt;0.001*</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA not met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">224 (44.09%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">254 (44.71%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90 (15.84%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">833 (289) [814&#x2013;853]</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">489 (83) [479&#x2013;499]</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">428 (108) [406&#x2013;450]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="3" valign="top">
                                    <bold>Energy (kcal)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">159 (45.4%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">141 (40.28%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50 (14.28%)</td>
                                <td align="left" colspan="1" rowspan="3" valign="top">&lt;0.0001*(&#x03c7;
                                    <sup>2</sup>) /0.425</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA not met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">656 (79.41%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">125 (15.13%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">45 (5.44%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1803 (256)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1804 (299)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1840 (227)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="3" valign="top">
                                    <bold>Fat (g)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">High</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">802 (68.9%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">266 (22.87%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">95 (8.61%)</td>
                                <td align="left" colspan="1" rowspan="3" valign="top">0.038 (&#x03c7;
                                    <sup>2</sup>) /0.108</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (1%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">36.8 (7.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">37.2 (7.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">38.4 (7.6)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="3" valign="top">
                                    <bold>Protein (g)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">293 (68.29%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">106 (24.70%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30 (6.99%)</td>
                                <td align="left" colspan="1" rowspan="3" valign="top">0.25 (&#x03c7;
                                    <sup>2</sup>) /0.865</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA not met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">522 (69.87%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">160 (21.41%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">65 (8.73%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">47.5 (9.04)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">47.2 (9.15)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">46.95 (8.38)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="3" valign="top">
                                    <bold>Magnesium (mg)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">450 (69.7%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">137 (21.24%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58 (8.99%)</td>
                                <td align="left" colspan="1" rowspan="3" valign="top">0.29 (&#x03c7;
                                    <sup>2</sup>), /0.639</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA not met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">365 (68.7%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">129 (24.29%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">37 (6.96%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">319 (115)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">313 (115)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">325 (103)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="3" valign="top">
                                    <bold>Folic Acid (&#x03bc;g)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">152 (66.96%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">62 (27.31%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (5.72%)</td>
                                <td align="left" colspan="1" rowspan="3" valign="top">0.097 (&#x03c7;
                                    <sup>2</sup>), /0.222</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA not met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">663 (69.86%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">204 (21.49%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">82 (8.64%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">153.7 (69.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">147.2 (63.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">142.3 (52.5)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>Iron (mg)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">112 (96.55%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">34 (30.35%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20 (17.85%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.69 (&#x03c7;
                                    <sup>2</sup>), /0.379</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16.8 (8.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15.5 (8.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15.6 (8.9)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>Niacin (mg)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">200 (57.14%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">110 (31.42%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">40 (11.42%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">&lt;0.0001*(&#x03c7;
                                    <sup>2</sup>), /0.993</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.5 (2.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.48 (3.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.5 (2.8)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>Riboflavin (mg)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">160 (61.30%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">74 (28.35%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27 (10.34%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.0048*(&#x03c7;
                                    <sup>2</sup>), /0.784</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.87 (0.33)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.88 (0.34)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.90 (0.32)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>
&#x03b2;-Carotene (&#x03bc;g)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">175 (68.09%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">53 (20.6%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (11.28%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.59 (&#x03c7;
                                    <sup>2</sup>), /0.270</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3343</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3130</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4260</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>Thiamine (&#x03bc;g)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">635 (67.55%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">218 (23.19%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87 (9.25%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.16 (&#x03c7;
