Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional study

Prem Shankar Chaurasiya; Shekhar Gurung; Saurab Karki; Krishna Chandra Mandal; Binod Mehta; Dipesh Kumar Rohita; Babli Mishra; Gopal Kumar Yadav; Surakshya Baral; Suhail Sapkota

doi:10.12688/f1000research.125103.1

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Research Article

Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional study

[version 1; peer review: 1 approved with reservations, 1 not approved]

Prem Shankar Chaurasiya¹, Shekhar Gurung², Saurab Karki ³, [...] Krishna Chandra Mandal⁴, Binod Mehta⁵, Dipesh Kumar Rohita⁵, Babli Mishra¹, Gopal Kumar Yadav¹, Surakshya Baral⁶, Suhail Sapkota⁷

Prem Shankar Chaurasiya¹, Shekhar Gurung², [...] Saurab Karki ³, Krishna Chandra Mandal⁴, Binod Mehta⁵, Dipesh Kumar Rohita⁵, Babli Mishra¹, Gopal Kumar Yadav¹, Surakshya Baral⁶, Suhail Sapkota⁷

PUBLISHED 23 Nov 2022

Author details Author details

¹ Kalaiya Provincial Hospital, Bara, Nepal
² Shivanagar Primary Health Care Center, Chitwan, Nepal
³ Military Hospital Itahari, Sunsari, Nepal
⁴ Gaur Provincial Hospital, Rautahat, Nepal
⁵ BP Koirala Institute of Health Sciences, Dharan, Nepal
⁶ Manipal College of Medical Sciences, Pokhara, Nepal
⁷ Nepalese Army Institute of Health Sciences, Kathmandu, Kathmandu, Nepal

Prem Shankar Chaurasiya
Roles: Conceptualization, Formal Analysis, Validation

Shekhar Gurung
Roles: Project Administration, Resources, Supervision

Saurab Karki
Roles: Supervision, Validation, Writing – Review & Editing

Krishna Chandra Mandal
Roles: Data Curation, Investigation

Binod Mehta
Roles: Investigation, Methodology, Software

Dipesh Kumar Rohita
Roles: Formal Analysis, Visualization, Writing – Original Draft Preparation

Babli Mishra
Roles: Formal Analysis, Methodology, Resources

Gopal Kumar Yadav
Roles: Methodology, Supervision

Surakshya Baral
Roles: Resources, Writing – Original Draft Preparation

Suhail Sapkota
Roles: Supervision, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Background: Anemia is a principal public health concern. Worldwide one-third of women of reproductive age are affected. A 2016 survey showed that 41% of women in Nepal had anemia with the highest prevalence in Pradesh two. A complex interaction among socio-political, biological, and ecological elements determines anemia. Assessing the factors would help in minimizing anemia and its consequences. The study aimed to determine the prevalence of anemia in the reproductive age group and the factors affecting anemia.

Methods: A hospital-based cross-sectional study was conducted among women of the reproductive age group (15–45) from 15th April to 15th June 2022 after ethical clearance was obtained from the Nepal health research council (Ref. 2737/2022). Regarding data collection, 375 women participants were selected via a simple random sampling technique. Participants underwent an interview after informed written consent followed by blood sample collection. Through a semi-structured questionnaire, the data was obtained. Then data entry and its analysis were performed via Microsoft Excel 2019 and Statistical Package for Social Sciences version 22.0.

Results: The study showed that 229 (61.3%) females of the reproductive age group had anemia. Inadequate nutrition (OR 3.0, 1.9–5.0), breastfeeding (OR 7.3, 4.5–11.9), and rural place of residence (OR 4.2, 2.5–7.0) were significantly associated with anemia, with a corresponding odds ratio at 95% confidence each.

Conclusions: The prevalence of anemia was higher among women of the reproductive age group compared to provincial and national prevalence. The interventions should be focused on breastfeeding, nutrition, and rural women to combat anemia.

Keywords

anemia, breastfeeding, economic, prevalence, nutrition, regression, reproductive age, survey

Corresponding author: Saurab Karki

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2022 Chaurasiya PS et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Chaurasiya PS, Gurung S, Karki S et al. Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional study [version 1; peer review: 1 approved with reservations, 1 not approved]. F1000Research 2022, 11:1367 (https://doi.org/10.12688/f1000research.125103.1) First published: 23 Nov 2022, 11:1367 (https://doi.org/10.12688/f1000research.125103.1) Latest published: 23 Nov 2022, 11:1367 (https://doi.org/10.12688/f1000research.125103.1)

Introduction

Anemia is a clinical condition with low hemoglobin levels in the blood, and hence, the oxygen-carrying capacity is compromised. With decreased iron levels being the most common in the developing world, iron deficiency anemia and anemia denote the same thing in this part of the world.¹ A wide variety of factors are responsible in developing countries and hence dealing with this issue is a public health summons around the world.² As per WHO and World Bank, the third paramount basis for disability-adjusted life years (DALY) loss among women of reproductive age accounts to iron deficiency anemia.² Owing to excess loss of blood during menstrual flow as well as the fetus extracting more iron from the maternal pool, these females are most vulnerable to suffering.³ Further, in the developing world, the challenges in tackling the problems associated with iron deficiency anemia include and are not limited to a greater burden of the problem, more reliance on plant-based diets, concerns regarding cost and accessibility to iron-rich foods, and absence of extra supplementation or food fortification.² Unable to address this issue, anemia can lead to multiple complications like dementia, fatigue, and impaired quality of life, along with adverse events during pregnancy including decreased productivity and physical abilities and even maternal deaths.⁴

Anemia is a serious global public health obstacle. It is estimated that one in three women of the reproductive age group (WRA) are anemic worldwide. It is associated with a greater risk in terms of maternal as well as perinatal morbidity and mortality and thus a greater economic burden to society. A survey demonstrates 41% anemia prevalence among WRA in Nepal, and province two has the highest anemia prevalence at 58%. A complex interaction among socio-political, biological, and ecological elements ultimately regulates anemia and its prevalence among women that incorporates rural places of residency, younger age, inadequate nutrition, pregnancy, repeated childbearing, breastfeeding, and lack of hormonal contraceptives.⁵

The prevalence of anemia among the WRA group in our belt is significantly under-reported. Adequate reporting helps understand the true burden of anemia. It will help implement policies more effectively. The study also aimed to estimate anemia prevalence among the WRA group and to know the effects of associated factors among them.

