<?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.133136.1</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>Determinants of fruit consumption in adult women in Indonesia</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 2 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Malkan Bakhrul Ilmi</surname>
                        <given-names>Ibnu</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/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-5946-6660</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>Nur Hasan Syah</surname>
                        <given-names>Muhammad</given-names>
                    </name>
                    <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>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Wahyuningsih</surname>
                        <given-names>Utami</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</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="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Crosita Octaria</surname>
                        <given-names>Yessi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</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="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Nutrition Study Program, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, Special Capital Region of Jakarta, 12450, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:ibnuilmi@upnvj.ac.id">ibnuilmi@upnvj.ac.id</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>5</day>
                <month>7</month>
                <year>2023</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2023</year>
            </pub-date>
            <volume>12</volume>
            <elocation-id>783</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>9</day>
                    <month>6</month>
                    <year>2023</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Malkan Bakhrul Ilmi I et al.</copyright-statement>
                <copyright-year>2023</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/12-783/pdf"/>
            <abstract>
                <p>
                    <bold>Background:</bold> Fruit consumption in Indonesia is low, while diet related diseases are climbing, including among adult women where obesity prevalence is the highest. This study aimed to analyze determinants of fruit consumption among adult women aged 19&#x2013;49 years in the country. 
                    <bold>Methods:</bold> Analysis was done to secondary data on food consumption obtained from a cross sectional survey of the national Basic Health Research 2010. The potential determinants analyzed were nutritional status (body mass index, BMI), age, formal education, marital status, economic status (quintile), and region. The logistic regression model was applied. 
                    <bold>Results:</bold> The results showed that adult women in Indonesia had higher odds of consuming more fruits if they were with higher BMI (OR BMI &gt; 25=1.093, CI:1.026&#x2013;1.165), in the older age group (OR middle-aged adult=1.079, CI:1.013&#x2013;1.150), had higher educational status (OR completed elementary School or higher=2.070, CI:1.909&#x2013;2.244), from higher economic status (OR high=2.258, CI:2.112&#x2013;2.413), and resided in urban regions (OR urban area=1.305, CI:1.230&#x2013;1.385). Meanwhile, being married appeared to hinder fruit consumption (OR=0.915, CI:0.849&#x2013;0.986). 
                    <bold>Conclusions:</bold> Fruit consumption among adult women in Indonesia showed disparities between socioeconomic and sociodemographic characteristics. Thus intervention to improve fruit consumption should involve improving nutritional knowledge, especially among those with lower level of consumption (
                    <italic toggle="yes">e.g</italic> married women), as well as improving access and availability of fruit for women from lower socioeconomic status and rural areas. This could include the use of locally available fruits that is less expensive and more accessible.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Adult</kwd>
                <kwd>Consumption</kwd>
                <kwd>Fruit</kwd>
                <kwd>Risk Factor</kwd>
                <kwd>Women</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>Universitas Pembangunan Nasional Veteran Jakarta</funding-source>
                    <award-id>731/UN61.0/HK.02/2021</award-id>
                </award-group>
                <funding-statement>We wish to thank Universitas Pembangunan Nasional (UPN) Veteran Jakarta for the kind financial support to this research (Grant number 731/UN61.0/HK.02/2021 to Ibnu Malkan Bakhrul Ilmi). </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="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>Easy access and advanced information push modern society to lead a life that dominantly involves mild activities and consume fast food with high fat, sugar, salt, and low fiber (
                <xref ref-type="bibr" rid="ref40">WHO, 2002</xref>). Based on 
                <xref ref-type="bibr" rid="ref46">WHO review (2021)</xref>, such meal plans increase the risk of having obesity and non-infection diseases.</p>
            <p>In Indonesia, the prevalence of obesity is considerably high, especially for adult women. In 2010, the prevalence percentage of adult women with obesity presented 15.4% (
                <xref ref-type="bibr" rid="ref27">Ministry of Health, 2010</xref>) and considered higher numbers in 2013 with 32.9% (
                <xref ref-type="bibr" rid="ref28">Ministry of Health, 2013</xref>). Obesity prevalence is higher in urban areas compared to rural areas, and the number of women affected by obesity is higher compared to their male counterparts (
                <xref ref-type="bibr" rid="ref28">Ministry of Health, 2013</xref>). Based on the 
                <xref ref-type="bibr" rid="ref44">WHO report (2020)</xref>, 73% of deaths in Indonesia happen due to non-infectious diseases. One of the non-infectious diseases that contribute to the highest numbers of death in Indonesia is diabetes mellitus (DM), according to the 
