A Multilevel Analysis of Factors Associated with Stunting Among Children Under Five Years in Lesotho: A Study of The Lesotho Multiple Cluster Indicator Study Of 2018

A Multilevel Analysis of Factors Associated with Stunting Among Children Under Five Years in Lesotho: A Study of The Lesotho Multiple Cluster Indicator Study Of 2018 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Multilevel Analysis of Factors Associated with Stunting Among Children Under Five Years in Lesotho: A Study of The Lesotho Multiple Cluster Indicator Study Of 2018 Nthatisi Leseba, Kerry Vermaak, Tiisetso Makatjane, Mapitso Lebuso This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4703564/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 May, 2025 Read the published version in Journal of Health, Population and Nutrition → Version 1 posted 10 You are reading this latest preprint version Abstract Background The growth pattern of a healthy, well-fed child is reflected in positive changes in their height and weight [ 1 ]. Globally, complex, and intertwined determinants of stunting have been explored at individual, household, and community level but not in Lesotho. The objective of the study is to investigate the determinants of stunting at individual, household, and community level. Methods We conducted a multilevel logistic regression using data from the Lesotho Multiple Cluster Indicator Study of 2018. Results In Lesotho a third (33.6%) of children under 5 were stunted in 2018. At individual level, child dietary intake, weight at birth and respiratory infection were determinants of stunting. At the household level, place of residence, household wealth, maternal residential status, maternal educational attainment, drinking water sources, and toilet facilities were also determinants of stunting. Moreover, at community levels, community female and male education, community poverty, sources of drinking water, toilet facilities and maternal media exposure were determinants of stunting in Lesotho in 2018. Conclusion There is evidence of variability in the data in relation to stunting at all levels of the study. It also shows that, child dietary intake and health, household care resources, and environments children reside in are important in improving child nutritional status. At the community level, knowledge and information acquisition and sharing are important in fighting child malnutrition. Therefore, strategies and programs to improve child nutritional status should be done in communities. Multilevel Child Malnutrition Stunting Childhood Introduction The growth pattern of a healthy, well-fed child is reflected in positive changes in their height and weight [1]. However, this is not the case for most children in the world. The impact of child malnutrition is more pronounced in low and middle-income countries, particularly in South Asia and Sub-Saharan Africa (SSA) [2,3,4,5]. This is because nine out of ten African children do not meet the criteria for a minimum acceptable diet outlined by the WHO; and two out of five do not eat meals regularly [6]. Health and physical consequences of prolonged states of malnourished among children are: developmental delays, lower intellectual quotient, delayed cognitive development, greater behavioural problems, and deficient social skills; susceptibility to contracting diseases [7, 8]. Moreover, long-term consequences of child malnutrition may be inclusive of increased chances of non-communicable diseases (hypertension, diabetes, and heart conditions), and poor maternal reproductive health outcomes later in life (perpetuating the cycle of malnutrition) and decreased work capacity and productivity as adults (thus affecting the household income and the country’s economy) [9]. Global, continental, and national resolutions have been in place to address child malnutrition; from the Convection on Rights of the Child (CRC), Sustainable Developmental Goals, and The Lesotho National Strategic Development Plan of 2020/2023. However, Lesotho is currently experiencing a triple burden of malnutrition, under and overnutrition across all age groups [10]. In 2014, Lesotho reported 33% of their children under the age of five were stunted and that proportion increased to 34.5% in 2018 [11]. Nonetheless, these numbers are an improvement because 44% in 2004 were stunted and 39% of the under-five population was stunted in 2009 and 15% were severely stunted [12, 11]. In Lesotho, among the various age groups, stunting was highest among children aged 24-35 months and the lowest among children under eight months [1]. An additional cluster of underlying causes leads to child malnutrition such as inadequate household food access [3]. This is because, the nurturing care that children receive in the household early in life provides the basis for development throughout childhood, adolescence and beyond [13]. Akombi et al., (2017) further indicated that children born to uneducated mothers tend to be at a higher risk of malnutrition than children born to educated mothers. On the other hand, community-level factors include geopolitical zones and access to health care facilities [7]. There are basic or structural causes of poor nutrition, such as societal structures and processes resulting in poverty, limiting or denying vulnerable population access to essential resources such as safe drinking water [41]. The study aimed to determine multilevel (immediate, underlying and basic) factors associated to stunting among children under five in Lesotho. Methodology Data Source and Study Design The analysis is based on the nationally representative study of the Multiple Indicator Cluster Survey (MICS-2018). The study was conducted by the Lesotho Ministry of Development Planning through the Department of the Bureau of Statistics in collaboration with the United Nations Children's Fund (UNICEF) as part of the Global MICS program. MICS covered several modules and indicators across households, children (0-17), women (15-49 and males (15-49) across all 10 districts of Lesotho and all ecological zones (highlands, lowlands, foothills and the Senqu Valley). The data was collected between April 2018 to September 2018. Lesotho MICS is a multistage stratified sampling survey. The sample was designed to meet the survey’s objectives by providing an estimate for a larger number of indicators at national/ area / sub-population level, for urban and rural areas together with four ecological zones: lowlands, foothills, mountains, and Senqu River Valley [11]. In stage one, urban, peri-urban areas within each district were identified as the main sampling strata (primary sampling units (PSUs); and in stage two, a sample of households was selected [11]. Within each stratum, a specific number of the Lesotho Census of Population and Housing of 2016 enumeration areas (EAs) were selected systematically with the probability proportional to size [11]. After the household listing was carried out within the selected EAs, a sample of 26 households was drawn in each sample EA (LMICS, 2018). However, in the data peri-urban strata were treated as rural to allow for comparability with previous surveys [11]. It was calculated that a minimum of 36 sample clusters were selected in each district [11]. There was an unequal allocation of the sample size within all ten districts- where some districts 42 clusters were collected in each district with a sample size of 10 400 households (400 clusters and 26 sample households per cluster) [11]. 10 413 households were sampled and only 8847 were interviewed (95.9% response rate). Among women aged 15-49, 7197 women were sampled and 6453 were interviewed (89.7% response rate), men (aged 15-49) 3417 were sampled but 2873 were interviewed with 84.1% response rate. Moreover, children under-five had a response rate of 91.2% and children aged 5-17 had a response rate of 94.0% [11]. For this study, the sample of children under-five is 3256. Data variables Dependent variables The dependent variables are determined by the anthropometric Z-scores assigned to children in surveys. The assignment of anthropometric Z-Scores is based on the WHO Child Growth Standards that are developed through interpolation functions that take into consideration the sex, age, height (in centimeters) and weight of the child (in kilograms) [14]. Children are considered stunted when their height-for-age falls below negative two standard deviations of the median of the reference population [11, 14]. Independent Variable This study follows the UNICEF framework for analyzing factors associated with child health and nutrition [11]. There are three levels predictors namely: immediate, underlying, and basic variables. Immediate variables are child sex, weight at birth and diarrhea as well as respiratory infection. At household level, underlying variables are households’ size, place of residence, female-headed households, household wealth, maternal age, maternal education as well as water sources and sanitation facilities. Moreover, at a community level, basic variables are community health seeking behavior, child immunization and antenatal care. Community food security, poverty, the proportion of mothers and males in the households with at least secondary, as well as communities with high proportions of female-headed households, and community media exposure, safe drinking water, and inadequate toilet facilities. The variables were constructed as follows, for child level factors, child sex is binary (male and female), child weight at birth is categorized into three categories (Low birth weight (Less than 2.5kg), average weight (between 2.6kg and 3.8kg) and above average weight (greater than 3.8kg). For diarrhea and respiratory infections two weeks before the survey was categorized into three categories (yes, no and I don’t know). Among household variables, household size is categorized into 2-5 and 5+ place of residence (rural and urban), maternal residential status (yes and no), and female-headed households is also binary (yes and no). Household wealth was categorized into poorest, second, middle, fourth and richest wealth quintiles, maternal age (15-24, 25-34, 35+), maternal education (primary/and or no education, secondary and highest education). Moreover, safe water sources (safe and unsafe water) and adequate toilet facilities (adequate and inadequate toilet facilities. In relation to basic community variables, all variables are categorized as low and high proportions, low proportions are clusters with proportions less than 40% and high proportions are clusters with proportions more than 40%. Data Analyses Data analysis is conducted in three steps, descriptive analyses, bivariate and multilevel logistic regression. Descriptive analysis of all the independent variables involves, frequencies, percentages, confidence intervals to determine statistical differences and p-values. Secondly, a chi-square analysis (bivariate analysis) is conducted to determine which variables are statistically significant to be included into the main model at 95% confidence internal (p-values <0.05). A multilevel logistic regression analysis is carried out because the data has evidence of clustering and hierarchy. In multi-level research, the structure of data in the population is hierarchical, and a sample for such a population can be viewed as a multistage sample [15]. With this explanation, the data analysis model best suits the MICS dataset because it was nested in two stages. The units at lower-level (level-1) are individual and clusters are again nested within units at the next higher level- which is level 2. This kind of clustering can introduce multi-level dependency or correlation among the observations that can have implication for model parameter estimates [15]. To measure the dependency in the data a three-stage multilevel analysis is conducted by running an empty model and calculating the intra-class correlation coefficient (ICC). The aim of the empty model is to find log-odds of the dependent variable while including no predictors [16]. Secondly, by running a model that will measure the effects of lower-level variables because these intermediate variables are allowed to vary from one cluster to another. Thirdly, running a model with level-2 predictors and level-3 predictors. Finally, by running the final model that includes individual, household, and community level variables. The statistical analyses are carried out in this study with the help of STATA15 software. Profile of the Study Population Table 1 shows