Minimum Dietary Diversity and Associated Factors Among Pregnant Women of Chepang Community in Nepal: A Community-Based Cross-Sectional Study

Minimum Dietary Diversity and Associated Factors Among Pregnant Women of Chepang Community in Nepal: A Community-Based Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Minimum Dietary Diversity and Associated Factors Among Pregnant Women of Chepang Community in Nepal: A Community-Based Cross-Sectional Study Samundra Lagun, Krishna Prasad Sapkota, Jagat Prasad Upadhyay, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6733246/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Adequate dietary diversity consumption during pregnancy is crucial for maternal and fetal health outcomes. Women from marginalized communities often face increased nutritional risks due to socioeconomic barriers. This study aimed to assess the prevalence of minimum dietary diversity and its associated factors among pregnant women of the Chepang community in Nepal. Methods: A community-based cross-sectional quantitative study was conducted among 281 randomly selected pregnant Chepang women across four districts (Gorkha, Dhading, Makawanpur, and Chitwan) in Nepal, from September to October 2024. Proportionate random sampling was used to select participants. Data was collected through face-to-face interviews using pretested structured questionnaires incorporating FAO’s Minimum Dietary Diversity for Women (MDD-W) guidelines. Descriptive statistics and inferential statistics involving bivariate and multivariate logistic regression analysis were performed to identify factors associated with minimum dietary diversity. Results: The prevalence of adequate minimum dietary diversity was 33.5% (95% CI: 28.0-39.3%) among the study participants. The mean (±SD) dietary diversity score was 3.88 (±1.364). In multivariate analysis, women with basic and secondary education (AOR = 9.02, 95% CI: 3.23-25.18), those consuming ≥4 meals per day (AOR = 2.88, 95% CI: 1.06-7.82), and those receiving husband support (AOR = 10.97, 95% CI: 3.17-37.97) were significantly more likely to achieve adequate dietary diversity. Conclusion: The prevalence of minimum dietary diversity among pregnant Chepang women was notably low. Interventions should focus on improving women's educational status, promoting adequate meal frequency, and engaging male partners in supporting dietary practices to enhance nutritional outcomes in this marginaliz1`ed indigenous community. Minimum dietary diversity Pregnant women Indigenous population Chepang community Nepal Figures Figure 1 Introduction Maternal nutrition represents a critical global health challenge with profound implications for both the maternal and child well-being. The physiological demands of pregnancy significantly elevate nutritional requirements, making women of childbearing age particularly vulnerable to nutritional deficiencies [ 1 , 2 ]. Inadequate dietary intake during pregnancy is associated with severe adverse outcomes, including low birth weight, intrauterine growth retardation, preterm birth, and increased maternal morbidity and mortality [ 3 , 4 ]. Globally, maternal malnutrition contributes substantially to the disease burden, with an estimated 32 million pregnant women (37%) experiencing anemia and dietary diversity challenges. Maternal inadequate dietary diversity contributed to (7%) of the global disease burden. In South Asia, the situation is particularly critical, with (52%) of pregnant women in the region suffering from nutritional inadequacies [ 5 – 7 ]. The World Health Organization and United Nations agencies emphasize dietary diversity as a key strategy for addressing maternal and child undernutrition, recognizing it as a fundamental indicator of nutrient adequacy [ 6 , 8 ]. Nepal also exemplifies these nutritional challenges. The Nepal Demographic and Health Survey (NDHS), 2022 revealed that only 56% of reproductive-age women achieve minimum dietary diversity, with 33% of pregnant women experiencing anemia. Maternal mortality ratio remains high at 151 per 100,000 live births, underscoring the urgent need for targeted nutritional interventions [ 9 – 12 ]. Indigenous populations like the Chepang community in Nepal represent a particularly vulnerable demographic group. With a total population of 84,364 and an alarming literacy rate where only 1% of women are literate, the Chepang face significant socioeconomic barriers to nutritional well-being. Food insecurity, limited access to healthcare, and systemic marginalization compound their nutritional vulnerabilities [ 12 – 15 ]. The Food and Agriculture Organization's Minimum Dietary Diversity for Women (MDD-W) guideline provides a critical framework for assessing micronutrient adequacy [ 1 ]. Despite extensive literature on maternal nutrition, significant knowledge gaps persist regarding determinants of dietary diversity specifically in highly marginalized indigenous populations like the Chepang community. While previous studies have examined dietary diversity in various regions of Nepal, the unique socio-cultural context, extreme poverty, geographical isolation, and traditional dietary practices of the Chepang community remain understudied. This research addresses this critical gap by providing evidence specifically focused on this vulnerable population. The study also contributes to broader public health goals in Nepal, particularly the Multi-Sector Nutrition Plan II (2018–2022) and the National Strategy for Reaching the Unreached (2016–2030), which emphasize the importance of targeted interventions for marginalized populations. Understanding specific determinants of dietary diversity among Chepang women is essential for developing effective, culturally [ 8 ]. Therefore, this study aimed to assess minimum dietary diversity and the associated factors among pregnant women of Chepang community in Nepal and generate evidence-based recommendations for targeted nutritional interventions. This study provides a critical lens into the complex nutritional realities of an underserved indigenous community, offering insights that can inform more equitable and effective public health interventions. Understanding the nuanced nutritional landscape of marginalized communities is crucial for developing effective, context-specific strategies to improve maternal and child health outcomes, which also aligns with broader global objectives, including the Sustainable Development Goal's commitment to eliminating malnutrition and promoting health and well-being for all [ 8 ]. This study provides a critical lens into the complex nutritional realities of an underserved indigenous community, offering insights that can inform more equitable and effective public health interventions. Methods Study Design and Setting This study was a community-based cross-sectional quantitative study conducted from September to October 2024. The study was conducted in four districts with significant Chepang populations: Gorkha, Dhading, Makawanpur, and Chitwan, an indigenously residing and highly marginalized group in terms of socioeconomic status and access to health and nutrition services. Of the total Chepang population of 84,364, the majority reside within 13 local administrative levels across these districts. From these 13 local levels, four (approximately one-third) were selected based on their dense Chepang populations, with one representing from each district: Gandaki Rural Municipality (RM) from Gorkha, Benighat-Rorang RM from Dhading, Raksirang RM from Makawanpur, and Rapti Municipality from Chitwan. Study Participants and Sampling The study targeted pregnant women from the Chepang community who were registered for antenatal care (ANC) services at local health institutions. All randomly selected pregnant women from the Chepang community, registered for ANC at local health institution were included in the study sample. Pregnant women with physical or mental health conditions preventing participation and those observing fasting during data collection were excluded to ensure data validity. The sample size was calculated using the single population proportion formula assuming 55% prevalence of MDD based on previous study in Western hill region, Nepal [ 17 ]. The prevalence estimate from this comparable geographic region was selected as the most appropriate reference point as no prior studies had specifically examined dietary diversity in the Chepang population. The margin of error was set at 5%, with 95% confidence interval (CI). The initial calculation yielded: n = (Z₁₋ₐ/₂) ² × p(1-p) / d² n = (1.96) ² × 0.55 (1-0.55) / (0.05) ² n = 380 By using correction formula since the total estimated pregnant women in the study area were 1,052: n = n₀ / (1 + n₀/N) = 380 / (1 + 380/1052) = 281 To address potential non-response, a 5% buffer was added, but all selected participants completed the study, resulting in a final sample of 281 pregnant women. In the first stage, the total number of participants to be selected from each of the districts were determined proportionately based on estimated pregnant women. Then the sampling frame was constructed using records from Female Community Health Volunteers (FCHVs) and antenatal care (ANC) registers from local health institutions, which identified 417 eligible pregnant women at the study's initiation. Final participant selection was conducted using a computerized random number generator to select 281 participants, ensuring unbiased selection and enrollment in the study. Data Collection Tools and Procedure Data were collected through face-to-face interviews using pretested structured questionnaire developed through extensive literature review and incorporated internationally validated tools. The questionnaire consisted two parts. The first part included sociodemographic, maternal related and household related factors (age, religion, education, employment, family type, family size and others). The second part was dietary-diversity related questionnaire which was adopted from Minimum Dietary Diversity for Women (MDD-W), developed by the Food and Agriculture Organization (FAO) [ 1 ]. It was assessed using 24-hr open dietary recall methods. Each food group consumption over the past 24-hr before the survey period got one point. Dietary diversity was considered adequate when participants reported consumption of foods from five or more of the ten defined food groups in the previous 24-hr period of a day [ 1 , 18 ]. Nutrition knowledge of pregnant women was assessed through scoring the correct answers from 16 items of questions on pregnancy related nutrition. The final nutrition knowledge section was tested for reliability and it had high level of internal consistency with Cronbach’s alpha (0.76). Score one for correct answer of each question and zero for wrongly answered question with overall score 16. Then mean was calculated, those with score above mean are considered to have high nutrition knowledge and those with score below mean to have low nutrition knowledge. Additionally, tool validation was done involving consultation with nutrition expert, health personal further pilot test was conducted before main study to ensure the consistency, relevance and clarity of the questionnaire. Household food security status was assessed using Household Food Insecurity Access Scale (HFIAS), then indicators categorized households into four levels of household food insecurity (access): food secure, mild insecure, moderately insecure and severely food insecure [ 19 ]. International Wealth Index (IWI) was used to assess socioeconomic status of the participant, which provides standardized measurement of socioeconomic status across developing countries. IWI score runs from zero to 100. The score was ranked on the IWI scale as three categories; low ( 66.67) [ 20 ]. Women empowerment was assessed using Nepal Demographic and Health survey (NDHS) WEI tool which provides the level of women empowerment among the study population. It was measured using women’s involvement in household decision-making, women’s membership in community groups, women’s cash earnings, women’s ownership of house/land and women’s education. And the level of empowerment categorized into low (score 0–2), moderate (score 3–4) and high (score 5–7) [ 21 ]. The questionnaire underwent a rigorous translation process, initially developed in English and subsequently translated into Nepali using forward-backward translation methodology to ensure conceptual equivalence. To assess its validity and cultural appropriateness, the questionnaire was pretested with 15 participants, representing 5% of the total sample size, in a comparable non-study population. Based on the pretest results, necessary modifications were implemented to enhance clarity and cultural suitability of the instrument. To maintain data quality and ensure adherence to research protocols, the research team provided continuous supervision throughout the data collection process. This comprehensive approach to data collection ensured methodological rigor and data reliability throughout the study. Data Processing and Analysis The data were entered into EpiData version 4.6 after cleaning and coding and then exported to Statistical Package for Social Sciences (SPSS) version 22 for analysis. Data cleaning involved checking for missing values, outliers, and inconsistencies. Missing data were minimal (< 1%) and were excluded from the specific analyses affected rather than imputing values. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were calculated to describe the findings and presented in text and tables. For continuous variables, measures of central tendency (means, medians) and dispersion (standard deviations, interquartile ranges) were calculated. The Minimum Dietary Diversity (MDD) score was dichotomized into two categories: inadequate (less than 5 food groups) and adequate (5 or more food groups) [ 1 , 18 ]. Bivariate analysis was conducted using logistic regression to identify variables significantly associated with MDD at a 95% confidence level and p < 0.05. Variables significant in the bivariate analysis were subjected to multicollinearity checks using Variance Inflation Factors (VIF), and only variables with VIF values less than 2 were included in the multivariable model. This threshold was chosen to ensure that multicollinearity did not substantially affect the stability of the regression estimates. A stepwise backward elimination logistic regression was done to identify associated factors with minimum dietary diversity. The initial model included all variables significant at p 0.10. The goodness-of-fit for the final logistic regression model was tested using the Hosmer and Lemeshow test (p = 0.815), which showed that the model was well-fitted. Additional model diagnostics included examination of residuals and influence statistics to identify potential outliers or influential cases. Both crude odds ratios (COR) and adjusted odds ratios (AOR), along with their corresponding 95% confidence intervals and p-values, were calculated to measure the strength and presence of associations between MDD and its associated factors. Results Sociodemographic Characteristics of Participants A total of 281 pregnant women participated in this study. The mean (± SD) age of participants was 22.9 (± 4.442) years, with two-thirds (66.5%) aged between 20–30 years. Majority of the participants were Christian (61.9%), followed by Hindu (34.5%) and Buddhist (3.6%). (61.9%) of participants had attained basic and secondary education, while (38.1%) were illiterate. Only few were (3.9%) engaged in employment. About two third (68.0%) of participants lived in joint or extended families, and most of them (90.7%) belonged to households with four or more family members. Male-headed households predominated at (89.0%) households. An analysis of spousal characteristics revealed that about two third (69.8%) of participant’s husbands had basic and secondary education, while (30.2%) were illiterate. The employment rate among husbands was (37.4%) (Table 1 ). Table 1 Sociodemographic Characteristics of Participants (n = 281) Characteristics Frequency (%) Characteristics Frequency (%) Age ( Mean ± SD = 22.9 ± 4.442) Family Type 30 Years old 24 (8.5) Family size Religion ≤ 4-member family 77 (27.4) Hindu 97 (34.5) > 4-member family 204 (72.6) Buddhist 10 (3.6) Household Head Christian 174 (61.9) Male headed 250 (89) Educational Status Female headed 31 (11) Illiterate 107 (38.1) Husband Educational Status Basic and Secondary 174 (61.9) Illiterate 85 (30.2) Employment Status Basic and Secondary 196 (69.8) Employed 11 (3.9) Husband Employment Status Unemployed 170 (96.1) Employed 105 (37.4) Unemployed 176 (62.6) Maternal Health and Dietary Characteristics Among the study participants, the distribution across gestational age showed that about half of the participant (51.6%) were in their second trimester followed by third trimester (38.4%) and remaining (10%) in first trimester. Majority of the participants (38.4%) were multiparous, (31.7%) primiparous with remaining nulliparous. Most of the participants (72.6%) were multigravida, while (27.4%) were primigravida. Few (10.7%) participants reported no ANC visits during their current pregnancy. Nearly three-quarters of participants (74.4%) were categorized as having low empowerment status. Most participants (86.5%) reported receiving nutrition counseling during pregnancy, almost half (48.4%) demonstrated poor nutrition knowledge. Nearly one fourth (23.1%) of participants reported exposure to pregnancy-related nutrition and health information through media channels. Cultural food restrictions as a taboo were followed by small proportion (3.6%) of participants. The majority of participants (85.8%) reported consuming fewer than four meals per day, falling below recommended guidelines for pregnant women (Table 2 ). Table 2 Maternal health characteristics of pregnant Chepang women (n = 281) Characteristics Frequency (%) Characteristics Frequency (%) Gestational Age Nutrition Counseling 1st trimester 28 (10) No 38 (13.5) 2nd trimester 145 (51.6) Yes 243 (86.5) 3rd trimester 108 (38.4) Media exposure Parity No 216 (76.9) Nulliparous 84 (29.9) Yes 65 (23.1) Primiparous 89 (31.7) Nutrition knowledge level Multiparous 108 (38.4) Poor 136 (48.4) Gravida Good 145 (51.6) Primigravida 77 (27.4) Food Restriction as a Taboo Multigravida 204 (72.6) No 271 (96.4) ANC Utilization Yes 10 (3.6) Yes 251 (89.3) Meal Frequency No 30 (10.7) < 4 meals per day 241 (85.8) Women Empowerment ≥ 4 meals per day 40 (14.2) Low 209 (74.4) Moderate 62 (22.1) High 10 (3.6) Household characteristics of pregnant Chepang women A concerning finding is the high prevalence (84.7%) of severe food insecurity among households, with (84.7%) of participants reporting this condition. A majority of women (80.1%) reported receiving support from their husband, However, (39.1%) of women did not receive support from family members (Table 3 ). Table 3 Household characteristics of pregnant Chepang women (n = 281) Characteristics Frequency (%) Characteristics Frequency (%) Socioeconomic status Husband Support Low 110 (39.1) No 56 (19.9) Middle 84 (29.9) Yes 225 (80.1) High 87 (31) Family Member Support Household food security No 110 (39.1) Food secure 30 (10.7) Yes 171 (60.9) Mildly food insecure 5 (1.8) Moderately food insecure 8 (2.8) Severely food insecure 238 (84.7) Dietary Diversity and Food Group Consumption Patterns According to this study, only about one third (33.5%) (95% CI: 28, 39.3) of pregnant Chepang women found to have adequate dietary diversity. Out of the 10 food groups, the mean dietary diversity score among pregnant women was (3.88 ± 1.364 SD) with scores ranging from 2 to 9 food groups (Table 4 ). Table 4 Maternal minimum dietary diversity among Chepang pregnant women in Nepal, (n = 281) Characteristics Frequency(n) Percent (%) 95% CI Lower Upper Dietary diversity adequacy Inadequate 187 66.5 60.7 72 Adequate 94 33.5 28 39.3 Mean ± SD = 3.88 ± 1.364 This study showed that among the different food groups consumed by pregnant women in previous 24hr, major food groups consumed were; all of the participants consumed starchy staple food, 85.8% dark green vegetables, 43.4% consumed pulses, 40.2% meat and poultry, other fruits and vegetables 46.6% and 40.6% respectively and few participants 18.1% consumed vit.A rich fruits and vegetables (Fig. 1 ) Factors Associated with Minimum Dietary Diversity Bivariate analysis revealed several factors significantly associated with increased odds of achieving minimum dietary diversity: maternal age (20–30 years), educational attainment, employment status, husband's education level, parity, women's empowerment status, media exposure, nutrition knowledge, meal frequency, socioeconomic status, household food security, and both husband and family support (p < 0.05). In the subsequent multivariable logistic regression analysis, three factors emerged as independent predictors of minimum dietary diversity: women with basic and secondary education were nine times more likely to achieve adequate dietary diversity compared to those without formal education (AOR = 9.02, 95% CI: 3.23–25.18); women consuming four or more meals per day had nearly three times higher odds of meeting minimum dietary diversity requirements (AOR = 2.88, 95% CI: 1.06–7.82); and those receiving husband support were almost eleven times more likely to achieve adequate dietary diversity (AOR = 10.97, 95% CI: 3.17–37.97) compared to those without spousal support (Table 5 ). Table 5 Factors associated with minimum dietary diversity (n = 281) Variables COR (95%CI) p - Value AOR (95%CI) p - Value Age of pregnant women < 20 years 4.4 (0.94, 20.47) 0.059 3.49 (0.45, 26.52) 0.227 20–30 years 6.88 (1.57, 30.16) 0.010* 4.57 (0.78, 26.73) 0.092 ≥ 30 years 1 1 Education Illiterate 1 1 Basic and Secondary 12.09 (5.54, 26.36) 0.001* 9.02 (3.23, 25.18) 0.001* Employment Employed 5.70 (1.47, 22.03) 0.012* 4.78 (0.53, 42.96) 0.162 Unemployed 1 1 Husband education Illiterate 1 1 Basic and Secondary 3.49 (1.84, 6.63) 0.001* 0.84 (0.33, 2.1) 0.711 Parity Nulliparous 1.35 (0.72, 2.53) 0.345 0.91 (0.3, 2.75) 0.868 Primiparous 2.22 (1.22, 4.06) 0.009* 1.08 (0.47, 2.5) 0.849 Multiparous 1 1 Women empowerment Low 1 1 Moderate 2.33 (1.30, 4.17) 0.004* 0.75 (0.31, 1.76) 0.510 High 3.08 (0.90, 10.49) 0.072 0.24 (0.03, 1.96) 0.184 Media exposure No 1 1 Yes 3.68 (2.07, 6.56) 0.001* 1.56 (0.7, 3.44) 0.270 Nutrition knowledge level Poor 1 1 Good 6.04 (3.4, 10.74) 0.001* 1.84 (0.86, 3.95) 0.114 Meal frequency < 4 meal/day 1 1 ≥ 4 meal/day 5.39 (2.62, 11.07) 0.001* 2.88 (1.06, 7.82) 0.038* Socioeconomic status Low 1 1 Middle 1.44 (0.75, 2.74) 0.268 0.6 (0.26, 1.41) 0.247 High 3.47 (1.88, 6.42) 0.001* 0.94 (0.36, 2.46) 0.910 Household food security status Food secure 3.39 (1.55, 7.40) 0.002* 1.79 (0.59, 5.43) 0.302 Mild/moderate insecure 0.67 (0.18, 2.53) 0.564 0.4 (0.07, 2.25) 0.304 Severe insecure 1 1 Husband support No 1 1 Yes 8.66 (3.02, 24.8) 0.001* 10.97(3.17, 37.97) 0.001* Family support No 1 1 Yes 1.98 (1.16, 3.37) 0.012* 1.27 (0.59, 2.75) 0.532 * Statistically significant. Discussion This study assessed the prevalence of minimum dietary diversity and its associated factors among pregnant women in the Chepang community of Nepal. The findings revealed that only around one third (33.5%) (95% CI: 28.0-39.3) of participants achieved the minimum dietary diversity for women (MDD-W), with a mean dietary diversity score of 3.88 (SD ± 1.364). This prevalence is comparable to findings from studies conducted in Northwest Ethiopia (31.4%) and Tanzania (28.0%) [ 22 , 23 ]. However, it is substantially lower than reported rates from other regions, including Baglung district, Nepal (55.0%), Southwest Ethiopia (51.7%), Somalia (48.2%), and Southern Ethiopia (42.1%) [ 17 , 18 , 24 , 25 ]. Additionally, the mean dietary diversity score was lower than that reported in a 2019 study conducted at Western Regional Hospital, Nepal (Mean = 4.96, SD ± 1.42) [ 26 ]. The relatively low MDD-W prevalence observed in this study may be attributed to the socioeconomic characteristics of the study population. The Chepang community, as an indigenous ethnic group, faces multiple barriers including household food insecurity, limited access to healthcare services, low educational attainment, poor transportation infrastructure, and limited employment opportunities. These socioeconomic disadvantages may collectively contribute to reduced dietary diversity among pregnant women in this community. The current study shows, among the Chepang pregnant women having basic and secondary education level were 9.02 times (AOR = 9.02, 95% CI: 3.23, 25.18), more likely to have a minimum dietary diversity. This result suggests that higher education level play a significant role in achieving better dietary diversity than illiterate pregnant women. This could be due to pregnant women having higher education