                <xref ref-type="bibr" rid="ref47">Ministry of Health of Indonesia (2020)</xref>. Diabetes mellitus can happen to anyone, though the higher risk applies from adults to elders, and can reduce life expectancy (
                <xref ref-type="bibr" rid="ref23">Magliano 
                    <italic toggle="yes">et al.,</italic> 2018</xref>). Diabetes mellitus can also affect workers&#x2019; productivity, as workers who have diabetes mellitus have lower productivity than those who do not (
                <xref ref-type="bibr" rid="ref36">Tabano 
                    <italic toggle="yes">et al.,</italic> 2018</xref>). Diabetes mellitus can consecutively decrease the productivity-adjusted life years (PALY) for 11.6% in men and 10.5% in women (
                <xref ref-type="bibr" rid="ref23">Magliano 
                    <italic toggle="yes">et al.</italic>, 2018</xref>). Also, based on the 
                <xref ref-type="bibr" rid="ref2">American Diabetes Association (2018)</xref>, workers who have diabetes mellitus have higher cost burdens. Diabetes economic cost in the US based on the calculation from direct medical costs and reduced productivity costs, increased by 26% in 5 years (2012&#x2013;2017) due to the increased prevalence of diabetes mellitus.</p>
            <p>To prevent obesity and non-infectious diseases, consuming a sufficient quantity of fruits helps. Fruits are good to avoid weight gain (
                <xref ref-type="bibr" rid="ref7">Bes-Rastrollo 
                    <italic toggle="yes">et al.</italic>, 2006</xref>) and helps to reduce blood low-density lipoprotein cholesterol (
                <xref ref-type="bibr" rid="ref22">Djouss&#x00e9; 
                    <italic toggle="yes">et al.</italic>, 2004</xref>), chronic disease risks (
                <xref ref-type="bibr" rid="ref33">Riboli and Norat, 2003</xref>), cardiovascular disease risks (
                <xref ref-type="bibr" rid="ref11">Dauchet 
                    <italic toggle="yes">et al.</italic>, 2006</xref>), cancer risks (
                <xref ref-type="bibr" rid="ref29">Pavia 
                    <italic toggle="yes">et al.</italic>, 2006</xref>; 
                <xref ref-type="bibr" rid="ref8">Boffetta 
                    <italic toggle="yes">et al.</italic>, 2010</xref>), and help to enhance women&#x2019;s bone health (
                <xref ref-type="bibr" rid="ref24">McGartland 
                    <italic toggle="yes">et al.</italic>, 2004</xref>).</p>
            <p>According to 
                <xref ref-type="bibr" rid="ref41">WHO (2003)</xref> and Ministry of Health Republic Indonesia (2014), the advised balanced nutrition guide to consuming fruits and vegetables is 400 grams/person/day. Among those numbers, 150 grams are fruits. In general, fruits contain phytonutrients, potassium, and fibers that help fight against non-infectious chronic diseases (
                <xref ref-type="bibr" rid="ref41">WHO, 2003</xref>). On the other hand, having less than five portions of fruits and vegetables per day affects a higher rate of deaths (Bellavia, 2013). In Indonesia, as much as 93.6% of the population aged 10 years old or more have fruits and vegetable consumption deficiency (
                <xref ref-type="bibr" rid="ref26">Ministry of Health, 2007</xref>). There are many factors that determine a person&#x2019;s consumption of fruit, including: sensory factors, social interactions, fruit price, time, personal principles, media and health advertising (
                <xref ref-type="bibr" rid="ref31">Pollard 
                    <italic toggle="yes">et al.</italic>, 2003</xref>).</p>
            <p>So far, there has been no national-scale research that analyzes determinants of fruit consumption in Indonesia for adult women, a socio-demographic with the highest prevalence of obesity in Indonesia. Thus, this research aims to analyze the determinants of fruit consumption for adult people aged from 19&#x2013;49 years old.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <sec id="sec3">
                <title>Data source and subject</title>
                <p>This research uses secondary data from Basic Health Research 2010, collected by Health Research and Development Agency, Ministry of Health, Republic of Indonesia. Basic Health Research 2010 uses a cross-sectional study design. Data has been collected from May 2010 to August 2010 by professionals. This analysis of research of fruit determinant factors was conducted from May 2021 to June 2021 in Universitas Pembangunan Nasional (UPN) Veteran Jakarta. This study was approved by Ethical Approval Involving Human Respondents Universitas Pembangunan Nasionan UPN Veteran Jakarta (Protocol number: 02/UN61/PT.01.06/2021).</p>
                <p>This research follows Basic Health Research 2010 method to collect sampling numbers and methods. The Basic Health Research data collected in 2010 comes from 441 regions/cities among 33 provinces. The numbers of households were 69,300, the number of household members were 251,388, and the number of women aged 19&#x2013;49 years old were 54,178. The cleaning of data was conducted by eliminating subjects that have no height data (143 people), weight data (135 people), food consumption data (228 people), and pregnancy status data (466 people). We eliminated subjects with calorie intakes numbers of &lt;0.3 and &gt;0.3 times to basal energy (536 people), nutrients adequacy of &gt;400% (635 people), body mass index (BMI) of &lt;12.5 and BMI of &gt;40 (123 people) and unusual consumption (1292 people). The total subjects were 50,620 adult women.</p>
            </sec>
            <sec id="sec4">
                <title>The types of data and methods of data</title>
                <p>From the Basic Health Research e-file in 2010, the collected data consists of individual characteristics, economic status characteristics, anthropometric, and food consumption. The individual characteristic data consists of age, origin, education, and jobs. The anthropometric data uses weight and height. The food consumption data uses fruits types and numbers of consumed fruits.</p>
            </sec>
            <sec id="sec5">
                <title>The processing of data and analyses of data</title>