all that majority of children in the sample did not receive minimal acceptable diet (MAD) the day before the survey (68.0%), aged 6-8 months (73.7%), and there was no significant difference between boys and girls (49% vs 50%). Moreover, majority of them were born with birth weight greater than 3.9kg (66.44%) and did not have diarrhea (91.4%) and respiratory infection (59.4% two weeks before the survey. At household level, majority of them were from households sized 5+ (61.0%), with residential mothers (85.3%), female headed households (59.8%), poorest households (22.7%), maternal education of no education and/or primary education (53.1%) as well as maternal age of 25-34 (47.1%). They were also from households with access to safe drinking water (82.3%) and adequate toilet facilities (70.0%). In relation to communities, majority of them were from communities with low proportions of health seeking behavior (68.9%), immunization (67.4%), males in households with at least secondary education (54.4%), female headed households (85.5%), poor households (61.0%) and from communities with low proportions of maternal media exposure (78.8%). Additionally, majority of them were from communities with high proportion of antenatal care (57.3%), food secure households (households that owned livestock and land) (70.0%), household with maternal education with at least secondary education (68.4%) and households with safe drinking water sources (81.5%) as well adequate toilet facilities (64.4%). Table 1: Characteristics of the study population: Lesotho 2018 (N= 3256) Immediate Variables N Percentage Dietary Intake No MAD 814 68.0 MAD 366 32.0 Child Age 6-8 2399 73.7 9-23 857 26.3 Child Sex Male 1595 49.0 Female 1661 51.0 Child Weight at Birth Less than 2.8kg 166 5.1 2.6kg to 3.8kg 928 28.5 ≥3.9kg 2163 66.4 Diarrhea Yes 281 8.6 No 2975 91.4 Respiratory Infection Yes 1324 40.6 No 1934 59.4 Underlying Variables Household Size 2-5 1271 39.0 5+ 1985 61.0 Place of Residence Urban 1328 40.8 Rural 1928 59.2 Maternal Residential Status Yes 2778 85.3 No 478 14.7 Female Headed Households Yes 1946 59.8 No 1311 40.2 Household Wealth Poorest 738 22.7 Second Wealth Quintile 702 21.6 Middle Wealth Quintile 662 20.3 Fourth Wealth Quintile 599 18.4 Richest 555 17.0 Maternal Age 15-24 833 33.2 25-34 1184 47.1 35+ 494 19.7 Maternal Education Primary or none 1381 53.1 Secondary 275 10.6 Beyond secondary 945 36.3 Sources of Drinking Water Unsafe 575 17.7 Safe 2681 82.3 Toilet Facilities Inadequate 978 30.0 Adequate 2278 70.0 Basic Variables Community Health Seeking Behavior Low 2244 68.9 High 1012 31.1 Community Immunization Low 2195 67.4 High 1061 32.6 Community Antenatal Care Low 128 12.7 High 876 87.3 Community Food Security Low 976 30.0 High 2280 70.0 Community Maternal Education Low 1030 31.6 High 2226 68.4 Community Male Education Low Proportion 1772 54.4 High Proportion 1484 45.6 Community Female-Headed Households Low 2783 85.5 High 473 14.5 Community Poverty Low 1985 61.0 High 1271 39.0 Community Media Exposure Low 2567 78.8 High 689 21.2 Community Safety of Sources of Drinking Water Low 603 18.5 High 2653 81.5 Community Adequacy of Toilet Facilities Low 1158 35.6 High 2098 64.4 Bivariate Analysis Table 2 presents all three level factors and their association (chi square p-value) with stunting at bivariate analysis. In Lesotho, a third (33.6%) of under5s were stunted. All variables with a p-value less than 0.05 from Chi-Square were considered significantly associated with stunting. Dietary intake, child weight at birth, and respiratory infections were immediate variables significantly associated with stunting. Underlying variables associated with stunting were place of residence, households’ wealth index, maternal education and residential status, water sources and toilet facilities. For basic community variables: community immunication rates community maternal and male education, community food security, community drinking water sources safety, community toilet facilities adequacy and community media exposure were significantly associated with stunting. All variables that were statistically significant in Table 2 were further tested using an Adjusted Wald Statistics where one variable (community immunization) was excluded in the main model. Table 2: Prevalence of Stunting among Children Under Five: Lesotho 2018 (N= 3256) Factors Not Stunted Stunted P-Value % N CI % N CI Immediate variables Dietary Intake No MAD 59.1 402 (54.8,63.4) 40.9 278 (36.6,45.2) 0.011 MAD 70.4 141 (62.6,77.2) 29.6 59 (22.8,37.4) Child Sex Male 64.5 1028 (61.1,67.7) 35.5 567 (32.3,38.9) 0.085 Female 68.2 1132 (65.6,70.7) 31.8 529 (29.3,34.5) Child Weight at Birth 3.8kg 66.8 1444 (4.2,6.2) 33.2 719 (26.5,30.6) Diarrhea Yes 66.5 187 (59.4,73.0) 33.5 94 (27.0,40.6) 0.963 No 66.3 1966 (64.1,68.5) 33.7 996 (31.5,35.9) Respiratory Infection Yes 62.8 831 (59.6,66.0) 37.2 492 (34.0,40.5) 0.002 No 68.7 1320 (66.3,71.1) 31.3 601 (28.9,33.7) Underlying variables Household Size 2-5 67.0 852 (63.3,70.5) 33.0 420 (29.5,36.7) 0.644 5+ 66.0 1309 (63.4,68.5) 34 676 (31.6,36.7) Place of Residence Urban 72.1 958 (68.6,75.4) 27.9 370 (24.6,31.4) 0.000 Rural 62.4 1201 (59.8,64.9) 37.6 726 (35.1,40.2) Household Heads Male 63.2 1314 (65.0,70.0) 36.8 632 (30.0 35.0) 0.156 Female 64.3 846 (61.2,67.9) 35.7 463 (32.1,38.8) Household Wealth Poorest 55.7 412 (52.2,59.2) 44.3 327 (40.8,47.8) 0.000 Second 62.3 438 (58.0,66.5) 37.7 265 (33.5,42.0) Middle 65.6 434 (60.5,70.3) 34.4 228 (29.7,39.5) Fourth 71.0 425 (65.1,76.2) 29.0 174 (23.8,34.9) Richest 81.5 452 (76.3,85.8) 18.5 103 (14.2,23.7) Maternal Age 15-24 64.0 534 (60.2,67.7) 36.0 300 (32.3,39.8) 0.266 25-34 68.3 808 (64.9,71.5) 31.7 375 (28.5,35.1) 35+ 66.8 330 (64.3,68.8) 33.2 164 (28.0,38.8) Mother’s Residential Status Yes 67.3 1868 (64.9,69.6) 32.7 909 (30.4,35.1) 0.008 No 61.1 293 (57.0,65.0) 38.9 186 (35.0 43.0) Maternal Education Primary or None 61.2 578 (55.7,64.5) 38.8 367 (35.5,42.3) 0.000 Secondary 67.1 926 (63.7,70.3) 32.9 454 (29.7,36.3) Beyond secondary 82.6 227 (75.0,88.3) 17.4 48 (11.7,25.1) Safety of drinking water Unsafe 60.4 347 (55.6,65.0) 39.6 228 (35.0,44.4) 0.007 Safe 67.6 1813 (65.3,70.0) 32.4 868 (30.1,34.7) Toilet Facilities adequacy Inadequate 59.3 580 (55.7,62.9) 40.7 398 (37.1,44.3) 0.000 Adequate 69.4 1580 (66.6,72.0) 30.6 698 (28.0,33.4) Basic variables Health Seeking Behavior (%) Low 65.9 1478 (63.3,68.3) 34.1 766 (31.7,36.7) 0.558 High 67.4 682 (63.0,71.5) 32.6 330 (28.5,37.0) Immunization (%) Low 66.0 1449 (63.2,68.6) 34.0 747 (31.4,36.8) 0.005 High 67.1 712 (63.6,70.4) 32.9 349 (29.6,36.4) Antenatal Care (%) Low 60.2 78 (47.8,72.1) 39.4 50 (27.9,52.2) 0.600 High 64.0 561 (60.4,67.4) 36.0 315 (32.6,39.6) Community Food Security (%) Low 67.6 1497 (68.5,76.4) 32.4 718 (23.6,31.5) 0.054 High 64.1 663 (61.2,66.1) 35.9 372 (33.9,38.8) Community Maternal Education (%) Low 60.3 621 (57.2,63.4) 39.7 408 (36.6,42.8) 0.000 High 69.1 1539 (66.3,71.8) 30.9 687 (28.2,33.7) Community Male Education (%) Low 61.8 1096 (59.0,64.5) 38.2 677 (35.5,41.0) 0.000 High 71.8 1065 (68.4,74.9) 28.2 419 (25.1,31.6) Female Headed Communities (%) Low 66.1 1840 (64.0,68.2) 33.3 943 (31.8,36.0) 0.642 High 67.7 320 (61.0,73.8) 32.3 153 (26.2,39.0) Community Poverty Low 71.5 1419 (68.4,74.3) 28.5 567 (25.7,31.6) 0.000 High 58.4 742 (55.1,61.5) 41.6 529 (38.5,44.9) Community Media Exposure Low 62.9 1615 (60.5,65.3) 37.1 952 (34.7,39.5) 0.000 High 79.1 546 (74.0,83.4) 20.9 144 (16.6,26.0) Community Sources of Drinking Water safety Low 60.8 367 (55.6,65.8) 39.2 236 (34.2,44.4) 0.014 High 67.6 1794 (65.3,69.8) 32.2 859 (30.2,34.7) Community Toilet Facilities adequacy Low 60.2 697 (56.9,63.4) 39.8 461 (36.6,43.2) 0.000 High 69.8 1464 (66.8,72.6) 30.2 634 (27.4,33.3) Multilevel Model The empty model (null model) was run to determine clustering, the second model included immediate and underlying variables (level 1 and level 2) and the third model included basic variables (level 3). In this study, there was evidence of variability in clustering. The null model had a Chi-Square of 19.91 and a p-value of 0.0000 making it statistically significant thus indicating clustering in the data. The Interclass correlation (ICC) of this model was right at the cut-off point at 0.054. Heck et al., 2014 discussed that 0.05 is often regarded as a conventional threshold to indicate more substantial evidence of clustering [17]. Moreover, the probability of being stunted in each community was (odd of being stunted/ (1+ odds of being stunted) 0.302. In general, the unconditional probability of a child being stunted is 30.2%. There was also variability of clustering between households and communities with a chi-square of 36.33 and p-value of 0.000 and ICC of 0.2574 (above the threshold). Factors associated with stunting Table 3 presents the main model of level one (immediate variables), level two (underlying variables) and level three (basic variables). At individual level, the odds are lower for children that did not receive MAD (WAOR=0.52; CI: 0.3, 0.9), born with greater than 3.8kg birth weight (WAOR=0.51; CI: 0.4, 0.6), and those that did not have respiratory infections two weeks before the survey (WAOR=0.61; CI: 0.4, 1.0) compared to their counterparts. At household level, the likelihood of stunting was lowest for education beyond secondary (WAOR=0.26; CI: 0.2, 0.4), fifth household wealth (WAOR=0.34; CI: 02, 03), safe sources of drinking water (WAOR=0.72; CI: 06, 09) and inadequate toilet facilities (WAOR=0.62; CI: 0.5, 0.7) compared to their counterparts. Higher odds were observed among Children from rural areas (WAOR=1.95; CI: 1.3, 2.1), mothers not residing within the household (WAOR=1.30; CI: 1.1, 1.6) compared to their counterparts. At community level, decreased odds were associated with children from communities with high community maternal education (WAOR=0.69; CI: 0.6, 0.8) and community male education (WAOR=0.56; CI: 0.5, 0.7) as well as those in communities with low safety of sources of drinking water (WAOR=0.73; CI: 0.3, 0.5), adequate toilet facilities (WAOR=0.66; CI: 0.5, 0.8) and high maternal media exposure (WAOR=0.37; CI: 0.3, 0.5) compared counterparts. Children from communities with high community poverty were two times (WAOR=2.04; CI: 1.7, 2.5) more likely to be stunted. Table 3: Immediate, underlying and community factors associated with stunting: Lesotho 2018 Immediate Variables UAOR (95% CI) WAOR (95% CI) WA (P-value) Dietary Intake MAD intake No MAD (RC) 1.00 1.00 1.00 MAD 0.45 (0.2, 0.9) 0.52 (0.3,0.9) 0.027 Child Weight at Birth < 2.6kg (RC) 1.00 1.00 1.00 2.6kg - 3.8kg 0.34 (0.1,0.9) 0.76 (0.6,0.9) 0.000 ≥3.9kg 0.35 (0.1,0.9) 0.51 (0.4,0.6) 0.000 Respiratory Infection Yes (RC) 1.00 1.00 1.00 No 0.86 (0.5,1.5) 0.61 (0.4,1.0) 0.004 Underlying Variables Place of Residence Urban (RC) 1.00 1.00 1.00 Rural 0.75 (0.4,1.3) 1.95 (1.3,2.1) 0.000 Household Wealth Poorest (RC) 1.00 1.00 1.00 Second 0.85 (0.5,1.5) 0.73 (0.6,0.9) 0.013 Middle 0.71 (0.4,1.4) 0.55 (0.4,0.7) 0.000 Fourth 0.36 (0.1,1.0) 0.38 (0.3,0.5) 0.000 Richest 0.22 (0.6,0.8) 0.24 (0.2,0.3) 0.000 Maternal Residential Status Yes (RC) 1.00 1.00 1.00 No 0.86 (0.5,1.5) 1.30 (1.1,1.6) 0.034 Maternal Educational Attainment Primary or None (RC) 1.00 1.00 1.00 Secondary 0.94 (0.6,1.5) 0.73 (0.6,0.9) 0.003 Beyond secondary 2.11 (0.7,6.1) 0.26 (0.2,0.4) 0.000 Safety of Drinking Water Unsafe (RC) 1.00 1.00 1.00 Safe 0.95 (0.6,1.6) 0.72 (0.6,0.9) 0.013 Adequacy of Toilet Facilities Inadequate (RC) 1.00 1.00 1.00 Adequate 0.97 (0.6,1.6) 0.62 (0.5,0.7) 0.000 Basic Variables Community Female Education Low (RC) 1.00 1.00 1.00 High 0.91 (0.7,0.1) 0.69 (0.6,0.8) 0.000 Community Male Education Low (RC) 1.00 1.00 1.00 High 0.95 (0.7,1.3) 0.56 (0.5,0.7) 0.000 Community Poverty Low (RC) 1.00 1.00 1.00 High 1.54 (1.2,2.0) 2.04 (1.7,2.5) 0.000 Community Safety of Drinking Water Low (RC) 1.00 1.00 1.00 High 0.86 (0.7,1.1) 0.73 (0.6,0.9) 0.017 Community Toilet Facilities Low 1.00 1.00 1.00 High 0.94 (0.7,1.2) 0.66 (0.5,0.8) 0.000 Female Community Media Exposure Low (RC) 1.00 1.00 1.00 High 0.51 (0.4,0.7) 0.37 (0.3,0.5) 0.000 Notes: MAD denoted Minimum Acceptable Diet, UAOR Unadjusted OR, WAOR, Wald Adjusted OR and WA Wald Adjusted Discussion The prevalence of stunting in Lesotho was 33.6% 95% CI (0.3365 0.316) in 2018. This was very close to that of West Africa (33.9%) [ 18 ]. However, it was lower than that of Burundi (54.6%), Nigeria (47.6%), Nepal (47%), India (43%), Kenya (39%), Rwanda (38%), Central Africa (37.8%), Mozambique (37%) and Democratic