level might have more employment chances and more aware about health, nutrition and food choices during pregnancy. The similar findings were reported from the study conducted in Kenya [ 2 ], western region Nepal [ 26 ] and Batu Ethiopia [ 27 ]. This consistent relationship between education and dietary quality suggests that education equips women with critical nutrition literacy and decision-making capacity regarding food choices. This study found that the pregnant women in the Chepang community who were having ≥ 4 meals per day were 2.88 times (AOR = 2.88, 95% CI: 1.06, 7.82) more likely to have adequate minimum dietary diversity as compared to those who had < 4 meals per day. The findings of this study is in similar with several studies conducted in Western Ethiopia [ 28 ], Rural Southwest Ethiopia[ 18 ], Puntland Somalia[ 24 ] and Eastern Ethiopia [ 29 ]. This might be the reason that pregnant women who were consuming additional meal per day have higher chances of access to diverse food groups. Recent metabolic research has also demonstrated that increased meal frequency can improve micronutrient absorption efficiency, potentially magnifying the nutritional benefits of more frequent eating patterns during pregnancy. Pregnant Chepang women whose husband supports them to consume diverse nutritious food found to have higher odds 10.97 times (AOR = 10.97, 95% CI: 3.17, 37.97) of minimum dietary diversity than those who do not have husband support. This result is similar to studies conducted in Central and Southwest Ethiopia [ 30 , 31 ]. This finding might have possible reason that most households were male headed most decision person; if they involved in pregnancy issues and if pregnant women could share their burden of income, food and other household issues, that could lead to increased intake of minimum dietary diversity among them. The exceptionally strong association between husband support and dietary diversity in our study suggests that male engagement may be particularly influential within the patriarchal social structure of the Chepang community. Our findings have several critical implications for nutrition policies in Nepal, particularly for programs targeting marginalized indigenous communities. First, the markedly low dietary diversity prevalence among Chepang pregnant women (33.5%) indicates that current nutrition interventions may not be adequately reaching or addressing the needs of indigenous populations, suggesting the need for targeted approaches within Nepal's Multi-Sector Nutrition Plan. The strong association between education and dietary diversity (AOR = 9.02) demonstrates that educational interventions should be integrated with nutritional programs, potentially through expanding female literacy initiatives in Chepang settlements coupled with culturally-appropriate nutrition education. The significant impact of husband support (AOR = 10.97) suggests that male engagement should be explicitly incorporated into maternal nutrition policy frameworks in Nepal. Current policies like the National Strategy for Reaching the Unreached (2016–2030) could be strengthened by adding specific provisions for engaging male household members in nutrition education and decision-making. Additionally, the association between meal frequency and dietary diversity indicates that food supplementation programs should emphasize not only food quality but also appropriate meal patterning. For effective implementation, these policy recommendations should incorporate decentralized approaches aligned with Nepal's federal structure, with local governments in Chepang-populated areas empowered to adapt interventions to community-specific needs. Cross-sectoral collaboration between education, health, agriculture, and social welfare departments will be essential for creating sustainable improvements in maternal nutrition within this vulnerable population. Our findings on dietary diversity among pregnant Chepang women directly relate to several Sustainable Development Goals (SDGs), particularly illuminating challenges in achieving these targets for indigenous populations in Nepal. The low prevalence of minimum dietary diversity (33.5%) reveals significant obstacles to achieving SDG 2 (Zero Hunger), specifically target 2.2 focused on ending all forms of malnutrition by 2030. The pronounced food insecurity (84.7% severely food insecure) among study participants further underscores the considerable distance to attaining target 2.1 on ensuring access to safe, nutritious, and sufficient food year-round. The study results also highlight barriers to achieving SDG 3 (Good Health and Well-being), particularly target 3.1 on reducing maternal mortality and target 3.2 on ending preventable deaths of newborns, both of which are directly influenced by maternal nutritional status. The significant educational disparities in dietary diversity connect to SDG 4 (Quality Education), demonstrating how educational achievement translates to improved health outcomes among indigenous women. The strong association between husband support and dietary diversity relates to SDG 5 (Gender Equality), revealing how household gender dynamics influence nutritional outcomes and suggesting that progress toward maternal nutrition goals requires addressing gender inequities within household decision-making structures. Additionally, the overall nutritional vulnerability of this indigenous community highlights challenges in achieving SDG 10 (Reduced Inequalities), particularly in eliminating disparities between indigenous and non-indigenous populations. These interconnections illustrate how Nepal's progress toward multiple SDGs requires focused attention on improving nutritional outcomes among indigenous communities like the Chepang, and how interventions addressing dietary diversity can simultaneously contribute to multiple development goals. This study conducted particularly in the specific highly marginalized group, the Chepang community of Nepal and is community based, which is novel and interesting. Therefore, the findings could be generalized to similar type of marginalized back warded community and also it could give useful information for nutritional intervention. However, this study has several limitations despite its strengths. Using a single 24-hour recall period was unable to reveal participant's habitual diet. The fact that the study was carried out in a specific ethnic community and limited to a single season may restrict the generalization of the results to other general community and subsequent seasons. Additionally, the cross-sectional design limits our ability to establish causal relationships between identified factors and dietary diversity outcomes. The study's timing during Nepal's pre-monsoon season may have influenced food availability patterns, potentially affecting dietary diversity scores. Finally, while we measured husband support, more nuanced assessment of household decision-making dynamics and women's autonomy would strengthen understanding of interpersonal influences on dietary choices. Conclusion This study revealed low minimum dietary diversity (33.5%) and severe food insecurity (84.7%) among pregnant Chepang women in Nepal, with formal education, adequate meal frequency, and husband support emerging as significant predictors of achieving minimum dietary diversity. These findings highlight the need for a multi-level approach to improving maternal nutrition in this indigenous population. We recommend implementing nutrition education programs tailored to low-literacy populations, developing male engagement initiatives to leverage husband support, establishing women's support groups for knowledge exchange, and creating targeted food security interventions at the policy level. Future research priorities should include longitudinal studies tracking dietary patterns across pregnancy trimesters, mixed-methods approaches exploring cultural food practices, implementation research on culturally-appropriate interventions, and biomarker assessment alongside dietary diversity measures. Addressing these nutritional challenges represents both a critical public health priority and an essential step toward health equity for indigenous communities, requiring culturally-sensitive interventions that acknowledge the unique socioeconomic constraints faced by these vulnerable populations. Abbreviations AOR: Adjusted Odds Ratio COR : Crude Odds Ratio FAO: Food and Agriculture Organization of the United Nations HFIAS: Household Food Insecurity Assessment Scale IWI: International Wealth Index MDD: Minimum Dietary Diversity MDDW: Minimum Dietary Diversity Women NDHS: Nepal Demographic and Health Survey RM: Rural Municipality SD : Standard Deviation SDG: Sustainable Development Goals UN: United Nations WEI: Women empowerment Index WHO: World Health Organization Declarations Acknowledgments: The author would like to acknowledge all the participants who actively participated in this study and provide valuable information. Furthermore, we extend appreciation to the local-level government bodies across Makawanpur, Dhading, Chitwan and Gorkha district for their cooperation and assistance in enabling access to the study sites and participants. Authors’ contributions: SL & KPS developed the concept. SL wrote the proposal, participated in data collection, study design, execution and major contributor in preparing the manuscript. SL & KPS analyzed and interpreted the data. SL, KPS, JPU & DPP wrote the manuscript. JPU & DPP involved in the feedback, suggestion & revision. All the authors read, revised, and approved the final version of manuscript. Funding: No funding was obtained for this study. Availability of data and materials: The datasets that were used in this study are available upon reasonable request from the corresponding author. Ethics approval and consent to participate: Ethical clearance was obtained from the Institutional Review Committee (IRC), Pokhara University (Ref. No. 91/2081/82). The study was conducted in accordance with the principles of the Declaration of Helsinki. An official support and permission letter was obtained from the local level of Gandaki RM, Benighat Rorang RM, Raksirang RM, Rapti Municipality. Written informed consent was obtained from the adult’s participants. For participants under 18 years of age, written informed consent was obtained from their parents or legal guardians, along with written assent from the minors themselves using an age-appropriate assent form after informing them about voluntary participation, their right to withdraw at any time, the confidentiality of the information shared, and the protection of their identity. This research is original and not considered in another journal for publication. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. References FAO and FHI 360 (2016). Minimum Dietary Diversity for Women: A Guide to Measurement. Food And Nutrition Technical Assistance Ⅲ. 2016. Kiboi W, Kimiywe J, Chege P. Determinants of dietary diversity among pregnant women in Laikipia County, Kenya: A cross-sectional study. BMC Nutrition. 2017;3:1–8. https://doi.org/10.1186/s40795-017-0126-6. Gebremichael MA, Belachew Lema T. Dietary Diversity, Nutritional Status, and Associated Factors Among Pregnant Women in Their First Trimester of Pregnancy in Ambo District, Western Ethiopia. Nutrition and metabolic insights. 2023;16:11786388231190516. https://doi.org/10.1177/11786388231190515. Gernand AD, Schulze KJ, Stewart CP, West KP, Christian P. Micronutrient deficiencies in pregnancy worldwide: Health effects and prevention. Nature Reviews Endocrinology. 2016;12:274–89. https://doi.org/10.1038/NRENDO.2016.37. Tilahun AG, Kebede AM. Maternal minimum dietary diversity and associated factors among pregnant women, Southwest Ethiopia, 2021. BMC nutrition. 2021;7:66. https://doi.org/10.1186/s40795-021-00474-8. Nguyen PH, Sanghvi T, Kim SS, Tran LM, Afsana K, Mahmud Z, et al. Factors influencing maternal nutrition practices in a large scale maternal, newborn and child health program in Bangladesh. PLoS One. 2017;12:e0179873. https://doi.org/10.1371/journal.pone.0179873. Anaemia Key Facts. World Health Organization (WHO). 2023. https://www.who.int/news-room/fact-sheets/detail/anaemia. Accessed 27 May 2024. Status and Roadmap: 2016-2030 Nepal Sustainable Development Goals. National planning commission, Kathmandu. 