                <p>Data processing was conducted after data cleaning. The cleaned data was used to calculate the total grams of fruit consumption and to create new variables or derivatives. The bivariate analysis uses the chi-square test to see the correlations of food consumption level to nutritional status, education, region, jobs, and economic status. The overview of the variables and their descriptions are presented in 
                    <xref ref-type="table" rid="T1">Table 1</xref>, and t test used for calculating the average gram per capita per day in fruit consumption and the difference between groups.</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>Table 1. </label>
                    <caption>
                        <title>Variable description for multiple regression model.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Variable name</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Description</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="top">Dependent variable</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x03c0; (x)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Fruit consumption probabilities [0=consumption &lt;75 g/day, 1=consumption &#x2265;75 g/day]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="2" rowspan="1" valign="top">Independent variable</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Nutritional status [0=BMI&lt;25, 1=BMI&#x2265;25]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Age [0=young adult (19&#x2013;29 years old), 1= middle-aged adult (30&#x2013;49 years old)]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Education [0=Elementary school, 1&#x2265;Elementary school]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Marital status [0=single, 1=married]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Jobs [0=unemployed, 1=employed]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Income [0=quintile 1 to 2, 1=quintile 3 to 5]</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">X7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Region type [0=rural, 1=urban]</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>BMI = Body Mass Index.</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>The cutoff point used for fruits was 75 g/day or half of fruit consumption recommendation based on balanced nutrients guidelines (150 g/day). This was because the average number of fruit consumption in Indonesia only reaches up to 76.4 g/day (
                    <xref ref-type="bibr" rid="ref27">Ministry of Health, 2010</xref>). Thus, to analyze the cut-off point, the number of recommended consumptions should be lowered to half point. The multiple logistic regression analysis was used to know the determinant factors of fruit consumption in adult women. All data cleaning and statistical analysis were done using the IBM 
                    <ext-link ext-link-type="uri" xlink:href="https://www.ibm.com/products/spss-statistics">SPSS</ext-link> version 17. The multiple regression model applied in the research is shown below:
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                    </disp-formula>
                </p>
            </sec>
        </sec>
        <sec id="sec6" sec-type="results|discussion">
            <title>Results and discussion</title>
            <p>The analysis results show that the number of adult women in Indonesia who consume less than half of the fruit consumption recommendation reaches 88%. Socioeconomic characteristic consists of nutritional status, age, education, marital status, jobs, economic status, and region type as shown in 
                <xref ref-type="table" rid="T2">Table 2</xref>.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Socioeconomic characteristics.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="3" valign="top">Socioeconomic characteristics</th>
                            <th align="left" colspan="4" rowspan="1" valign="top">Fruit consumption</th>
                            <th align="left" colspan="1" rowspan="3" valign="top">
                                <italic toggle="yes">X</italic>
                                <sup>2</sup> test (p&lt;0.05)
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </th>
                        </tr>
                        <tr>
                            <th align="left" colspan="2" rowspan="1" valign="top">&lt;75 g/day (n=46118)</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">&#x2265;75 g/day (n=5665)</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">n</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">N</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">%</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Nutritional status</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI&lt;25</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33887</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">65.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3989</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.7</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI&#x2265;25</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12231</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23.6</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1676</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.2</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Age</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Young adult (19&#x2013;29 years old)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16871</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">32.6</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1992</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.8</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.036</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Middle-aged adult (30&#x2013;49 years old)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">29247</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">56.5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3673</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.2</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Education</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Elementary