Republic of Congo (35.2%) [ 18 , 19 , 20 , 21 ]. In this study at individual level, children who had MAD the day before the survey, those with low birth weight (LBW) and respiratory infections were more likely to be stunted than their counterparts. This was observed in South Ethiopia, Rwanda, Ecuador, Mexico, Mozambique, and Malawi children that did not receive MAD were more likely to be stunted compared to their counterparts [ 22 , 23 , 24 , 25 , 26 ] Moreover, Cruz et al., (2017) indicated that children born with LBW are born with low reserves of vital growth nutrients such as vitamin A, zinc, and iron [ 22 ]. They are also prone to contact diseases and infections such as diarrhea, anemia, and respiratory infections, thereby increasing their likelihood of becoming stunted [ 27 , 28 ]. At household level, children in rural areas, poor households, households with non-resident mothers, maternal education with primary or no education, unsafe sources of drinking water and inadequate toilet facilities were more likely to be stunted. Poverty in Lesotho is deeply entrenched in rural areas, where 70% of the population resides [ 29 ]. More than half of the population in Lesotho's rural areas is poor [ 29 ]. Amegbor et al., (2020) indicated that there is an association between different indicators of childhood malnutrition and region of residence to regional socio-economic differences [ 30 ]. In Low- and Middle-Income countries, such as Uganda, Indonesia, Kenya, and Niger, children in rural areas were more likely to be stunted compared to those in urban areas [ 30 , 31 ]. Economic, social environments and their inequality are important reasons for child malnutrition (Ghosh et al., 2020). This was also observed in Bangladesh, Ecuador, Cambodia, India, Ethiopia, Nigeria, Nepal, Parahmantan, Haiti, Burkina Faso, Malawi, Iran, Zimbabwe, Mozambique and Peru [ 32 , 33 , 30 , 27 , 34 , 35 , 36 ]. In relation to maternal residential status, this was also reported in China, Bangladesh, and Guatemala [ 37 , 38 , 39 ]. Migration is often considered an important way of improving livelihood conditions for the households and individuals [ 39 ]. Migration is often considered an important way of improving livelihood conditions for the households and individuals [ 39 ]. Historically, migration has been a male phenomenon in most countries, particularly in Lesotho [ 40 ]. However, in recent years there has been an increase in female migration noted in several contexts in Africa, many of whom are mothers [ 40 ]. In most cases, children of these migrants are often left behind with extended family such as grandparents, uncles, and aunts; because of unstable income, and unfriendly housing in host areas [ 39 ]. In this study, sources of drinking water and toilet facilities were determinants of stunting at household and community level. Water, Sanitation and Hygiene variables are intertwined. At household level, the same was reported in 172 countries, Pakistan, and Ethiopia, were children from households with access to unsafe drinking water were more likely to be stunted [ 55 , 56 , 57 ]. The lack of access to safe drinking water sources affects children’s health and well-being through repeated diarrheal infections [ 57 ]. In Lesotho, the majority of communities do not have access to safe drinking water. Despite exporting water to South Africa (contributing to 8% -10% of the country's gross domestic product), about 63% rural domestic communities do not have access to safe drinking water, thus forcing them to use unprotected sources of drinking water with the majority of them having to travel more than 30 minutes to collect the unsafe water [ 58 , 59 ]. Nearly 85% of the rural population use traditional drinking water sources such as open reservoirs, springs, and open wells [ 58 ]. These water sources are normally contaminated with E-Coli that causes stomach and intestinal illnesses including diarrhea and nausea even leading to death and stunting [ 58 , 56 ]. Water can be contaminated through environmental enteric dysfunction (EED) and soil-transmitted helminths [ 58 ]. Intestinal worms (soil-transmitted helminths) can predispose children to stunting through direct contact or through dust [ 58 ]. Pollution of the water sites can also be due to sanitation facilities such as pit latrines and open defecation along the boundaries of the water source as these may contaminate the water with faecal pathogens [ 42 ]. At community level, children from communities with high proportions of adequate toilet facilities were less likely to being stunted than children in communities with low proportions of adequate toilet facilities. In Mozambique, Burkina Faso, Indonesia, Mali, Rwanda, Bangladesh, Brazil, Cambodia, Tanzania, and Ethiopia studies, India's poor household hygienic practices such as access to safe water, handwashing using soup and other sanitation practices increased the risk of stunting [ 42 , 43 , 44 , 45 , 46 , 47 ]A large proportion of Lesotho’s population remains without access to proper water and sanitation services [ 48 ]. ILO (2020) highlighted that, in Lesotho, most people are also subjected to poor drainage facilities and agreements for solid waste disposal with around 30% of the population openly defecating [ 49 ]. Sanitation issues are more complicated than any other underlying and basic variables because one or more inadequate toilet facility in the community can contaminate the water of a larger group of people. Inadequate sanitation facilities contribute to increasing contamination of food and drinking water and children living in a household without a proper toilet are more likely to be stunted [ 43 , 44 , 45 ]. At community level, children from communities with high proportions of poor households, low proportions of males in the household with males and mothers with at least secondary education, safe sources of drinking water, adequate toilet facilities as well as maternal media exposure were more likely to be stunted. It is well documented that educated mothers have greater knowledge of appropriate care practices that improve the nutritional status of their children [ 50 , 51 , 52 ]. Therefore, children in communities with a high proportion of educated women are more likely to be healthier than those in low-proportion communities. Neighbourhoods constitute the key determinants of socioeconomic disparities in health, as they shape individual opportunities and exposes residents to multiple risks and resources [ 53 ]. In neighbourhoods with high proportions of educated women, social interactions are key to the dissemination of information in bettering the lives of children in that neighbourhood [ 54 ]. Moreover, educated households reproduce neighbourhood characteristics by choosing neighbourhoods with people with similar educational levels and affluence [ 54 ]. On the other hand, exposure to mass media is an important as a source of knowledge [ 60 ]. There is a gap in the literature on how community maternal media exposure impacts child malnutrition. However, what is known is, mass media provides information that is essential to amplifying people’s knowledge and awareness regarding issues of day-to-day life [ 60 ]. Mass media also has a greater role in building health and nutrition-related behaviours, attitudes as well as promoting socio-cultural and economic development that might contribute to improving the nutritional outcomes of children [ 61 , 62 ]. In Indonesia, mass media also strengthened the role of frontline workers as well as reinforcing their status as experts and depicting them as educated, trusted, and reliable people [ 62 ]. It also promoted health seeking behavior and appropriate childcare practices [ 63 ]. This was also found in Sub-Saharan Africa, Bangladesh, China, Pakistan, Indonesia, and Tanzania [ 64 , 60 , 61 , 65 ]. Conclusion This study aimed to find determinants of stunting in Lesotho at three levels- individual, household, and community level. At individual level, determinants of stunting were child dietary intake and child health. At household level, the household’s care resources and the environment they reside in were determinants of stunting. The same applies at community level, variables that were determinants of stunting are thematically variables that are proxies for knowledge, information acquisition, and sharing about infant care as well as the environment they reside in. Therefore, strategies and programs to improve child nutritional status should be done in communities. Limitations The study shares a common limitation of cross-sectional study-the study supports the association between child diet, stunting, and independent variables, but not proving the causal relationship. Moreover, this study had limitations in that, the majority of the data is self-reported by mothers/caregivers, making it subject to recall bias and it can be subject to social-desirability bias. On the other hand, the study used clustering by aggregating individual and household variables, these may in misclassification or overestimation. Moreover, communities were created using clusters derived from Enumeration areas which might also be subject to coverage error. Declarations Acknowledgements The study is part of the author’s thesis for a doctoral dissertation with the School of Built Environment and Development Studies at the University of Kwa-Zulu Natal, Durban, South Africa. We are grateful to the UNICEF, MICS team for providing the 2018 MICS dataset for the analysis. Funding No grant was received for the study from any agency, university or public. Availability of data and materials The study used the LMICS 2018 dataset which is publicly available on the MICS data official website https://mics.unicef.org/surveys with all respondents identifier information removed. Authors’ contributions The study was designed by NL and KV. TT and ML were involved in the revision of the paper as well as the editing of the final manuscript. Competing interests The author declares that they have no competing interests. Ethics approval and consent to participate The author communicated with the UNICEF MICS team in 3 UN Plaza, New York, USA and was granted permission to download and use the LMICS dataset. Authors details 1 Department of Statistics and Demography, Faculty of Social Sciences. National University of Lesotho. Maseru. 2 Population Studies, School of Built Environment and Development Studies, University of KwaZulu-Natal, Durban, South Africa. 3 Department of Statistics and Demography, Faculty of Social Sciences. National University of Lesotho. Maseru. 4 Department of Statistics and Demography, Faculty of Social Sciences. National University of Lesotho. Maseru. References Lesotho Demographic and Health Survey Report., (2014) Ministry of Health Lesotho. UNICEF. 2022. NUTRITION, FOR EVERY CHILD UNICEF Nutrition Strategy 2020–2030. [online] Available at: https://www.unicef.org/media/91741/file/UNICEF-Nutrition-Strategy-2020-2030-Brief.pdf [Accessed 27 April 2022]. UNICEF. 2018. CHILD MALNUTRITION: Unfolding the Situation in Egypt. [online] Available at: https://www.unicef.org/egypt/media/2686/file [Accessed 27 May 2021]. Anjorin, S., Uthman, O., Ameyaw, E., Ahinkorah, B., Chattu, V., Bishwajit, G., Seidu, A., Darteh, E. And Yaya, S., 2020. Undernutrition, polygynous context and family structure: a multilevel analysis of cross-sectional surveys of 350 000 mother–child pairs from 32 countries. BMJ Global Health, 5(10), p.e002637. WHO. 2020. Fact sheets - Malnutrition. 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Cite Share Download PDF Status: Published Journal Publication published 24 May, 2025 Read the published version in Journal of Health, Population and Nutrition → Version 1 posted Editorial decision: Revision requested 06 Feb, 2025 Reviews received at journal 04 Feb, 2025 Reviews received at journal 04 Dec, 2024 Reviewers agreed at journal 25 Nov, 2024 Reviewers agreed at journal 24 Nov, 2024 Reviewers agreed at journal 16 Aug, 2024 Reviewers invited by journal 13 Aug, 2024 Editor assigned by journal 10 Jul, 2024 Submission checks completed at journal 09 Jul, 2024 First submitted to journal 08 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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However, this is not the case for most children in the world. The impact of child malnutrition is more pronounced in low and middle-income countries, particularly in South Asia and Sub-Saharan Africa (SSA) [2,3,4,5]. This is because nine out of ten African children do not meet the criteria for a minimum acceptable diet outlined by the WHO; and two out of five do not eat meals regularly [6]. Health and physical consequences of prolonged states of malnourished among children are: developmental delays, lower intellectual quotient, delayed cognitive development, greater behavioural problems, and deficient social skills; susceptibility to contracting diseases [7, 8]. Moreover, long-term consequences of child malnutrition may be inclusive of increased chances of non-communicable diseases (hypertension, diabetes, and heart conditions), and poor maternal reproductive health outcomes later in life (perpetuating the cycle of malnutrition) and decreased work capacity and productivity as adults (thus affecting the household income and the country\u0026rsquo;s economy) [9].