2016;:2016–30. Ministry of Health and Population [Nepal], New ERA, and ICF. 2023. Nepal Demographic and Health Survey 2022. Kathmandu NM of H and P [Nepal]. Ndhs 2022. MoHP, NSO. (2022). National Population and Housing Census 2021: Nepal Maternal Mortality Study 2021. Kathmandu: Ministry of Health and Population; National Statistics Office. Zerfu TA, Biadgilign S. Pregnant mothers have limited knowledge and poor dietary diversity practices, but favorable attitude towards nutritional recommendations in rural Ethiopia: evidence from community-based study. BMC Nutrition. 2018;4:43. https://doi.org/10.1186/s40795-018-0251-x. Mahara G, Barr J, Thomas J, Wang W, Guo X. Maternal health and its affecting factors in Nepal. Family Medicine and Community Health. 2016;4:30–4. https://doi.org/10.15212/FMCH.2015.0155. National population and housing census 2021. National Report on caste/ethnicity, language and religion. Government of Nepal, National statistics office. Shrestha 1 MS, Shrestha R, Tej M, Shrestha 2 K, Shrestha E, Joshi S, et al. Knowledge and Practice of Antenatal Care among Chepang Women from Chitwan, Nepal. ARC Journal of Public Health and Community Medicine. 2018;3. https://doi.org/10.20431/2456-0596.0302002. Nath Ghimire M. Food security practices of Chepang community of Nepal. International journal of applied research. 2018;4:172–7. Chepangs’ Struggle for Survival: Views from Makwanpur and Chitwan Districts. United Nations, RCHC Office, Nepal. 2012. Shrestha V, Paudel R, Sunuwar DR, Lyman ALT, Manohar S, Amatya A. Factors associated with dietary diversity among pregnant women in the western hill region of Nepal: A community based crosssectional study. PLoS ONE. 2021;16 4 April:1–17. https://doi.org/10.1371/journal.pone.0247085. Kuma MN, Tamiru D, Belachew T. Level and predictors of dietary diversity among pregnant women in rural South-West Ethiopia: a community-based cross-sectional study. BMJ Open. 2021;11:e055125. https://doi.org/10.1136/bmjopen-2021-055125. Coates J, Swindale A, Bilinsky P. Household Food Insecurity Access Scale (HFIAS) for Measurement of Household Food Access: Indicator Guide (v. 3). Washington, DC: FHI 360/FANTA. 2007. Smits J, Steendijk R. The International Wealth Index (IWI). Social Indicators Research. 2015;122:65–85. https://doi.org/10.1007/s11205-014-0683-x. Tuladhar S, Khanal KR, K.C. L, Ghimire PK, Onta K. Tuladhar S., Khanal K.R., K.C. Lila, Ghimire P.K., Onta K., 2013. Women’s Empowerment and Spousal Violence in Relation to Health Outcomes in Nepal: Further analysis of the 2011 Nepal Demographic and Health Survey. Calverton, Maryland, USA: Nepal Ministry . 2013; March:1–59. Heri R, Malqvist M, Yahya-Malima KI, Mselle LT. Dietary diversity and associated factors among women attending antenatal clinics in the coast region of Tanzania. BMC Nutrion. 2024;10:16. https://doi.org/10.1186/s40795-024-00825-1. Aliwo S, Fentie M, Awoke T, Gizaw Z. Dietary diversity practice and associated factors among pregnant women in North East Ethiopia. BMC Research Notes. 2019;12. https://doi.org/10.1186/s13104-019-4159-6. Mohammed F, Abdirizak N, Jibril A, Oumer A. Correlates of minimum dietary diversity among pregnant women on antenatal care follow up at public health facility in Puntland, Somalia. Nature scientific reports. 2023;13. https://doi.org/10.1038/S41598-023-48983-9. Gudeta TG, Terefe AB, Mengistu GT, Sori SA. Determinants of Dietary Diversity Practice among Pregnant Women in the Gurage Zone, Southern Ethiopia, 2021: Community-Based Cross-Sectional Study. Obstetrics and gynecology international. 2022;2022:8086793. https://doi.org/10.1155/2022/8086793. Lama N, Lamichhne R, Bhandari R, K.C. S, Sharma D, Bhandari GP, et al. Factors Influencing Dietary Diversity of Pregnant Women Attending Antenatal Care in Western Regional Hospital, Nepal: A Cross-sectional Study. Journal of Karnali Academy of Health Sciences. 2019;2:189–96. https://doi.org/10.3126/jkahs.v2i3.26653. Getahun GK, Ahmed SM, Degif AB, Haile MG. The assessment of dietary diversity score and associated factors among pregnant women of Batu district, Southern Ethiopia, 2021: a community-based cross-sectional study. Annals of medicine and surgery (2012). 2023;85:383–9. https://doi.org/10.1097/MS9.0000000000000239. Bikila H, Tessisa Ariti B, Belete Fite M, Hatahu Sanbata J, Kobayashi M, Amini M, et al. Prevalence and factors associated with adequate dietary diversity among pregnant women in Nekemte town, Western Ethiopia, 2021. Frontiers in nutrition. 2023;10:1248974. https://doi.org/10.3389/fnut.2023.1248974. Geremew H, Abdisa | Samuel, Zerihun | Ebisa, Yitagesu |, Gizaw K, Kassa Y, et al. Dietary diversity practice and its associated factors among pregnant women in Eastern Ethiopia: A community-based cross-sectional study. Food science & nutrition. 2023. https://doi.org/10.1002/fsn3.3892. https://doi.org/10.1002/fsn3.3892. Desta M, Akibu M, Tadese M, Tesfaye M. Dietary Diversity and Associated Factors among Pregnant Women Attending Antenatal Clinic in Shashemane, Oromia, Central Ethiopia: A Cross-Sectional Study. Journal of nutrition and metabolism. 2019;2019:3916864. https://doi.org/10.1155/2019/3916864. Tariku Y, Baye K. Pregnant Mothers Diversified Dietary Intake and Associated Factors in Southwest Ethiopia: A Cross-Sectional Study. Journal of nutrition and metabolism. 2022;2022:4613165. https://doi.org/10.1155/2022/4613165. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6733246","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":461955952,"identity":"9c76a76c-a424-41a2-ac1a-98408adb053e","order_by":0,"name":"Samundra Lagun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYNACNgYGPjCjwgZIMDYeIEoLG5hxJg2kpYEELYxth8F8vFrk20+nSReU3ZNnYz9+TbrgzHm7te2HgbbU2ETj0mJwJneb9IxzxYZtPDll0jMqbidvO5MI1HIsLbcBlxYGoBbetgTGNoacNGmeM7eTzQ4AtTA2HMapRb7/LViLfRv/mzQg41yy2fmH+LUw3IDYktgmkX4MyDhgZ3aDgC0GN95utuY5l5DcJvGG2ZrnTHKC2Q2gLQl4/CLfn7vxNk9Zgm0/f/rD2zwVdvZm59MfPvhQY4PbYQjAYwAiE8EqEwgrBwH2ByDSnjjFo2AUjIJRMJIAACKVYNEzBmeIAAAAAElFTkSuQmCC","orcid":"","institution":"School of Health and Allied Sciences, Pokhara University, Pokhara, Nepal","correspondingAuthor":true,"prefix":"","firstName":"Samundra","middleName":"","lastName":"Lagun","suffix":""},{"id":461955954,"identity":"08b0f610-e4da-459f-98fe-65800c06db04","order_by":1,"name":"Krishna Prasad Sapkota","email":"","orcid":"","institution":"School of Health and Allied Sciences, Pokhara University, Pokhara, Nepal","correspondingAuthor":false,"prefix":"","firstName":"Krishna","middleName":"Prasad","lastName":"Sapkota","suffix":""},{"id":461955958,"identity":"ed5787e3-1ca9-42c6-9ccb-414feee00d2a","order_by":2,"name":"Jagat Prasad Upadhyay","email":"","orcid":"","institution":"School of Health and Allied Sciences, Pokhara University, Pokhara, Nepal","correspondingAuthor":false,"prefix":"","firstName":"Jagat","middleName":"Prasad","lastName":"Upadhyay","suffix":""},{"id":461955959,"identity":"881f011f-40e6-4c75-8559-464225c9ed2c","order_by":3,"name":"Damaru Prasad Paneru","email":"","orcid":"","institution":"School of Health and Allied Sciences, Pokhara University, Pokhara, Nepal","correspondingAuthor":false,"prefix":"","firstName":"Damaru","middleName":"Prasad","lastName":"Paneru","suffix":""}],"badges":[],"createdAt":"2025-05-23 13:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6733246/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6733246/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83610684,"identity":"0cada342-180d-47d5-a177-00badcf2d7ca","added_by":"auto","created_at":"2025-05-29 12:10:19","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85626,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePattern of food consumption from specific food group among pregnant women in Nepal (n=281)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6733246/v1/b89c28eed7645f0804ee76f3.jpg"},{"id":83612125,"identity":"3b0800b7-5e9b-4bf6-91dc-867d0f10cb3b","added_by":"auto","created_at":"2025-05-29 12:34:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1502897,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6733246/v1/5f969002-f099-4d7f-a27b-5e2061036310.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eMinimum Dietary Diversity and Associated Factors Among Pregnant Women of Chepang Community in Nepal: A Community-Based Cross-Sectional Study\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMaternal nutrition represents a critical global health challenge with profound implications for both the maternal and child well-being. The physiological demands of pregnancy significantly elevate nutritional requirements, making women of childbearing age particularly vulnerable to nutritional deficiencies [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Inadequate dietary intake during pregnancy is associated with severe adverse outcomes, including low birth weight, intrauterine growth retardation, preterm birth, and increased maternal morbidity and mortality [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Globally, maternal malnutrition contributes substantially to the disease burden, with an estimated 32\u0026nbsp;million pregnant women (37%) experiencing anemia and dietary diversity challenges. Maternal inadequate dietary diversity contributed to (7%) of the global disease burden. In South Asia, the situation is particularly critical, with (52%) of pregnant women in the region suffering from nutritional inadequacies [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The World Health Organization and United Nations agencies emphasize dietary diversity as a key strategy for addressing maternal and child undernutrition, recognizing it as a fundamental indicator of nutrient adequacy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNepal also exemplifies these nutritional challenges. The Nepal Demographic and Health Survey (NDHS), 2022 revealed that only 56% of reproductive-age women achieve minimum dietary diversity, with 33% of pregnant women experiencing anemia. Maternal mortality ratio remains high at 151 per 100,000 live births, underscoring the urgent need for targeted nutritional interventions [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Indigenous populations like the Chepang community in Nepal represent a particularly vulnerable demographic group. With a total population of 84,364 and an alarming literacy rate where only 1% of women are literate, the Chepang face significant socioeconomic barriers to nutritional well-being. Food insecurity, limited access to healthcare, and systemic marginalization compound their nutritional vulnerabilities [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The Food and Agriculture Organization's Minimum Dietary Diversity for Women (MDD-W) guideline provides a critical framework for assessing micronutrient adequacy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite extensive literature on maternal nutrition, significant knowledge gaps persist regarding determinants of dietary diversity specifically in highly marginalized indigenous populations like the Chepang community. While previous studies have examined dietary diversity in various regions of Nepal, the unique socio-cultural context, extreme poverty, geographical isolation, and traditional dietary practices of the Chepang community remain understudied. This research addresses this critical gap by providing evidence specifically focused on this vulnerable population.