                                    <sup>2</sup>), /0.210</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.30 (0.39)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.29 (0.41)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.37 (0.34)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>Vitamin C (mg)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">752 (69.75%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">236 (21.89%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90 (8.34%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.073 (&#x03c7;
                                    <sup>2</sup>), /0.791</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">110.2 (69.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">107.7 (74.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">113.2 (66.3)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>Zinc (mg)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18 (58.06%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10 (32.2%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (9.67%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.167 (&#x03c7;
                                    <sup>2</sup>), /0.893</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.70 (1.68)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.78 (1.81)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.73 (1.58)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>Phosphorus (mg)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">RDA met</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">790 (67.18%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">251 (21.34%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89 (7.57%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.04 (&#x03c7;
                                    <sup>2</sup>), /0.224</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Mean intake</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1292 (426)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1257 (429)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1226 (331)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>

                            <bold>Notes:</bold> BMD&#x00a0;=&#x00a0;Bone Mineral Density; RDA&#x00a0;=&#x00a0;Recommended Dietary Allowance; CI&#x00a0;=&#x00a0;Confidence Interval. BMD groups: Normal (Z&#x00a0;&gt;&#x00a0;&#x2212;2.0), Low (&#x2212;2.0 to &#x2212;3.0), Very-Low (Z&#x00a0;&lt;&#x00a0;&#x2212;3.0). RDA adequacy based on ICMR/NIN. &#x03c7;
                            <sup>2</sup> test used for categorical variables; ANOVA F-test used for continuous variables. Significance at p&#x00a0;&lt;&#x00a0;0.05.</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>For several other nutrients, such as protein, magnesium, folic acid, iron, and vitamin C the proportions were relatively similar across all groups, indicating that these deficits are widespread in the population rather than specific to any BMD category. On the other hand, nutrients like niacin and riboflavin showed meaningful differences, with adequate intake observed more frequently among women with normal BMD.</p>
                <p>In summary, the findings point to insufficient calcium intake as the most influential dietary factor associated with reduced BMD, while shortages of other micronutrients appear to be common across all women, regardless of their bone density status.</p>
                <p>
                    <xref ref-type="table" rid="T5">
Table 5</xref> presents the multinomial regression analysis results after adjusting for the confounding variables BMI, SES, exercise, history of osteoporosis, and stress) showed that more than 3 pregnancies and late menarche age were found to be significant risk factors of low bone mineral density (p&#x00a0;&lt;&#x00a0;0.001). The presence of hypothyroidism was positively associated with low bone mineral density conditions. Further, lifestyle variables (high perceived stress, low SES, low sun exposure) were also positively correlated with low z-score categories. In addition, it was found that an increase of every 10 unit increase in physical activity levels was found to be a significant protective factor in delaying the onset of low bone mineral density (p&#x00a0;&lt;&#x00a0;0.001).</p>
                <table-wrap id="T5" orientation="portrait" position="float">
                    <label>
Table 5. </label>
                    <caption>
                        <title>Adjusted risk factors for (z score&#x00a0;&lt;&#x00a0;&#x2212;3)/ (z score&#x00a0;&lt;&#x00a0;&#x2212;2 to -&#x00a0;&#x2265;&#x00a0;3) of 20&#x2013;40&#x00a0;years old women participants (1176) assessed by multinomial logistic regression using force entry method.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top"/>
                                <th align="left" colspan="3" rowspan="1" valign="top">Very low BMD (3) (z score&#x00a0;&lt;&#x00a0;&#x2212;3) (n&#x00a0;=&#x00a0;95)</th>
                                <th align="left" colspan="3" rowspan="1" valign="top">Low BMD () (z score&#x00a0;&lt;&#x00a0;&#x2212;2 to -&#x00a0;&#x2265;&#x00a0;3) (n&#x00a0;=&#x00a0;266)</th>
                                <th align="left" colspan="1" rowspan="2" valign="top">Over-all 
p-value</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Risk factor</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">OR (95% CI)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">P-value
</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">OR (95% CI)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">p-value
</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>BMI (kg/m</bold>
                                    <sup>

                                        <bold>2</bold>
                                    </sup>
                                    <bold>)</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt;23</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">53</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.38 (0.54&#x2013;3.53)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.499</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">129</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.12 (0.61&#x2013;2.01)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.727</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.792</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;23</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">137</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Number of pregnancies</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">110</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt;3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">68</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>5.22 (2.16&#x2013;12.63)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">156</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.89 (1.02&#x2013;3.50)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.042</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.001</bold>
                                    <xref ref-type="table-fn" rid="tfn1">