Methods

Ethical consideration

The ethical approval was obtained from Nepal Health Research Council (Reference no. 2737/2022) on 31^st March 2022 after submitting the approval letter from the hospital. Informed verbal and written consent was taken before the study and confidentiality was maintained. In the case of a minor, we received assent from them as well.

Study design and setting

This was a hospital-based cross-sectional study that was conducted in the Rautahat district of Nepal served by Gaur provincial hospital. The study was done with a target population (women of reproductive age 15–45 age group) of 375, attending regular out-patient department (OPD) visits at Gaur hospital. The hospital is located at the district headquarters of Rautahat, Nepal, in southern bordering India. It is a primary referral center for all health posts, primary health care (PHC), and local clinics located in the Rautahat district. The Ministry of Health and Population of Nepal has categorized it as a 75 bedded hospital with more than 80% occupancy. Now it is run under the government of province no 2.

The study followed the Strengthening the Reporting Observational Studies in Epidemiology (STROBE) guidelines.²⁷

Participants, sample size, and sampling methods

All women of the reproductive age group (15–45) visiting OPD at Gaur Hospital during the period of 15^th April to 15^th June 2022, were included in the study. The women who were seriously ill at the time of study and those taking iron supplements were, however, excluded from the study.

According to the study by Sunuwar et al., the prevalence of anemia was 58% among WRA of Madhesh province.⁵ Considering the anemia prevalence of 58 % at a 95% confidence interval with a 5% allowable error, the calculated sample size was 375. The detailed elaboration is as follows:

n = z^{2} \times \frac{pxq}{E^{2}} = {1.96}^{2} \times \frac{0.58 \times 0.42}{{0.05}^{2}} = 374.3 \sim 375

where,

n = required sample size

z = 1.96 at alpha 5% level of significance

p = prevalence = 0.58; q (compliment of prevalence) = 0.42

E = allowable error, 5%

Then women for this study were chosen through simple random sampling. A thorough physical examination was performed. Data regarding residency, pregnancy status, nutritional status, parity, breastfeeding status, nutrition, contraception, and income were collected through a semi-structured questionnaire. The questionnaires were developed after a full review of literature about anemia and the factor affecting it in women. Hemoglobin level was recorded from individual laboratory test reports.

Each day, after proper consent and introduction, participants were asked about their name, age, address, marital status, religion, and nutritional status (adequate ≥ 1600 Kcal/day and inadequate < 1600 Kcal/day in single-day dietary recall of the preceding day), breastfeeding (not within 3 months of postpartum and ongoing breastfeeding for past 4 weeks was categorized as “yes” group), parity, contraception, residence (urban and rural), income per month per family (low < 20,000 NRs (Nepali Rupees), medium 20,000–40,000 NRs and high > 40,000 NRs) and hemoglobin level. A hemoglobin level of fewer than 12 g/dl was considered anemia, which was further graded into mild anemia (10–11.9 g/dl), moderate anemia (7–9.9 g/dl), and severe anemia (<7 g/dl) as per the recommendations of the World Health Organization.¹

After the interview, the individual participant was sent to the laboratory department. Approximately 1 ml of venous blood from each participant was taken from the arm via a sterile hypodermic syringe in a specific sterile EDTA tube. Samples were processed into an automated analyzer. The analyzer display showed the hemoglobin level, and the results were noted down.

Statistical analysis

The data was entered in to an Excel sheet (Microsoft Excel v16.0, WA, USA) and was analyzed using Statistical Packages for Social Sciences (SPSS), IBM SPSS^® v21 (IBM, Armonk, New York).⁸ Frequency, percentage, mean, standard deviations, and/or interquartile range were used to express descriptive statistics as applicable. We described the categorical data in terms of frequency and proportions and continuous data in terms of mean ± standard deviation (SD) and interquartile range. Differences in participants’ characteristics were explored using the chi-squared test. The binary logistic regression was used to identify the association of anemia with the background characteristics of WRA. For binary logistic regression analysis, odds ratios (OR) and 95% confidence intervals (CI) were calculated.

Results

A total of 375 females of the reproductive age group participated in our study without a null response.²⁷ Table 1 shows the mean age of participants was found to have 24.5±6.56 years. Most women belonged to the 20 to 34 age group (258 (68.8%)), followed by the less than 20 age group (78 (20.8%)). Most of the women were already married (94.9%) at the time of the interview.

Table 1. Basic characteristics of women of reproductive age group.

Characteristics	Frequency	Percentage (%)
Age (years)
Mean ± SD (Range)	24.6 ± 6.6 (15–45)
<20	78	20.8
20–34	258	68.8
≥35	39	10.4
Marital status
Married	356	94.9
Single¹	19	5.1
Education
Informal	103	27.5
Up to Primary level	207	55.2
Up to secondary level	55	14.7
Higher secondary education and/or above	10	2.7
Nutrition satisfaction
Adequate	124	33.1
Inadequate	251	66.9
Breastfeeding
No	183	48.8
Yes	192	51.2
Parity
0	67	17.9
1	173	46.1
2	116	30.9
3 and above	19	5.1
Contraception
No	161	42.9
Yes	214	57.1
Residence
Urban	286	84.3
Rural	89	15.7
Income per month²
Low	183	48.8
Middle	173	46.1
High	19	5.1

1 Single: divorced, separated, widowed.

2 Income per month per family: Low<20,000 NRs (Nepalese Rupees); Middle: 20,000–40,000 NRs and High >40,000 NRs.

More than half of the women (207 (55%)) completed the primary level of education, followed by 103 (27.5%) who had informal education. The nutritional assessment revealed that two-thirds of the women (251 (66.9%)) had inadequate nutrition intake. Similarly, 192 (51.2%) women were engaged in breastfeeding at the time of the interview. Many women (173 (46.1%)) had one child whereas, 116 women had two children. More than half (214 (57.1%)) of the women were contraception users. Regarding residence, out of 375, 286 (84.3%) women lived in urban areas. Regarding monthly family income, most of the families belong to the low 183 (48.8%) and middle-income 173 (46.1%) categories.