school</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">42828</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">82.7</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4667</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.0</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Elementary school and higher</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3290</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">998</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.9</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Marital status</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8562</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1174</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.3</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Married</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">37556</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">72.5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4491</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.7</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Jobs</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Unemployed</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19727</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">38.1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2325</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.5</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.013</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Employed</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26391</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">51.0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3340</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.4</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Economic status</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Low (quintile 1&#x2013;2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20659</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">39.9</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1328</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.6</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Upper middle (quintile 3&#x2013;5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25459</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">49.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4337</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.4</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Region type</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Rural</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">22532</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">43.5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2103</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.1</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Urban</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23586</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45.5</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3562</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.9</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>BMI=Body Mass Index.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>*</label>
                            <p>Chi Square test sig&lt;0.05.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>
                <xref ref-type="table" rid="T2">Table 2</xref> shows that women with BMI&lt;25 tend to consume fruits less than 75 g/day (65.4% of all women). Both young adults (32.6% of all women) and middle-aged women (56.5% of all women) tend to consume fruits less than 75 g/day. This showed that fruits consumption in women in Indonesia is low. In addition, women who have elementary school education (82.7% of all women) and are married (72.5% of all women) tend to consume fruits less than 75 g/day. Higher percentage of women who are employed (6.4% of all women) consume more than 75 g/day of fruit compared to only 4.5% of all women among women who are unemployed. More women who are coming from the upper middle-income bracket and those living in urban areas consume fruits more than 75 g/day.</p>
            <p>As it was mentioned earlier, the average number of fruit consumption in Indonesia only reaches up to 76.4 g/day (
                <xref ref-type="bibr" rid="ref27">Ministry of Health, 2010</xref>). This average consumption per capita is even lower among adult women, which was only around 23 g/day. The t test results presented in 
                <xref ref-type="table" rid="T3">Table 3</xref> showed that all socio demographic characteristics significantly correlated to total average consumption of fruit per capita per day. Total average consumption of fruit among women with BMI&gt;25 kg/m
                <sup>2</sup>, older women aged 30&#x2013;49 years old, women with higher education of elementary school or higher, women who are single and employed, women coming from upper middle quintile of income bracket as well as women living in urban areas all show significantly higher average of fruit consumption per capita per day. Sadly, despite fruit consumption being significantly higher among these sociodemographic groups, the total average was very low compared to the national recommendation of 150 g/day and only one third of the national average of fruit consumption which is around 76 g/day. In addition, the calculation also showed very high standard deviation. Thus, caution should be applied in reading the result which indicates low consumption and large disparities.</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>The average fruit consumption (g/capita/day) and standard deviation based on the socioeconomic characteristic of adult women aged 19&#x2013;49 years old.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Socioeconomic characteristic</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Average</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Standard deviation</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">T-Test
                                <xref ref-type="table-fn" rid="tfn2">*</xref>