\u003c/p\u003e \u003cp\u003eThe study also contributes to broader public health goals in Nepal, particularly the Multi-Sector Nutrition Plan II (2018\u0026ndash;2022) and the National Strategy for Reaching the Unreached (2016\u0026ndash;2030), which emphasize the importance of targeted interventions for marginalized populations. Understanding specific determinants of dietary diversity among Chepang women is essential for developing effective, culturally [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, this study aimed to assess minimum dietary diversity and the associated factors among pregnant women of Chepang community in Nepal and generate evidence-based recommendations for targeted nutritional interventions. This study provides a critical lens into the complex nutritional realities of an underserved indigenous community, offering insights that can inform more equitable and effective public health interventions. Understanding the nuanced nutritional landscape of marginalized communities is crucial for developing effective, context-specific strategies to improve maternal and child health outcomes, which also aligns with broader global objectives, including the Sustainable Development Goal's commitment to eliminating malnutrition and promoting health and well-being for all [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This study provides a critical lens into the complex nutritional realities of an underserved indigenous community, offering insights that can inform more equitable and effective public health interventions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis study was a community-based cross-sectional quantitative study conducted from September to October 2024. The study was conducted in four districts with significant Chepang populations: Gorkha, Dhading, Makawanpur, and Chitwan, an indigenously residing and highly marginalized group in terms of socioeconomic status and access to health and nutrition services. Of the total Chepang population of 84,364, the majority reside within 13 local administrative levels across these districts. From these 13 local levels, four (approximately one-third) were selected based on their dense Chepang populations, with one representing from each district: Gandaki Rural Municipality (RM) from Gorkha, Benighat-Rorang RM from Dhading, Raksirang RM from Makawanpur, and Rapti Municipality from Chitwan.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Participants and Sampling\u003c/h3\u003e\n\u003cp\u003eThe study targeted pregnant women from the Chepang community who were registered for antenatal care (ANC) services at local health institutions. All randomly selected pregnant women from the Chepang community, registered for ANC at local health institution were included in the study sample. Pregnant women with physical or mental health conditions preventing participation and those observing fasting during data collection were excluded to ensure data validity.\u003c/p\u003e \u003cp\u003eThe sample size was calculated using the single population proportion formula assuming 55% prevalence of MDD based on previous study in Western hill region, Nepal [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The prevalence estimate from this comparable geographic region was selected as the most appropriate reference point as no prior studies had specifically examined dietary diversity in the Chepang population. The margin of error was set at 5%, with 95% confidence interval (CI). The initial calculation yielded:\u003c/p\u003e \u003cp\u003en = (Z₁₋ₐ/₂) \u0026sup2; \u0026times; p(1-p) / d\u0026sup2;\u003c/p\u003e \u003cp\u003en = (1.96) \u0026sup2; \u0026times; 0.55 (1-0.55) / (0.05) \u0026sup2;\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;380\u003c/p\u003e \u003cp\u003eBy using correction formula since the total estimated pregnant women in the study area were 1,052:\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;n₀ / (1\u0026thinsp;+\u0026thinsp;n₀/N)\u0026thinsp;=\u0026thinsp;380 / (1\u0026thinsp;+\u0026thinsp;380/1052)\u0026thinsp;=\u0026thinsp;281\u003c/p\u003e \u003cp\u003eTo address potential non-response, a 5% buffer was added, but all selected participants completed the study, resulting in a final sample of 281 pregnant women.\u003c/p\u003e \u003cp\u003eIn the first stage, the total number of participants to be selected from each of the districts were determined proportionately based on estimated pregnant women. Then the sampling frame was constructed using records from Female Community Health Volunteers (FCHVs) and antenatal care (ANC) registers from local health institutions, which identified 417 eligible pregnant women at the study's initiation. Final participant selection was conducted using a computerized random number generator to select 281 participants, ensuring unbiased selection and enrollment in the study.\u003c/p\u003e\n\u003ch3\u003eData Collection Tools and Procedure\u003c/h3\u003e\n\u003cp\u003eData were collected through face-to-face interviews using pretested structured questionnaire developed through extensive literature review and incorporated internationally validated tools. The questionnaire consisted two parts. The first part included sociodemographic, maternal related and household related factors (age, religion, education, employment, family type, family size and others). The second part was dietary-diversity related questionnaire which was adopted from Minimum Dietary Diversity for Women (MDD-W), developed by the Food and Agriculture Organization (FAO) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It was assessed using 24-hr open dietary recall methods. Each food group consumption over the past 24-hr before the survey period got one point. Dietary diversity was considered adequate when participants reported consumption of foods from five or more of the ten defined food groups in the previous 24-hr period of a day [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNutrition knowledge of pregnant women was assessed through scoring the correct answers from 16 items of questions on pregnancy related nutrition. The final nutrition knowledge section was tested for reliability and it had high level of internal consistency with Cronbach\u0026rsquo;s alpha (0.76). Score one for correct answer of each question and zero for wrongly answered question with overall score 16. Then mean was calculated, those with score above mean are considered to have high nutrition knowledge and those with score below mean to have low nutrition knowledge. Additionally, tool validation was done involving consultation with nutrition expert, health personal further pilot test was conducted before main study to ensure the consistency, relevance and clarity of the questionnaire. Household food security status was assessed using Household Food Insecurity Access Scale (HFIAS), then indicators categorized households into four levels of household food insecurity (access): food secure, mild insecure, moderately insecure and severely food insecure [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInternational Wealth Index (IWI) was used to assess socioeconomic status of the participant, which provides standardized measurement of socioeconomic status across developing countries. IWI score runs from zero to 100. The score was ranked on the IWI scale as three categories; low (\u0026lt;\u0026thinsp;33.3%), medium (33.33\u0026ndash;66.67%) and high (\u0026gt;\u0026thinsp;66.67) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWomen empowerment was assessed using Nepal Demographic and Health survey (NDHS) WEI tool which provides the level of women empowerment among the study population. It was measured using women\u0026rsquo;s involvement in household decision-making, women\u0026rsquo;s membership in community groups, women\u0026rsquo;s cash earnings, women\u0026rsquo;s ownership of house/land and women\u0026rsquo;s education. And the level of empowerment categorized into low (score 0\u0026ndash;2), moderate (score 3\u0026ndash;4) and high (score 5\u0026ndash;7) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe questionnaire underwent a rigorous translation process, initially developed in English and subsequently translated into Nepali using forward-backward translation methodology to ensure conceptual equivalence. To assess its validity and cultural appropriateness, the questionnaire was pretested with 15 participants, representing 5% of the total sample size, in a comparable non-study population. Based on the pretest results, necessary modifications were implemented to enhance clarity and cultural suitability of the instrument. To maintain data quality and ensure adherence to research protocols, the research team provided continuous supervision throughout the data collection process. This comprehensive approach to data collection ensured methodological rigor and data reliability throughout the study.\u003c/p\u003e\n\u003ch3\u003eData Processing and Analysis\u003c/h3\u003e\n\u003cp\u003eThe data were entered into EpiData version 4.6 after cleaning and coding and then exported to Statistical Package for Social Sciences (SPSS) version 22 for analysis. Data cleaning involved checking for missing values, outliers, and inconsistencies. Missing data were minimal (\u0026lt;\u0026thinsp;1%) and were excluded from the specific analyses affected rather than imputing values. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were calculated to describe the findings and presented in text and tables. For continuous variables, measures of central tendency (means, medians) and dispersion (standard deviations, interquartile ranges) were calculated. The Minimum Dietary Diversity (MDD) score was dichotomized into two categories: inadequate (less than 5 food groups) and adequate (5 or more food groups) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBivariate analysis was conducted using logistic regression to identify variables significantly associated with MDD at a 95% confidence level and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Variables significant in the bivariate analysis were subjected to multicollinearity checks using Variance Inflation Factors (VIF), and only variables with VIF values less than 2 were included in the multivariable model. This threshold was chosen to ensure that multicollinearity did not substantially affect the stability of the regression estimates.\u003c/p\u003e \u003cp\u003eA stepwise backward elimination logistic regression was done to identify associated factors with minimum dietary diversity. The initial model included all variables significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in bivariate analysis, and variables were progressively removed based on likelihood ratio tests with removal criterion set at p\u0026thinsp;\u0026gt;\u0026thinsp;0.10. The goodness-of-fit for the final logistic regression model was tested using the Hosmer and Lemeshow test (p\u0026thinsp;=\u0026thinsp;0.815), which showed that the model was well-fitted. Additional model diagnostics included examination of residuals and influence statistics to identify potential outliers or influential cases. Both crude odds ratios (COR) and adjusted odds ratios (AOR), along with their corresponding 95% confidence intervals and p-values, were calculated to measure the strength and presence of associations between MDD and its associated factors.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic Characteristics of Participants\u003c/h2\u003e \u003cp\u003eA total of 281 pregnant women participated in this study. The mean (\u0026plusmn;\u0026thinsp;SD) age of participants was 22.9 (\u0026plusmn;\u0026thinsp;4.442) years, with two-thirds (66.5%) aged between 20\u0026ndash;30 years. Majority of the participants were Christian (61.9%), followed by Hindu (34.5%) and Buddhist (3.6%). (61.9%) of participants had attained basic and secondary education, while (38.1%) were illiterate. Only few were (3.9%) engaged in employment. About two third (68.0%) of participants lived in joint or extended families, and most of them (90.7%) belonged to households with four or more family members. Male-headed households predominated at (89.0%) households. An analysis of spousal characteristics revealed that about two third (69.8%) of participant\u0026rsquo;s husbands had basic and secondary education, while (30.2%) were illiterate. The employment rate among husbands was (37.4%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic Characteristics of Participants (n\u0026thinsp;=\u0026thinsp;281)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (\u003c/b\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.442)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFamily Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20 Years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70 (24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNuclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;30 Years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e187 (66.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJoint or Extended\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191 (68)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30 Years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFamily size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;4-member family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77 (27.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHindu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4-member family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e204 (72.