The study showed that 231 (61.6%) women of the reproductive age group had anemia with an average hemoglobin level of 11.3 ± 1.8 g/dl. Among the 231 women, 148 (64.1%) belonged to a mild type of anemia, followed by moderate and severe anemia in 34.2% (79) and 1.7%⁴ women respectively [Table 2].

Table 2. Anemia among women of reproductive age group.

Characteristics	Frequency	Percentage (%)
Anemia
Mean hemoglobin ± SD (Range)	11.3 ± 1.8 (5.5–16.0)
No	144	38.4
Yes	231	61.6
Anemia severity (g/dl)¹
Mild (10–11.9 g/dl)	148	64.1
Moderate (7–9.9 g/dl)	79	34.2
Severe (<7 g/dl)	4	1.7

1 Out of 231 participants.

The factors linked to anemia among females were analyzed using the binary regression model. Inadequate nutritional status was significantly associated with anemia (OR 3.0, 95% CI: 1.9-5.0). Similarly, breastfeeding women were significantly associated with anemia as compared to those currently not breastfeeding (OR 7.3, 95% CI: 4.5-11.9). Compared to urban dwellers, women living in the rural region were found to be statistically associated with anemia significantly (OR 4.2, 95% CI: 2.5-7.0) [Table 3].

Table 3. Factors affecting anemia among women of reproductive age group.

Characteristics	Anemia		Binary logistics regression
Characteristics	No (%)	Yes (%)	OR	95% CI	P-value
Age (years)					0.533
20–34	159 (61.6)	99 (38.4)	1 (Ref.)
<20	44 (56.4)	34 (43.6)	1.2	0.7-2.1
≥35	26 (66.7)	13 (33.3)	0.8	0.4-1.6
Education					0.480
Informal	62 (60.2)	41 (39.8)	1 (Ref.)
Up to 5 class	123 (59.4)	84 (40.6)	1.1	0.6-1.7
Up to 10 class & /or above	44 (67.7)	21 (32.3)	0.7	0.4-1.4
Marital status					0.439
Married	219 (61.5)	137 (38.5)	1 (Ref.)
Single	10 (52.6)	9 (47.4)	1.4	0.6-3.6
Nutritional satisfaction					<0.001
Adequate	96 (77.4)	28 (22.6)	1 (Ref.)
Inadequate	133 (53.0)	118 (47.0)	3.0	1.9-5.0
Breastfeeding					<0.001
No	152 (83.1)	31 (16.9)	1 (Ref.)
Yes	77 (40.1)	115 (59.9)	7.3	4.5-11.9
Parity					0.502
0	45 (67.2)	22 (32.8)	1 (Ref.)
1	102 (59.0)	71 (41.0)	1.4	0.8-2.6
2 and above	82 (60.7)	53 (39.3)	1.3	0.7-2.4
Contraception					0.620
No	96 (59.6)	65 (40.4)	1 (Ref.)
Yes	133 (62.1)	81 (37.9)	0.9	0.6-1.4
Residence					<0.001
Urban	198 (69.2)	88 (30.8)	1 (Ref.)
Rural	31 (34.8)	58 (65.2)	4.2	2.5-7.0
Income per month					0.168
Low	117 (63.9)	66 (36.1)	1 (Ref.)
Middle	104 (60.1)	69 (39.9)	1.2	0.8-1.8
High	8 (42.1)	11 (57.9)	2.4	0.9-6.36