                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Hysterectomy</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Absent (1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">28</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">224</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Present (0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.60 (0.20&#x2013;12.89)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.661</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.46 (0.22&#x2013;9.36)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.694</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.905</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Menarche age (years)</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;14</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.074</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.001</bold>
                                    <xref ref-type="table-fn" rid="tfn1">

                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt;14</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">45</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>4.73 (2.06&#x2013;10.82)</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">180</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.71 (0.95&#x2013;3.08)</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Hypothyroid</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Absent (1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">80</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">248</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Present (0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>3.84 (0.89&#x2013;16.49)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.070</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.41 (0.47&#x2013;4.22)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.545</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.130</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Hyperthyroid</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Absent (1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">77</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">239</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Present (0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>4.48 (1.12&#x2013;17.97)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.034</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.59 (0.52&#x2013;4.86)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.416</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.048</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Diabetes</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Absent (1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">258</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Present (0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.49 (0.05&#x2013;5.23)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.554</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.78 (0.12&#x2013;5.00)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.796</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.807</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Hypertension</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Absent (1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">225</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Present (0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">26</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>3.05 (0.97&#x2013;9.52)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.055</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">41</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.43 (0.62&#x2013;3.29)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.398</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.134</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Perceived Stress</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Upto High</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">129</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Very high</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>7.87 (2.26&#x2013;27.36)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>5.30 (2.63&#x2013;10.67)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>&lt;0.001</bold>
                                    <xref ref-type="table-fn" rid="tfn1">

                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Sun Exposure</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Low</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>6.43 (2.81&#x2013;14.72)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">127</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>2.87 (1.61&#x2013;5.12)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>&lt;0.001</bold>
                                    <xref ref-type="table-fn" rid="tfn1">

                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Optimum +high</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">26</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">139</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1.0</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">
                                    <bold>Physical-Activity (METS)</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Per 10-unit increase</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.40 (0.34&#x2013;0.46)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.52 (0.46&#x2013;0.58)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>&lt;0.001</bold>
                                    <xref ref-type="table-fn" rid="tfn1">

                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Note: Multinomial logistic regression was performed on the complete-case dataset of 1,176 participants, adjusting for BMI, socioeconomic status (SES), physical activity, history of osteoporosis, and perceived stress.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn1">
                                <label>*</label>
                                <p>Significant at p&#x00a0;&lt;&#x00a0;0.05.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec22">
                <title>Nutrient risk factors for low z-score categories</title>
                <p>Multiple regression analysis was used to find the dietary risk factors related to low bone mineral density. After adjusting for some confounding variables for low bone mineral density categories, the results revealed that low calcium intake was found to be independently associated with low z-score categories (OR: 7.09, 95% CI: 2.89&#x2013;17.22; OR: 6.19, 95% CI: 1.52&#x2013;25.24) (p&#x00a0;&lt;&#x00a0;0.01), respectively. All other factors were non-significant (p&#x00a0;&gt;&#x00a0;0.05).</p>
            </sec>
        </sec>
        <sec id="sec23" sec-type="discussion">
            <title>Discussion</title>
            <p>The current study revealed that low and very low bone mineral density (BMD) is a significant concern in young Indian women, underscoring the importance of early skeletal health assessment. Consistent with previous studies, later age at menarche, limited sun exposure, low dietary calcium intake, parity, and hypothyroid status were significantly associated with low BMD. Given the cross-sectional design of this research, these associations cannot be interpreted as causal; however, they align with biological plausibility and existing evidence. Similar prevalence trends have been reported in other Asian populations, with low BMD observed in 20&#x2013;26% of Vietnamese premenopausal women
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> and 18&#x2013;22% of Chinese cohorts.
