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Height-age is the age at which growth-faltered children’s average observed height or length equals the median height or length of a child growth standard, corresponding to a length-for-age z-score (LAZ) of 0. In randomized controlled trials (RCTs) in low- and middle-income countries (LMICs), expression of linear growth outcomes using height-age may enhance the interpretability of intervention effects compared to conventional use of LAZ. Height-age can be used to derive the proportion of maximal benefit (PMB), whereby PMB = 0% indicates no effect and PMB = 100% indicates the intervention promoted growth at the rate expected for healthy children with the same starting height-age. In this proof-of-concept study, height-age and PMB were compared to LAZ in a meta-analysis of RCTs of small-quantity lipid-based nutrient supplements (SQ-LNS). Pooling across 15 trials in 10 LMICs, mean differences (MD; SQ-LNS minus control) in LAZ and height-age were 0.15 (95%CI: 0.12, 0.17) and 12 days (95%CI: 9, 14), respectively (N = 36,970). LAZ MD and height-age MD were highly correlated (rho = 0.74 overall and 0.94 upon exclusion of an outlier). The pooled PMB indicated that SQ-LNS achieves 11% of optimal growth potential (95% CI: [9.4, 12]; N = 19,768; 12 comparisons), but there was a substantial impact of between-trial heterogeneity (I 2  = 90%). In conclusion, the effect of SQ-LNS on linear growth can be alternatively expressed in terms of height-age instead of LAZ. The PMB may enhance the interpretability of effect estimates by quantifying the extent to which an intervention improves growth in relation to a biological threshold, but further research is required to establish its validity and usefulness for assessing and comparing intervention effectiveness.

The double burden of malnutrition (under- and overnutrition) is a serious public health issue in childhood. The mid-upper arm circumference (MUAC) is a simple tool for screening nutritional status, but studies of the optimal cutoff to define malnutrition are limited. This study aimed to explore the prediction of malnutrition by MUAC in Sri Lankan schoolchildren. The participants were 538 students (202 boys, 336 girls) aged 5–10 years. Spearman’s rank correlation was calculated for MUAC and both body-mass-index-for-age z-score (BAZ) and height-for-age z-score (HAZ). Receiver operating characteristic (ROC) analysis was conducted to assess the ability of MUAC to correctly classify malnutrition, after stratifying for age and birth weight. MUAC correlated significantly with BAZ (r = 0.84) and HAZ (r = 0.35). The areas under the ROC curve for thinness, overweight, obesity, and stunting were 0.88, 0.97, 0.97, and 0.77, respectively. The optimal MUAC cutoff values for predicting thinness and stunting were 167.5 mm and 162.5 mm, respectively; the optimal cutoffs for predicting overweight and obesity were 190.5 mm and 218.0 mm, respectively. These cutoffs differed after stratification by age group and birth weight. Our results confirm MUAC to be a useful tool for monitoring growth in schoolchildren.

Aim To synthesize available evidence on the association between change in linear growth (height for age z score, HAZ) beyond the first two years of life with later child neurodevelopment outcomes in Low- and middle-income countries (LMICs). Methods We searched PubMed, Web of Science, and EMBASE for cohort studies on the association between change in HAZ after age two and neurodevelopment outcomes in middle or late childhood. Data extraction was done independently by two reviewers. Results A total of 21 studies, that included 64,562 children from 13 LMICs were identified. Each unit increase in change in HAZ above two years is associated with a + 0.01 increase ( N  = 8 studies, 27,393 children) in the cognitive scores at 3.5 to 12 years of age and a + 0.05-standard deviation (SD) increase (95% CI 0.02 to 0.08, N  = 3 studies, 17,830 children) in the language score at 5 to 15 years of age. No significant association of change in HAZ with motor (standardized mean difference (SMD) 0.04; 95% CI: -0.10, 0.18, N  = 1 study, 966 children) or socio-emotional scores (SMD 0.00; 95% CI: -0.02, 0.01, N  = 4 studies, 14,616 participants) was observed. Conclusion Changes in HAZ after the first two years of life appear to have a small or no association with child neurodevelopment outcomes in LMICs.