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuddhist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eHousehold Head\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e174 (61.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale headed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250 (89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale headed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107 (38.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eHusband Educational Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic and Secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e174 (61.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 (30.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBasic and Secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e196 (69.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eHusband Employment Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170 (96.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105 (37.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e176 (62.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMaternal Health and Dietary Characteristics\u003c/h3\u003e\n\u003cp\u003eAmong the study participants, the distribution across gestational age showed that about half of the participant (51.6%) were in their second trimester followed by third trimester (38.4%) and remaining (10%) in first trimester. Majority of the participants (38.4%) were multiparous, (31.7%) primiparous with remaining nulliparous. Most of the participants (72.6%) were multigravida, while (27.4%) were primigravida. Few (10.7%) participants reported no ANC visits during their current pregnancy. Nearly three-quarters of participants (74.4%) were categorized as having low empowerment status. Most participants (86.5%) reported receiving nutrition counseling during pregnancy, almost half (48.4%) demonstrated poor nutrition knowledge. Nearly one fourth (23.1%) of participants reported exposure to pregnancy-related nutrition and health information through media channels. Cultural food restrictions as a taboo were followed by small proportion (3.6%) of participants. The majority of participants (85.8%) reported consuming fewer than four meals per day, falling below recommended guidelines for pregnant women (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMaternal health characteristics of pregnant Chepang women (n\u0026thinsp;=\u0026thinsp;281)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational Age\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNutrition Counseling\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1st trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (13.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e243 (86.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd trimester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMedia exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e216 (76.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNulliparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65 (23.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eNutrition knowledge level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (38.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e136 (48.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGravida\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e145 (51.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFood Restriction as a Taboo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e204 (72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e271 (96.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eANC Utilization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e251 (89.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMeal Frequency\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;4 meals per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e241 (85.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen Empowerment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 meals per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40 (14.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eHousehold characteristics of pregnant Chepang women\u003c/h3\u003e\n\u003cp\u003eA concerning finding is the high prevalence (84.7%) of severe food insecurity among households, with (84.7%) of participants reporting this condition. A majority of women (80.1%) reported receiving support from their husband, However, (39.1%) of women did not receive support from family members (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHousehold characteristics of pregnant Chepang women (n\u0026thinsp;=\u0026thinsp;281)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocioeconomic status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHusband Support\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56 (19.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e225 (80.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFamily Member Support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold food security\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e110 (39.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e171 (60.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMildly food insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately food insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverely food insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e238 (84.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDietary Diversity and Food Group Consumption Patterns\u003c/h2\u003e \u003cp\u003eAccording to this study, only about one third (33.5%) (95% CI: 28, 39.3) of pregnant Chepang women found to have adequate dietary diversity. Out of the 10 food groups, the mean dietary diversity score among pregnant women was (3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.364 SD) with scores ranging from 2 to 9 food groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMaternal minimum dietary diversity among Chepang pregnant women in Nepal, (n\u0026thinsp;=\u0026thinsp;281)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFrequency(n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePercent (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary diversity adequacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInadequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis study showed that among the different food groups consumed by pregnant women in previous 24hr, major food groups consumed were; all of the participants consumed starchy staple food, 85.8% dark green vegetables, 43.4% consumed pulses, 40.2% meat and poultry, other fruits and vegetables 46.6% and 40.6% respectively and few participants 18.1% consumed vit.A rich fruits and vegetables (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFactors Associated with Minimum Dietary Diversity\u003c/h2\u003e \u003cp\u003eBivariate analysis revealed several factors significantly associated with increased odds of achieving minimum dietary diversity: maternal age (20\u0026ndash;30 years), educational attainment, employment status, husband's education level, parity, women's empowerment status, media exposure, nutrition knowledge, meal frequency, socioeconomic status, household food security, and both husband and family support (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the subsequent multivariable logistic regression analysis, three factors emerged as independent predictors of minimum dietary diversity: women with basic and secondary education were nine times more likely to achieve adequate dietary diversity compared to those without formal education (AOR\u0026thinsp;=\u0026thinsp;9.02, 95% CI: 3.23\u0026ndash;25.18); women consuming four or more meals per day had nearly three times higher odds of meeting minimum dietary diversity requirements (AOR\u0026thinsp;=\u0026thinsp;2.88, 95% CI: 1.06\u0026ndash;7.82); and those receiving husband support were almost eleven times more likely to achieve adequate dietary diversity (AOR\u0026thinsp;=\u0026thinsp;10.97, 95% CI: 3.17\u0026ndash;37.97) compared to those without spousal support (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with minimum dietary diversity (n\u0026thinsp;=\u0026thinsp;281)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e - Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e - Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of pregnant women\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4 (0.94, 20.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.49 (0.45, 26.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.88 (1.57, 30.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.010*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.57 (0.78, 26.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic and Secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.09 (5.54, 26.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9.02 (3.23, 25.18)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.70 (1.47, 22.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.78 (0.53, 42.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic and Secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.49 (1.84, 6.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.33, 2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNulliparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35 (0.72, 2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91 (0.3, 2.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.22 (1.22, 4.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08 (0.47, 2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen empowerment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.33 (1.30, 4.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75 (0.31, 1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.08 (0.90, 10.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24 (0.03, 1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedia exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.68 (2.07, 6.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56 (0.7, 3.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNutrition knowledge level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.04 (3.4, 10.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84 (0.86, 3.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMeal frequency\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;4 meal/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 meal/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.39 (2.62, 11.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.88 (1.06, 7.82)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.038*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocioeconomic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.44 (0.75, 2.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 (0.26, 1.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.47 (1.88, 6.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94 (0.36, 2.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold food security status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.39 (1.55, 7.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79 (0.59, 5.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild/moderate insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67 (0.18, 2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4 (0.07, 2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.304\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.66 (3.02, 24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e10.97(3.17, 37.97)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.98 (1.16, 3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27 (0.59, 2.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e* Statistically significant.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed the prevalence of minimum dietary diversity and its associated factors among pregnant women in the Chepang community of Nepal. The findings revealed that only around one third (33.5%) (95% CI: 28.0-39.3) of participants achieved the minimum dietary diversity for women (MDD-W), with a mean dietary diversity score of 3.88 (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;1.364).