                            </th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Nutritional status</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI&lt;25</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">22.80</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">77.14</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI&#x2265;25</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">24.81</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">79.37</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Age</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Young adult (19-29 years old)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">22.44</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">74.50</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Middle-aged adult (30-49 years old)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">23.85</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">79.55</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Education</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Elementary school</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20.12</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">70.00</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Elementary school and higher</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">58.96</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">131.71</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Marital status</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26.76</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">84.33</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Married</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">22.55</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">76.12</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Jobs</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Unemployed</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21.34</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">70.99</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Employed</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">24.82</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">82.38</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Economic status</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Low (quintile 1-2)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.35</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">47.57</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Upper middle (quintile 3-5)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">32.19</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">93.02</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Region type</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Rural</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.11</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.68</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Urban</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">40.03</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">98.44</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>BMI=Body Mass Index.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn2">
                            <label>*</label>
                            <p>T-Test sig&lt;0.05.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>Multiple logistic regression results showed (
                <xref ref-type="table" rid="T4">Table 4</xref>) that adult women in Indonesia had higher odds of consuming more fruits if they were with higher BMI (OR BMI&gt;25=1.093, CI: 1.026&#x2013;1.165), in the older age group (OR middle-aged adult=1.079, CI: 1.013&#x2013;1.150), had higher educational status (OR completed elementary School or higher=2.070, CI: 1.909&#x2013;2.244), from higher economic status (OR high=2.258, CI: 2.112&#x2013;2.413), and residing in urban regions (OR urban area=1.305, CI: 1.230&#x2013;1.385). Meanwhile, being married appeared to hinder fruits consumption (OR=0.915, CI: 0.849&#x2013;0.986).</p>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>Table 4. </label>
                <caption>
                    <title>The determinant factors of higher fruit consumption in adult women age 19&#x2013;49 years old in Indonesia.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variable</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">B</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P value</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">OR (95% CI)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Constant</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">-2.877</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Nutritional status</bold> (1=BMI&#x2265;25, 0=BMI&lt;25)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.089</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.006</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.093 (1.026&#x2013;1.165)
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Age</bold> (1=Middle-aged adult, 0=young adult)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.076</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.018</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.079 (1.013&#x2013;1.150)
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Education</bold> (1&#x2265;Elementary school, 0=Elementary school)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.728</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.070 (1.909&#x2013;2.244)
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Marital status</bold> (1=Married, 0=Single)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">-0.089</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.020</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.915 (0.849&#x2013;0.986)
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Jobs</bold> (1=Employed, 0=Unemployed)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">-0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.961</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.999 (0.942&#x2013;1.058)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Economic status</bold> (1=Upper middle, 0=Low)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.814</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.258 (2.112&#x2013;2.413)