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> In the present study, nearly one-third of the participants demonstrated compromised bone health, emphasizing the need for routine screening and preventive measures in young adult women.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>,
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> European studies reported lower rates, possibly due to higher dietary calcium intake and more structured physical activity.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> These findings contribute to the growing consensus that low BMD is not confined to postmenopausal women but is increasingly relevant in younger populations.</p>
            <p>Since the sample size was large and to simplify the data grouping for statistical computation, the data was divided into two categories: z scores below &#x2212;2.0,
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup> as having low bone mineral density, and z score below-3.0 has very low bone mineral density, for women who had not attained their menopausal status were used using QUS. The prevalence of low bone mineral density, categorized as z-score below &#x2212;2.0 and z- score below &#x2212;3.0, was found to be 22.6% and 8.1%, respectively. Our study results showed a higher prevalence (8.1%) of low bone mineral density (z score below &#x2212;3.0), whereas a large sample-sized QUS study based on Vietnamese women of a similar age group showed a prevalence of osteoporosis as 3.9%.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> The current study results also suggest that, on average, every third woman surveyed had low bone mineral density.</p>
            <p>Numerous studies have suggested various factors are responsible for low bone mineral density conditions using the QUS technique.
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>,
                    <xref ref-type="bibr" rid="ref20">20</xref>,
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> In the current study, analysis of the adjusted regression model revealed that an increased number of pregnancies (&gt;3) and late menarche (&gt;14&#x00a0;years) appeared as significant risk factors for low bone mineral density conditions. The results showed 45.3% of the women surveyed had a history of more than 3 pregnancies, of which 86.65% had low SOS values. Further, 63.77% of the women had a late onset of menarche (&gt;14&#x00a0;years), and 35.6% of women had breastfed for more than a year. It is known that late menarche, multiple pregnancies, and prolonged lactation period in the absence of adequate calcium intake result in decreased BMD levels.
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> Further, it is to be noted that no woman participant was pregnant nor breast-feeding at the time of the study. All women surveyed had recorded their last lactation period 6&#x2013;9&#x00a0;months before at the time of investigation, which is sufficient time for the bone loss to recover post-weaning.
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup> Our findings are consistent with recent studies reporting rising prevalence of low BMD among younger women in South and East Asia, emphasizing the importance of early screening in this population.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
            </p>
            <p>A notable finding in this study was the presence of several young women who had undergone hysterectomy or oophorectomy at an unusually early age. Although these procedures were not significant predictors in the regression analysis, their occurrence raises concerns about the reproductive health status of young women. Most affected participants belonged to rural communities and had undergone these surgeries following pregnancy-related complications. This pattern aligns with national reports showing that early marriage, poor nutrition, and limited access to quality maternal healthcare contribute to higher gynaecological morbidity in rural India.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> Prior studies also highlight that many women undergo hysterectomy or sterilization without adequate counselling and may not even be aware of whether their ovaries were retained.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup> These observations underscore the need for better reproductive health awareness, improved counselling, and access to conservative treatment options in rural regions.</p>
            <p>Further, it was observed that 69.04% had high perceived stress. Increased stress levels are known to be related to osteoporosis.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> Increased monetary expenses owing to rapid economic growth, poor spousal relations causing physical abuse, especially among rural women, were cited as possible causes for their increased stress levels. Thus, high perceived stress scores were found to be a significant risk factor for low bone mineral density status of women.</p>
            <p>Another notable observation found in the study was the increased prevalence of central obesity (WC&#x00a0;&gt;&#x00a0;80&#x00a0;cm) in the studied women. The results showed that 86.39% of the women had high WC, of which 50.39% of the women had low bone mineral density scores. High fat intake could be one of the possible reasons for this obesity, as 98.99% of the women surveyed had excess of fat intake in their diet.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> These figures suggest that the main form of meeting the calorie demands is through increased fat intake. Rapid urbanization and a changing economy might have stimulated these habits, as a high-fat and high-sugar diet is cheaper than healthy foods.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> In addition, we also found increased mobility and physical activity levels reflected as a significant protective factor against low bone mineral density conditions (p&#x00a0;&lt;&#x00a0;0.001). It was observed that 55.95% of the women surveyed were physically active, that is, they expended 600 METS/min-wk. But 
                <italic toggle="yes">no women</italic> were reported to be in the &#x201c;Active&#x201d; category (meeting the minimum criteria of expending 3000 METS-min/wk).