\u003c/p\u003e \u003cp\u003eThis prevalence is comparable to findings from studies conducted in Northwest Ethiopia (31.4%) and Tanzania (28.0%) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, it is substantially lower than reported rates from other regions, including Baglung district, Nepal (55.0%), Southwest Ethiopia (51.7%), Somalia (48.2%), and Southern Ethiopia (42.1%) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Additionally, the mean dietary diversity score was lower than that reported in a 2019 study conducted at Western Regional Hospital, Nepal (Mean\u0026thinsp;=\u0026thinsp;4.96, SD\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The relatively low MDD-W prevalence observed in this study may be attributed to the socioeconomic characteristics of the study population. The Chepang community, as an indigenous ethnic group, faces multiple barriers including household food insecurity, limited access to healthcare services, low educational attainment, poor transportation infrastructure, and limited employment opportunities. These socioeconomic disadvantages may collectively contribute to reduced dietary diversity among pregnant women in this community.\u003c/p\u003e \u003cp\u003eThe current study shows, among the Chepang pregnant women having basic and secondary education level were 9.02 times (AOR\u0026thinsp;=\u0026thinsp;9.02, 95% CI: 3.23, 25.18), more likely to have a minimum dietary diversity. This result suggests that higher education level play a significant role in achieving better dietary diversity than illiterate pregnant women. This could be due to pregnant women having higher education level might have more employment chances and more aware about health, nutrition and food choices during pregnancy. The similar findings were reported from the study conducted in Kenya [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], western region Nepal [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and Batu Ethiopia [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This consistent relationship between education and dietary quality suggests that education equips women with critical nutrition literacy and decision-making capacity regarding food choices. This study found that the pregnant women in the Chepang community who were having\u0026thinsp;\u0026ge;\u0026thinsp;4 meals per day were 2.88 times (AOR\u0026thinsp;=\u0026thinsp;2.88, 95% CI: 1.06, 7.82) more likely to have adequate minimum dietary diversity as compared to those who had\u0026thinsp;\u0026lt;\u0026thinsp;4 meals per day. The findings of this study is in similar with several studies conducted in Western Ethiopia [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Rural Southwest Ethiopia[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Puntland Somalia[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and Eastern Ethiopia [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This might be the reason that pregnant women who were consuming additional meal per day have higher chances of access to diverse food groups. Recent metabolic research has also demonstrated that increased meal frequency can improve micronutrient absorption efficiency, potentially magnifying the nutritional benefits of more frequent eating patterns during pregnancy.\u003c/p\u003e \u003cp\u003ePregnant Chepang women whose husband supports them to consume diverse nutritious food found to have higher odds 10.97 times (AOR\u0026thinsp;=\u0026thinsp;10.97, 95% CI: 3.17, 37.97) of minimum dietary diversity than those who do not have husband support. This result is similar to studies conducted in Central and Southwest Ethiopia [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This finding might have possible reason that most households were male headed most decision person; if they involved in pregnancy issues and if pregnant women could share their burden of income, food and other household issues, that could lead to increased intake of minimum dietary diversity among them. The exceptionally strong association between husband support and dietary diversity in our study suggests that male engagement may be particularly influential within the patriarchal social structure of the Chepang community.\u003c/p\u003e \u003cp\u003eOur findings have several critical implications for nutrition policies in Nepal, particularly for programs targeting marginalized indigenous communities. First, the markedly low dietary diversity prevalence among Chepang pregnant women (33.5%) indicates that current nutrition interventions may not be adequately reaching or addressing the needs of indigenous populations, suggesting the need for targeted approaches within Nepal's Multi-Sector Nutrition Plan. The strong association between education and dietary diversity (AOR\u0026thinsp;=\u0026thinsp;9.02) demonstrates that educational interventions should be integrated with nutritional programs, potentially through expanding female literacy initiatives in Chepang settlements coupled with culturally-appropriate nutrition education.\u003c/p\u003e \u003cp\u003eThe significant impact of husband support (AOR\u0026thinsp;=\u0026thinsp;10.97) suggests that male engagement should be explicitly incorporated into maternal nutrition policy frameworks in Nepal. Current policies like the National Strategy for Reaching the Unreached (2016\u0026ndash;2030) could be strengthened by adding specific provisions for engaging male household members in nutrition education and decision-making. Additionally, the association between meal frequency and dietary diversity indicates that food supplementation programs should emphasize not only food quality but also appropriate meal patterning.\u003c/p\u003e \u003cp\u003eFor effective implementation, these policy recommendations should incorporate decentralized approaches aligned with Nepal's federal structure, with local governments in Chepang-populated areas empowered to adapt interventions to community-specific needs. Cross-sectoral collaboration between education, health, agriculture, and social welfare departments will be essential for creating sustainable improvements in maternal nutrition within this vulnerable population.\u003c/p\u003e \u003cp\u003eOur findings on dietary diversity among pregnant Chepang women directly relate to several Sustainable Development Goals (SDGs), particularly illuminating challenges in achieving these targets for indigenous populations in Nepal. The low prevalence of minimum dietary diversity (33.5%) reveals significant obstacles to achieving SDG 2 (Zero Hunger), specifically target 2.2 focused on ending all forms of malnutrition by 2030. The pronounced food insecurity (84.7% severely food insecure) among study participants further underscores the considerable distance to attaining target 2.1 on ensuring access to safe, nutritious, and sufficient food year-round. The study results also highlight barriers to achieving SDG 3 (Good Health and Well-being), particularly target 3.1 on reducing maternal mortality and target 3.2 on ending preventable deaths of newborns, both of which are directly influenced by maternal nutritional status. The significant educational disparities in dietary diversity connect to SDG 4 (Quality Education), demonstrating how educational achievement translates to improved health outcomes among indigenous women. The strong association between husband support and dietary diversity relates to SDG 5 (Gender Equality), revealing how household gender dynamics influence nutritional outcomes and suggesting that progress toward maternal nutrition goals requires addressing gender inequities within household decision-making structures. Additionally, the overall nutritional vulnerability of this indigenous community highlights challenges in achieving SDG 10 (Reduced Inequalities), particularly in eliminating disparities between indigenous and non-indigenous populations. These interconnections illustrate how Nepal's progress toward multiple SDGs requires focused attention on improving nutritional outcomes among indigenous communities like the Chepang, and how interventions addressing dietary diversity can simultaneously contribute to multiple development goals.\u003c/p\u003e \u003cp\u003eThis study conducted particularly in the specific highly marginalized group, the Chepang community of Nepal and is community based, which is novel and interesting. Therefore, the findings could be generalized to similar type of marginalized back warded community and also it could give useful information for nutritional intervention.\u003c/p\u003e \u003cp\u003eHowever, this study has several limitations despite its strengths. Using a single 24-hour recall period was unable to reveal participant's habitual diet. The fact that the study was carried out in a specific ethnic community and limited to a single season may restrict the generalization of the results to other general community and subsequent seasons. Additionally, the cross-sectional design limits our ability to establish causal relationships between identified factors and dietary diversity outcomes. The study's timing during Nepal's pre-monsoon season may have influenced food availability patterns, potentially affecting dietary diversity scores. Finally, while we measured husband support, more nuanced assessment of household decision-making dynamics and women's autonomy would strengthen understanding of interpersonal influences on dietary choices.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed low minimum dietary diversity (33.5%) and severe food insecurity (84.7%) among pregnant Chepang women in Nepal, with formal education, adequate meal frequency, and husband support emerging as significant predictors of achieving minimum dietary diversity. These findings highlight the need for a multi-level approach to improving maternal nutrition in this indigenous population. We recommend implementing nutrition education programs tailored to low-literacy populations, developing male engagement initiatives to leverage husband support, establishing women's support groups for knowledge exchange, and creating targeted food security interventions at the policy level. Future research priorities should include longitudinal studies tracking dietary patterns across pregnancy trimesters, mixed-methods approaches exploring cultural food practices, implementation research on culturally-appropriate interventions, and biomarker assessment alongside dietary diversity measures. Addressing these nutritional challenges represents both a critical public health priority and an essential step toward health equity for indigenous communities, requiring culturally-sensitive interventions that acknowledge the unique socioeconomic constraints faced by these vulnerable populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eAOR:\u0026nbsp;\u003c/strong\u003eAdjusted Odds Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOR\u003c/strong\u003e: Crude Odds Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFAO:\u0026nbsp;\u003c/strong\u003eFood and Agriculture Organization of the United Nations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHFIAS:\u003c/strong\u003e Household Food Insecurity Assessment Scale\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIWI:\u0026nbsp;\u003c/strong\u003eInternational Wealth Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMDD:\u0026nbsp;\u003c/strong\u003eMinimum Dietary Diversity\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMDDW:\u0026nbsp;\u003c/strong\u003eMinimum Dietary Diversity Women\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNDHS:\u0026nbsp;\u003c/strong\u003eNepal Demographic and Health Survey\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRM:\u0026nbsp;\u003c/strong\u003eRural Municipality\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e: Standard Deviation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSDG:\u0026nbsp;\u003c/strong\u003eSustainable Development Goals\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUN:\u0026nbsp;\u003c/strong\u003eUnited Nations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWEI:\u0026nbsp;\u003c/strong\u003eWomen empowerment Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWHO:\u0026nbsp;\u003c/strong\u003eWorld Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author would like to acknowledge all the participants who actively participated in this study and provide valuable information. Furthermore, we extend appreciation to the local-level government bodies across Makawanpur, Dhading, Chitwan and Gorkha district for their cooperation and assistance in enabling access to the study sites and participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSL \u0026amp; KPS developed the concept. SL wrote the proposal, participated in data collection, study design, execution and major contributor in preparing the manuscript. SL \u0026amp; KPS analyzed and interpreted the data. SL, KPS, JPU \u0026amp; DPP wrote the manuscript. JPU \u0026amp; DPP involved in the feedback, suggestion \u0026amp; revision. All the authors read, revised, and approved the final version of manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets that were used in this study are available upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from the Institutional Review Committee (IRC), Pokhara University (Ref. No. 91/2081/82). The study was conducted in accordance with the principles of the Declaration of Helsinki. An official support and permission letter was obtained from the local level of Gandaki RM, Benighat Rorang RM, Raksirang RM, Rapti Municipality. Written informed consent was obtained from the adult\u0026rsquo;s participants. For participants under 18 years of age, written informed consent was obtained from their parents or legal guardians, along with written assent from the minors themselves using an age-appropriate assent form after informing them about voluntary participation, their right to withdraw at any time, the confidentiality of the information shared, and the protection of their identity. This research is original and not considered in another journal for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFAO and FHI 360 (2016). Minimum Dietary Diversity for Women: A Guide to Measurement. Food And Nutrition Technical Assistance Ⅲ. 2016.