\u003c/p\u003e\n\u003cp\u003eGlobal, continental, and national resolutions have been in place to address child malnutrition; from the Convection on Rights of the Child (CRC), Sustainable Developmental Goals, and The Lesotho National Strategic Development Plan of 2020/2023. However, Lesotho is currently experiencing a triple burden of malnutrition, under and overnutrition across all age groups [10]. In 2014, Lesotho reported 33% of their children under the age of five were stunted and that proportion increased to 34.5% in 2018 [11]. Nonetheless, these numbers are an improvement because 44% in 2004 were stunted and 39% of the under-five population was stunted in 2009 and 15% were severely stunted [12, 11]. In Lesotho, among the various age groups, stunting was highest among children aged 24-35 months and the lowest among children under eight months [1].\u003c/p\u003e\n\u003cp\u003eAn additional cluster of underlying causes leads to child malnutrition such as inadequate household food access [3]. This is because, the nurturing care that children receive in the household early in life provides the basis for development throughout childhood, adolescence and beyond [13]. Akombi et al., (2017) further indicated that children born to uneducated mothers tend to be at a higher risk of malnutrition than children born to educated mothers. On the other hand, community-level factors include geopolitical zones and access to health care facilities [7]. There are basic or structural causes of poor nutrition, such as societal structures and processes resulting in poverty, limiting or denying vulnerable population access to essential resources such as safe drinking water [41]. The study aimed to determine multilevel (immediate, underlying and basic) factors associated to stunting among children under five in Lesotho.\u003c/p\u003e"},{"header":"Methodology","content":"\u003ch2\u003eData Source and Study Design\u003c/h2\u003e\n\u003cp\u003eThe analysis is based on the nationally representative study of the Multiple Indicator Cluster Survey (MICS-2018). The study was conducted by the Lesotho Ministry of Development Planning through the Department of the Bureau of Statistics in collaboration with the United Nations Children\u0026apos;s Fund (UNICEF) as part of the Global MICS program. MICS covered several modules and indicators across households, children (0-17), women (15-49 and males (15-49) across all 10 districts of Lesotho and all ecological zones (highlands, lowlands, foothills and the Senqu Valley). The data was collected between April 2018 to September 2018.\u003c/p\u003e\n\u003cp\u003eLesotho MICS is a multistage stratified sampling survey. The sample was designed to meet the survey\u0026rsquo;s objectives by providing an estimate for a larger number of indicators at national/ area / sub-population level, for urban and rural areas together with four ecological zones: lowlands, foothills, mountains, and Senqu River Valley [11]. In stage one, urban, peri-urban areas within each district were identified as the main sampling strata (primary sampling units (PSUs); and in stage two, a sample of households was selected [11]. Within each stratum, a specific number of the Lesotho Census of Population and Housing of 2016 enumeration areas (EAs) were selected systematically with the probability proportional to size [11]. After the household listing was carried out within the selected EAs, a sample of 26 households was drawn in each sample EA (LMICS, 2018). However, in the data peri-urban strata were treated as rural to allow for comparability with previous surveys [11]. It was calculated that a minimum of 36 sample clusters were selected in each district [11]. There was an unequal allocation of the sample size within all ten districts- where some districts 42 clusters were collected in each district with a sample size of 10 400 households (400 clusters and 26 sample households per cluster) [11]. 10 413 households were sampled and only 8847 were interviewed (95.9% response rate). Among women aged 15-49, 7197 women were sampled and 6453 were interviewed (89.7% response rate), men (aged 15-49) 3417 were sampled but 2873 were interviewed with 84.1% response rate. Moreover, children under-five had a response rate of 91.2% and children aged 5-17 had a response rate of 94.0% [11]. For this study, the sample of children under-five is 3256.\u003c/p\u003e\n\u003ch2\u003eData variables\u003c/h2\u003e\n\u003ch3\u003eDependent variables\u003c/h3\u003e\n\u003cp\u003eThe dependent variables are determined by the anthropometric Z-scores assigned to children in surveys. The assignment of anthropometric Z-Scores is based on the WHO Child Growth Standards that are developed through interpolation functions that take into consideration the sex, age, height (in centimeters) and weight of the child (in kilograms) [14]. Children are considered stunted when their height-for-age falls below negative two standard deviations of the median of the reference population [11, 14].\u003c/p\u003e\n\u003ch3\u003eIndependent Variable\u003c/h3\u003e\n\u003cp\u003eThis study follows the UNICEF framework for analyzing factors associated with child health and nutrition [11]. There are three levels predictors namely: immediate, underlying, and basic variables. Immediate variables are child sex, weight at birth and diarrhea as well as respiratory infection. At household level, underlying variables are households\u0026rsquo; size, place of residence, female-headed households, household wealth, maternal age, maternal education as well as water sources and sanitation facilities. Moreover, at a community level, basic variables are community health seeking behavior, child immunization and antenatal care. Community food security, poverty, the proportion of mothers and males in the households with at least secondary, as well as communities with high proportions of female-headed households, and community media exposure, safe drinking water, and inadequate toilet facilities.\u003c/p\u003e\n\u003cp\u003eThe variables were constructed as follows, for child level factors, child sex is binary (male and female), child weight at birth is categorized into three categories (Low birth weight (Less than 2.5kg), average weight (between 2.6kg and 3.8kg) and above average weight (greater than 3.8kg). For diarrhea and respiratory infections two weeks before the survey was categorized into three categories (yes, no and I don\u0026rsquo;t know). Among household variables, household size is categorized into 2-5 and 5+ place of residence (rural and urban), maternal residential status (yes and no), and female-headed households is also binary (yes and no). Household wealth was categorized into poorest, second, middle, fourth and richest wealth quintiles, maternal age (15-24, 25-34, 35+), maternal education (primary/and or no education, secondary and highest education). Moreover, safe water sources (safe and unsafe water) and adequate toilet facilities (adequate and inadequate toilet facilities. In relation to basic community variables, all variables are categorized as low and high proportions, low proportions are clusters with proportions less than 40% and high proportions are clusters with proportions more than 40%. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eData Analyses\u003c/h4\u003e\n\u003cp\u003eData analysis is conducted in three steps, descriptive analyses, bivariate and multilevel logistic regression. Descriptive analysis of all the independent variables involves, frequencies, percentages, confidence intervals to determine statistical differences and p-values. Secondly, a chi-square analysis (bivariate analysis) is conducted to determine which variables are statistically significant to be included into the main model at 95% confidence internal (p-values \u0026lt;0.05). A multilevel logistic regression analysis is carried out because the data has evidence of clustering and hierarchy. In multi-level research, the structure of data in the population is hierarchical, and a sample for such a population can be viewed as a multistage sample [15]. With this explanation, the data analysis model best suits the MICS dataset because it was nested in two stages. The units at lower-level (level-1) are individual and clusters are again nested within units at the next higher level- which is level 2. \u0026nbsp;This kind of clustering can introduce multi-level dependency or correlation among the observations that can have implication for model parameter estimates [15].\u003c/p\u003e\n\u003cp\u003eTo measure the dependency in the data a three-stage multilevel analysis is conducted by running an empty model and calculating the intra-class correlation coefficient (ICC). The aim of the empty model is to find log-odds of the dependent variable while including no predictors [16]. Secondly, by running a model that will measure the effects of lower-level variables because these intermediate variables are allowed to vary from one cluster to another. Thirdly, running a model with level-2 predictors and level-3 predictors. Finally, by running the final model that includes individual, household, and community level variables. The statistical analyses are carried out in this study with the help of STATA15 software.\u003c/p\u003e\n\u003ch2\u003eProfile of the Study Population\u003c/h2\u003e\n\u003cp\u003eTable 1 shows all that majority of children in the sample did not receive minimal acceptable diet (MAD) the day before the survey (68.0%), aged 6-8 months (73.7%), and there was no significant difference between boys and girls (49% vs 50%). Moreover, majority of them were born with birth weight greater than 3.9kg (66.44%) and did not have diarrhea (91.4%) and respiratory infection (59.4% two weeks before the survey. At household level, majority of them were from households sized 5+ (61.0%), with residential mothers (85.3%), female headed households (59.8%), poorest households (22.7%), maternal education of no education and/or primary education (53.1%) as well as maternal age of 25-34 (47.1%). They were also from households with access to safe drinking water (82.3%) and adequate toilet facilities (70.0%). In relation to communities, majority of them were from communities with low proportions of health seeking behavior (68.9%), immunization (67.4%), males in households with at least secondary education (54.4%), female headed households (85.5%), poor households (61.0%) and from communities with low proportions of maternal media exposure (78.8%). Additionally, majority of them were from communities with high proportion of antenatal care (57.3%), food secure households (households that owned livestock and land) (70.0%), household with maternal education with at least secondary education (68.4%) and households with safe drinking water sources (81.5%) as well adequate toilet facilities (64.4%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Characteristics of the study population: Lesotho 2018 (N= 3256)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"498\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmediate Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDietary Intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eNo MAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e68.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eMAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e32.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild Age\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e6-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e73.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e9-23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e26.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild Sex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e51.