Discussion

Our study shows the overall prevalence of anemia among women under the reproductive age group was 231 (61.6%) and found it comparable to the prevalence of anemia in Province number two (58%). However, the figure is much higher if we compare it with the national data of Nepal in 2016 (41%) and the world. As per the reports of a study in East Africa, 34.85 (95% CI: 34.56–35.14) was the anemia prevalence in women of reproductive age.⁶ There is a complex interplay between various factors such as nutrition, infectious diseases, etc. which creates challenges and obstacles to addressing the population indicators leading to anemia.⁷ The study revealed that with poor nutritional status, the likelihood of having anemia was three times higher than those with good nutritional status. Likewise, the odds of anemia are two times higher if we compare data in province two of Nepal overall. This can partly be explained by the fundamental role of nutrition including micronutrients, iron in red blood cell (RBC) formation, and survival. The most frequently occurring anemia owes to iron deficiency. For a woman, iron loss from one’s body happens mostly either by the sloughing of cells from duodenal enterocytes or through blood loss following menstruation and postpartum, which results in deprivation of the iron from the circulatory pool. This iron is usually available for usage in different target organs and hence, it leads to the condition of functional iron insufficiency in the body.⁸ Although anemia can affect persons of any age group, the reproductive age group are more vulnerable due to busy timetables, inconsistent mealtimes, and working with longer schedules.⁹^,¹⁰ It is a concern among the reproductive age-group females that anemia is supposed to have a massive impact on these groups of people like; loss of efficiency owing to decline in work capacity, impairment of perception and cognition, increased vulnerability towards infections due to its consequences on immunity, miscarriage or stillbirths, and maternal deaths.¹¹ The consequences like having a preterm or low birth weight neonates, dry iron stores among new-borns, and overall increased infant/child mortality are an outcome among women suffering from anemia during their reproductive age.¹² Every year, anemia leads to an excess of 115,000 maternal as well as 591,000 perinatal deaths around the globe.¹³ Prior studies had demonstrated that females from province number two had an increased likelihood to be arriving from a lower socioeconomic position with a lesser variety of the foods they consumed. The study demonstrates breastfeeding women are more than seven times more susceptible (OR = 7.3) to anemia as compared to non-breastfeeding. A study done in Myanmar, however, revealed there was no association between anemia with breastfeeding status.¹⁴ As the mothers are lactating, they are more likely to be anemic as their iron stores would have significantly depleted during breastfeeding in addition to the blood loss that had occurred at delivery.¹⁵ Additionally, the urban-rural residence also has a significant effect on the prevalence of this condition. In our study among women residing in rural places, they had 4.2 times more risk of having anemia. These women who live in rural sites have better access to nutrition along with health facilities. One study done in Ethiopia in 2016 demonstrates that the odds of suffering from anemia were significantly greater in women with low household wealth cohorts and those who lived in rural areas in comparison to females from the middle and higher household wealth cohorts who were from the urban area of residence (AOR = 1.37, 95% CI 1.14–1.65, P < 0.001).¹⁶ Similar studies have demonstrated that the status of anemia is greater among rural females (66%). Likewise, the odds of suffering from anemia are greater along with decreasing financial status and conditions whatever their address was, but it has been demonstrated that the odds are greater if a poor woman belongs to urban areas as compared to similar ones in rural places after covariates have been adjusted.¹⁷ According to a study conducted in Nepal, women living in rural parts of the country had 68.1% anemia as compared to only 31.9% among those women who live in urban areas.¹⁸ Although our study does not reveal an association with educational status, low educational standards do have a role in the higher prevalence of iron deficit.¹⁹ In addition, family income plays a significant role in anemia. The prevalent cases of anemia among women in their reproductive period are highest in low- and middle-income nations.²⁰^,²¹ Our study failed to show any association. The study reveals no correlation between hormonal contraception use and anemia. However, one study done in sub-Saharan countries elucidated that oral contraceptive pills (OCP) usage, prominently decreases the odds of having anemia by 38%.²² Similarly, another study’s result demonstrated the likelihood of anemia was decreased by around 40% as opposed to those who practiced the barrier method of contraception (OR=0.6,95% CI: 0.45 to 1.12).²³ While mentioning parity, multiparous females were found to have reduced serum ferritin levels (and hence low hemoglobin) as compared to the controls, indicating that multiple pregnancies do play a role in the context of the iron content inside the body.²⁴ Likewise, our study also had similar findings that the prevalence of anemia and iron deficiency was more among multiparous females as compared to nulliparous females.²⁵ Women with high parity pregnancies had an increased risk of anemia than those women who had had a lesser number of pregnancies (risk ratio, RR = 2.92; 95% CI 2.02, 4.59). Also, the risk of anemia during pregnancy increased in a dose-response manner over multiple parity categories.²⁶

To reduce the poor nutritional impact on anemia, The Ministry of Health and Population of Nepal has been delivering iron-folic acid (IFA) supplements to pregnant female cohorts and also to post-partum females since 1998 to reduce maternal anemia.

The sample was taken from the study population visiting Gaur Hospital. Therefore, its findings cannot be generalized to other hospitals/places. As this is a longitudinal study, different anemia-associated factors can’t establish causality. These were the limiting factors encountered during the study.

Conclusion

The prevalence of anemia was higher among women of the reproductive age group than in other studies done in a similar setting. Most of the women did not have knowledge and access to proper nutrition. Similarly, there should be the provision for additional nutrients and vitamins/minerals supplementation in breastfeeding women to counteract anemia. Special dietary awareness and interventions should be prioritized for multiparous women and women of rural areas to decelerate anemia and/or its possible consequences on women of reproductive potential. This fact might guide policy makers to target the above factors to decrease the prevalence of anemia and raise overall health.

Consent

Written informed consent from all the participants was taken.

Data availability

Underlying data

Figshare: Prevalence of anemia and its associated factors among women of reproductive age group attending at Gaur Provincial Hospital: A cross-sectional study. https://doi.org/10.6084/m9.figshare.20378268.²⁷

This project contains the following underlying data:

• Data anemia Rautahat v3wra.xlsx (raw data for the 375 individuals included in final analysis)

Extended data

Figshare: Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional study. https://doi.org/10.6084/m9.figshare.20378268.²⁷

The project contains the following extended data:

• Questionnaire updated.docx (tool used for data collection)

Reporting guidelines

Figshare: STROBE checklist for ‘Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional study’. https://doi.org/10.6084/m9.figshare.20378268.²⁷

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Acknowledgments

The authors would like to thank Mr. Ram Prabesh, a lab technician at Gaur hospital and Gaur provincial hospital, Gaur following his permission for its support. They express their sincere gratitude to all participants who gave consent to conduct research.