Nutrition is an important factor in mental development and, as a consequence, in cognitive performance. Malnutrition is reflected in children's weight, height and BMI curves. The present cross-sectional study aimed to evaluate the association between anthropometric indices and cognitive performance in 6746 school-aged children (aged 6–12 years) of four Southeast Asian countries: Indonesia; Malaysia; Thailand; Vietnam. Cognitive performance (non-verbal intelligence quotient (IQ)) was measured using Raven's Progressive Matrices test or Test of Non-Verbal Intelligence, third edition (TONI-3). Height-for-age z-scores (HAZ), weight-for-age z-scores (WAZ) and BMI-for-age z-scores (BAZ) were used as anthropometric nutritional status indices. Data were weighted using age, sex and urban/rural weight factors to resemble the total primary school-aged population per country. Overall, 21 % of the children in the four countries were underweight and 19 % were stunted. Children with low WAZ were 3·5 times more likely to have a non-verbal IQ < 89 (OR 3·53 and 95 % CI 3·52, 3·54). The chance of having a non-verbal IQ < 89 was also doubled with low BAZ and HAZ. In contrast, except for severe obesity, the relationship between high BAZ and IQ was less clear and differed per country. The odds of having non-verbal IQ levels < 89 also increased with severe obesity. In conclusion, undernourishment and non-verbal IQ are significantly associated in 6–12-year-old children. Effective strategies to improve nutrition in preschoolers and school-aged children can have a pronounced effect on cognition and, in the longer term, help in positively contributing to individual and national development.

Introduction Many low-and middle-income countries (LMICs) have improved health indicators in the past decades, however, there is a differential in outcomes between socioeconomic groups. Systematic analysis of drivers of child nutrition gap between non-poor and poor groups has a policy relevance in Nepal and other countries to make progress towards universal health coverage (UHC). The objective of this paper was to estimate the mean height-for-age z scores (HAZ) gap between under-five children belonging to non-poor and poor groups, divide the gap into components (endowments, coefficients and interaction), and identify the factors that contributed most to each of the component. Methods Information about 6277 under-five children was extracted from the most recent nationally representative Nepal Multiple Indicator Cluster Survey (MICS) 2019. HAZ was used to assess nutritional status of children. Wealth index was used to categorize children into non-poor and poor. Mean HAZ gap between groups was decomposed using Blinder-Oaxaca technique into components: endowments (group difference in levels of predictors), coefficients (group difference in effects of predictors), and interaction (group difference due to interaction between levels and effects of predictors). Detailed decomposition was carried out to identify the factors that contributed most to each component. Results There was a significant non-poor and poor gap in nutrition outcome measured in HAZ (0.447; p  < 0.001) among under-five children in Nepal. The between-group mean differences in the predictors of study participants (endowments) contributed 0.210 (47%) to the gap. Similarly, the between-group differences in effects of the predictors (coefficients) contributed 0.308 (68.8%) towards the gap. The interaction contributed -0.071 (15.8%) towards minimizing the gap. The predictors/variables that contributed most towards the gap due to (i) endowments were: maternal education, province (Karnali, Sudurpaschim, Madhesh), residence (rural/urban), type of toilet facility and ethnic group (Dalit and Muslim); (ii) coefficients were: number of under-five children in family, ethnic group (Dalit and Muslim), type of toilet facility, maternal age and education. Conclusion Decomposition of the child nutrition gap revealed that narrowing the inequality between wealth groups depends not only on improving the level of the predictors (endowments) in the poor group but also on reducing differential effects of the predictors (coefficients).