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> Moreover, the majority (75.09%) of the women surveyed had optimal sun exposure, suggesting that in spite of social and cultural limitations posed on Indian women, the traditional habit of sitting in the sunlight still exists. The results of the current research correspond to the existing literature that records bone-related issues at the early ages in young women living in Asian and low-middle-income countries. Emerging factors in low BMD in younger women younger than 40&#x00a0;years have been pointed out by modern research due to nutritional deficiencies, lifestyle habits, and late reproductive maturation.
                <sup>
                    <xref ref-type="bibr" rid="ref34">34</xref>,
                    <xref ref-type="bibr" rid="ref35">35</xref>
                </sup> These similarities support the utilization of bone health assessment as a priority area of concern in reproductive-age populations.</p>
            <p>An additional goal of the study was to observe the role of micro and macronutrients in bone health. It is known that a sufficient amount of calcium and other nutrients play a vital role in maintaining good bone health status.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> In the current study, analysis of nutrient intake through the 24-hour dietary recall method showed low calcium levels posed as an independent risk factor for low bone mineral density conditions among women(p&#x00a0;&lt;&#x00a0;0.001). Further, all major and micro nutrients (protein, folic acid, niacin, riboflavin, &#x03b2;-carotene, vitamin B12, and zinc) assessed did not meet the recommended dietary levels, which may lead to several multiple nutritional deficiencies. Also, deficiency of vitamin A and iron, which is viewed as a well-recognized problem in Indian women (WHO, 2010) was prevalent in the current study as well.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup>
            </p>
            <sec id="sec24">
                <title>Limitations and strengths</title>
                <p>The present study has several limitations that should be considered. First, the cross-sectional design precludes any causal inferences between risk factors and bone mineral density. Second, although multi-site quantitative ultrasound (QUS) is a practical and widely used screening tool for assessing bone health in large population studies, it cannot replace dual-energy X-ray absorptiometry (DXA), the gold standard for BMD measurement. Additionally, reference ranges of z-scores for young Indian women using multi-site QUS have not yet been firmly established, which may affect interpretation. Important variables such as serum vitamin D levels, genetic factors, biochemical markers related to bone metabolism, and detailed quantification of physical activity were not assessed. Finally, the study sample was drawn from northern India, limiting the generalizability of the findings to other regions. Despite these limitations, the results emphasize the public health importance of early bone health screening and lifestyle interventions in young Indian women, particularly in settings where access to DXA is limited.</p>
                <p>The study has several major strengths. It is the first large-scale Indian study to estimate the prevalence of low bone mineral density in young women using QUS technology. The accuracy and reliability of bone measurements were ensured, as all densitometer assessments were performed by a single trained operator. Nutritional assessments were consistently conducted by a qualified dietician, and all relevant factors related to low bone mineral density were included in the study. Additionally, the questionnaires were translated and validated in Punjabi, and the multisite Omnisense QUS device was validated for use in the Punjabi population for epidemiological purposes. Importantly, the final analytical sample (n&#x00a0;=&#x00a0;1,176) exceeded the minimum required size, reflecting higher-than-expected participation and improving statistical precision, without introducing methodological bias, as the same inclusion criteria and ethical protocols were applied throughout.</p>
            </sec>
        </sec>
        <sec id="sec25" sec-type="conclusion">
            <title>Conclusion</title>
            <p>The present study presents the prevalence of low bone mineral density status in young women of Punjab using a validated multisite QUS technique. Our results show that there is an increased prevalence of low bone mineral density in these young women. A multiple logistic regression model assessed associations between various factors and low SOS. Our study strongly advocates the need to propagate effective preventive measures (increased physical activity and healthy dietary habits) and educate women to improve bone health on a large scale, as most of the women are unaware of the importance of these healthy practices in building healthy bone status.</p>