References

1. Tolentino K, Friedman JF: An update on anemia in less developed countries. Am. J. Trop. Med. Hyg. 2007; 77(1): 44–51. PubMed Abstract | Publisher Full Text
2. Yip R, Ramakrishnan U: Experiences and challenges in developing countries. J. Nutr. 2002; 132(4 SUPPL): 827S–830S. Publisher Full Text
3. Levy JE, Jin O, Fujiwara Y, et al.: Transferrin receptor is necessary for development of erythrocytes and the nervous system. Nat. Genet. 1999 Apr [cited 2022 Oct 22]; 21(4): 396–9. PubMed Abstract | Publisher Full Text
4. Prasanth R: Prevalence of Anemia in both Developing and Developed Countries around the World. World J. Anemia. 2017 Jun; 1(2): 40–43. Publisher Full Text
5. Sunuwar DR, Singh DR, Adhikari B, et al.: Factors affecting anaemia among women of reproductive age in Nepal: a multilevel and spatial analysis. BMJ Open. 2021 Mar 1 [cited 2022 Jul 11]; 11(3): e041982.Reference Source
6. Teshale AB, Tesema GA, Worku MG, et al.: Anemia and its associated factors among women of reproductive age in eastern Africa: A multilevel mixed-effects generalized linear model. PLoS One. 2020 Sep 1 [cited 2022 Jul 11]; 15(9): e0238957. PubMed Abstract | Publisher Full Text
7. Balarajan Y, Ramakrishnan U, Özaltin E, et al.: Anaemia in low-income and middle-income countries. Lancet. 2011 [cited 2022 Oct 22]; 378(9809): 2123–2135. Publisher Full Text Reference Source
8. Negi PC, Dev M, Paul P, et al.: Prevalence, risk factors, and significance of iron deficiency and anemia in nonischemic heart failure patients with reduced ejection fraction from a Himachal Pradesh heart failure registry. Indian Heart J. 2018 Dec 1 [cited 2022 Jul 11]; 70(Suppl 3): S182–S188. Publisher Full Text Reference Source
9. Vibhute N, Shah U, Belgaumi U, et al.: Prevalence and awareness of nutritional anemia among female medical students in Karad, Maharashtra, India: A cross-sectional study. J. Family Med. Prim. Care. 2019 [cited 2022 Jul 11]; 8(7): 2369–2372. PubMed Abstract | Publisher Full Text
10. Retnakumar C, Chacko M, Ramakrishnan D, et al.: Prevalence of anemia and its association with dietary pattern among elderly population of urban slums in Kochi. J. Family Med. Prim. Care. 2020 [cited 2022 Jul 11]; 9(3): 1533–1537. PubMed Abstract | Publisher Full Text
11. Teshale AB, Tesema GA, Worku MG, et al.: Anemia and its associated factors among women of reproductive age in eastern Africa: A multilevel mixed-effects generalized linear model. PLoS One. 2020 Sep 1 [cited 2022 Jul 11]; 15(9): e0238957. PubMed Abstract | Publisher Full Text
12. Mawani M, Aziz AS: Iron Deficiency Anemia among Women of Reproductive Age, an Important Public Health Problem: Situation Analysis. Reprod. Syst. Sex. Disord. 2016; 5(3). Publisher Full Text
13. Tirore LL, Mulugeta A, Belachew AB, et al.: Factors associated with anaemia among women of reproductive age in Ethiopia: Multilevel ordinal logistic regression analysis. Matern. Child Nutr. 2021 Jan 1 [cited 2022 Jul11]; 17(1): e13063. PubMed Abstract | Publisher Full Text
14. Zhao A, Zhang Y, Li B, et al.: Prevalence of Anemia and Its Risk Factors Among Lactating Mothers in Myanmar. Am. J. Trop. Med. Hyg. 2014 May 5 [cited 2022 Jul 6]; 90(5): 963–967. PubMed Abstract | Publisher Full Text | Free Full Text
15. Lakew Y, Biadgilign S, Haile D: Anaemia prevalence and associated factors among lactating mothers in Ethiopia: evidence from the 2005 and 2011 demographic and health surveys. BMJ Open. 2015 [cited 2022 Jul 8]; 5(4): e006001. Publisher Full Text | Free Full Text
16. Abate TW, Getahun B, Birhan MM, et al.: The urban–rural differential in the association between household wealth index and anemia among women in reproductive age in Ethiopia, 2016. BMC Womens Health. 2021 Dec 1[cited2022Jul6]; 21(1): 311–318. PubMed Abstract | Publisher Full Text
17. Awoleye AF, Alawode OA, Chima V, et al.: Rural-urban differentials in the relationship between household wealth index and maternal anaemia status in Nigeria.2022 [cited 2022 Jul 11]. Publisher Full Text
18. Acharya D, Adhikari R, Simkhada P: Prevalence and Determinants of Anaemia among Women aged 15-49 in Nepal: A Trend Analysis from Nepal Demographic and Health Surveys from 2006 to 2016. Asian J. Popul. Sci. 2022 Mar 3; 32–48. Publisher Full Text
19. Yadav UK, Ghimire P, Amatya A, et al.: Factors Associated with Anemia among Pregnant Women of Underprivileged Ethnic Groups Attending Antenatal Care at Provincial Level Hospital of Province 2, Nepal. Anemia. 2021 [cited 2022 Jul 11]; 2021: 1–9. PubMed Abstract | Publisher Full Text | Free Full Text
20. Stevens GA, Finucane MM, De-Regil LM, et al.: Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995-2011: a systematic analysis of population-representative data. Lancet Glob. Health. 2013 Sep [cited 2022 Jul 11]; 1(1): e16–e25. Publisher Full Text Reference Source
21. Daru J, Zamora J, Fernández-Félix BM, et al.: Risk of maternal mortality in women with severe anaemia during pregnancy and post partum: a multilevel analysis. Lancet Glob. Health. 2018 May 1 [cited 2022 Jul 11]; 6(5): e548–e554. PubMed Abstract | Publisher Full Text
22. Gebremedhin S, Asefa A: Association between type of contraceptive use and haemoglobin status among women of reproductive age in 24 sub-Saharan Africa countries. BMJ Sex Reprod Health. 2018 Jan 1 [cited 2022 Jul 11]; 45(1): 54–60.Reference Source
23. Teshome AA, Berra WG, Huryi AF: Modern Contraceptive Methods Predict Hemoglobin Levels Among Women of Childbearing Age from DHS 2016. Open Access J. Contracept. 2022 Jan [cited 2022 Jul 11]; 13: 1–8. PubMed Abstract | Publisher Full Text
24. Farooq A, Rauf S, Hassan U, et al.: IMPACT OF MULTIPARITY ON IRON CONTENT IN MULTIPAROUS WOMEN. J. Ayub Med. Coll. Abbottabad. 2011; 23.Reference Source
25. Imai K: Parity-based assessment of anemia and iron deficiency in pregnant women. Taiwan. J. Obstet. Gynecol. 2020 Nov 1; 59(6): 838–841.
26. Al-Farsi YM, Brooks DR, Werler MM, et al.: Effect of high parity on occurrence of anemia in pregnancy: A cohort study. BMC Pregnancy Childbirth. 2011 Jan 20 [cited 2022 Jul 11]; 11(1): 1–7. PubMed Abstract | Publisher Full Text
27. Chaurasiya PS, Gurung S, Karki S, et al.:Data anemia Rautahat v3wra.xlsx (Version 4). figshare. [Dataset].2022. Publisher Full Text

