Understanding resilience to anthropometric malnutrition: Why some children in poverty remain free from all forms of malnutrition – An analysis of India’s National Family Health Survey-5

Understanding resilience to anthropometric malnutrition: Why some children in poverty remain free from all forms of malnutrition – An analysis of India’s National Family Health Survey-5 | 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 Article Understanding resilience to anthropometric malnutrition: Why some children in poverty remain free from all forms of malnutrition – An analysis of India’s National Family Health Survey-5 Abdul Jaleel, Nandeep E R, Arlappa N, Bhasker Reddy P, Sunu PV, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8140708/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract While most research focuses on the causes of child malnutrition, less is known about children who stay healthy despite poverty. This study explores nutritional resilience, defined as the absence of all anthropometric malnutrition, among India’s poorest households. Using NFHS-5 (2019–2021) data, we examined children aged 0–59 months in the lowest wealth quintile. A Composite Index of Anthropometric Malnutrition measured nine malnutrition states, and binary logistic regression identified key predictors. About 35% of children in extreme poverty were malnutrition-free. Maternal height above 155 cm (OR: 2.74, 95% CI), maternal education, smaller families, adequate birth weight (≥ 2500 g), and improved sanitation promoted resilience. Findings highlight that child nutrition depends on maternal health, education, and environmental quality, beyond poverty reduction alone. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Anthropometric malnutrition children under five years poverty NFHS India Figures Figure 1 1. Introduction Childhood malnutrition remains a major global health challenge, disproportionately affecting children in low-income and resource-constrained settings (Aguayo & Menon, 2016 ; Siddiqui, Salam, Lassi, & Das, 2020 ; UNICEF, 2022 ; Villadsen et al., 2023 ). This disproportionate burden is largely driven by a range of interrelated disadvantages, including inadequate access to nutritious food, essential healthcare services, proper sanitation, and safe living conditions (Deolalikar, 2005 ; Panda, Mohanty, Nayak, Shastri, & Subramanian, 2020 ; Peña & Bacallao, 2002 ; WHO, 2020 ). These intersecting deprivations increase the immediate risk of malnutrition and disease, and also contribute to long-term adverse outcomes such as impaired cognitive development, reduced productivity, and persistent health inequalities—ultimately hindering broader societal and economic development (Bhutta et al., 2017 ; Gupta, de Wit, & McKeown, 2007 ; Hoddinott, Maluccio, Behrman, Flores, & Martorell, 2008 ; C. G. Victora et al., 2008 ). Recognizing these far-reaching consequences, the 2030 Agenda for Sustainable Development have placed the elimination of poverty and malnutrition at the forefront of international development goals (Scott et al., 2020 ; Sherratt, 2023 ). Globally, an estimated 333 million children live in extreme poverty, with approximately 90% residing in Sub-Saharan Africa and South Asia (Salmeron Gomez, Engilbertsdottir, Cuesta Leiva, Newhouse, & Stewart, 2023 ). Despite India’s notable economic growth in recent decades, child malnutrition persists as a serious public health concern, marked by significant regional and socio-economic disparities (Joe, Rajaram, & Subramanian, 2016 ; Nguyen et al., 2021 ). According to the most recent National Family Health Survey (NFHS-5), 35.5% of Indian children under the age of five are stunted, 19.3% are wasted, and 32.1% are underweight (IIPS & ICF, 2021). These figures are even higher in communities where poverty remains widespread (Jaleel et al., 2023 ; S. K. Singh, Srivastava, & Chauhan, 2020 ; Striessnig & Bora, 2020 ). Although a substantial body of research has examined the risk factors contributing to child malnutrition—such as dietary inadequacies, poor maternal health, inadequate sanitation, and low household income (Adeyeye, Ashaolu, Bolaji, Abegunde, & Omoyajowo, 2023 ; Atinmo, Mirmiran, Oyewole, Belahsen, & Serra-Majem, 2009 ; Birdi, Joshi, Kotian, & Shah, 2014 ; Gulati, Ganesh-Kumar, Shreedhar, & Nandakumar, 2012 ; Siddiqui et al., 2020 ; Tanumihardjo et al., 2007 ) —comparatively less attention has been paid to understanding why some children manage to remain well-nourished despite living in similarly adverse conditions. This gap in research limits the development of strengths-based and resilience-focused approaches to malnutrition prevention. To address this gap, the present study explores the factors that enable certain children in impoverished Indian households to remain free from all forms of anthropometric malnutrition. Drawing on data from India’s National Family Health Survey-5, the study employs a Positive Deviance (PD) approach (Zeitlin, 1991 ), which seeks to identify the unique features of children who achieve better outcomes than their peers despite facing similar risks. By identifying these resilience factors, this study aims to inform nutrition interventions for leveraging the existing strengths within vulnerable communities for more sustainable malnutrition prevention interventions. 2. Data and methods This study utilizes data from the National Family Health Survey-5 (NFHS-5), a nationally representative household survey conducted between 2019 and 2021 in India. The NFHS-5 provides comprehensive estimates on population, health, and nutrition at the National, State/Union Territory (UT), and District levels. The survey was conducted in 636,699 households across India using Computer-Assisted Personal Interviewing (CAPI), collecting data from 724,115 women (aged 15–49 years), 101,839 men (aged 15–54 years), and 232,920 children (aged 0–59 months). For this analysis, we used the children’s dataset (IAKR7AFL file) in Stata format, obtained from the Demographic and Health Survey (DHS) Program portal. The dataset includes information on children's health and nutrition, immunization history, feeding practices, and maternal characteristics. The NFHS also contains children's anthropometric measurements—height/length (in cm) and weight (in kg). Children's weight (0–59 months) was measured using the Seca 874 digital scale. The height of the children (24–59 months) was measured with a Seca 213 stadiometer. The Seca 417 infantometer was used to measure the recumbent length of children under two years. Additionally, the dataset includes World Health Organization (WHO) Z-scores for Height-for-Age (HAZ), Weight-for-Height (WHZ), and Weight-for-Age (WAZ), allowing classification of children as stunted, wasted, and underweight. NFHS-5 assessed household wealth based on the ownership of consumer goods (e.g., televisions, bicycles, cars, etc.) and housing characteristics (e.g., water source, toilet facilities, flooring material). A wealth score was assigned using principal component analysis (PCA), ranking households into five wealth quintiles such as poorest (lowest quintile); poor (second quintile); middle (third quintile); rich (fourth quintile); richest (fifth quintile). For this study, we focused exclusively on children from the poorest wealth quintile (see Fig. 1 ). In this analysis, we calculated a Composite Index of Anthropometric Malnutrition (CIAM) (Nandeep ER, 2023). This index accounts for nine biologically possible forms of malnutrition among children under five years, derived from HAZ, WHZ, and WAZ scores. The possible forms of malnutrition conditions among children under five years are: Stunting only (HAZ < -2SD) Wasting only (WHZ < -2SD) Underweight only (WAZ < -2SD) Stunting + Wasting + Underweight (HAZ < -2SD & WHZ < -2SD & WAZ < -2SD) Stunting + Underweight (HAZ < -2SD & WAZ < -2SD) Wasting + Underweight (WHZ < -2SD & WAZ < -2SD) Stunting + Overweight (HAZ + 2SD) Overweight only (WHZ > + 2SD) Stunting + Underweight + Overweight (HAZ < -2SD & WAZ + 2SD) For this analysis, we dichotomized the index into two — Children experiencing any form of malnutrition = 0, and Children free from all forms of malnutrition = 1. We employed binary logistic regression analysis to examine factors associated with the absence of all forms of anthropometric malnutrition among children aged 0–59 months in the poorest households. The analysis produced unadjusted and adjusted odds ratios (ORs) with corresponding p-values and 95% confidence intervals (CIs). The independent variables included in the analysis were: Demographic factors (child’s age, sex, birth weight); maternal characteristics (mother’s education level, height, number of living children); household environment (place of residence, sanitation facilities, healthcare access); socio-cultural factors (religion, caste/tribe), and factors associated to healthcare access (place of delivery, proximity to healthcare facility). To account for multiple testing and reduce the risk of Type 1 errors (false positives), significance was determined at a false discovery rate (FDR) of 0.005. 3. Results 3.1. Prevalence and characteristics of anthropometric malnutrition Table 1 presents the prevalence of different forms of anthropometric malnutrition among children under five years of age in the poorest households in India. The findings reveal that nearly 65% of these children experience some form of malnutrition, with stunting, wasting, underweight, and overweight occurring either independently or in combination. The most prevalent form of malnutrition is the coexistence of stunting and underweight (22.2%), followed by stunting alone (15%), wasting combined with underweight (9%), and the simultaneous presence of stunting, wasting, and underweight (7.8%). Notably, despite living in extreme poverty, 35% of children do not show any form of malnutrition. Table 2 provides the weighted proportion and distribution of children under five years of age in extreme poverty who do not experience anthropometric malnutrition, categorised by household, maternal, and individual characteristics. The proportion of children without malnutrition is highest among Christians (38.0%). Caste disparities are evident, with children from 'Other castes' having the highest proportion of no anthropometric malnutrition (39.7%), compared to those belonging to Scheduled Castes, Scheduled Tribes, and Other Backward Classes. Household sanitation access emerges as a crucial factor, with children living in households with improved sanitation facilities showing the highest proportion of no anthropometric malnutrition (37.5%). Maternal education is another enabler; the proportion of children without anthropometric malnutrition increases with higher maternal education, reaching 50.3% among children of mothers with higher education, compared to 31.4% among those whose mothers have no formal education. Maternal height also plays a critical role. Children born to mothers with a height of 155 cm or more have the highest proportion of no anthropometric malnutrition (47%). Similarly, family size influences malnutrition outcomes, with the highest proportion of well-nourished children observed among those whose mothers have only one living child (38.8%), decreasing as the number of siblings increases. Birth circumstances further impact malnutrition status, with children delivered in health facilities showing a higher proportion of no anthropometric malnutrition (36.5%) compared to those born at home. Age and birth weight are also key factors; children aged 0–11 months have the highest proportion of no anthropometric malnutrition (43.4%), while those aged 12–23 months have the lowest (31.8%). Additionally, children with a birth weight of at least 2500 grams are more likely to remain unaffected by any malnutrition (38.1%) compared to those with a birth weight below 2500 grams (29.2%). 