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild Weight at Birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLess than 2.8kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e5.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e2.6kg to 3.8kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e28.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;3.9kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e66.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiarrhea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e91.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory Infection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e40.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnderlying Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e2-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e5+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e61.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of Residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e40.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e59.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal Residential Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e85.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale Headed Households\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1946\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e59.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e40.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Wealth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e22.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eSecond Wealth Quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eMiddle Wealth Quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e20.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eFourth Wealth Quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e17.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal Age\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e47.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e35+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary or none\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e53.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eBeyond secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e36.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSources of Drinking Water\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eUnsafe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eSafe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e82.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eToilet Facilities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eInadequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eAdequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e70.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBasic Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Health Seeking Behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e68.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e31.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Immunization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e67.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e32.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Antenatal Care\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e87.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Food Security\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e70.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Maternal Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e68.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Male Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow Proportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e54.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh Proportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e45.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Female-Headed Households\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e85.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Poverty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e61.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Media Exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e78.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Safety of Sources of Drinking Water\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e81.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Adequacy of Toilet Facilities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e1158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e35.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"72.28915662650603%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\" valign=\"top\"\u003e\n \u003cp\u003e2098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.072289156626507%\" valign=\"top\"\u003e\n \u003cp\u003e64.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eBivariate Analysis\u003c/h3\u003e\n\u003cp\u003eTable 2 presents all three level factors and their association (chi square p-value) with stunting at bivariate analysis. In Lesotho, a third (33.6%) of under5s were stunted. All variables with a p-value less than 0.05 from Chi-Square were considered significantly associated with stunting. Dietary intake, child weight at birth, and respiratory infections were immediate variables significantly associated with stunting. Underlying variables associated with stunting were place of residence, households\u0026rsquo; wealth index, maternal education and residential status, water sources and toilet facilities. For basic community variables: community immunication rates community maternal and male education, community food security, community drinking water sources safety, community toilet facilities adequacy and community media exposure were significantly associated with stunting. All variables that were statistically significant in Table 2 were further tested using an Adjusted Wald Statistics where one variable (community immunization) was excluded in the main model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePrevalence of Stunting among Children Under Five: Lesotho 2018\u0026nbsp;(N= 3256)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" rowspan=\"2\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNot Stunted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStunted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.516129032258064%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.193548387096776%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.903225806451612%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.290322580645162%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.193548387096776%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmediate variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eDietary Intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\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 width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eNo MAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e59.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(54.8,63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e40.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(36.6,45.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eMAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e70.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(62.6,77.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e29.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(22.8,37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eChild Sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e64.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(61.1,67.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e35.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(32.3,38.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e68.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(65.6,70.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e31.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(29.3,34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eChild Weight at Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 2.5kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(2.8, 4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e52.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(27.1,32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e2.6 kg - 3.8kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e68.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(6.1 10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e31.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(23.6,29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 3.8kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e66.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(4.2,6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(26.5,30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eDiarrhea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e66.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(59.4,73.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e33.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e94 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(27.0,40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e66.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(64.1,68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e33.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e996 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(31.5,35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory Infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e62.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(59.6,66.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e37.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e492 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(34.0,40.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e68.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(66.3,71.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e31.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e601 \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(28.9,33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnderlying variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eHousehold Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003e2-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e67.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(63.3,70.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(29.5,36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e5+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e66.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(63.4,68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(31.6,36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003ePlace of Residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e72.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(68.6,75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e27.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(24.6,31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e62.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(59.8,64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e37.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(35.1,40.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eHousehold Heads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e63.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(65.0,70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(30.0 \u0026nbsp;35.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e64.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(61.2,67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(32.1,38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eHousehold Wealth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e55.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(52.2,59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e44.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(40.8,47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"5\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSecond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e62.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(58.0,66.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e37.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(33.5,42.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e65.