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VERSION 1 PUBLISHED 23 Nov 2022

Author details Author details

¹ Kalaiya Provincial Hospital, Bara, Nepal
² Shivanagar Primary Health Care Center, Chitwan, Nepal
³ Military Hospital Itahari, Sunsari, Nepal
⁴ Gaur Provincial Hospital, Rautahat, Nepal
⁵ BP Koirala Institute of Health Sciences, Dharan, Nepal
⁶ Manipal College of Medical Sciences, Pokhara, Nepal
⁷ Nepalese Army Institute of Health Sciences, Kathmandu, Kathmandu, Nepal

Prem Shankar Chaurasiya
Roles: Conceptualization, Formal Analysis, Validation

Shekhar Gurung
Roles: Project Administration, Resources, Supervision

Saurab Karki
Roles: Supervision, Validation, Writing – Review & Editing

Krishna Chandra Mandal
Roles: Data Curation, Investigation

Binod Mehta
Roles: Investigation, Methodology, Software

Dipesh Kumar Rohita
Roles: Formal Analysis, Visualization, Writing – Original Draft Preparation

Babli Mishra
Roles: Formal Analysis, Methodology, Resources

Gopal Kumar Yadav
Roles: Methodology, Supervision

Surakshya Baral
Roles: Resources, Writing – Original Draft Preparation

Suhail Sapkota
Roles: Supervision, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

Article Versions (1)

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Published: 23 Nov 2022, 11:1367

https://doi.org/10.12688/f1000research.125103.1

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Chaurasiya PS, Gurung S, Karki S et al. Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional study [version 1; peer review: 1 approved with reservations, 1 not approved]. F1000Research 2022, 11:1367 (https://doi.org/10.12688/f1000research.125103.1)

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Version 1

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PUBLISHED 23 Nov 2022

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Reviewer Report 24 Apr 2024

Armando García-Guerra, Instituto Nacional de Salud Pública, Morelos, Mexico

Approved with Reservations

https://doi.org/10.5256/f1000research.137372.r240661

General comment:
This article presents an estimate of the prevalence of anemia and some associated factors in women of reproductive age. Due to the high prevalence of anemia reported in the region, it is of interest to know which ... Continue reading

General comment:
This article presents an estimate of the prevalence of anemia and some associated factors in women of reproductive age. Due to the high prevalence of anemia reported in the region, it is of interest to know which characteristics are locally associated with anemia in this population. Comments or questions are invited in each section below to improve the presentation of this article.
Introduction
-In this section you could include the latest information on hemoglobin measurement.
-In addition, you could include in the objective the scenario of the study and mention what kind of factors were measured, i.e. are they individual factors, residential structures, etc., this in order to know what the new contribution of this study is to the evidence on the subject.
Methods
The following information must be given or included:
-Describe the inclusion criteria of the study population, e.g. whether pregnant women were excluded or not.
-Describe the size of the population from which the study sample was drawn.
-Describe the type of person who collected the information, took the blood sample and measured the hemoglobin concentration.
-Indicate whether any adjustments were made to the hemoglobin concentration, e.g. for smoking, local altitude. Read the latest WHO publication on hemoglobin measurement.
Results
The main comment is that they present the estimates through a binary regression model. They did not run a multiple logistic regression model, which provides these associated variables and controls for other variables.
Discussion
-In general, in this section you need a little more order in the ideas and for the paragraphs to be shorter.
-Interpret the findings, considering the population and setting of the study.
-Include the limitations and strengths of the study.
-Indicate why information on the delivery and consumption of iron and folic acid supplements was not collected or measured, as this is a delivery practice that has been in place in the region for many years.
-Revise the paragraph before the conclusion section because it states that this is a longitudinal study, which it is not.
Conclussion
Once the pertinent adjustments have been made, they could rethink the conclusions and assess which of them can be granted based on the findings.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Nutritional epidemiology, maternal and child nutrition, evaluation of social programs.

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.

CITE

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Reviewer Report 05 Mar 2024

Hugo G Quezada-Pinedo, Erasmus MC, University Medical Center Rotterdam,, Rotterdam, The Netherlands

Not Approved

https://doi.org/10.5256/f1000research.137372.r240664

Thank you for the opportunity to review the study: “Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional stud”
The topic is a very interesting, given that anemia stands ... Continue reading

Thank you for the opportunity to review the study: “Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional stud”
The topic is a very interesting, given that anemia stands as a substantial global public health concern, impacting over 2 billion individuals worldwide. As current interventions failed to reduce this burden, there is an imperative for additional studies. These studies are essential to identify local factors contributing to anemia, allowing interventions to be tailored more effectively and addressing the disease burden at a local level.

Major comments:

Methods
The main limitation of the study is the absence of critical variables such as inflammation, (specially for hospital settings), comorbidities and BMI.
Thus, I think the models did not adequately capture the complexity of anemia among women of reproductive age. For example, the model showed contradictory evidence between parity and breastfeeding and did not find evidence with important variables such as income, age and education.

Minor comments:
Methods
Could the authors provide more details about the rationality / related mechanisms to include marital status, breastfeeding, contraception as potential explanatory variables?