3.2. Predictors of anthropometric resilience among children Table 3 presents the results of the logistic regression analysis examining the predictors of resilience to anthropometric malnutrition among children under five years from the poorest households in India. Both unadjusted and adjusted odds ratios, along with their respective p -values and 95% confidence intervals, are reported. Among all predictors, maternal height has the strongest association with the absence of anthropometric malnutrition. Compared to children of mothers shorter than 145 cm, those born to mothers with heights of 145–154.9 cm and ≥ 155 cm has substantially higher odds of remaining well-nourished (OR: 1.67 and 2.71, respectively). Maternal education is also strongly associated with malnutrition resilience, with children of mothers with primary, secondary, and higher education levels exhibiting significantly higher odds of being free from all forms of malnutrition compared to those whose mothers have no formal education. Family size is another key predictor, with children from smaller families having a greater likelihood of avoiding malnutrition. Birth weight is also a significant determinant, as children born weighing 2500 grams or more have significantly higher odds of no anthropometric malnutrition compared to those with lower birth weights. Lastly, as children grow older, their probability of being unaffected by anthropometric malnutrition also increases. Caste emerges as a significant factor, with children belonging to the 'Other caste' category having higher odds (OR: 1.3) of being well-nourished compared to those from Scheduled Castes. Sanitation access is also a crucial determinant; children in households with improved sanitation facilities have significantly higher odds of being free from anthropometric malnutrition compared to those without any sanitation facilities. 4. Discussion This study identifies the key characteristics of children who achieved exceptional nutritional outcomes despite living in economically disadvantaged households. Our analysis of India's National Family Health Survey-5 (NFHS-5) reveals that maternal height (above 155 cm) and maternal education (beyond secondary level) are the most significant predictors of optimal child nutritional outcomes in poor households. In addition, programmatic factors—including access to improved sanitation, smaller family sizes, and a healthy birth weight (≥ 2500 g)—emerge as critical determinants that mitigate the risk of all forms of anthropometric malnutrition. 4.1. Maternal nutrition and intergenerational effects Maternal nutrition and linear growth are foundational determinants of child health. The literature consistently underscores the intergenerational consequences of maternal undernutrition, particularly short maternal stature, which is associated with adverse birth outcomes such as low birth weight, child stunting, increased delivery complications, and higher child mortality rates (Abu-Saad & Fraser, 2010 ; Kozuki et al., 2015 ; Martorell & Zongrone, 2012 ; Ozaltin, Hill, & Subramanian, 2010 ; D. P. Singh, Biradar, Halli, & Dwivedi, 2021 ; Cesar G. Victora et al., 2008 ). Mothers with inadequate linear growth are more likely to give birth to stunted children, perpetuating a cycle of malnutrition across generations (Félix-Beltrán, Macinko, & Kuhn, 2021 ; Porwal et al., 2021 ). This highlights the urgent need for targeted interventions focusing on the nutritional needs of adolescent girls and women of reproductive age. Such interventions are essential not only to improve birth outcomes but also to enhance long-term child development and human capital formation. 4.2. Maternal education and health literacy Maternal education is another crucial protective factor. Educated mothers are more likely to possess knowledge about appropriate feeding practices, healthcare utilization, and hygiene, which directly contributes to better nutritional outcomes in children (Abuya, Ciera, & Kimani-Murage, 2012 ; Gbratto-Dobe & Segnon, 2025 ; Prasetyo, Permatasari, & Susanti, 2023 ; Rezaeizadeh et al., 2024 ). Health education interventions delivered by frontline health workers (FHWs)—through home visits, antenatal counseling, and community outreach—have proven effective in increasing awareness and adoption of optimal childcare practices, especially in resource-constrained settings (Rammohan, Goli, Saroj, & Jaleel, 2021 ). Expanding the reach and capacity of FHWs can therefore play a transformative role in improving child health and nutrition in impoverished households. Sanitation and hygiene Access to improved sanitation remains a powerful, yet unequally distributed, determinant of child nutritional status. Sanitation-related inequities disproportionately affect the poorest households, contributing to a high burden of infectious diseases, including diarrhea, which in turn exacerbates malnutrition (Li, Li, Subramanian, & Lu, 2017 ). Studies have shown that inadequate sanitation contributes significantly to anemia in women and malnutrition in children, often through chronic enteric infections and environmental enteropathy (Kothari et al., 2019 ). Between 1990 and 2015, improvements in sanitation infrastructure contributed to a 10% reduction in child mortality globally, underscoring its vital role in public health (Headey & Palloni, 2019 ). Bridging the sanitation gap is thus imperative to improving nutritional resilience among the poorest. 4.3. Birth weight and early life nutrition Healthy birth weight serves as a strong protective factor against all forms of anthropometric malnutrition. Low birth weight (LBW) infants are significantly more likely to suffer from stunting, wasting, and underweight compared to their normal-weight peers (A. Jana, D. Dey, & R. Ghosh, 2023 ; Rahman, Howlader, Masud, & Rahman, 2016 ). Evidence suggests that LBW accounts for 10–15% of the variation in anthropometric malnutrition outcomes among children across socioeconomic strata. (Arup Jana, Deepshikha Dey, & Ranjita Ghosh, 2023). Preventing LBW through adequate antenatal care, maternal nutrition, and timely interventions during pregnancy is critical to disrupting the early onset of growth faltering and undernutrition. 4.4. Structural inequalities and social exclusion Finally, structural determinants such as caste-based social exclusion exacerbate malnutrition risks among India’s poorest children. Our findings corroborate previous research showing that children from Scheduled Castes (SCs), Scheduled Tribes (STs), and Other Backward Classes (OBCs) are disproportionately affected by malnutrition—even when controlling for economic status. These disparities highlight the intersectionality of poverty and marginalization, where caste-based discrimination compounds the effects of material deprivation (Samuel, Flores, & Frisancho, 2020 ). Addressing malnutrition in India therefore requires more than just economic or healthcare inputs; it calls for institutional reforms aimed at dismantling social hierarchies and democratizing access to health and nutrition services. 4.5. Strengths and limitations This study benefits from the use of a nationally representative dataset, enhancing the generalisability of the findings to India’s broader population living in poverty. The large sample size provides statistical power, enabling robust examination of multiple socioeconomic and programmatic predictors associated with resilience to anthropometric malnutrition. By incorporating a diverse set of variables, the analysis provides a comprehensive understanding of the factors that protect children in impoverished households from all forms of anthropometric malnutrition. A key methodological strength lies in the intentional restriction of the sample to children from the poorest wealth quintile. This approach addresses an important epistemological concern: statistical models, while effective in identifying population-level trends, often obscure the heterogeneity of individual experiences. Aggregated patterns may offer actuarial rather than causal explanations. By narrowing the analytical focus, we sought to reduce within-group variability and improve the internal validity of the findings. This design choice enhances the study’s ability to generate actionable insights for policymakers aiming to strengthen resilience among the most vulnerable. However, certain limitations warrant consideration. First, there is the potential for residual confounding. Although the model accounts for a broad range of variables grounded in existing literature, unmeasured or unobserved factors—such as caregiving quality, psychosocial stress, or micronutrient intake—may influence nutritional outcomes and were not captured in this dataset. Second, the study may be subject to reporting biases, particularly concerning household assets. Respondents may under-report possessions due to perceived links between survey responses and eligibility for government programs. While such misreporting is unlikely to vary substantially within the poorest quintile, it could slightly affect household rankings or wealth indices. 5. Conclusion In the context of children's nutritional well-being, certain factors possess the potential to mitigate even the most profound form of deprivation faced by humanity—poverty. These factors include maternal nutrition, maternal education, access to safe sanitation, optimal birth weight, and protection from social exclusion and discrimination. Strengthening maternal education, improving sanitation infrastructure, and promoting inclusive access to healthcare are critical strategies for enhancing nutritional resilience among children in economically disadvantaged households in India. Declarations Competing Interests The author(s) declare that they have no competing interests. Data Availability Statement The data utilized in this study are publicly accessible through the Demographic and Health Survey (DHS) Program portal: https://dhsprogram.com/data/ Ethical Approval The analysis draws on secondary data from the National Family Health Survey-5 (NFHS-5), accessed via the Demographic and Health Surveys (DHS) program portal. The survey was implemented by the International Institute for Population Sciences (IIPS), Mumbai, with all necessary ethical and regulatory approvals in place. As the data are de-identified and publicly available, no further ethical approval was required for this study. Usage of AI and software: ChatGPT ( https://chatgpt.com/) was used solely for language accuracy verification. No content of this manuscript was generated by artificial intelligence. Funding Declaration This research received no specific funding from public, commercial, or not-for-profit agencies. Author Contributions Statement AJ and SRN conceptualised the study. AJ and NER conducted the analyses. SRN, AN, BRP, SPV, and HM validated the analytical approach. AJ drafted the manuscript and prepared all figures and tables. All authors reviewed and approved the final manuscript. References Abu-Saad, K., & Fraser, D. (2010). Maternal Nutrition and Birth Outcomes. Epidemiologic Reviews, 32 (1), 5-25. doi:10.1093/epirev/mxq001 %J Epidemiologic Reviews Abuya, B. A., Ciera, J., & Kimani-Murage, E. (2012). Effect of mother’s education on child’s nutritional status in the slums of Nairobi. BMC Pediatrics, 12 (1), 80. doi:10.1186/1471-2431-12-80 Adeyeye, S. A. O., Ashaolu, T. J., Bolaji, O. T., Abegunde, T. A., & Omoyajowo, A. O. (2023). Africa and the Nexus of poverty, malnutrition and diseases. Crit Rev Food Sci Nutr, 63 (5), 641-656. doi:10.1080/10408398.2021.1952160 Aguayo, V. M., & Menon, P. (2016). Stop stunting: improving child feeding, women's nutrition and household sanitation in South Asia. Matern Child Nutr, 12 Suppl 1 (Suppl 1), 3-11. doi:10.1111/mcn.12283 Atinmo, T., Mirmiran, P., Oyewole, O. E., Belahsen, R., & Serra-Majem, L. (2009). Breaking the poverty/malnutrition cycle in Africa and the Middle East. Nutr Rev, 67 Suppl 1 , S40-46. doi:10.1111/j.1753-4887.2009.00158.x Bhutta, Z. A., Berkley, J. A., Bandsma, R. H. J., Kerac, M., Trehan, I., & Briend, A. (2017). Severe childhood malnutrition. Nat Rev Dis Primers, 3 , 17067. doi:10.1038/nrdp.2017.67 Birdi, T. J., Joshi, S., Kotian, S., & Shah, S. (2014). Possible causes of malnutrition in Melghat, a tribal region of Maharashtra, India. Glob J Health Sci, 6 (5), 164-173. doi:10.5539/gjhs.v6n5p164 Deolalikar, A. B. J. J. o. D. S. (2005). Poverty and child malnutrition in Bangladesh. 21 (1-2), 55-90. Félix-Beltrán, L., Macinko, J., & Kuhn, R. (2021). Maternal height and double-burden of malnutrition households in Mexico: stunted children with overweight or obese mothers. Public Health Nutr, 24 (1), 106-116. doi:10.1017/s136898002000292x Gbratto-Dobe, S. A. W., & Segnon, H. B. (2025). Is mother's education essential to improving the nutritional status of children under five in Côte d′Ivoire? SSM - Health Systems, 4 , 100056. doi:https://doi.org/10.1016/j.ssmhs.2025.100056 Gulati, A., Ganesh-Kumar, A., Shreedhar, G., & Nandakumar, T. (2012). Agriculture and malnutrition in India. Food Nutr Bull, 33 (1), 74-86. doi:10.1177/156482651203300108 Gupta, R. P., de Wit, M. L., & McKeown, D. (2007). The impact of poverty on the current and future health status of children. Paediatr Child Health, 12 (8), 667-672. doi:10.1093/pch/12.8.667 Headey, D., & Palloni, G. (2019). Water, Sanitation, and Child Health: Evidence From Subnational Panel Data in 59 Countries. Demography, 56 (2), 729-752. doi:10.1007/s13524-019-00760-y Hoddinott, J., Maluccio, J. A., Behrman, J. R., Flores, R., & Martorell, R. (2008). Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults. Lancet, 371 (9610), 411-416. doi:10.1016/s0140-6736(08)60205-6 IIPS, & ICF. (2021). National Family Health Survey -5 . Retrieved from Mumbai: Jaleel, A., Arlappa, N., Ramakrishna, K. S., Sunu, P., Jayalakshmi, G., Neeraja, G., . . . Kumar, S. B. (2023). Examining the Triple Burden of Malnutrition: Insights from a Community-Based Comprehensive Nutrition Survey among Indigenous Tribal Children (0–19 Years) in the Western Ghats Hills of India. Nutrients, 15 (18), 3995. Jana, A., Dey, D., & Ghosh, R. (2023). Contribution of low birth weight to childhood undernutrition in India: evidence from the national family health survey 2019-2021. BMC Public Health, 23 (1), 1336. doi:10.1186/s12889-023-16160-2 Jana, A., Dey, D., & Ghosh, R. (2023). Contribution of low birth weight to childhood undernutrition in India: evidence from the national family health survey 2019–2021. BMC Public Health, 23 (1), 1336. doi:10.1186/s12889-023-16160-2 Joe, W., Rajaram, R., & Subramanian, S. V. (2016). Understanding the null-to-small association between increased macroeconomic growth and reducing child undernutrition in India: role of development expenditures and poverty alleviation. Matern Child Nutr, 12 Suppl 1 (Suppl 1), 196-209. doi:10.1111/mcn.12256 Kothari, M. T., Coile, A., Huestis, A., Pullum, T., Garrett, D., & Engmann, C. (2019). Exploring associations between water, sanitation, and anemia through 47 nationally representative demographic and health surveys. Ann N Y Acad Sci, 1450 (1), 249-267. doi:10.1111/nyas.14109 Kozuki, N., Katz, J., Lee, A. C. C., Vogel, J. P., Silveira, M. F., Sania, A., . . . Black, R. E. (2015). Short Maternal Stature Increases Risk of Small-for-Gestational-Age and Preterm Births in Low- and Middle-Income Countries: Individual Participant Data Meta-Analysis and Population Attributable Fraction1, 2, 3. J Nutr, 145 (11), 2542-2550. doi:https://doi.org/10.3945/jn.115.216374 Li, Z., Li, M., Subramanian, S. V., & Lu, C. (2017). Assessing levels and trends of child health inequality in 88 developing countries: from 2000 to 2014. Glob Health Action, 10 (1), 1408385. doi:10.1080/16549716.2017.1408385 Martorell, R., & Zongrone, A. (2012). Intergenerational influences on child growth and undernutrition. Paediatr Perinat Epidemiol, 26 Suppl 1 , 302-314. doi:10.1111/j.1365-3016.2012.01298.x Nandeep ER, J. A., Reddy PB, Geddam JJB, Reddy NS and Hemalatha R. (2023). Developing and demonstrating an atomistic and holistic model of anthropometric failure among children under five years of age using the National Family Health Survey (NFHS)-5 data from India. Frontiers in Nutrition, 10: 1280219 . Nguyen, P. H., Scott, S., Headey, D., Singh, N., Tran, L. M., Menon, P., & Ruel, M. T. (2021). The double burden of malnutrition in India: Trends and inequalities (2006-2016). PLoS One, 16 (2), e0247856. doi:10.1371/journal.pone.0247856 Ozaltin, E., Hill, K., & Subramanian, S. V. (2010). Association of maternal stature with offspring mortality, underweight, and stunting in low- to middle-income countries. JAMA, 303 (15), 1507-1516. doi:10.1001/jama.2010.450 Panda, B. K., Mohanty, S. K., Nayak, I., Shastri, V. D., & Subramanian, S. V. (2020). Malnutrition and poverty in India: does the use of public distribution system matter? BMC Nutr, 6 , 41. doi:10.1186/s40795-020-00369-0 Peña, M., & Bacallao, J. (2002). Malnutrition and poverty. Annu Rev Nutr, 22 , 241-253. doi:10.1146/annurev.nutr.22.120701.141104 Porwal, A., Agarwal, P. K., Ashraf, S., Acharya, R., Ramesh, S., Khan, N., . . . Sarna, A. (2021). Association of maternal height and body mass index with nutrition of children under 5 years of age in India: Evidence from Comprehensive National Nutrition Survey 2016-18. Asia Pac J Clin Nutr, 30 (4), 675-686. doi:10.6133/apjcn.202112_30(4).0014 Prasetyo, Y. B., Permatasari, P., & Susanti, H. D. (2023). The effect of mothers’ nutritional education and knowledge on children’s nutritional status: a systematic review. International Journal of Child Care and Education Policy, 17 (1), 11. doi:10.1186/s40723-023-00114-7 Rahman, M. S., Howlader, T., Masud, M. S., & Rahman, M. L. (2016). Association of Low-Birth Weight with Malnutrition in Children under Five Years in Bangladesh: Do Mother's Education, Socio-Economic Status, and Birth Interval Matter? PLoS One, 11 (6), e0157814. doi:10.1371/journal.pone.0157814 Rammohan, A., Goli, S., Saroj, S. K., & Jaleel, C. P. A. (2021). Does engagement with frontline health workers improve maternal and child healthcare utilisation and outcomes in India? Hum Resour Health, 19 (1), 45. doi:10.1186/s12960-021-00592-1 Rezaeizadeh, G., Mansournia, M. A., Keshtkar, A., Farahani, Z., Zarepour, F., Sharafkhah, M., . . . Poustchi, H. (2024). Maternal education and its influence on child growth and nutritional status during the first two years of life: a systematic review and meta-analysis. eClinicalMedicine, 71 , 102574. doi:10.1016/j.eclinm.2024.102574 Salmeron Gomez, D., Engilbertsdottir, S., Cuesta Leiva, J. A., Newhouse, D., & Stewart, D. (2023). Global Trends in Child Monetary Poverty According to International Poverty Lines. Samuel, J., Flores, W., & Frisancho, A. (2020). Social exclusion and universal health coverage: health care rights and citizen-led accountability in Guatemala and Peru. Int J Equity Health, 19 (1), 216. doi:10.1186/s12939-020-01308-y Scott, N., Delport, D., Hainsworth, S., Pearson, R., Morgan, C., Huang, S., . . . Homer, C. S. E. (2020). Ending malnutrition in all its forms requires scaling up proven nutrition interventions and much more: a 129-country analysis. BMC Med, 18 (1), 356. doi:10.1186/s12916-020-01786-5 Sherratt, S. (2023). Ameliorating poverty-related communication and swallowing disabilities: Sustainable Development Goal 1. Int J Speech Lang Pathol, 25 (1), 32-36. doi:10.1080/17549507.2022.2134458 Siddiqui, F., Salam, R. A., Lassi, Z. S., & Das, J. K. (2020). The Intertwined Relationship Between Malnutrition and Poverty. Front Public Health, 8 , 453. doi:10.3389/fpubh.2020.00453 Singh, D. P., Biradar, R. A., Halli, S. S., & Dwivedi, L. K. (2021). Effect of maternal nutritional status on children nutritional status in India. Children and Youth Services Review, 120 , 105727. doi:https://doi.org/10.1016/j.childyouth.2020.105727 Singh, S. K., Srivastava, S., & Chauhan, S. (2020). Inequality in child undernutrition among urban population in India: a decomposition analysis. BMC Public Health, 20 (1), 1852. doi:10.1186/s12889-020-09864-2 Striessnig, E., & Bora, J. K. (2020). Under-Five Child Growth and Nutrition Status: Spatial Clustering of Indian Districts. Spatial Demography, 8 (1), 63-84. doi:10.1007/s40980-020-00058-3 Tanumihardjo, S. A., Anderson, C., Kaufer-Horwitz, M., Bode, L., Emenaker, N. J., Haqq, A. M., . . . Stadler, D. D. (2007). Poverty, obesity, and malnutrition: an international perspective recognizing the paradox. J Am Diet Assoc, 107 (11), 1966-1972. doi:10.1016/j.jada.2007.08.007 UNICEF. (2022). Child Food Poverty: A Nutrition Crisis in Early Childhood . Retrieved from New York: Victora, C. G., Adair, L., Fall, C., Hallal, P. C., Martorell, R., Richter, L., & Sachdev, H. S. (2008). Maternal and child undernutrition: consequences for adult health and human capital. The Lancet, 371 (9609), 340-357. doi:10.1016/S0140-6736(07)61692-4 Victora, C. G., Adair, L., Fall, C., Hallal, P. C., Martorell, R., Richter, L., & Sachdev, H. S. (2008). Maternal and child undernutrition: consequences for adult health and human capital. Lancet, 371 (9609), 340-357. doi:10.1016/s0140-6736(07)61692-4 Villadsen, A., Asaria, M., Skarda, I., Ploubidis, G. B., Williams, M. M., Brunner, E. J., & Cookson, R. (2023). Clustering of adverse health and educational outcomes in adolescence following early childhood disadvantage: population-based retrospective UK cohort study. Lancet Public Health, 8 (4), e286-e293. doi:10.1016/s2468-2667(23)00029-4 WHO. (2020). Global nutrition policy review 2016-2017: country progress in creating enabling policy environments for promoting healthy diets and nutrition: summary. In Global nutrition policy review 2016-2017: country progress in creating enabling policy environments for promoting healthy diets and nutrition: summary . Zeitlin, M. (1991). Nutritional resilience in a hostile environment: positive deviance in child nutrition. Nutr Rev, 49 (9), 259-268. doi:10.1111/j.1753-4887.1991.tb07417.x Tables Table-1: Prevalence of different types of anthropometric malnutrition among children (aged 0-59 months) living in the poorest households in India Malnutrition conditions Weighted frequency (N=47,467) Weighted proportion [95% CI] Stunting and underweight [HAZ < -2SD & WAZ < -2SD] 10,534 22.2 [21.8 - 22.6] Stunting only [HAZ < -2SD] 7,118 15.0 [14.7 - 15.3] Wasting and underweight [WHZ < -2SD & WAZ < -2SD] 4,275 9.0 [8.8 - 9.3] Stunting, wasting and underweight [HAZ < -2SD & WHZ < -2SD & WAZ < -2SD] 3,725 7.8 [7.6 - 8.1] Wasting only [WHZ < -2SD] 2,717 5.7 [5.5 - 5.9] Underweight only [WAZ < -2SD] 1,203 2.5 [2.4 - 2.7] Stunting and overweight [HAZ + 2SD] 761 1.6 [1.5 - 1.7] Overweight only [WHZ > + 2SD] 245 0.5 [0.5 - 0.6] Stunting, underweight and overweight [HAZ < -2SD & WAZ + 2SD] 79 0.2 [0.1- 0.2] Any forms of anthropometric malnutrition 30,657 64.5 [64.1 - 65.0] No forms of anthropometric malnutrition 16,810 35.5 [35.0 - 35.8] Table-2: Proportion of children (aged 0-59 months) living in the poorest households in India with no anthropometric malnutrition by their household, maternal, and individual characteristics Characteristics Weighted N Weighted Proportion [95% CI] Religion Hindu 47,467 38,502 35.1 [34.7 - 35.6] Muslim 7,319 36.4 [35.3 - 37.5] Christian 987 38.0 [35.0 - 41.0] Others 659 37.7 [34.0 - 41.4] Caste/Tribe Others 44,197 3,893 39.7 [38.2 - 41.2] Scheduled Caste 13,813 33.6 [32.8 - 34.4] Scheduled Tribe 9,658 35.3 [34.4 - 36.3] Other Backwards classes 16,833 35.2 [34.5 - 35.9] Place of residence Urban 47,467 2,277 34.8 [32.0 - 36.8] Rural 45,190 35.4 [35.0 - 35.9] Availability of sanitation facility Improved 44,743 17,860 37.5 [36.8 - 38.2] Unimproved 1,767 38.7 [36.4 - 41.0] No facility 25,116 33.2 [32.6 - 33.8] Distance to health facility Distance is not a problem 47,467 29,801 35.7 [35.1 - 36.2] Distance is a problem 17,666 35.0 [34.3 - 35.7] Age at first birth 25-31 years 47,467 3,858 35.7 [34.2 - 37.2] 31 years 332 34.9 [30.0 - 40.2] Maternal education Higher education 47,468 818 50.3 [46.9 - 53.7] Secondary 16,633 39.8 [39.1 - 40.6] Primary 8,720 35.4 [34.4 - 36.4] No education 21,297 31.4 [30.8 - 32.0] Maternal height < 145 cm 47,259 8,513 24.7 [23.8-25.6] 145 cm to 154.9 cm 30,476 35.3 [34.7-35-8] ≥ 155 cm 8,270 47.0 [46.0-48.1] No. of living children 1 child 47,467 9,029 38.8 [37.8 - 39.8] 2 children 15,487 38.0 [37.2 - 38.7] 3 children 11,431 33.8 [32.9 - 34.7] > 3 children 11,520 30.9 [30.1 - 31.8] Place of delivery Health facility 47,376 36,393 36.5 [36.0 - 37.0] Home 10,983 32.0 [31.1 - 32.9] Age of the child 0-11 months 47,467 8,766 43.4 [42.3 - 44.4] 12-23 months 9,258 31.8 [30.9 - 32.8] 24-35 months 9,536 32.8 [31.9 - 33.8] 36-47 months 9,849 33.1 [32.2 - 34.1] 47-59 months 10,058 36.5 [35.5 - 37.4] Sex of the child Male 47,467 24,212 34.6 [34.0 - 35.2] Female 23,255 36.3 [35.7 - 36.9] Birth weight Birth weight ≥ 2500 gm 39,262 31,414 38.1 [37.6 - 38.7] Birth weight < 2500 gm 7,848 29.2 [28.2 - 30.2] Table-3: Logistic regression odds ratios showing predictors of no anthropometric malnutrition among children (aged 0-59 months) living in the poorest households in India Characteristics Unadjusted Odd Ratio Adjusted Odd Ratio OR [95% CI] p value OR [95% CI] p value Religion Hindu 1 1 Muslim 1.06 [1.00 - 1.11] 0.040 0.89 [0.82 - 0.97] 0.008 Christian 1.13 [0.99 - 1.29] 0.065 1.07 [0.92 - 1.26] 0.369 Others 1.12 [0.95 - 1.31] 0.178 1.13 [0.94 - 1.37] 0.173 Caste/Tribe Scheduled Caste 1 1 Scheduled Tribe 1.08 [1.02 - 1.14] 0.006 0.99 [0.93 - 1.06] 0.785 Other Backwards classes 1.08 [1.03 - 1.13] 0.003 1.04 [0.99 - 1.10] 0.130 Others 1.30 [1.21 - 1.40] 0.000 1.30 [1.18 - 1.43] 0.000 Place of residence Urban 1 1 Rural 1.03 [0.94 - 1.12] 0.540 0.97 [0.87 - 1.08] 0.630 Availability of sanitation facility No facility 1 1 Unimproved 1.27 [1.15 - 1.40] 0.000 1.22 [1.07 - 1.38] 0.002 Improved 1.20 [1.16 - 1.25] 0.000 1.09 [1.04 - 1.15] 0.000 Distance to health facility Distance is not a problem 1 1 Distance is a problem 0.97 [0.94 - 1.01] 0.156 0.97 [0.93 - 1.02] 0.272 Age at first birth 25-31 years 1 1 31 years 0.97 [0.76 - 1.22] 0.783 1.01 [0.77 - 1.32] 0.929 Maternal education No education 1 1 Primary 1.20 [1.13 - 1.26] 0.000 1.13 [1.05 - 1.20] 0.000 Secondary 1.45 [1.39 - 1.51] 0.000 1.30 [1.20 - 1.34] 0.000 Higher education 2.21 [1.92 - 2.54] 0.000 1.92 [1.63 - 2.28] 0.000 Maternal height 3 children 1 1 3 children 1.14 [1.08 - 1.21] 0.000 1.05 [0.99 - 1.13] 0.101 2 children 1.37 [1.30 - 1.44] 0.000 1.21 [1.14 - 1.29] 0.000 1 child 1.41 [1.34 - 1.50] 0.000 1.21 [1.12 - 1.31] 0.000 Place of delivery Home 1 1 Health facility 1.22 [1.17 - 1.28] 0.000 1.06 [0.99 - 1.15] 0.062 Age of the child 0-11 months 1 1 12-23 months 0.61 [0.57 - 0.65] 0.000 0.61 [0.57 - 0.66] 0.000 24-35 months 0.64 [0.60 - 0.68] 0.000 0.64 [0.60 - 0.69] 0.000 36-47 months 0.65 [0.61 - 0.69] 0.000 0.70 [0.65 - 0.75] 0.000 48-59 months 0.75 [0.71 - 0.79] 0.000 0.82 [0.76 - 0.88] 0.000 Sex of the child Male 1 1 Female 1.08 [1.04 - 1.12] 0.000 1.09 [1.04 - 1.14] 0.000 Birth weight Birth weight < 2500 gm 1 1 Birth weight ≥ 2500 gm 1.49 [1.41 - 1.57] 0.000 1.51 [1.42 - 1.60] 0.000 Additional Declarations No competing interests reported. 