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">
                                <bold>Region type</bold> (1=Urban, 0=Rural)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.266</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.305 (1.230&#x2013;1.385)
                                <xref ref-type="table-fn" rid="tfn3">*</xref>
                            </td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>BMI=Body Mass Index, OR=Odd Ratio, CI=Confidence Interval.</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn3">
                            <label>*</label>
                            <p>Significant (p&lt;0.05).</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>Our findings showed a similar picture in comparison to previous studies regarding the topic. In the USA, a study on consumption pattern among different socioeconomic groups and demographics showed that consumption of fruit and fruit juices are higher among more affluent communities and among those with active lifestyles (
                <xref ref-type="bibr" rid="ref12">Deshmukh-Taskar 
                    <italic toggle="yes">et al.,</italic> 2007</xref>). Regarding the correlation between education level and fruit consumption, it is assumed that people with higher education levels have better knowledge and awareness to consume healthier foods (
                <xref ref-type="bibr" rid="ref45">Elfhag, 2008</xref>). Having a good understanding of nutrition significantly relates to fruit and vegetable consumption (
                <xref ref-type="bibr" rid="ref39">Wardle, Parmenter &amp; Waller, 2000</xref>). On the other hand, an individual with lower education may be less likely to consume fruit every day (
                <xref ref-type="bibr" rid="ref17">Giskes 
                    <italic toggle="yes">et al.,</italic> 2008</xref>) which affects low fruit and vegetable consumption (
                <xref ref-type="bibr" rid="ref10">Darmon &amp; Drewnowski, 2008</xref>). The research result of 
                <xref ref-type="bibr" rid="ref14">Dynesen 
                    <italic toggle="yes">et al.</italic> (2003)</xref> shows that adult women with higher education levels and those who live with two members at the house both have higher frequencies of consuming fruits.</p>
            <p>In contrast to reviews from 
                <xref ref-type="bibr" rid="ref1">Ab Karim 
                    <italic toggle="yes">et al.</italic> (2012)</xref> which shows that marital status has a significant and positive impact on fruit and vegetable consumption, our study showed the opposite where being single was correlated with significantly higher fruit intake. Married people tend to have a higher income than those who are single or those who are unmarried (
                <xref ref-type="bibr" rid="ref16">Friel 
                    <italic toggle="yes">et al.,</italic> 2005</xref>). Research by 
                <xref ref-type="bibr" rid="ref30">Pollard 
                    <italic toggle="yes">et al.</italic> (2001)</xref> shows that being married and having smaller number of members living in one house share a positive impact on fruit consumption level, while the mixed result are shown with children. In our case, it is likely that importance of body image and higher agency of choosing better diet may contribute to the higher intake of fruits among unmarried adult women in Indonesia.</p>
            <p>The multivariate test result shows that job status is not significant as fruit consumption determinants. The research result from 
                <xref ref-type="bibr" rid="ref37">Shohaimi (2004)</xref> shows there are strong and independent relations between a social class of work and education level to fruit consumption. Women from lower working social class and have less educational background have less fruit consumption. These findings link to higher awareness of the benefits of consuming fruits (
                <xref ref-type="bibr" rid="ref25">McIntosh 
                    <italic toggle="yes">et al.</italic>, 1990</xref>). The effect of peer pressure in the workplace are considered non-significant (
                <xref ref-type="bibr" rid="ref37">Shohaimi, 2004</xref>).</p>
            <p>Our findings show that in adult women with low economic status, the fruit consumption level is lower than upper-middle-class women. This is in line with research on adolescents (
                <xref ref-type="bibr" rid="ref34">Riediger 
                    <italic toggle="yes">et al.</italic>, 2007</xref>). Both populations in the USA (
                <xref ref-type="bibr" rid="ref35">Rose &amp; Richards, 2004</xref>) and Canada (
                <xref ref-type="bibr" rid="ref34">Riediger 
                    <italic toggle="yes">et al.</italic>, 2007</xref>) show that higher family economic status showed higher fruit and vegetable diet than those with lower economic status. People with lower economic status tend to spend their income for basic needs than for fruits and vegetables, as may be considered as non-beneficial products (
                <xref ref-type="bibr" rid="ref1">Ab Karim 
                    <italic toggle="yes">et al.,</italic> 2012</xref>). Research in the UK also shows that fruit and vegetable consumption or healthy food in general are considered costly (
                <xref ref-type="bibr" rid="ref38">Thompson, 2008</xref>). Based on research held by 
                <xref ref-type="bibr" rid="ref42">WHO (2005)</xref>, the cost of fruits and vegetables had a negative impact on the consumption of fruits for both people with higher and lower incomes. In line with this, Indonesia has similar condition, as a case study from 
                <xref ref-type="bibr" rid="ref19">Hartini 
                    <italic toggle="yes">et al.</italic> (2003)</xref> shows that fruit consumption in women in urban areas are higher than in women in rural areas. Thus, systematic education and transformation in the food system to change this point of view is needed.</p>
            <p>Residing area types also influence the consumption of fruits. Our study found that women who live in rural areas have lower levels of consumption than those who live in urban areas. 