\u003c/li\u003e\n\u003cli\u003eKiboi W, Kimiywe J, Chege P. Determinants of dietary diversity among pregnant women in Laikipia County, Kenya: A cross-sectional study. BMC Nutrition. 2017;3:1\u0026ndash;8. https://doi.org/10.1186/s40795-017-0126-6.\u003c/li\u003e\n\u003cli\u003eGebremichael MA, Belachew Lema T. Dietary Diversity, Nutritional Status, and Associated Factors Among Pregnant Women in Their First Trimester of Pregnancy in Ambo District, Western Ethiopia. Nutrition and metabolic insights. 2023;16:11786388231190516. https://doi.org/10.1177/11786388231190515.\u003c/li\u003e\n\u003cli\u003eGernand AD, Schulze KJ, Stewart CP, West KP, Christian P. Micronutrient deficiencies in pregnancy worldwide: Health effects and prevention. Nature Reviews Endocrinology. 2016;12:274\u0026ndash;89. https://doi.org/10.1038/NRENDO.2016.37.\u003c/li\u003e\n\u003cli\u003eTilahun AG, Kebede AM. Maternal minimum dietary diversity and associated factors among pregnant women, Southwest Ethiopia, 2021. BMC nutrition. 2021;7:66. https://doi.org/10.1186/s40795-021-00474-8.\u003c/li\u003e\n\u003cli\u003eNguyen PH, Sanghvi T, Kim SS, Tran LM, Afsana K, Mahmud Z, et al. Factors influencing maternal nutrition practices in a large scale maternal, newborn and child health program in Bangladesh. PLoS One. 2017;12:e0179873. https://doi.org/10.1371/journal.pone.0179873.\u003c/li\u003e\n\u003cli\u003eAnaemia Key Facts. World Health Organization (WHO). 2023. https://www.who.int/news-room/fact-sheets/detail/anaemia. Accessed 27 May 2024.\u003c/li\u003e\n\u003cli\u003eStatus and Roadmap: 2016-2030 Nepal Sustainable Development Goals. National planning commission, Kathmandu. 2016;:2016\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eMinistry of Health and Population [Nepal], New ERA, and ICF. 2023. Nepal Demographic and Health Survey 2022. Kathmandu NM of H and P [Nepal]. Ndhs 2022.\u003c/li\u003e\n\u003cli\u003eMoHP, NSO. (2022). National Population and Housing Census 2021: Nepal Maternal Mortality Study 2021. Kathmandu: Ministry of Health and Population; National Statistics Office.\u003c/li\u003e\n\u003cli\u003eZerfu TA, Biadgilign S. Pregnant mothers have limited knowledge and poor dietary diversity practices, but favorable attitude towards nutritional recommendations in rural Ethiopia: evidence from community-based study. BMC Nutrition. 2018;4:43. https://doi.org/10.1186/s40795-018-0251-x.\u003c/li\u003e\n\u003cli\u003eMahara G, Barr J, Thomas J, Wang W, Guo X. Maternal health and its affecting factors in Nepal. Family Medicine and Community Health. 2016;4:30\u0026ndash;4. https://doi.org/10.15212/FMCH.2015.0155.\u003c/li\u003e\n\u003cli\u003eNational population and housing census 2021. National Report on caste/ethnicity, language and religion. Government of Nepal, National statistics office.\u003c/li\u003e\n\u003cli\u003eShrestha\u003csup\u003e1\u003c/sup\u003e MS, Shrestha R, Tej M, Shrestha\u003csup\u003e2\u003c/sup\u003e K, Shrestha E, Joshi S, et al. Knowledge and Practice of Antenatal Care among Chepang Women from Chitwan, Nepal. ARC Journal of Public Health and Community Medicine. 2018;3. https://doi.org/10.20431/2456-0596.0302002.\u003c/li\u003e\n\u003cli\u003eNath Ghimire M. Food security practices of Chepang community of Nepal. International journal of applied research. 2018;4:172\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eChepangs\u0026rsquo; Struggle for Survival: Views from Makwanpur and Chitwan Districts. United Nations, RCHC Office, Nepal. 2012.\u003c/li\u003e\n\u003cli\u003eShrestha V, Paudel R, Sunuwar DR, Lyman ALT, Manohar S, Amatya A. Factors associated with dietary diversity among pregnant women in the western hill region of Nepal: A community based crosssectional study. PLoS ONE. 2021;16 4 April:1\u0026ndash;17. https://doi.org/10.1371/journal.pone.0247085.\u003c/li\u003e\n\u003cli\u003eKuma MN, Tamiru D, Belachew T. Level and predictors of dietary diversity among pregnant women in rural South-West Ethiopia: a community-based cross-sectional study. BMJ Open. 2021;11:e055125. https://doi.org/10.1136/bmjopen-2021-055125.\u003c/li\u003e\n\u003cli\u003eCoates J, Swindale A, Bilinsky P. Household Food Insecurity Access Scale (HFIAS) for Measurement of Household Food Access: Indicator Guide (v. 3). Washington, DC: FHI 360/FANTA. 2007.\u003c/li\u003e\n\u003cli\u003eSmits J, Steendijk R. The International Wealth Index (IWI). Social Indicators Research. 2015;122:65\u0026ndash;85. https://doi.org/10.1007/s11205-014-0683-x.\u003c/li\u003e\n\u003cli\u003eTuladhar S, Khanal KR, K.C. L, Ghimire PK, Onta K. Tuladhar S., Khanal K.R., K.C. Lila, Ghimire P.K., Onta K., 2013. Women\u0026rsquo;s Empowerment and Spousal Violence in Relation to Health Outcomes in Nepal: Further analysis of the 2011 Nepal Demographic and Health Survey. Calverton, Maryland, USA: Nepal Ministry . 2013; March:1\u0026ndash;59.\u003c/li\u003e\n\u003cli\u003eHeri R, Malqvist M, Yahya-Malima KI, Mselle LT. Dietary diversity and associated factors among women attending antenatal clinics in the coast region of Tanzania. BMC Nutrion. 2024;10:16. https://doi.org/10.1186/s40795-024-00825-1.\u003c/li\u003e\n\u003cli\u003eAliwo S, Fentie M, Awoke T, Gizaw Z. Dietary diversity practice and associated factors among pregnant women in North East Ethiopia. BMC Research Notes. 2019;12. https://doi.org/10.1186/s13104-019-4159-6.\u003c/li\u003e\n\u003cli\u003eMohammed F, Abdirizak N, Jibril A, Oumer A. Correlates of minimum dietary diversity among pregnant women on antenatal care follow up at public health facility in Puntland, Somalia. Nature scientific reports. 2023;13. https://doi.org/10.1038/S41598-023-48983-9.\u003c/li\u003e\n\u003cli\u003eGudeta TG, Terefe AB, Mengistu GT, Sori SA. Determinants of Dietary Diversity Practice among Pregnant Women in the Gurage Zone, Southern Ethiopia, 2021: Community-Based Cross-Sectional Study. Obstetrics and gynecology international. 2022;2022:8086793. https://doi.org/10.1155/2022/8086793.\u003c/li\u003e\n\u003cli\u003eLama N, Lamichhne R, Bhandari R, K.C. S, Sharma D, Bhandari GP, et al. Factors Influencing Dietary Diversity of Pregnant Women Attending Antenatal Care in Western Regional Hospital, Nepal: A Cross-sectional Study. Journal of Karnali Academy of Health Sciences. 2019;2:189\u0026ndash;96. https://doi.org/10.3126/jkahs.v2i3.26653.\u003c/li\u003e\n\u003cli\u003eGetahun GK, Ahmed SM, Degif AB, Haile MG. The assessment of dietary diversity score and associated factors among pregnant women of Batu district, Southern Ethiopia, 2021: a community-based cross-sectional study. Annals of medicine and surgery (2012). 2023;85:383\u0026ndash;9. https://doi.org/10.1097/MS9.0000000000000239.\u003c/li\u003e\n\u003cli\u003eBikila H, Tessisa Ariti B, Belete Fite M, Hatahu Sanbata J, Kobayashi M, Amini M, et al. Prevalence and factors associated with adequate dietary diversity among pregnant women in Nekemte town, Western Ethiopia, 2021. Frontiers in nutrition. 2023;10:1248974. https://doi.org/10.3389/fnut.2023.1248974.\u003c/li\u003e\n\u003cli\u003eGeremew H, Abdisa | Samuel, Zerihun | Ebisa, Yitagesu |, Gizaw K, Kassa Y, et al. Dietary diversity practice and its associated factors among pregnant women in Eastern Ethiopia: A community-based cross-sectional study. Food science \u0026amp; nutrition. 2023. https://doi.org/10.1002/fsn3.3892. https://doi.org/10.1002/fsn3.3892.\u003c/li\u003e\n\u003cli\u003eDesta M, Akibu M, Tadese M, Tesfaye M. Dietary Diversity and Associated Factors among Pregnant Women Attending Antenatal Clinic in Shashemane, Oromia, Central Ethiopia: A Cross-Sectional Study. Journal of nutrition and metabolism. 2019;2019:3916864. https://doi.org/10.1155/2019/3916864.\u003c/li\u003e\n\u003cli\u003eTariku Y, Baye K. Pregnant Mothers Diversified Dietary Intake and Associated Factors in Southwest Ethiopia: A Cross-Sectional Study. Journal of nutrition and metabolism. 2022;2022:4613165. https://doi.org/10.1155/2022/4613165.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Minimum dietary diversity, Pregnant women, Indigenous population, Chepang community, Nepal","lastPublishedDoi":"10.21203/rs.3.rs-6733246/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6733246/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Adequate dietary diversity consumption during pregnancy is crucial for maternal and fetal health outcomes. Women from marginalized communities often face increased nutritional risks due to socioeconomic barriers. This study aimed to assess the prevalence of minimum dietary diversity and its associated factors among pregnant women of the Chepang community in Nepal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA community-based cross-sectional quantitative study was conducted among 281 randomly selected pregnant Chepang women across four districts (Gorkha, Dhading, Makawanpur, and Chitwan) in Nepal, from September to October 2024. Proportionate random sampling was used to select participants. Data was collected through face-to-face interviews using pretested structured questionnaires incorporating FAO’s Minimum Dietary Diversity for Women (MDD-W) guidelines. Descriptive statistics and inferential statistics involving bivariate and multivariate logistic regression analysis were performed to identify factors associated with minimum dietary diversity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The prevalence of adequate minimum dietary diversity was 33.5% (95% CI: 28.0-39.3%) among the study participants. The mean (±SD) dietary diversity score was 3.88 (±1.364). In multivariate analysis, women with basic and secondary education (AOR = 9.02, 95% CI: 3.23-25.18), those consuming ≥4 meals per day (AOR = 2.88, 95% CI: 1.06-7.82), and those receiving husband support (AOR = 10.97, 95% CI: 3.17-37.97) were significantly more likely to achieve adequate dietary diversity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eThe prevalence of minimum dietary diversity among pregnant Chepang women was notably low. Interventions should focus on improving women's educational status, promoting adequate meal frequency, and engaging male partners in supporting dietary practices to enhance nutritional outcomes in this marginaliz1`ed indigenous community.\u003c/p\u003e","manuscriptTitle":"Minimum Dietary Diversity and Associated Factors Among Pregnant Women of Chepang Community in Nepal: A Community-Based Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-29 12:10:12","doi":"10.21203/rs.3.rs-6733246/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d43b333e-60ad-4460-b296-946d8ed44232","owner":[],"postedDate":"May 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-29T12:10:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-29 12:10:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6733246","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6733246","identity":"rs-6733246","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}