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

No

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: fetal programing, anemia, iron deficiency

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

CITE

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Version 1

VERSION 1 PUBLISHED 23 Nov 2022

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Version 1 23 Nov 22	read	read

Hugo G Quezada-Pinedo, Erasmus MC, University Medical Center Rotterdam,, Rotterdam, The Netherlands
Armando García-Guerra, Instituto Nacional de Salud Pública, Morelos, Mexico

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Reviewer Report

2 Views

24 Apr 2024 | for Version 1

Armando García-Guerra, Instituto Nacional de Salud Pública, Morelos, Mexico

2 Views Cite this report Responses(0)

Approved With Reservations

General comment:
This article presents an estimate of the prevalence of anemia and some associated factors in women of reproductive age. Due to the high prevalence of anemia reported in the region, it is of interest to know which characteristics are locally associated with anemia in this population. Comments or questions are invited in each section below to improve the presentation of this article.
Introduction
-In this section you could include the latest information on hemoglobin measurement.
-In addition, you could include in the objective the scenario of the study and mention what kind of factors were measured, i.e. are they individual factors, residential structures, etc., this in order to know what the new contribution of this study is to the evidence on the subject.
Methods
The following information must be given or included:
-Describe the inclusion criteria of the study population, e.g. whether pregnant women were excluded or not.
-Describe the size of the population from which the study sample was drawn.
-Describe the type of person who collected the information, took the blood sample and measured the hemoglobin concentration.
-Indicate whether any adjustments were made to the hemoglobin concentration, e.g. for smoking, local altitude. Read the latest WHO publication on hemoglobin measurement.
Results
The main comment is that they present the estimates through a binary regression model. They did not run a multiple logistic regression model, which provides these associated variables and controls for other variables.
Discussion
-In general, in this section you need a little more order in the ideas and for the paragraphs to be shorter.
-Interpret the findings, considering the population and setting of the study.
-Include the limitations and strengths of the study.
-Indicate why information on the delivery and consumption of iron and folic acid supplements was not collected or measured, as this is a delivery practice that has been in place in the region for many years.
-Revise the paragraph before the conclusion section because it states that this is a longitudinal study, which it is not.
Conclussion
Once the pertinent adjustments have been made, they could rethink the conclusions and assess which of them can be granted based on the findings.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Partly
Are the conclusions drawn adequately supported by the results?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Nutritional epidemiology, maternal and child nutrition, evaluation of social programs.

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.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

2 Views

05 Mar 2024 | for Version 1

Hugo G Quezada-Pinedo, Erasmus MC, University Medical Center Rotterdam,, Rotterdam, The Netherlands

2 Views Cite this report Responses(0)

Not Approved

Thank you for the opportunity to review the study: “Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional stud”
The topic is a very interesting, given that anemia stands as a substantial global public health concern, impacting over 2 billion individuals worldwide. As current interventions failed to reduce this burden, there is an imperative for additional studies. These studies are essential to identify local factors contributing to anemia, allowing interventions to be tailored more effectively and addressing the disease burden at a local level.

Major comments:

Methods
The main limitation of the study is the absence of critical variables such as inflammation, (specially for hospital settings), comorbidities and BMI.
Thus, I think the models did not adequately capture the complexity of anemia among women of reproductive age. For example, the model showed contradictory evidence between parity and breastfeeding and did not find evidence with important variables such as income, age and education.

Minor comments:
Methods
Could the authors provide more details about the rationality / related mechanisms to include marital status, breastfeeding, contraception as potential explanatory variables?

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

No
Are all the source data underlying the results available to ensure full reproducibility?

No
Are the conclusions drawn adequately supported by the results?

No

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

fetal programing, anemia, iron deficiency

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

Respond to this report

Responses (0)

[1] 1. Tolentino K, Friedman JF: An update on anemia in less developed countries. Am. J. Trop. Med. Hyg. 2007; 77(1): 44–51. PubMed Abstract | Publisher Full Text

[2] 2. Yip R, Ramakrishnan U: Experiences and challenges in developing countries. J. Nutr. 2002; 132(4 SUPPL): 827S–830S. Publisher Full Text

[3] 3. Levy JE, Jin O, Fujiwara Y, et al.: Transferrin receptor is necessary for development of erythrocytes and the nervous system. Nat. Genet. 1999 Apr [cited 2022 Oct 22]; 21(4): 396–9. PubMed Abstract | Publisher Full Text

[4] 4. Prasanth R: Prevalence of Anemia in both Developing and Developed Countries around the World. World J. Anemia. 2017 Jun; 1(2): 40–43. Publisher Full Text

[5] 5. Sunuwar DR, Singh DR, Adhikari B, et al.: Factors affecting anaemia among women of reproductive age in Nepal: a multilevel and spatial analysis. BMJ Open. 2021 Mar 1 [cited 2022 Jul 11]; 11(3): e041982.Reference Source

[6] 6. Teshale AB, Tesema GA, Worku MG, et al.: Anemia and its associated factors among women of reproductive age in eastern Africa: A multilevel mixed-effects generalized linear model. PLoS One. 2020 Sep 1 [cited 2022 Jul 11]; 15(9): e0238957. PubMed Abstract | Publisher Full Text

[7] 7. Balarajan Y, Ramakrishnan U, Özaltin E, et al.: Anaemia in low-income and middle-income countries. Lancet. 2011 [cited 2022 Oct 22]; 378(9809): 2123–2135. Publisher Full Text Reference Source

[8] 8. Negi PC, Dev M, Paul P, et al.: Prevalence, risk factors, and significance of iron deficiency and anemia in nonischemic heart failure patients with reduced ejection fraction from a Himachal Pradesh heart failure registry. Indian Heart J. 2018 Dec 1 [cited 2022 Jul 11]; 70(Suppl 3): S182–S188. Publisher Full Text Reference Source

[9] 9. Vibhute N, Shah U, Belgaumi U, et al.: Prevalence and awareness of nutritional anemia among female medical students in Karad, Maharashtra, India: A cross-sectional study. J. Family Med. Prim. Care. 2019 [cited 2022 Jul 11]; 8(7): 2369–2372. PubMed Abstract | Publisher Full Text

