Mean consumption of SSBs, fruit juice, milk, and calcium by age, sex, and country income level.

<p>¹Income categorizations based on the World Bank classification system: (<a href="http://data.worldbank.org/about/country-classifications/country-and-lending-groups" target="_blank">http://data.worldbank.org/about/country-classifications/country-and-lending-groups</a>).</p><p>Mean consumption of SSBs, fruit juice, milk, and calcium by age, sex, and country income level.</p

Consumption of non-alcoholic caloric beverages in 187 countries worldwide.

<p>A) SSBs, B) Fruit juice, C) Milk. Mean country-level beverage consumption levels in servings/day are represented by the color scales in each panel. Note that the scale range differs in each panel.</p

Regional age and time trends in SSB consumption and BMI.

<p>Each three-dimensional plot shows age, mean BMI, and mean SSB intake on the x-, y-, and z-axes respectively. Each point represents one age group in one country and the points are color-coded by super-region as shown in the legend. The top panel shows data from 1990 and the bottom panel shows data from 2010.</p

Risk Factors for Childhood Stunting in 137 Developing Countries: A Comparative Risk Assessment Analysis at Global, Regional, and Country Levels

<div><p>Background</p><p>Stunting affects one-third of children under 5 y old in developing countries, and 14% of childhood deaths are attributable to it. A large number of risk factors for stunting have been identified in epidemiological studies. However, the relative contribution of these risk factors to stunting has not been examined across countries. We estimated the number of stunting cases among children aged 24–35 mo (i.e., at the end of the 1,000 days’ period of vulnerability) that are attributable to 18 risk factors in 137 developing countries.</p><p>Methods and Findings</p><p>We classified risk factors into five clusters: maternal nutrition and infection, teenage motherhood and short birth intervals, fetal growth restriction (FGR) and preterm birth, child nutrition and infection, and environmental factors. We combined published estimates and individual-level data from population-based surveys to derive risk factor prevalence in each country in 2010 and identified the most recent meta-analysis or conducted de novo reviews to derive effect sizes. We estimated the prevalence of stunting and the number of stunting cases that were attributable to each risk factor and cluster of risk factors by country and region.</p><p>The leading risk worldwide was FGR, defined as being term and small for gestational age, and 10.8 million cases (95% CI 9.1 million–12.6 million) of stunting (out of 44.1 million) were attributable to it, followed by unimproved sanitation, with 7.2 million (95% CI 6.3 million–8.2 million), and diarrhea with 5.8 million (95% CI 2.4 million–9.2 million). FGR and preterm birth was the leading risk factor cluster in all regions. Environmental risks had the second largest estimated impact on stunting globally and in the South Asia, sub-Saharan Africa, and East Asia and Pacific regions, whereas child nutrition and infection was the second leading cluster of risk factors in other regions.</p><p>Although extensive, our analysis is limited to risk factors for which effect sizes and country-level exposure data were available. The global nature of the study required approximations (e.g., using exposures estimated among women of reproductive age as a proxy for maternal exposures, or estimating the impact of risk factors on stunting through a mediator rather than directly on stunting). Finally, as is standard in global risk factor analyses, we used the effect size of risk factors on stunting from meta-analyses of epidemiological studies and assumed that proportional effects were fairly similar across countries.</p><p>Conclusions</p><p>FGR and unimproved sanitation are the leading risk factors for stunting in developing countries. Reducing the burden of stunting requires a paradigm shift from interventions focusing solely on children and infants to those that reach mothers and families and improve their living environment and nutrition.</p></div

Mapping harmonization findings to the analytic framework.

<p>Mapping harmonization findings to the analytic framework.</p

Assessment of current status of harmonization by study participants.

<p>Assessment of current status of harmonization by study participants.</p

Selected characteristics of the study participants.

<p>Selected characteristics of the study participants.</p

Mediators of harmonization mentioned by study participants.

<p>Mediators of harmonization mentioned by study participants.</p

Sources of data on the selected risk factors and their effect size for stunting.

<p>Sources of data on the selected risk factors and their effect size for stunting.</p

Risk factors ranked within each cluster by number of attributable stunting cases in children aged 2 y in 137 developing countries in 2011.

<p>Whiskers indicate 95% confidence intervals. Effects are not additive because each case of stunting can be attributed to more than one risk factor. Untreated HIV infection is not included because exposure data for all countries were not available. PAGA, preterm, appropriate for gestational age; PSGA, preterm, small for gestational age; TSGA, term, small for gestational age.</p