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(60.5,70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e34.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(29.7,39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eFourth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e71.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e425\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(65.1,76.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e29.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(23.8,34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e81.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e452\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(76.3,85.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(14.2,23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eMaternal Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003e15-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e64.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(60.2,67.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(32.3,39.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e68.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(64.9,71.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e31.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(28.5,35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e35+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e66.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(64.3,68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(28.0,38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMother\u0026rsquo;s Residential Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e67.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(64.9,69.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e32.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(30.4,35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e61.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(57.0,65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e38.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(35.0 \u0026nbsp;43.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eMaternal Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary or None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e61.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(55.7,64.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e38.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(35.5,42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e67.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(63.7,70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(29.7,36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eBeyond secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e82.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(75.0,88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e17.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(11.7,25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"60%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSafety of drinking water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eUnsafe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(55.6,65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e39.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(35.0,44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSafe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e67.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(65.3,70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(30.1,34.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eToilet Facilities adequacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eInadequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e59.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(55.7,62.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e40.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(37.1,44.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eAdequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e69.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(66.6,72.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e30.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(28.0,33.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBasic variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHealth Seeking Behavior (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e65.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(63.3,68.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e34.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(31.7,36.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e67.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(63.0,71.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e32.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(28.5,37.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eImmunization (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e66.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(63.2,68.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e34.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(31.4,36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e67.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(63.6,70.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(29.6,36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAntenatal Care (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e60.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(47.8,72.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e39.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(27.9,52.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e64.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(60.4,67.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(32.6,39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eCommunity Food Security (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e67.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(68.5,76.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(23.6,31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e64.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(61.2,66.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e35.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(33.9,38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCommunity Maternal Education (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e60.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(57.2,63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e39.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(36.6,42.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e69.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(66.3,71.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e30.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(28.2,33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCommunity Male Education (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e61.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(59.0,64.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e38.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(35.5,41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e71.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(68.4,74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(25.1,31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eFemale Headed Communities (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e66.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(64.0,68.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(31.8,36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.642\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e67.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(61.0,73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e32.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(26.2,39.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eCommunity Poverty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e71.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(68.4,74.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e28.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(25.7,31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e58.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(55.1,61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e41.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(38.5,44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eCommunity Media Exposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e62.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e1615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(60.5,65.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e37.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(34.7,39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e79.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(74.0,83.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e20.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(16.6,26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"60%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eCommunity Sources of Drinking Water safety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e60.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e367\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(55.6,65.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e39.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(34.2,44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e67.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(65.3,69.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(30.2,34.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCommunity Toilet Facilities adequacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28%\" valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e60.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(56.9,63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8%\" valign=\"top\"\u003e\n \u003cp\u003e39.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7%\" valign=\"top\"\u003e\n \u003cp\u003e461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15%\" valign=\"top\"\u003e\n \u003cp\u003e(36.6,43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e69.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e1464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(66.8,72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.88888888888889%\" valign=\"top\"\u003e\n \u003cp\u003e30.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.777777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e(27.4,33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eMultilevel Model\u003c/h2\u003e\n\u003cp\u003eThe empty model (null model) was run to determine clustering, the second model included immediate and underlying variables (level 1 and level 2) and the third model included basic variables (level 3). In this study, there was evidence of variability in clustering. The null model had a Chi-Square of 19.91 and a p-value of 0.0000 making it statistically significant thus indicating clustering in the data. The Interclass correlation (ICC) of this model was right at the cut-off point at 0.054. Heck et al., 2014 discussed that 0.05 is often regarded as a conventional threshold to indicate more substantial evidence of clustering [17]. Moreover, the probability of being stunted in each community was (odd of being stunted/ (1+ odds of being stunted) 0.302. In general, the unconditional probability of a child being stunted is 30.2%. There was also variability of clustering between households and communities with a chi-square of 36.33 and p-value of 0.000 and ICC of 0.2574 (above the threshold).