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11:17:27","extension":"html","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":153673,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8140708/v1/573777fac4cede4a19834496.html"},{"id":100388301,"identity":"7c4c0392-154a-4b27-b836-1eae57eac995","added_by":"auto","created_at":"2026-01-16 11:17:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84186,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram showing inclusion and exclusion criteria followed for arriving at the final analytical samples\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8140708/v1/5deb67e166dd884fa6b8a500.png"},{"id":100421471,"identity":"eafa53de-5640-4639-9f95-665b0c78347a","added_by":"auto","created_at":"2026-01-16 13:33:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1446678,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8140708/v1/42a36af4-fdf0-4d07-9021-e2a7da013214.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding resilience to anthropometric malnutrition: Why some children in poverty remain free from all forms of malnutrition – An analysis of India’s National Family Health Survey-5","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eChildhood malnutrition remains a major global health challenge, disproportionately affecting children in low-income and resource-constrained settings (Aguayo \u0026amp; Menon, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Siddiqui, Salam, Lassi, \u0026amp; Das, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; UNICEF, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Villadsen et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This disproportionate burden is largely driven by a range of interrelated disadvantages, including inadequate access to nutritious food, essential healthcare services, proper sanitation, and safe living conditions (Deolalikar, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Panda, Mohanty, Nayak, Shastri, \u0026amp; Subramanian, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Pe\u0026ntilde;a \u0026amp; Bacallao, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; WHO, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These intersecting deprivations increase the immediate risk of malnutrition and disease, and also contribute to long-term adverse outcomes such as impaired cognitive development, reduced productivity, and persistent health inequalities\u0026mdash;ultimately hindering broader societal and economic development (Bhutta et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Gupta, de Wit, \u0026amp; McKeown, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Hoddinott, Maluccio, Behrman, Flores, \u0026amp; Martorell, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; C. G. Victora et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Recognizing these far-reaching consequences, the 2030 Agenda for Sustainable Development have placed the elimination of poverty and malnutrition at the forefront of international development goals (Scott et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sherratt, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGlobally, an estimated 333\u0026nbsp;million children live in extreme poverty, with approximately 90% residing in Sub-Saharan Africa and South Asia (Salmeron Gomez, Engilbertsdottir, Cuesta Leiva, Newhouse, \u0026amp; Stewart, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite India\u0026rsquo;s notable economic growth in recent decades, child malnutrition persists as a serious public health concern, marked by significant regional and socio-economic disparities (Joe, Rajaram, \u0026amp; Subramanian, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nguyen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). According to the most recent National Family Health Survey (NFHS-5), 35.5% of Indian children under the age of five are stunted, 19.3% are wasted, and 32.1% are underweight (IIPS \u0026amp; ICF, 2021). These figures are even higher in communities where poverty remains widespread (Jaleel et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; S. K. Singh, Srivastava, \u0026amp; Chauhan, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Striessnig \u0026amp; Bora, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough a substantial body of research has examined the risk factors contributing to child malnutrition\u0026mdash;such as dietary inadequacies, poor maternal health, inadequate sanitation, and low household income (Adeyeye, Ashaolu, Bolaji, Abegunde, \u0026amp; Omoyajowo, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Atinmo, Mirmiran, Oyewole, Belahsen, \u0026amp; Serra-Majem, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Birdi, Joshi, Kotian, \u0026amp; Shah, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gulati, Ganesh-Kumar, Shreedhar, \u0026amp; Nandakumar, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Siddiqui et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tanumihardjo et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) \u0026mdash;comparatively less attention has been paid to understanding why some children manage to remain well-nourished despite living in similarly adverse conditions. This gap in research limits the development of strengths-based and resilience-focused approaches to malnutrition prevention.\u003c/p\u003e \u003cp\u003eTo address this gap, the present study explores the factors that enable certain children in impoverished Indian households to remain free from all forms of anthropometric malnutrition. Drawing on data from India\u0026rsquo;s National Family Health Survey-5, the study employs a Positive Deviance (PD) approach (Zeitlin, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), which seeks to identify the unique features of children who achieve better outcomes than their peers despite facing similar risks. By identifying these resilience factors, this study aims to inform nutrition interventions for leveraging the existing strengths within vulnerable communities for more sustainable malnutrition prevention interventions.\u003c/p\u003e"},{"header":"2. Data and methods","content":"\u003cp\u003eThis study utilizes data from the National Family Health Survey-5 (NFHS-5), a nationally representative household survey conducted between 2019 and 2021 in India. The NFHS-5 provides comprehensive estimates on population, health, and nutrition at the National, State/Union Territory (UT), and District levels. The survey was conducted in 636,699 households across India using Computer-Assisted Personal Interviewing (CAPI), collecting data from 724,115 women (aged 15\u0026ndash;49 years), 101,839 men (aged 15\u0026ndash;54 years), and 232,920 children (aged 0\u0026ndash;59 months).\u003c/p\u003e \u003cp\u003eFor this analysis, we used the children\u0026rsquo;s dataset (IAKR7AFL file) in Stata format, obtained from the Demographic and Health Survey (DHS) Program portal. The dataset includes information on children's health and nutrition, immunization history, feeding practices, and maternal characteristics. The NFHS also contains children's anthropometric measurements\u0026mdash;height/length (in cm) and weight (in kg). Children's weight (0\u0026ndash;59 months) was measured using the Seca 874 digital scale. The height of the children (24\u0026ndash;59 months) was measured with a Seca 213 stadiometer. The Seca 417 infantometer was used to measure the recumbent length of children under two years. Additionally, the dataset includes World Health Organization (WHO) Z-scores for Height-for-Age (HAZ), Weight-for-Height (WHZ), and Weight-for-Age (WAZ), allowing classification of children as stunted, wasted, and underweight.\u003c/p\u003e \u003cp\u003eNFHS-5 assessed household wealth based on the ownership of consumer goods (e.g., televisions, bicycles, cars, etc.) and housing characteristics (e.g., water source, toilet facilities, flooring material). A wealth score was assigned using principal component analysis (PCA), ranking households into five wealth quintiles such as poorest (lowest quintile); poor (second quintile); middle (third quintile); rich (fourth quintile); richest (fifth quintile). For this study, we focused exclusively on children from the poorest wealth quintile (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn this analysis, we calculated a Composite Index of Anthropometric Malnutrition (CIAM) (Nandeep ER, 2023). This index accounts for nine biologically possible forms of malnutrition among children under five years, derived from HAZ, WHZ, and WAZ scores. The possible forms of malnutrition conditions among children under five years are:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStunting only \u003cem\u003e(HAZ \u0026lt; -2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWasting only \u003cem\u003e(WHZ \u0026lt; -2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUnderweight only \u003cem\u003e(WAZ \u0026lt; -2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStunting\u0026thinsp;+\u0026thinsp;Wasting\u0026thinsp;+\u0026thinsp;Underweight \u003cem\u003e(HAZ \u0026lt; -2SD \u0026amp; WHZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStunting\u0026thinsp;+\u0026thinsp;Underweight \u003cem\u003e(HAZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWasting\u0026thinsp;+\u0026thinsp;Underweight \u003cem\u003e(WHZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStunting\u0026thinsp;+\u0026thinsp;Overweight \u003cem\u003e(HAZ \u0026lt; -2SD \u0026amp; WHZ\u0026thinsp;\u0026gt;\u0026thinsp;+\u0026thinsp;2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eOverweight only \u003cem\u003e(WHZ\u0026thinsp;\u0026gt;\u0026thinsp;+\u0026thinsp;2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStunting\u0026thinsp;+\u0026thinsp;Underweight\u0026thinsp;+\u0026thinsp;Overweight \u003cem\u003e(HAZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD \u0026amp; WHZ\u0026thinsp;\u0026gt;\u0026thinsp;+\u0026thinsp;2SD)\u003c/em\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eFor this analysis, we dichotomized the index into two \u0026mdash; Children experiencing any form of malnutrition\u0026thinsp;=\u0026thinsp;0, and Children free from all forms of malnutrition\u0026thinsp;=\u0026thinsp;1. We employed binary logistic regression analysis to examine factors associated with the absence of all forms of anthropometric malnutrition among children aged 0\u0026ndash;59 months in the poorest households. The analysis produced unadjusted and adjusted odds ratios (ORs) with corresponding \u003cem\u003ep-values\u003c/em\u003e and 95% confidence intervals (CIs). The independent variables included in the analysis were: Demographic factors (child\u0026rsquo;s age, sex, birth weight); maternal characteristics (mother\u0026rsquo;s education level, height, number of living children); household environment (place of residence, sanitation facilities, healthcare access); socio-cultural factors (religion, caste/tribe), and factors associated to healthcare access (place of delivery, proximity to healthcare facility). To account for multiple testing and reduce the risk of Type 1 errors (false positives), significance was determined at a false discovery rate (FDR) of 0.005.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Prevalence and characteristics of anthropometric malnutrition\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;1 presents the prevalence of different forms of anthropometric malnutrition among children under five years of age in the poorest households in India. The findings reveal that nearly 65% of these children experience some form of malnutrition, with stunting, wasting, underweight, and overweight occurring either independently or in combination. The most prevalent form of malnutrition is the coexistence of stunting and underweight (22.2%), followed by stunting alone (15%), wasting combined with underweight (9%), and the simultaneous presence of stunting, wasting, and underweight (7.8%). Notably, despite living in extreme poverty, 35% of children do not show any form of malnutrition.