Introduction Prevalence of undernutrition continues to be high in India and low household wealth is consistently associated with undernutrition. This association could be modified through improved dietary intake, including dairy consumption in young children. The beneficial effect of dairy on child growth has not been explored at a national level in India. The present analyses aimed to evaluate the direct and indirect (modifying association of household level per adult female equivalent milk and milk product consumption) associations between household wealth index on height for age (HAZ) and weight for age (WAZ) in 6-59 months old Indian children using data from of nationally representative surveys. Methods Two triangulated datasets of two rounds of National Family Health Survey, (NFHS-3 and 4) and food expenditure (National Sample Survey, NSS61 and 68) surveys, were produced by statistical matching of households using Non-Iterative Bayesian Approach to Statistical Matching technique. A Directed Acyclic Graph was constructed to map the pathways in the relationship of household wealth with HAZ and WAZ based on literature. The direct association of wealth index and its indirect association through per adult female equivalent dairy consumption on HAZ and WAZ were estimated using separate path models for each round of the surveys. Results Wealth index was directly associated with HAZ and WAZ in both the rounds, but the association decreased from NFHS-3 (β HAZ : 0.145; 95% CI: 0.129, 0.16) to NFHS-4 (β HAZ : 0.102; 95%CI: 0.093, 0.11). Adult female equivalent milk intake (increase of 10gm/day) was associated with higher HAZ (β_NFHS-3=0.001;95% CI: 0, 0.002; β_NFHS-4=0.002;95% CI: 0.002, 0.003) but had no association with WAZ. The indirect association of wealth with HAZ through dairy consumption was 2-fold higher in NFHS-4 compared to NFHS-3. Conclusions The analysis of triangulated survey data shows that household level per- adult female equivalent dairy consumption positively modified the association between wealth index and HAZ, suggesting that regular inclusion of milk and milk products in the diets of children from households across all wealth quintiles could improve linear growth in this population.

Background Child undernutrition continues to be a major public health problem in many countries, including Nepal. The repercussions of undernutrition are not only limited to the affected children and families but also transcend to the national and global economy. Earlier studies from Nepal have predominantly used either ordinary least squares (OLS) regression or binary regression to analyse the socioeconomic and demographic correlates of the nutritional outcome. In this study, quantile regression was used to understand a complete and more precise estimate of the effects of the covariates on the child nutritional status. Methods This study was based on the most recent nationally representative Nepal Multiple Indicator Cluster Survey (MICS) 2019. Height-for-age z scores (HAZ) were used as an indicator for assessing the nutritional status of under-five children. Quantile regression was used to examine the heterogeneous association of covariates with conditional HAZ distribution across the different quantiles (0.10, 0.30, 0.50, 0.85). As a comparison, the effects of covariates at conditional mean of HAZ using OLS regression was also analysed. The graphs were plotted to visualize the changes in the coefficients for each regressor across the entire conditional HAZ distribution. Results Age of children, sex of children, province and wealth had a consistent and statistically significant association with HAZ in both OLS and quantile regression. Improved toilet facility was positively correlated with HAZ at the lower tails (tenth and thirtieth percentiles). Ethnicity (Janajati and Newer) was positively correlated with HAZ at the lower tail (thirtieth percentile) and mean (OLS regression). Maternal education was a significant predictor of improved height-for-age across conditional quantiles, except at the tenth percentile. Maternal age, number of under-five children in household, number of household members, and improved source of drinking water showed heterogeneous effects across different quantiles of conditional HAZ distribution. Conclusion Use of quantile regression approach showed that the effect of different factors differed across the conditional distribution of HAZ. Policymakers should consider the heterogeneous effect of different factors on HAZ so that the targeted intervention could be implemented to maximize the nutritional benefits to children.