\u003c/p\u003e\n\u003ch2\u003eFactors associated with stunting\u003c/h2\u003e\n\u003cp\u003eTable 3 presents the main model of level one (immediate variables), level two (underlying variables) and level three (basic variables). \u0026nbsp; At individual level, the odds are lower for children that did not receive MAD (WAOR=0.52; CI: 0.3, 0.9), born with greater than 3.8kg birth weight (WAOR=0.51; CI: 0.4, 0.6), and those that did not have respiratory infections two weeks before the survey (WAOR=0.61; CI: 0.4, 1.0) compared to their counterparts. At household level, the likelihood of stunting was lowest for education beyond secondary (WAOR=0.26; CI: 0.2, 0.4), fifth household wealth (WAOR=0.34; CI: 02, 03), safe sources of drinking water (WAOR=0.72; CI: 06, 09) and inadequate toilet facilities (WAOR=0.62; CI: 0.5, 0.7) compared to their counterparts. Higher odds were observed among Children from rural areas (WAOR=1.95; CI: 1.3, 2.1), mothers not residing within the household (WAOR=1.30; CI: 1.1, 1.6) compared to their counterparts. At community level, decreased odds were associated with children from communities with high community maternal education (WAOR=0.69; CI: 0.6, 0.8) and community male education (WAOR=0.56; CI: 0.5, 0.7) as well as those in communities with low safety of sources of drinking water (WAOR=0.73; CI: 0.3, 0.5), adequate toilet facilities (WAOR=0.66; CI: 0.5, 0.8) and high maternal media exposure (WAOR=0.37; CI: 0.3, 0.5) compared counterparts. Children from communities with high community poverty were two times (WAOR=2.04; CI: 1.7, 2.5) more likely to be stunted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Immediate, underlying and community factors associated with stunting: Lesotho 2018\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmediate Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUAOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWAOR (95% CI)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWA (P-value)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDietary Intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMAD intake\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo MAD (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMAD\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.45 (0.2, 0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.52 (0.3,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild Weight at Birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 2.6kg (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.6kg - 3.8kg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.34 (0.1,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.76 (0.6,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;3.9kg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.35 (0.1,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.51 (0.4,0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory Infection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 (0.5,1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.61 (0.4,1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnderlying Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of Residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRural\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.75 (0.4,1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.95 (1.3,2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold Wealth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoorest (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.85 (0.5,1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (0.6,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiddle\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.71 (0.4,1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.55 (0.4,0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFourth\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.36 (0.1,1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.38 (0.3,0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRichest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.22 (0.6,0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.24 (0.2,0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal Residential Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 (0.5,1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.30 (1.1,1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal Educational Attainment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary or None (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.6,1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (0.6,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeyond secondary\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e2.11 (0.7,6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.26 (0.2,0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSafety of Drinking Water\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnsafe (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSafe\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.95 (0.6,1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.72 (0.6,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdequacy of Toilet Facilities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInadequate (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdequate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.97 (0.6,1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.62 (0.5,0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBasic Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Female Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.91 (0.7,0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.69 (0.6,0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Male Education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.95 (0.7,1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.56 (0.5,0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Poverty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.54 (1.2,2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e2.04 (1.7,2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Safety of Drinking Water\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.86 (0.7,1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (0.6,0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity Toilet Facilities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.7,1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.66 (0.5,0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale Community Media Exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow (RC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.64356435643565%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.782178217821784%\" valign=\"top\"\u003e\n \u003cp\u003e0.51 (0.4,0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.762376237623762%\" valign=\"top\"\u003e\n \u003cp\u003e0.37 (0.3,0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\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\u003cp\u003eNotes: MAD denoted Minimum Acceptable Diet, UAOR Unadjusted OR, WAOR, Wald Adjusted OR and WA Wald Adjusted\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe prevalence of stunting in Lesotho was 33.6% 95% CI (0.3365 0.316) in 2018. This was very close to that of West Africa (33.9%) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, it was lower than that of Burundi (54.6%), Nigeria (47.6%), Nepal (47%), India (43%), Kenya (39%), Rwanda (38%), Central Africa (37.8%), Mozambique (37%) and Democratic Republic of Congo (35.2%) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study at individual level, children who had MAD the day before the survey, those with low birth weight (LBW) and respiratory infections were more likely to be stunted than their counterparts. This was observed in South Ethiopia, Rwanda, Ecuador, Mexico, Mozambique, and Malawi children that did not receive MAD were more likely to be stunted compared to their counterparts [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] Moreover, Cruz et al., (2017) indicated that children born with LBW are born with low reserves of vital growth nutrients such as vitamin A, zinc, and iron [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. They are also prone to contact diseases and infections such as diarrhea, anemia, and respiratory infections, thereby increasing their likelihood of becoming stunted [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt household level, children in rural areas, poor households, households with non-resident mothers, maternal education with primary or no education, unsafe sources of drinking water and inadequate toilet facilities were more likely to be stunted. Poverty in Lesotho is deeply entrenched in rural areas, where 70% of the population resides [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. More than half of the population in Lesotho's rural areas is poor [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Amegbor et al., (2020) indicated that there is an association between different indicators of childhood malnutrition and region of residence to regional socio-economic differences [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In Low- and Middle-Income countries, such as Uganda, Indonesia, Kenya, and Niger, children in rural areas were more likely to be stunted compared to those in urban areas [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Economic, social environments and their inequality are important reasons for child malnutrition (Ghosh et al., 2020). This was also observed in Bangladesh, Ecuador, Cambodia, India, Ethiopia, Nigeria, Nepal, Parahmantan, Haiti, Burkina Faso, Malawi, Iran, Zimbabwe, Mozambique and Peru [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In relation to maternal residential status, this was also reported in China, Bangladesh, and Guatemala [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Migration is often considered an important way of improving livelihood conditions for the households and individuals [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Migration is often considered an important way of improving livelihood conditions for the households and individuals [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Historically, migration has been a male phenomenon in most countries, particularly in Lesotho [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, in recent years there has been an increase in female migration noted in several contexts in Africa, many of whom are mothers [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In most cases, children of these migrants are often left behind with extended family such as grandparents, uncles, and aunts; because of unstable income, and unfriendly housing in host areas [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, sources of drinking water and toilet facilities were determinants of stunting at household and community level. Water, Sanitation and Hygiene variables are intertwined. At household level, the same was reported in 172 countries, Pakistan, and Ethiopia, were children from households with access to unsafe drinking water were more likely to be stunted [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The lack of access to safe drinking water sources affects children\u0026rsquo;s health and well-being through repeated diarrheal infections [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. In Lesotho, the majority of communities do not have access to safe drinking water. Despite exporting water to South Africa (contributing to 8% -10% of the country's gross domestic product), about 63% rural domestic communities do not have access to safe drinking water, thus forcing them to use unprotected sources of drinking water with the majority of them having to travel more than 30 minutes to collect the unsafe water [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Nearly 85% of the rural population use traditional drinking water sources such as open reservoirs, springs, and open wells [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. These water sources are normally contaminated with E-Coli that causes stomach and intestinal illnesses including diarrhea and nausea even leading to death and stunting [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Water can be contaminated through environmental enteric dysfunction (EED) and soil-transmitted helminths [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Intestinal worms (soil-transmitted helminths) can predispose children to stunting through direct contact or through dust [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Pollution of the water sites can also be due to sanitation facilities such as pit latrines and open defecation along the boundaries of the water source as these may contaminate the water with faecal pathogens [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. At community level, children from communities with high proportions of adequate toilet facilities were less likely to being stunted than children in communities with low proportions of adequate toilet facilities. In Mozambique, Burkina Faso, Indonesia, Mali, Rwanda, Bangladesh, Brazil, Cambodia, Tanzania, and Ethiopia studies, India's poor household hygienic practices such as access