        </sec>
        <sec id="sec26">
            <title>Ethics approval and consent to participate</title>
            <p>The study was conducted in line with the Declaration of Helsinki for human participants and approved by the Institutional Ethics Committee, Faculty of Sports Medicine and Physiotherapy, Guru Nanak Dev University, Amritsar (No-1319/SMP). This study is registered with the Clinical Trial Registry of India (CTRI/2015/10/006240).</p>
        </sec>
        <sec id="sec27">
            <title>Consent to participate</title>
            <p>Written informed consent was taken from all participants for their voluntary participation in the study before data collection, explaining the possible use of the data for research and publication without revealing their identity.</p>
        </sec>
    </body>
    <back>
        <sec id="sec30" sec-type="data-availability">
            <title>Availability of data and materials</title>
            <p>The complete dataset has been given in the online repository.</p>
            <p>[Figshare]: [BMD IN INDIAN WOMEN].</p>
            <p>[
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.32165151">https://doi.org/10.6084/m9.figshare.32165151</ext-link>]</p>
            <p>

                <ext-link ext-link-type="uri" xlink:href="https://figshare.com/articles/dataset/BMD_IN_INDIAN_WOMEN/32165151">https://figshare.com/articles/dataset/BMD_IN_INDIAN_WOMEN/32165151</ext-link>.
                <sup>
                    <xref ref-type="bibr" rid="ref36">36</xref>
                </sup>
            </p>
            <p>The project contains the following underlying data:</p>
            <p>[Masterchat Raw data, IRB Approval, CONSORT Checklist, CONSORT Flowchart].</p>
            <p>Data are available under the terms of the 
                <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            <p>The manuscript is available as a preprint on the Research Square platform.
                <sup>
                    <xref ref-type="bibr" rid="ref37">37</xref>
                </sup>
            </p>
        </sec>
        <ack>
            <title>Acknowledgement</title>
            <p>This study forms part of a larger Ph.D. research project, and the authors gratefully acknowledge the support provided by Guru Nanak Dev University, India, and Gulf Medical University, UAE, for their valuable assistance in the successful completion of this project.</p>
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    <sub-article article-type="reviewer-report" id="report491995">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.201005.r491995</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Jahagirdar</surname>
                        <given-names>Sampada</given-names>
                    </name>
                    <xref ref-type="aff" rid="r491995a1">1</xref>
                    <xref ref-type="aff" rid="r491995a2">2</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r491995a1">
                    <label>1</label>Physiotherapy, Amar Jyoti institute of Physiotherapy, University of Delhi, Delhi, Delhi, India</aff>
                <aff id="r491995a2">
                    <label>2</label>K R Mangalam University, Gurugram, Haryana, India</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>16</day>
                <month>6</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Jahagirdar S</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport491995" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.182100.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Study period of 
                <bold>10 years </bold>is unusually long for a cross-sectional study. Population characteristics may had been changed during this time, especially with the Covid happening during this time.</p>
            <p> Prevalence source for sample size calculations can be provided.</p>
            <p> Conditions like Hyperparathyroidism, Rheumatoid arthritis, Diabetes mellitus could confound bone health. Ideally, these participants could have been excluded.</p>
            <p> As DEXA is the gold standard for BMD assessment and QUS assesses bone properties indirectly, it is better to use that bone health status or a similar term rather than BMD.</p>
            <p> ISCD recommendations generally classify Z-score &#x2265; -2.0 as within expected range and Z-score &lt; -2.0 as below expected range for age. Very low category is not standard.</p>
            <p> Self-reported questionnaire could have been validated if such a large study was anticipated.</p>
            <p> Hosmer-Lemeshow test is designed for binary logistic regression and is not appropriate for multinomial logistic regression. Please check.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Geriatric Physiotherapy, Women's Health</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
    </sub-article>
</article>