Background To determine the prevalence of enteric infections in Aboriginal children aged 0–2 years using conventional and molecular diagnostic techniques and to explore associations between the presence of pathogens and child growth. Methods Cross-sectional analysis of Aboriginal children ( n  = 62) residing in a remote community in Northern Australia, conducted from July 24th - October 30th 2017. Stool samples were analysed for organisms by microscopy (directly in the field and following fixation and storage in sodium-acetate formalin), and by qualitative PCR for viruses, bacteria and parasites and serology for Strongyloides -specific IgG. Child growth (height and weight) was measured and z scores calculated according to WHO growth standards. Results Nearly 60% of children had evidence for at least one enteric pathogen in their stool (37/62). The highest burden of infection was with adenovirus/sapovirus (22.9%), followed by astrovirus (9.8%) and Cryptosporidium hominis/parvum (8.2%). Non-pathogenic organisms were detected in 22.5% of children. Ten percent of children had diarrhea at the time of stool collection. Infection with two or more pathogens was negatively associated with height for age z scores (− 1.34, 95% CI − 2.61 to − 0.07), as was carriage of the non-pathogen Blastocystis hominis (− 2.05, 95% CI - 3.55 to − 0.54). Conclusions Infants and toddlers living in this remote Northern Australian Aboriginal community had a high burden of enteric pathogens and non-pathogens. The association between carriage of pathogens/non-pathogens with impaired child growth in the critical first 1000 days of life has implications for healthy child growth and development and warrants further investigation. These findings have relevance for many other First Nations Communities that face many of the same challenges with regard to poverty, infections, and malnutrition.

Child malnutrition remains a challenge in Ethiopia despite progress in development goals. Stunting in children under five leads to disease, impaired development, and increased mortality. Earlier studies have used linear and logistic regressions to identify the drivers of stunting. These models overlook variations across outcome distributions. This study employed simultaneous quantile regression to identify the association between chronic malnutrition across different height-for-age z-score (HAZ) quantiles in children under the age of five. Data were drawn from the 2016 Ethiopian Demographic and Health Survey, including 8,592 women aged 15 – 49 years and their under-five children. After cleaning missing variables, HAZ score served as the dependent variable. Simultaneous quantile regression modeled covariates across multiple quantiles. The findings indicated that 34.75% of children were stunted. Significant variables associated with HAZ score included place of residence, shared toilet facility, respondent employed, vaccination, succeeding birth interval in months, frequency of checking antenatal care, literacy, type of toilet facility, anemia level, wealth index of household, twin status, place of delivery, highest level of education of mother and father and age of child. The association of these factors varied across quantiles, with slope differences between the 10 th and 90 th quantiles. The quantile regression plots for the selected quantiles 10 th to 90 th revealed significant differences in the association of the covariates across the HAZ quantiles under consideration. Quantile regression revealed that various factors work differently across the HAZ distribution. Findings demonstrate the benefit of quantile regression in revealing differential impacts and guiding targeted policy. Addressing stunting requires coordinated efforts to enhance child nutrition and achieve the Sustainable Development Goals by 2030.

Stunting is an important risk factor for early growth and health implications throughout the life course, yet until recently, studies have rarely focused on populations exposed to high levels of particulate matter pollution or on developing countries most vulnerable to stunting and its associated health and developmental impacts. We systematically searched for epidemiologic studies published up to 15 August 2020 that examined the association between ambient and household particulate exposure and postnatal stunting (height-for-age z-score) and prenatal determinants (small for gestational age or SGA, or equivalent) of stunting. We conducted the literature search in PUBMED, MEDLINE, EMBASE, and Web of Science databases in August 2020, using keywords including, but not limited to, “particulate matter,” “indoor/household air pollution,” and “adverse birth outcomes,” to identify relevant articles. Forty-five studies conducted in 29 countries met our inclusion criteria for meta-analysis. We found significant positive associations between SGA and a 10 μg/m 3 increase in fine particulate matter (PM 2.5 ) exposure over the entire pregnancy [OR = 1.08; 95% confidence interval (CI): 1.03–1.13], with similar SGA impact during the second and third trimesters, and from high exposure quartile of PM 2.5 exposure during the entire pregnancy. A 19% increased risk of postnatal stunting (95% CI: 1.10, 1.29) was also associated with postnatal exposure to household air pollution. Our analysis shows consistent, significant, and noteworthy evidence of elevated risk of stunting-related health outcomes with ambient PM 2.5 and household air pollution exposure. This evidence reinforces the importance of promoting clean air as part of an integrated approach to preventing stunting.