[10] 10. Retnakumar C, Chacko M, Ramakrishnan D, et al.: Prevalence of anemia and its association with dietary pattern among elderly population of urban slums in Kochi. J. Family Med. Prim. Care. 2020 [cited 2022 Jul 11]; 9(3): 1533–1537. PubMed Abstract | Publisher Full Text

[11] 11. Teshale AB, Tesema GA, Worku MG, et al.: Anemia and its associated factors among women of reproductive age in eastern Africa: A multilevel mixed-effects generalized linear model. PLoS One. 2020 Sep 1 [cited 2022 Jul 11]; 15(9): e0238957. PubMed Abstract | Publisher Full Text

[12] 12. Mawani M, Aziz AS: Iron Deficiency Anemia among Women of Reproductive Age, an Important Public Health Problem: Situation Analysis. Reprod. Syst. Sex. Disord. 2016; 5(3). Publisher Full Text

[13] 13. Tirore LL, Mulugeta A, Belachew AB, et al.: Factors associated with anaemia among women of reproductive age in Ethiopia: Multilevel ordinal logistic regression analysis. Matern. Child Nutr. 2021 Jan 1 [cited 2022 Jul11]; 17(1): e13063. PubMed Abstract | Publisher Full Text

[14] 14. Zhao A, Zhang Y, Li B, et al.: Prevalence of Anemia and Its Risk Factors Among Lactating Mothers in Myanmar. Am. J. Trop. Med. Hyg. 2014 May 5 [cited 2022 Jul 6]; 90(5): 963–967. PubMed Abstract | Publisher Full Text | Free Full Text

[15] 15. Lakew Y, Biadgilign S, Haile D: Anaemia prevalence and associated factors among lactating mothers in Ethiopia: evidence from the 2005 and 2011 demographic and health surveys. BMJ Open. 2015 [cited 2022 Jul 8]; 5(4): e006001. Publisher Full Text | Free Full Text

[16] 16. Abate TW, Getahun B, Birhan MM, et al.: The urban–rural differential in the association between household wealth index and anemia among women in reproductive age in Ethiopia, 2016. BMC Womens Health. 2021 Dec 1[cited2022Jul6]; 21(1): 311–318. PubMed Abstract | Publisher Full Text

[17] 17. Awoleye AF, Alawode OA, Chima V, et al.: Rural-urban differentials in the relationship between household wealth index and maternal anaemia status in Nigeria.2022 [cited 2022 Jul 11]. Publisher Full Text

[18] 18. Acharya D, Adhikari R, Simkhada P: Prevalence and Determinants of Anaemia among Women aged 15-49 in Nepal: A Trend Analysis from Nepal Demographic and Health Surveys from 2006 to 2016. Asian J. Popul. Sci. 2022 Mar 3; 32–48. Publisher Full Text

[19] 19. Yadav UK, Ghimire P, Amatya A, et al.: Factors Associated with Anemia among Pregnant Women of Underprivileged Ethnic Groups Attending Antenatal Care at Provincial Level Hospital of Province 2, Nepal. Anemia. 2021 [cited 2022 Jul 11]; 2021: 1–9. PubMed Abstract | Publisher Full Text | Free Full Text

[20] 20. Stevens GA, Finucane MM, De-Regil LM, et al.: Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995-2011: a systematic analysis of population-representative data. Lancet Glob. Health. 2013 Sep [cited 2022 Jul 11]; 1(1): e16–e25. Publisher Full Text Reference Source

[21] 21. Daru J, Zamora J, Fernández-Félix BM, et al.: Risk of maternal mortality in women with severe anaemia during pregnancy and post partum: a multilevel analysis. Lancet Glob. Health. 2018 May 1 [cited 2022 Jul 11]; 6(5): e548–e554. PubMed Abstract | Publisher Full Text

[22] 22. Gebremedhin S, Asefa A: Association between type of contraceptive use and haemoglobin status among women of reproductive age in 24 sub-Saharan Africa countries. BMJ Sex Reprod Health. 2018 Jan 1 [cited 2022 Jul 11]; 45(1): 54–60.Reference Source

[23] 23. Teshome AA, Berra WG, Huryi AF: Modern Contraceptive Methods Predict Hemoglobin Levels Among Women of Childbearing Age from DHS 2016. Open Access J. Contracept. 2022 Jan [cited 2022 Jul 11]; 13: 1–8. PubMed Abstract | Publisher Full Text

[24] 24. Farooq A, Rauf S, Hassan U, et al.: IMPACT OF MULTIPARITY ON IRON CONTENT IN MULTIPAROUS WOMEN. J. Ayub Med. Coll. Abbottabad. 2011; 23.Reference Source

[25] 25. Imai K: Parity-based assessment of anemia and iron deficiency in pregnant women. Taiwan. J. Obstet. Gynecol. 2020 Nov 1; 59(6): 838–841.

[26] 26. Al-Farsi YM, Brooks DR, Werler MM, et al.: Effect of high parity on occurrence of anemia in pregnancy: A cohort study. BMC Pregnancy Childbirth. 2011 Jan 20 [cited 2022 Jul 11]; 11(1): 1–7. PubMed Abstract | Publisher Full Text

[27] 27. Chaurasiya PS, Gurung S, Karki S, et al.:Data anemia Rautahat v3wra.xlsx (Version 4). figshare. [Dataset].2022. Publisher Full Text

Prevalence of anemia and its associated factors among women of reproductive age group attending Gaur Provincial Hospital: A cross-sectional study

Abstract

Keywords

Introduction

Methods

Ethical consideration

Study design and setting

Participants, sample size, and sampling methods

Statistical analysis

Results

Table 1. Basic characteristics of women of reproductive age group.

Table 2. Anemia among women of reproductive age group.

Table 3. Factors affecting anemia among women of reproductive age group.

Discussion

Conclusion

Consent

Data availability

Underlying data

Extended data

Reporting guidelines

Acknowledgments

References

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