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;2 provides the weighted proportion and distribution of children under five years of age in extreme poverty who do not experience anthropometric malnutrition, categorised by household, maternal, and individual characteristics. The proportion of children without malnutrition is highest among Christians (38.0%). Caste disparities are evident, with children from 'Other castes' having the highest proportion of no anthropometric malnutrition (39.7%), compared to those belonging to Scheduled Castes, Scheduled Tribes, and Other Backward Classes.\u003c/p\u003e \u003cp\u003eHousehold sanitation access emerges as a crucial factor, with children living in households with improved sanitation facilities showing the highest proportion of no anthropometric malnutrition (37.5%). Maternal education is another enabler; the proportion of children without anthropometric malnutrition increases with higher maternal education, reaching 50.3% among children of mothers with higher education, compared to 31.4% among those whose mothers have no formal education.\u003c/p\u003e \u003cp\u003eMaternal height also plays a critical role. Children born to mothers with a height of 155 cm or more have the highest proportion of no anthropometric malnutrition (47%). Similarly, family size influences malnutrition outcomes, with the highest proportion of well-nourished children observed among those whose mothers have only one living child (38.8%), decreasing as the number of siblings increases. Birth circumstances further impact malnutrition status, with children delivered in health facilities showing a higher proportion of no anthropometric malnutrition (36.5%) compared to those born at home. Age and birth weight are also key factors; children aged 0\u0026ndash;11 months have the highest proportion of no anthropometric malnutrition (43.4%), while those aged 12\u0026ndash;23 months have the lowest (31.8%). Additionally, children with a birth weight of at least 2500 grams are more likely to remain unaffected by any malnutrition (38.1%) compared to those with a birth weight below 2500 grams (29.2%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Predictors of anthropometric resilience among children\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;3 presents the results of the logistic regression analysis examining the predictors of resilience to anthropometric malnutrition among children under five years from the poorest households in India. Both unadjusted and adjusted odds ratios, along with their respective \u003cem\u003ep\u003c/em\u003e-values and 95% confidence intervals, are reported. Among all predictors, maternal height has the strongest association with the absence of anthropometric malnutrition. Compared to children of mothers shorter than 145 cm, those born to mothers with heights of 145\u0026ndash;154.9 cm and \u0026ge;\u0026thinsp;155 cm has substantially higher odds of remaining well-nourished (OR: 1.67 and 2.71, respectively). Maternal education is also strongly associated with malnutrition resilience, with children of mothers with primary, secondary, and higher education levels exhibiting significantly higher odds of being free from all forms of malnutrition compared to those whose mothers have no formal education.\u003c/p\u003e \u003cp\u003eFamily size is another key predictor, with children from smaller families having a greater likelihood of avoiding malnutrition. Birth weight is also a significant determinant, as children born weighing 2500 grams or more have significantly higher odds of no anthropometric malnutrition compared to those with lower birth weights. Lastly, as children grow older, their probability of being unaffected by anthropometric malnutrition also increases.\u003c/p\u003e \u003cp\u003eCaste emerges as a significant factor, with children belonging to the 'Other caste' category having higher odds (OR: 1.3) of being well-nourished compared to those from Scheduled Castes. Sanitation access is also a crucial determinant; children in households with improved sanitation facilities have significantly higher odds of being free from anthropometric malnutrition compared to those without any sanitation facilities.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study identifies the key characteristics of children who achieved exceptional nutritional outcomes despite living in economically disadvantaged households. Our analysis of India's National Family Health Survey-5 (NFHS-5) reveals that maternal height (above 155 cm) and maternal education (beyond secondary level) are the most significant predictors of optimal child nutritional outcomes in poor households. In addition, programmatic factors\u0026mdash;including access to improved sanitation, smaller family sizes, and a healthy birth weight (\u0026ge;\u0026thinsp;2500 g)\u0026mdash;emerge as critical determinants that mitigate the risk of all forms of anthropometric malnutrition.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Maternal nutrition and intergenerational effects\u003c/h2\u003e \u003cp\u003eMaternal nutrition and linear growth are foundational determinants of child health. The literature consistently underscores the intergenerational consequences of maternal undernutrition, particularly short maternal stature, which is associated with adverse birth outcomes such as low birth weight, child stunting, increased delivery complications, and higher child mortality rates (Abu-Saad \u0026amp; Fraser, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kozuki et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Martorell \u0026amp; Zongrone, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ozaltin, Hill, \u0026amp; Subramanian, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; D. P. Singh, Biradar, Halli, \u0026amp; Dwivedi, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Cesar G. Victora et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Mothers with inadequate linear growth are more likely to give birth to stunted children, perpetuating a cycle of malnutrition across generations (F\u0026eacute;lix-Beltr\u0026aacute;n, Macinko, \u0026amp; Kuhn, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Porwal et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This highlights the urgent need for targeted interventions focusing on the nutritional needs of adolescent girls and women of reproductive age. Such interventions are essential not only to improve birth outcomes but also to enhance long-term child development and human capital formation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Maternal education and health literacy\u003c/h2\u003e \u003cp\u003eMaternal education is another crucial protective factor. Educated mothers are more likely to possess knowledge about appropriate feeding practices, healthcare utilization, and hygiene, which directly contributes to better nutritional outcomes in children (Abuya, Ciera, \u0026amp; Kimani-Murage, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Gbratto-Dobe \u0026amp; Segnon, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Prasetyo, Permatasari, \u0026amp; Susanti, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rezaeizadeh et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Health education interventions delivered by frontline health workers (FHWs)\u0026mdash;through home visits, antenatal counseling, and community outreach\u0026mdash;have proven effective in increasing awareness and adoption of optimal childcare practices, especially in resource-constrained settings (Rammohan, Goli, Saroj, \u0026amp; Jaleel, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Expanding the reach and capacity of FHWs can therefore play a transformative role in improving child health and nutrition in impoverished households.\u003c/p\u003e \u003cp\u003e \u003cem\u003eSanitation and hygiene\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAccess to improved sanitation remains a powerful, yet unequally distributed, determinant of child nutritional status. Sanitation-related inequities disproportionately affect the poorest households, contributing to a high burden of infectious diseases, including diarrhea, which in turn exacerbates malnutrition (Li, Li, Subramanian, \u0026amp; Lu, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Studies have shown that inadequate sanitation contributes significantly to anemia in women and malnutrition in children, often through chronic enteric infections and environmental enteropathy (Kothari et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Between 1990 and 2015, improvements in sanitation infrastructure contributed to a 10% reduction in child mortality globally, underscoring its vital role in public health (Headey \u0026amp; Palloni, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Bridging the sanitation gap is thus imperative to improving nutritional resilience among the poorest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Birth weight and early life nutrition\u003c/h2\u003e \u003cp\u003eHealthy birth weight serves as a strong protective factor against all forms of anthropometric malnutrition. Low birth weight (LBW) infants are significantly more likely to suffer from stunting, wasting, and underweight compared to their normal-weight peers (A. Jana, D. Dey, \u0026amp; R. Ghosh, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rahman, Howlader, Masud, \u0026amp; Rahman, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Evidence suggests that LBW accounts for 10\u0026ndash;15% of the variation in anthropometric malnutrition outcomes among children across socioeconomic strata. (Arup Jana, Deepshikha Dey, \u0026amp; Ranjita Ghosh, 2023). Preventing LBW through adequate antenatal care, maternal nutrition, and timely interventions during pregnancy is critical to disrupting the early onset of growth faltering and undernutrition.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Structural inequalities and social exclusion\u003c/h2\u003e \u003cp\u003eFinally, structural determinants such as caste-based social exclusion exacerbate malnutrition risks among India\u0026rsquo;s poorest children. Our findings corroborate previous research showing that children from Scheduled Castes (SCs), Scheduled Tribes (STs), and Other Backward Classes (OBCs) are disproportionately affected by malnutrition\u0026mdash;even when controlling for economic status. These disparities highlight the intersectionality of poverty and marginalization, where caste-based discrimination compounds the effects of material deprivation (Samuel, Flores, \u0026amp; Frisancho, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Addressing malnutrition in India therefore requires more than just economic or healthcare inputs; it calls for institutional reforms aimed at dismantling social hierarchies and democratizing access to health and nutrition services.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Strengths and limitations\u003c/h2\u003e \u003cp\u003eThis study benefits from the use of a nationally representative dataset, enhancing the generalisability of the findings to India\u0026rsquo;s broader population living in poverty. The large sample size provides statistical power, enabling robust examination of multiple socioeconomic and programmatic predictors associated with resilience to anthropometric malnutrition. By incorporating a diverse set of variables, the analysis provides a comprehensive understanding of the factors that protect children in impoverished households from all forms of anthropometric malnutrition.\u003c/p\u003e \u003cp\u003eA key methodological strength lies in the intentional restriction of the sample to children from the poorest wealth quintile. This approach addresses an important epistemological concern: statistical models, while effective in identifying population-level trends, often obscure the heterogeneity of individual experiences. Aggregated patterns may offer actuarial rather than causal explanations. By narrowing the analytical focus, we sought to reduce within-group variability and improve the internal validity of the findings. This design choice enhances the study\u0026rsquo;s ability to generate actionable insights for policymakers aiming to strengthen resilience among the most vulnerable.\u003c/p\u003e \u003cp\u003eHowever, certain limitations warrant consideration. First, there is the potential for residual confounding. Although the model accounts for a broad range of variables grounded in existing literature, unmeasured or unobserved factors\u0026mdash;such as caregiving quality, psychosocial stress, or micronutrient intake\u0026mdash;may influence nutritional outcomes and were not captured in this dataset. Second, the study may be subject to reporting biases, particularly concerning household assets. Respondents may under-report possessions due to perceived links between survey responses and eligibility for government programs. While such misreporting is unlikely to vary substantially within the poorest quintile, it could slightly affect household rankings or wealth indices.