                <xref ref-type="bibr" rid="ref18">Gustafson 
                    <italic toggle="yes">et al.</italic> (2007)</xref> reports that there are different numbers of fruit and vegetable consumption between people who live in rural areas to urban areas. This is also related to different job statues and workloads from both areas (
                <xref ref-type="bibr" rid="ref13">Devine 
                    <italic toggle="yes">et al.,</italic> 2003</xref>), despite the assumption that in urban areas, the probabilities of increased price impact to low demand, the availability and accessibility to various type of fruits may result in increased consumption (
                <xref ref-type="bibr" rid="ref42">WHO, 2005</xref>).</p>
            <p>This research used a cross-sectional study from the Basic Health Research 2010, collected by Health Research and Development Agency of the Ministry of Health of Indonesia, and has limited views to differentiate cause and effects in variables. Furthermore, it used 24 hours recall calculating data about food consumption, which gives less detailed food consumption habits. However, this research generally shows results that are in line with other previous works.</p>
        </sec>
        <sec id="sec7">
            <title>Conclusions and suggestions</title>
            <sec id="sec8">
                <title>Conclusions</title>
                <p>The study examined the determinants of fruit consumption among adult women in Indonesia. The finding revealed that fruit consumption among adult women in Indonesia remains low, with nutritional status, age, education level, and income as the determinants of adequate fruit consumption. Based on this research, fruit consumption can elevate in several ways. This includes upgrading information related to nutrition and improving the availability of fruits in each area at an affordable price. Health promotion interventions to scale up fruit consumption should pay attention to the factors identified in this study. The results of this study are expected to provide input to existing government policies. The Indonesian government so far has had guidelines for fruit consumption for the community, but it must continue to be socialized regarding this matter in increasing fruit consumption. Further research is necessary to analyze other determinant factors related to fruit consumption.</p>
            </sec>
        </sec>
    </body>
    <back>
        <sec id="sec11" sec-type="data-availability">
            <title>Data availability</title>
            <p>The data of this study are from the Indonesian Ministry of Health. The data can be obtained trough the following process:
                <list list-type="order">
                    <list-item>
                        <label>1.</label>
                        <p>Submit an application and proposal to the Indonesian Ministry of Health Balitbangkes (
                            <ext-link ext-link-type="uri" xlink:href="https://www.badankebijakan.kemkes.go.id/">https://www.badankebijakan.kemkes.go.id/</ext-link>)</p>
                    </list-item>
                    <list-item>
                        <label>2.</label>
                        <p>Assessment of proposals by the data owner of the Indonesian Ministry of Health&#x2019;s Balitbangkes</p>
                    </list-item>
                    <list-item>
                        <label>3.</label>
                        <p>If approved, raw data are given according to what is needed in the research</p>
                    </list-item>
                    <list-item>
                        <label>4.</label>
                        <p>Authors are required to sign disclaimer which prohibits data sharing by data owner (Indonesian Ministry of Health Balitbangkes) and only allowed to share results of analysis
</p>
                    </list-item>
                </list>
            </p>
        </sec>
        <ack>
            <title>Acknowledgements</title>
            <p>We thank Arini Nurul Fikri who has supported accessing and processing data and the Ministry of Health, Republic of Indonesia for data support.</p>
        </ack>
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    <sub-article article-type="reviewer-report" id="report226104">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.146111.r226104</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>DIANA</surname>
                        <given-names>RIAN</given-names>
                    </name>
                    <xref ref-type="aff" rid="r226104a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-9708-2449</uri>
                </contrib>
                <aff id="r226104a1">
                    <label>1</label>Department of Nutrition, Universitas Airlangga, Surabaya, East Java, Indonesia</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>18</day>
                <month>12</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 DIANA R</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport226104" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.133136.1"/>
            <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>Comments to authors: 
                <list list-type="order">
                    <list-item>
                        <p>Title: This study analyzed socioeconomic factors as determinants of fruit consumption. Therefore, a more specific title would be more appropriate.</p>
                    </list-item>
                    <list-item>
                        <p>It is advisable to use references from the last three to five years due to the abundance of relevant studies conducted in low, middle, and high-income countries.</p>
                    </list-item>
                    <list-item>
                        <p>Introduction: 
                            <list list-type="order">
                                <list-item>
                                    <p>In the introduction, it would be helpful to include information about global fruit consumption, particularly in low and middle-income countries. Comparing Indonesia's situation to these nations can provide insight into the current scenario. This comparison helps readers understand that the issue of low fruit consumption is widespread, affecting numerous countries, including Indonesia.</p>
                                </list-item>
                                <list-item>
                                    <p>Low fruit and vegetable intake is a risk factor for non-communicable diseases. This study, in particular, emphasizes fruit consumption. Hence, it is imperative to provide a robust rationale for the exclusive focus on fruit consumption in this investigation</p>
                                </list-item>
                            </list> </p>
                    </list-item>
                    <list-item>