to safe water, handwashing using soup and other sanitation practices increased the risk of stunting [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]A large proportion of Lesotho\u0026rsquo;s population remains without access to proper water and sanitation services [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. ILO (2020) highlighted that, in Lesotho, most people are also subjected to poor drainage facilities and agreements for solid waste disposal with around 30% of the population openly defecating [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Sanitation issues are more complicated than any other underlying and basic variables because one or more inadequate toilet facility in the community can contaminate the water of a larger group of people. Inadequate sanitation facilities contribute to increasing contamination of food and drinking water and children living in a household without a proper toilet are more likely to be stunted [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt community level, children from communities with high proportions of poor households, low proportions of males in the household with males and mothers with at least secondary education, safe sources of drinking water, adequate toilet facilities as well as maternal media exposure were more likely to be stunted. It is well documented that educated mothers have greater knowledge of appropriate care practices that improve the nutritional status of their children [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Therefore, children in communities with a high proportion of educated women are more likely to be healthier than those in low-proportion communities. Neighbourhoods constitute the key determinants of socioeconomic disparities in health, as they shape individual opportunities and exposes residents to multiple risks and resources [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In neighbourhoods with high proportions of educated women, social interactions are key to the dissemination of information in bettering the lives of children in that neighbourhood [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Moreover, educated households reproduce neighbourhood characteristics by choosing neighbourhoods with people with similar educational levels and affluence [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. On the other hand, exposure to mass media is an important as a source of knowledge [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. There is a gap in the literature on how community maternal media exposure impacts child malnutrition. However, what is known is, mass media provides information that is essential to amplifying people\u0026rsquo;s knowledge and awareness regarding issues of day-to-day life [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Mass media also has a greater role in building health and nutrition-related behaviours, attitudes as well as promoting socio-cultural and economic development that might contribute to improving the nutritional outcomes of children [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. In Indonesia, mass media also strengthened the role of frontline workers as well as reinforcing their status as experts and depicting them as educated, trusted, and reliable people [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. It also promoted health seeking behavior and appropriate childcare practices [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. This was also found in Sub-Saharan Africa, Bangladesh, China, Pakistan, Indonesia, and Tanzania [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study aimed to find determinants of stunting in Lesotho at three levels- individual, household, and community level. At individual level, determinants of stunting were child dietary intake and child health. At household level, the household\u0026rsquo;s care resources and the environment they reside in were determinants of stunting. The same applies at community level, variables that were determinants of stunting are thematically variables that are proxies for knowledge, information acquisition, and sharing about infant care as well as the environment they reside in. Therefore, strategies and programs to improve child nutritional status should be done in communities.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThe study shares a common limitation of cross-sectional study-the study supports the association between child diet, stunting, and independent variables, but not proving the causal relationship. Moreover, this study had limitations in that, the majority of the data is self-reported by mothers/caregivers, making it subject to recall bias and it can be subject to social-desirability bias. On the other hand, the study used clustering by aggregating individual and household variables, these may in misclassification or overestimation. Moreover, communities were created using clusters derived from Enumeration areas which might also be subject to coverage error.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study is part of the author’s thesis for a doctoral dissertation with the School of Built Environment and Development Studies at the University of Kwa-Zulu Natal, Durban, South Africa. We are grateful to the UNICEF, MICS team for providing the 2018 MICS dataset for the analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo grant was received for the study from any agency, university or public.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study used the LMICS 2018 dataset which \u0026nbsp;is publicly available on the MICS data official website https://mics.unicef.org/surveys \u0026nbsp;with all respondents identifier information removed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was designed by NL and KV. TT and ML were involved in the revision of the paper as well as the editing of the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author communicated with the UNICEF MICS team in 3 UN Plaza, New York, USA and was granted permission to download and use the LMICS dataset.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Statistics and Demography, Faculty of Social Sciences. National University of Lesotho. Maseru. \u003csup\u003e2\u0026nbsp;\u003c/sup\u003ePopulation Studies, School of Built Environment and Development Studies, University of KwaZulu-Natal, Durban, South Africa. \u003csup\u003e3\u0026nbsp;\u003c/sup\u003eDepartment of Statistics and Demography, Faculty of Social Sciences. National University of Lesotho. Maseru. \u003csup\u003e4\u0026nbsp;\u003c/sup\u003eDepartment of Statistics and Demography, Faculty of Social Sciences. National University of Lesotho. Maseru.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLesotho Demographic and Health Survey Report., (2014) Ministry of Health Lesotho.\u003c/li\u003e\n\u003cli\u003eUNICEF. 2022. NUTRITION, FOR EVERY CHILD UNICEF Nutrition Strategy 2020\u0026ndash;2030. [online] Available at: https://www.unicef.org/media/91741/file/UNICEF-Nutrition-Strategy-2020-2030-Brief.pdf [Accessed 27 April 2022].\u003c/li\u003e\n\u003cli\u003eUNICEF. 2018. CHILD MALNUTRITION: Unfolding the Situation in Egypt. 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(2017) \u0026ldquo;Effects of individual, household and community characteristics on child nutritional status in the slums of urban Bangladesh,\u0026rdquo; Archives of Public Health, 75(1). Available at: https://doi.org/10.1186/s13690-017-0176-x. \u003c/li\u003e\n\u003cli\u003eMoffat, R. et al. (2022) \u0026lsquo;A national communications campaign to decrease childhood stunting in Tanzania: An analysis of the factors associated with exposure\u0026rsquo;, BMC Public Health, 22(1). doi:10.1186/s12889-022-12930-6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-health-population-and-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"johp","sideBox":"Learn more about [Journal of Health, Population and Nutrition](http://jhpn.biomedcentral.com/)","snPcode":"41043","submissionUrl":"https://submission.nature.com/new-submission/41043/3","title":"Journal of Health, Population and Nutrition","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Multilevel, Child Malnutrition, Stunting, Childhood","lastPublishedDoi":"10.21203/rs.3.rs-4703564/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4703564/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe growth pattern of a healthy, well-fed child is reflected in positive changes in their height and weight [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Globally, complex, and intertwined determinants of stunting have been explored at individual, household, and community level but not in Lesotho. The objective of the study is to investigate the determinants of stunting at individual, household, and community level.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a multilevel logistic regression using data from the Lesotho Multiple Cluster Indicator Study of 2018.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn Lesotho a third (33.6%) of children under 5 were stunted in 2018. At individual level, child dietary intake, weight at birth and respiratory infection were determinants of stunting. At the household level, place of residence, household wealth, maternal residential status, maternal educational attainment, drinking water sources, and toilet facilities were also determinants of stunting. Moreover, at community levels, community female and male education, community poverty, sources of drinking water, toilet facilities and maternal media exposure were determinants of stunting in Lesotho in 2018.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThere is evidence of variability in the data in relation to stunting at all levels of the study. It also shows that, child dietary intake and health, household care resources, and environments children reside in are important in improving child nutritional status. At the community level, knowledge and information acquisition and sharing are important in fighting child malnutrition. Therefore, strategies and programs to improve child nutritional status should be done in communities.\u003c/p\u003e","manuscriptTitle":"A Multilevel Analysis of Factors Associated with Stunting Among Children Under Five Years in Lesotho: A Study of The Lesotho Multiple Cluster Indicator Study Of 2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-01 17:38:32","doi":"10.21203/rs.3.rs-4703564/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-06T07:02:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-04T12:10:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-04T20:15:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302233101265409040388895889485919208385","date":"2024-11-25T10:56:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175364710690971686352423782527540176999","date":"2024-11-24T07:18:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143228182547279269059602864348074930358","date":"2024-08-16T07:02:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-13T07:20:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-10T16:27:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-09T14:40:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Health, Population and Nutrition","date":"2024-07-08T07:42:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-health-population-and-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"johp","sideBox":"Learn more about [Journal of Health, Population and Nutrition](http://jhpn.biomedcentral.com/)","snPcode":"41043","submissionUrl":"https://submission.nature.com/new-submission/41043/3","title":"Journal of Health, Population and Nutrition","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a1ee6282-bbba-4284-b7ec-ace74a113bc5","owner":[],"postedDate":"August 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T16:00:23+00:00","versionOfRecord":{"articleIdentity":"rs-4703564","link":"https://doi.org/10.1186/s41043-025-00901-7","journal":{"identity":"journal-of-health-population-and-nutrition","isVorOnly":false,"title":"Journal of Health, Population and Nutrition"},"publishedOn":"2025-05-24 15:57:20","publishedOnDateReadable":"May 24th, 2025"},"versionCreatedAt":"2024-08-01 17:38:32","video":"","vorDoi":"10.1186/s41043-025-00901-7","vorDoiUrl":"https://doi.org/10.1186/s41043-025-00901-7","workflowStages":[]},"version":"v1","identity":"rs-4703564","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4703564","identity":"rs-4703564","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}