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn the context of children's nutritional well-being, certain factors possess the potential to mitigate even the most profound form of deprivation faced by humanity\u0026mdash;poverty. These factors include maternal nutrition, maternal education, access to safe sanitation, optimal birth weight, and protection from social exclusion and discrimination. Strengthening maternal education, improving sanitation infrastructure, and promoting inclusive access to healthcare are critical strategies for enhancing nutritional resilience among children in economically disadvantaged households in India.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare that they have no competing interests.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data utilized in this study are publicly accessible through the Demographic and Health Survey (DHS) Program portal: https://dhsprogram.com/data/\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis draws on secondary data from the National Family Health Survey-5 (NFHS-5), accessed via the Demographic and Health Surveys (DHS) program portal. The survey was implemented by the International Institute for Population Sciences (IIPS), Mumbai, with all necessary ethical and regulatory approvals in place. As the data are de-identified and publicly available, no further ethical approval was required for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUsage of AI and software:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChatGPT ( https://chatgpt.com/) was used solely for language accuracy verification. No content of this manuscript was generated by artificial intelligence.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific funding from public, commercial, or not-for-profit agencies.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAJ and SRN conceptualised the study. AJ and NER conducted the analyses. SRN, AN, BRP, SPV, and HM validated the analytical approach. AJ drafted the manuscript and prepared all figures and tables. All authors reviewed and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbu-Saad, K., \u0026amp; Fraser, D. (2010). Maternal Nutrition and Birth Outcomes. \u003cem\u003eEpidemiologic Reviews, 32\u003c/em\u003e(1), 5-25. doi:10.1093/epirev/mxq001 %J Epidemiologic Reviews\u003c/li\u003e\n \u003cli\u003eAbuya, B. A., Ciera, J., \u0026amp; Kimani-Murage, E. (2012). Effect of mother\u0026rsquo;s education on child\u0026rsquo;s nutritional status in the slums of Nairobi. \u003cem\u003eBMC Pediatrics, 12\u003c/em\u003e(1), 80. doi:10.1186/1471-2431-12-80\u003c/li\u003e\n \u003cli\u003eAdeyeye, S. A. O., Ashaolu, T. J., Bolaji, O. T., Abegunde, T. A., \u0026amp; Omoyajowo, A. O. (2023). Africa and the Nexus of poverty, malnutrition and diseases. \u003cem\u003eCrit Rev Food Sci Nutr, 63\u003c/em\u003e(5), 641-656. doi:10.1080/10408398.2021.1952160\u003c/li\u003e\n \u003cli\u003eAguayo, V. M., \u0026amp; Menon, P. (2016). Stop stunting: improving child feeding, women\u0026apos;s nutrition and household sanitation in South Asia. \u003cem\u003eMatern Child Nutr, 12 Suppl 1\u003c/em\u003e(Suppl 1), 3-11. doi:10.1111/mcn.12283\u003c/li\u003e\n \u003cli\u003eAtinmo, T., Mirmiran, P., Oyewole, O. E., Belahsen, R., \u0026amp; Serra-Majem, L. (2009). Breaking the poverty/malnutrition cycle in Africa and the Middle East. \u003cem\u003eNutr Rev, 67 Suppl 1\u003c/em\u003e, S40-46. doi:10.1111/j.1753-4887.2009.00158.x\u003c/li\u003e\n \u003cli\u003eBhutta, Z. A., Berkley, J. A., Bandsma, R. H. J., Kerac, M., Trehan, I., \u0026amp; Briend, A. (2017). Severe childhood malnutrition. \u003cem\u003eNat Rev Dis Primers, 3\u003c/em\u003e, 17067. doi:10.1038/nrdp.2017.67\u003c/li\u003e\n \u003cli\u003eBirdi, T. J., Joshi, S., Kotian, S., \u0026amp; Shah, S. (2014). Possible causes of malnutrition in Melghat, a tribal region of Maharashtra, India. \u003cem\u003eGlob J Health Sci, 6\u003c/em\u003e(5), 164-173. doi:10.5539/gjhs.v6n5p164\u003c/li\u003e\n \u003cli\u003eDeolalikar, A. B. J. J. o. D. S. (2005). Poverty and child malnutrition in Bangladesh.\u003cem\u003e\u0026nbsp;21\u003c/em\u003e(1-2), 55-90.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eF\u0026eacute;lix-Beltr\u0026aacute;n, L., Macinko, J., \u0026amp; Kuhn, R. (2021). Maternal height and double-burden of malnutrition households in Mexico: stunted children with overweight or obese mothers. \u003cem\u003ePublic Health Nutr, 24\u003c/em\u003e(1), 106-116. doi:10.1017/s136898002000292x\u003c/li\u003e\n \u003cli\u003eGbratto-Dobe, S. A. W., \u0026amp; Segnon, H. B. (2025). Is mother\u0026apos;s education essential to improving the nutritional status of children under five in C\u0026ocirc;te d\u0026prime;Ivoire? \u003cem\u003eSSM - Health Systems, 4\u003c/em\u003e, 100056. doi:https://doi.org/10.1016/j.ssmhs.2025.100056\u003c/li\u003e\n \u003cli\u003eGulati, A., Ganesh-Kumar, A., Shreedhar, G., \u0026amp; Nandakumar, T. (2012). Agriculture and malnutrition in India. \u003cem\u003eFood Nutr Bull, 33\u003c/em\u003e(1), 74-86. doi:10.1177/156482651203300108\u003c/li\u003e\n \u003cli\u003eGupta, R. P., de Wit, M. L., \u0026amp; McKeown, D. (2007). The impact of poverty on the current and future health status of children. \u003cem\u003ePaediatr Child Health, 12\u003c/em\u003e(8), 667-672. doi:10.1093/pch/12.8.667\u003c/li\u003e\n \u003cli\u003eHeadey, D., \u0026amp; Palloni, G. (2019). Water, Sanitation, and Child Health: Evidence From Subnational Panel Data in 59 Countries. \u003cem\u003eDemography, 56\u003c/em\u003e(2), 729-752. doi:10.1007/s13524-019-00760-y\u003c/li\u003e\n \u003cli\u003eHoddinott, J., Maluccio, J. A., Behrman, J. R., Flores, R., \u0026amp; Martorell, R. (2008). Effect of a nutrition intervention during early childhood on economic productivity in Guatemalan adults. \u003cem\u003eLancet, 371\u003c/em\u003e(9610), 411-416. doi:10.1016/s0140-6736(08)60205-6\u003c/li\u003e\n \u003cli\u003eIIPS, \u0026amp; ICF. (2021). \u003cem\u003eNational Family Health Survey -5\u003c/em\u003e. Retrieved from Mumbai:\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJaleel, A., Arlappa, N., Ramakrishna, K. S., Sunu, P., Jayalakshmi, G., Neeraja, G., . . . Kumar, S. B. (2023). Examining the Triple Burden of Malnutrition: Insights from a Community-Based Comprehensive Nutrition Survey among Indigenous Tribal Children (0\u0026ndash;19 Years) in the Western Ghats Hills of India. \u003cem\u003eNutrients, 15\u003c/em\u003e(18), 3995.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eJana, A., Dey, D., \u0026amp; Ghosh, R. (2023). Contribution of low birth weight to childhood undernutrition in India: evidence from the national family health survey 2019-2021. \u003cem\u003eBMC Public Health, 23\u003c/em\u003e(1), 1336. doi:10.1186/s12889-023-16160-2\u003c/li\u003e\n \u003cli\u003eJana, A., Dey, D., \u0026amp; Ghosh, R. (2023). Contribution of low birth weight to childhood undernutrition in India: evidence from the national family health survey 2019\u0026ndash;2021. \u003cem\u003eBMC Public Health, 23\u003c/em\u003e(1), 1336. doi:10.1186/s12889-023-16160-2\u003c/li\u003e\n \u003cli\u003eJoe, W., Rajaram, R., \u0026amp; Subramanian, S. V. (2016). Understanding the null-to-small association between increased macroeconomic growth and reducing child undernutrition in India: role of development expenditures and poverty alleviation. \u003cem\u003eMatern Child Nutr, 12 Suppl 1\u003c/em\u003e(Suppl 1), 196-209. doi:10.1111/mcn.12256\u003c/li\u003e\n \u003cli\u003eKothari, M. T., Coile, A., Huestis, A., Pullum, T., Garrett, D., \u0026amp; Engmann, C. (2019). Exploring associations between water, sanitation, and anemia through 47 nationally representative demographic and health surveys. \u003cem\u003eAnn N Y Acad Sci, 1450\u003c/em\u003e(1), 249-267. doi:10.1111/nyas.14109\u003c/li\u003e\n \u003cli\u003eKozuki, N., Katz, J., Lee, A. C. C., Vogel, J. P., Silveira, M. F., Sania, A., . . . Black, R. E. (2015). Short Maternal Stature Increases Risk of Small-for-Gestational-Age and Preterm Births in Low- and Middle-Income Countries: Individual Participant Data Meta-Analysis and Population Attributable Fraction1, 2, 3. \u003cem\u003eJ Nutr, 145\u003c/em\u003e(11), 2542-2550. doi:https://doi.org/10.3945/jn.115.216374\u003c/li\u003e\n \u003cli\u003eLi, Z., Li, M., Subramanian, S. V., \u0026amp; Lu, C. (2017). Assessing levels and trends of child health inequality in 88 developing countries: from 2000 to 2014. \u003cem\u003eGlob Health Action, 10\u003c/em\u003e(1), 1408385. doi:10.1080/16549716.2017.1408385\u003c/li\u003e\n \u003cli\u003eMartorell, R., \u0026amp; Zongrone, A. (2012). Intergenerational influences on child growth and undernutrition. \u003cem\u003ePaediatr Perinat Epidemiol, 26 Suppl 1\u003c/em\u003e, 302-314. doi:10.1111/j.1365-3016.2012.01298.x\u003c/li\u003e\n \u003cli\u003eNandeep ER, J. A., Reddy PB, Geddam JJB, Reddy NS and Hemalatha R. (2023). Developing and demonstrating an atomistic and holistic model of anthropometric failure among children under five years of age using the National Family Health Survey (NFHS)-5 data from India. \u003cem\u003eFrontiers in Nutrition, 10: 1280219\u003c/em\u003e.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNguyen, P. H., Scott, S., Headey, D., Singh, N., Tran, L. M., Menon, P., \u0026amp; Ruel, M. T. (2021). The double burden of malnutrition in India: Trends and inequalities (2006-2016). \u003cem\u003ePLoS One, 16\u003c/em\u003e(2), e0247856. doi:10.1371/journal.pone.0247856\u003c/li\u003e\n \u003cli\u003eOzaltin, E., Hill, K., \u0026amp; Subramanian, S. V. (2010). Association of maternal stature with offspring mortality, underweight, and stunting in low- to middle-income countries. \u003cem\u003eJAMA, 303\u003c/em\u003e(15), 1507-1516. doi:10.1001/jama.2010.450\u003c/li\u003e\n \u003cli\u003ePanda, B. K., Mohanty, S. K., Nayak, I., Shastri, V. D., \u0026amp; Subramanian, S. V. (2020). Malnutrition and poverty in India: does the use of public distribution system matter? \u003cem\u003eBMC Nutr, 6\u003c/em\u003e, 41. doi:10.1186/s40795-020-00369-0\u003c/li\u003e\n \u003cli\u003ePe\u0026ntilde;a, M., \u0026amp; Bacallao, J. (2002). Malnutrition and poverty. \u003cem\u003eAnnu Rev Nutr, 22\u003c/em\u003e, 241-253. doi:10.1146/annurev.nutr.22.120701.141104\u003c/li\u003e\n \u003cli\u003ePorwal, A., Agarwal, P. K., Ashraf, S., Acharya, R., Ramesh, S., Khan, N., . . . Sarna, A. (2021). Association of maternal height and body mass index with nutrition of children under 5 years of age in India: Evidence from Comprehensive National Nutrition Survey 2016-18. \u003cem\u003eAsia Pac J Clin Nutr, 30\u003c/em\u003e(4), 675-686. doi:10.6133/apjcn.202112_30(4).0014\u003c/li\u003e\n \u003cli\u003ePrasetyo, Y. B., Permatasari, P., \u0026amp; Susanti, H. D. (2023). The effect of mothers\u0026rsquo; nutritional education and knowledge on children\u0026rsquo;s nutritional status: a systematic review. \u003cem\u003eInternational Journal of Child Care and Education Policy, 17\u003c/em\u003e(1), 11. doi:10.1186/s40723-023-00114-7\u003c/li\u003e\n \u003cli\u003eRahman, M. S., Howlader, T., Masud, M. S., \u0026amp; Rahman, M. L. (2016). Association of Low-Birth Weight with Malnutrition in Children under Five Years in Bangladesh: Do Mother\u0026apos;s Education, Socio-Economic Status, and Birth Interval Matter? \u003cem\u003ePLoS One, 11\u003c/em\u003e(6), e0157814. doi:10.1371/journal.pone.0157814\u003c/li\u003e\n \u003cli\u003eRammohan, A., Goli, S., Saroj, S. K., \u0026amp; Jaleel, C. P. A. (2021). Does engagement with frontline health workers improve maternal and child healthcare utilisation and outcomes in India? \u003cem\u003eHum Resour Health, 19\u003c/em\u003e(1), 45. doi:10.1186/s12960-021-00592-1\u003c/li\u003e\n \u003cli\u003eRezaeizadeh, G., Mansournia, M. A., Keshtkar, A., Farahani, Z., Zarepour, F., Sharafkhah, M., . . . Poustchi, H. (2024). Maternal education and its influence on child growth and nutritional status during the first two years of life: a systematic review and meta-analysis. \u003cem\u003eeClinicalMedicine, 71\u003c/em\u003e, 102574. doi:10.1016/j.eclinm.2024.102574\u003c/li\u003e\n \u003cli\u003eSalmeron Gomez, D., Engilbertsdottir, S., Cuesta Leiva, J. A., Newhouse, D., \u0026amp; Stewart, D. (2023). Global Trends in Child Monetary Poverty According to International Poverty Lines.