                        <p>Results &amp; Discussion: 
                            <list list-type="order">
                                <list-item>
                                    <p>In the methods section, it is explicitly indicated that fruit consumption was acquired via a 24-hour recall. As a result, this investigation allows delineating details regarding the specific fruits (fruits types) commonly consumed in dietary practices, thereby allowing the manuscript to provide a more comprehensive understanding of the quantity and predominant varieties of fruits ingested by adult women. This, in turn, facilitates a nuanced examination of nutritional compositions and underpins strategies aimed at fostering fruit consumption that is more attuned to the preferences and socioeconomic conditions of adult women.</p>
                                </list-item>
                                <list-item>
                                    <p>Please provide information on the prevalence of adequate fruit consumption (150 g/day) among adult women, followed by the prevalence of half of the recommended intake (75 g/day), to emphasize the magnitude of the issue.</p>
                                </list-item>
                                <list-item>
                                    <p>Table 3 shows a standard deviation exceeding the mean, signifying a non-normal distribution of the data. Therefore, the use of parametric statistics is considered unsuitable for this dataset. It is advisable to consider employing non-parametric methods when presenting results and conducting inferential analysis.</p>
                                </list-item>
                                <list-item>
                                    <p>Please check the decimal numbers. The total percentage should be 100%, but several data points do not sum up to 100%, including nutritional status (99%), age (100.1%), education, etc.</p>
                                </list-item>
                                <list-item>
                                    <p>When presenting a p-value of 0.000, it should be expressed as p &lt; 0.001.</p>
                                </list-item>
                                <list-item>
                                    <p>Please provide information on how fruit consumption could benefit adult women. Specifically, elaborate on the nutritional content of fruits that can confer these benefits, especially in preventing non-communicable diseases as mentioned in the introduction.</p>
                                </list-item>
                                <list-item>
                                    <p>Kindly provide a comprehensive discussion of the association between fruit consumption and factors, including income, education, urban residency, marital status, and BMI. Consider these factors comprehensively rather than as individual components. Additionally, explore whether income and educational attainment demonstrate a more robust correlation or serve as the main predictors for fruit consumption when contrasted with other socioeconomic variables. &#x00a0;</p>
                                </list-item>
                            </list> </p>
                    </list-item>
                    <list-item>
                        <p>Strength and limitation. This study utilizes data from the 2010 Basic Health Survey, which was conducted 13 years ago. Therefore, it is necessary to address the strengths and limitations of the study and explain why this data was chosen. Is the current situation still relevant? Are there no more recent data available for use,</p>
                    </list-item>
                    <list-item>
                        <p>Conclusions &amp; suggestions: Low fruit consumption was identified in this study. Please rephrase the implications to align with the findings. How can the government develop strategies to increase fruit consumption among adult women? Which characteristics of adult women need enhancement to increase their fruit consumption?</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>No</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>Community Nutrition</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>
    <sub-article article-type="reviewer-report" id="report184683">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.146111.r184683</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
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                    <name>
                        <surname>Fikri</surname>
                        <given-names>Al Mukhlas</given-names>
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                </contrib>
                <aff id="r184683a1">
                    <label>1</label>Departement of Nutrition, Faculty of Health Sciences, University of Singaperbangsa Karawang, Karawang Regency, West Java, Indonesia</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>11</day>
                <month>7</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Fikri AM</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport184683" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.133136.1"/>
            <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>This study analyzed and found an interesting result using a huge data from national study. However, several points below must be clarified before its indexing:&#x00a0; 
                <list list-type="order">
                    <list-item>
                        <p>The used data were from a survey in 2010. It is too old.</p>
                    </list-item>
                    <list-item>
                        <p>Abstract must consist of the number of involved subjects.</p>
                    </list-item>
                    <list-item>
                        <p>Several presented data in introduction are also too old.</p>
                    </list-item>
                    <list-item>
                        <p>Introduction does not include the reasons of why this study evaluated on adult women.</p>
                    </list-item>
                    <list-item>
                        <p>Please provide some literature supporting your speculation regarding the reason for unmarried women having higher fruit consumption.</p>
                    </list-item>
                    <list-item>
                        <p>Please also provide the reason why women who live in rural have lower levels of consumption. The reason of the result of BMI correlation with fruit consumption also needs to be discussed.&#x00a0;</p>
                    </list-item>
                </list>
            </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>Yes</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>Food and Nutrition</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>