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSamuel, J., Flores, W., \u0026amp; Frisancho, A. (2020). Social exclusion and universal health coverage: health care rights and citizen-led accountability in Guatemala and Peru. \u003cem\u003eInt J Equity Health, 19\u003c/em\u003e(1), 216. doi:10.1186/s12939-020-01308-y\u003c/li\u003e\n \u003cli\u003eScott, N., Delport, D., Hainsworth, S., Pearson, R., Morgan, C., Huang, S., . . . Homer, C. S. E. (2020). Ending malnutrition in all its forms requires scaling up proven nutrition interventions and much more: a 129-country analysis. \u003cem\u003eBMC Med, 18\u003c/em\u003e(1), 356. doi:10.1186/s12916-020-01786-5\u003c/li\u003e\n \u003cli\u003eSherratt, S. (2023). Ameliorating poverty-related communication and swallowing disabilities: Sustainable Development Goal 1. \u003cem\u003eInt J Speech Lang Pathol, 25\u003c/em\u003e(1), 32-36. doi:10.1080/17549507.2022.2134458\u003c/li\u003e\n \u003cli\u003eSiddiqui, F., Salam, R. A., Lassi, Z. S., \u0026amp; Das, J. K. (2020). The Intertwined Relationship Between Malnutrition and Poverty. \u003cem\u003eFront Public Health, 8\u003c/em\u003e, 453. doi:10.3389/fpubh.2020.00453\u003c/li\u003e\n \u003cli\u003eSingh, D. P., Biradar, R. A., Halli, S. S., \u0026amp; Dwivedi, L. K. (2021). Effect of maternal nutritional status on children nutritional status in India. \u003cem\u003eChildren and Youth Services Review, 120\u003c/em\u003e, 105727. doi:https://doi.org/10.1016/j.childyouth.2020.105727\u003c/li\u003e\n \u003cli\u003eSingh, S. K., Srivastava, S., \u0026amp; Chauhan, S. (2020). Inequality in child undernutrition among urban population in India: a decomposition analysis. \u003cem\u003eBMC Public Health, 20\u003c/em\u003e(1), 1852. doi:10.1186/s12889-020-09864-2\u003c/li\u003e\n \u003cli\u003eStriessnig, E., \u0026amp; Bora, J. K. (2020). Under-Five Child Growth and Nutrition Status: Spatial Clustering of Indian Districts. \u003cem\u003eSpatial Demography, 8\u003c/em\u003e(1), 63-84. doi:10.1007/s40980-020-00058-3\u003c/li\u003e\n \u003cli\u003eTanumihardjo, S. A., Anderson, C., Kaufer-Horwitz, M., Bode, L., Emenaker, N. J., Haqq, A. M., . . . Stadler, D. D. (2007). Poverty, obesity, and malnutrition: an international perspective recognizing the paradox. \u003cem\u003eJ Am Diet Assoc, 107\u003c/em\u003e(11), 1966-1972. doi:10.1016/j.jada.2007.08.007\u003c/li\u003e\n \u003cli\u003eUNICEF. (2022). \u003cem\u003eChild Food Poverty: A Nutrition Crisis in Early Childhood\u003c/em\u003e. Retrieved from New York:\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eVictora, C. G., Adair, L., Fall, C., Hallal, P. C., Martorell, R., Richter, L., \u0026amp; Sachdev, H. S. (2008). Maternal and child undernutrition: consequences for adult health and human capital. \u003cem\u003eThe Lancet, 371\u003c/em\u003e(9609), 340-357. doi:10.1016/S0140-6736(07)61692-4\u003c/li\u003e\n \u003cli\u003eVictora, C. G., Adair, L., Fall, C., Hallal, P. C., Martorell, R., Richter, L., \u0026amp; Sachdev, H. S. (2008). Maternal and child undernutrition: consequences for adult health and human capital. \u003cem\u003eLancet, 371\u003c/em\u003e(9609), 340-357. doi:10.1016/s0140-6736(07)61692-4\u003c/li\u003e\n \u003cli\u003eVilladsen, A., Asaria, M., Skarda, I., Ploubidis, G. B., Williams, M. M., Brunner, E. J., \u0026amp; Cookson, R. (2023). Clustering of adverse health and educational outcomes in adolescence following early childhood disadvantage: population-based retrospective UK cohort study. \u003cem\u003eLancet Public Health, 8\u003c/em\u003e(4), e286-e293. doi:10.1016/s2468-2667(23)00029-4\u003c/li\u003e\n \u003cli\u003eWHO. (2020). Global nutrition policy review 2016-2017: country progress in creating enabling policy environments for promoting healthy diets and nutrition: summary. In \u003cem\u003eGlobal nutrition policy review 2016-2017: country progress in creating enabling policy environments for promoting healthy diets and nutrition: summary\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eZeitlin, M. (1991). Nutritional resilience in a hostile environment: positive deviance in child nutrition. \u003cem\u003eNutr Rev, 49\u003c/em\u003e(9), 259-268. doi:10.1111/j.1753-4887.1991.tb07417.x\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable-1: Prevalence of different types of anthropometric malnutrition among\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003echildren\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(aged 0-59 months)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;living in the poorest households in India\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalnutrition conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003efrequency\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=47,467)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted proportion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eStunting and underweight\u003c/p\u003e\n \u003cp\u003e[HAZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e10,534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e22.2 [21.8 - 22.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eStunting only\u003c/p\u003e\n \u003cp\u003e[HAZ \u0026lt; -2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e7,118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e15.0 [14.7 - 15.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eWasting and underweight\u003c/p\u003e\n \u003cp\u003e[WHZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e4,275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e9.0 [8.8 - 9.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eStunting, wasting and underweight\u003c/p\u003e\n \u003cp\u003e[HAZ \u0026lt; -2SD \u0026amp; WHZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3,725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e7.8 [7.6 - 8.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eWasting only\u003c/p\u003e\n \u003cp\u003e[WHZ \u0026lt; -2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2,717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e5.7 [5.5 - 5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eUnderweight only\u003c/p\u003e\n \u003cp\u003e[WAZ \u0026lt; -2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1,203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.5 [2.4 - 2.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eStunting and overweight\u003c/p\u003e\n \u003cp\u003e[HAZ \u0026lt; -2SD \u0026amp; WHZ \u0026gt; + 2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.6 [1.5 - 1.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eOverweight only\u003c/p\u003e\n \u003cp\u003e[WHZ \u0026gt; + 2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.5 [0.5 - 0.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eStunting, underweight and overweight\u003c/p\u003e\n \u003cp\u003e[HAZ \u0026lt; -2SD \u0026amp; WAZ \u0026lt; -2SD \u0026amp; WHZ \u0026gt; + 2SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.2 [0.1- 0.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eAny forms of anthropometric malnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e30,657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e64.5 [64.1 - 65.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 340px;\"\u003e\n \u003cp\u003eNo forms of anthropometric malnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e16,810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e35.5 [35.0 - 35.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable-2: Proportion of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003echildren\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(aged 0-59 months)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;living in the poorest households in India with\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eno anthropometric malnutrition\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;by their\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ehousehold, maternal, and individual characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"519\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Weighted N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted Proportion\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;[95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eHindu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e38,502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.1 [34.7 - 35.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7,319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e36.4 [35.3 - 37.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eChristian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e38.0 [35.0 - 41.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e37.7 [34.0 - 41.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCaste/Tribe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 62px;\"\u003e\n \u003cp\u003e44,197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3,893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e39.7 [38.2 - 41.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eScheduled Caste\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e13,813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e33.6 [32.8 - 34.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eScheduled Tribe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9,658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.3 [34.4 - 36.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eOther Backwards classes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e16,833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.2 [34.5 - 35.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2,277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e34.8 [32.0 - 36.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e45,190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.4 [35.0 - 35.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAvailability of sanitation facility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eImproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 62px;\"\u003e\n \u003cp\u003e44,743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e17,860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e37.5 [36.8 - 38.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eUnimproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1,767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e38.7 [36.4 - 41.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eNo facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e25,116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e33.2 [32.6 - 33.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance to health facility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eDistance is not a problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e29,801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.7 [35.1 - 36.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eDistance is a problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e17,666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.0 [34.3 - 35.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at first birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e25-31 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3,858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.7 [34.2 - 37.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u0026lt;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8,731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e34.8 [33.8 - 35.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e18-24 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e34,546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.5 [35.0 - 36.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u0026gt; 31 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e34.9 [30.0 - 40.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eHigher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e50.3 [46.9 - 53.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e16,633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e39.8 [39.1 - 40.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8,720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.4 [34.4 - 36.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e21,297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e31.4 [30.8 - 32.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal height\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u0026lt; 145 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8,513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e24.7 [23.8-25.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e145 cm to 154.9 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e30,476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e35.3 [34.7-35-8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u0026ge; 155 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8,270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e47.0 [46.0-48.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. of living children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e1 child\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9,029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e38.8 [37.8 - 39.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e2 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e15,487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e38.0 [37.2 - 38.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e3 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e11,431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e33.8 [32.9 - 34.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u0026gt; 3 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e11,520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e30.9 [30.1 - 31.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of delivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eHealth facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e36,393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e36.5 [36.0 - 37.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eHome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e10,983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e32.0 [31.1 - 32.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of the child\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e0-11 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8,766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e43.4 [42.3 - 44.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e12-23 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9,258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e31.8 [30.9 - 32.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e24-35 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9,536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e32.8 [31.9 - 33.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e36-47 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9,849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e33.1 [32.2 - 34.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e47-59 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e10,058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e36.5 [35.5 - 37.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex of the child\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e47,467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e24,212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e34.6 [34.0 - 35.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e23,255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e36.3 [35.7 - 36.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eBirth weight \u0026ge; 2500 gm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e39,262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e31,414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e38.1 [37.6 - 38.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 231px;\"\u003e\n \u003cp\u003eBirth weight \u0026lt; 2500 gm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7,848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e29.2 [28.2 - 30.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable-3: Logistic regression\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eodds\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;ratios showing predictors of no anthropometric malnutrition among children (aged 0-59 months) living in the poorest households in India\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnadjusted Odd Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted Odd Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR [95% CI]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eHindu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.06 [1.00 - 1.11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.89 [0.82 - 0.97]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eChristian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.13 [0.99 - 1.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.07 [0.92 - 1.26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.12 [0.95 - 1.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.13 [0.94 - 1.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCaste/Tribe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eScheduled Caste\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eScheduled Tribe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.08 [1.02 - 1.14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.99 [0.93 - 1.06]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eOther Backwards classes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.08 [1.03 - 1.13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.04 [0.99 - 1.10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.30 [1.21 - 1.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.30 [1.18 - 1.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.03 [0.94 - 1.12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.97 [0.87 - 1.08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.630\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAvailability of sanitation facility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eNo facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eUnimproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.27 [1.15 - 1.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.22 [1.07 - 1.38]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eImproved\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.20 [1.16 - 1.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.09 [1.04 - 1.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance to health facility\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eDistance is not a problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eDistance is a problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.97 [0.94 - 1.01]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.97 [0.93 - 1.02]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at first birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e25-31 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026lt;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.96 [0.89 - 1.04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.94 [0.86 - 1.04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e18-24 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.99 [0.93 - 1.07]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.96 [0.88 - 1.04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.331\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026gt; 31 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.97 [0.76 - 1.22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.01 [0.77 - 1.32]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.20 [1.13 - 1.26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.13 [1.05 - 1.20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.45 [1.39 - 1.51]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.30 [1.20 - 1.34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eHigher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.21 [1.92 - 2.54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.92 [1.63 - 2.28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal height\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026lt; 145 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e145 cm to 154.9 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.67 [1.53-1.80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.69 [1.59-1.81]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026ge; 155 cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.71 [2.47-2.98]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.74 [2.54-2.97]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. of living children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u0026gt; 3 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e3 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.14 [1.08 - 1.21]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.05 [0.99 - 1.13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e2 children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.37 [1.30 - 1.44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.21 [1.14 - 1.29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e1 child\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.41 [1.34 - 1.50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.21 [1.12 - 1.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of delivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eHome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eHealth facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.22 [1.17 - 1.28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.06 [0.99 - 1.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge of the child\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e0-11 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e12-23 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.61 [0.57 - 0.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.61 [0.57 - 0.66]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e24-35 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.64 [0.60 - 0.68]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.64 [0.60 - 0.69]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e36-47 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.65 [0.61 - 0.69]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.70 [0.65 - 0.75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e48-59 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.75 [0.71 - 0.79]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.82 [0.76 - 0.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex of the child\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.08 [1.04 - 1.12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.09 [1.04 - 1.14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eBirth weight \u0026lt; 2500 gm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 245px;\"\u003e\n \u003cp\u003eBirth weight \u0026ge; 2500 gm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.49 [1.41 - 1.57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.51 [1.42 - 1.60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Anthropometric malnutrition, children under five years, poverty, NFHS, India","lastPublishedDoi":"10.21203/rs.3.rs-8140708/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8140708/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWhile most research focuses on the causes of child malnutrition, less is known about children who stay healthy despite poverty. This study explores nutritional resilience, defined as the absence of all anthropometric malnutrition, among India\u0026rsquo;s poorest households. Using NFHS-5 (2019\u0026ndash;2021) data, we examined children aged 0\u0026ndash;59 months in the lowest wealth quintile. A Composite Index of Anthropometric Malnutrition measured nine malnutrition states, and binary logistic regression identified key predictors. About 35% of children in extreme poverty were malnutrition-free. Maternal height above 155 cm (OR: 2.74, 95% CI), maternal education, smaller families, adequate birth weight (\u0026ge;\u0026thinsp;2500 g), and improved sanitation promoted resilience. Findings highlight that child nutrition depends on maternal health, education, and environmental quality, beyond poverty reduction alone.\u003c/p\u003e","manuscriptTitle":"Understanding resilience to anthropometric malnutrition: Why some children in poverty remain free from all forms of malnutrition – An analysis of India’s National Family Health Survey-5","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 06:22:55","doi":"10.21203/rs.3.rs-8140708/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"44561470952212546044868740571421749777","date":"2026-04-27T10:43:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-09T04:08:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-11T10:21:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-11T09:54:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-10T06:47:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-12-10T06:36:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6c068408-275b-4821-b98d-34a298e411a5","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":60949296,"name":"Health sciences/Diseases"},{"id":60949297,"name":"Health sciences/Health care"},{"id":60949298,"name":"Health sciences/Medical research"},{"id":60949299,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-01-16T06:22:55+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 06:22:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8140708","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8140708","identity":"rs-8140708","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}