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Globally, 21 percent of young women are married before their 18th birthday. Despite some progress in addressing child marriage, it remains a widespread practice, in particular in South Asia. While household predictors of child marriage have been studied extensively in the literature, the evidence base on macro-economic factors contributing to child marriage and models that predict where child marriage cases are most likely to occur remains limited. In this paper we aim to fill this gap and explore region-level indicators to predict the persistence of child marriage in four countries in South Asia, namely Bangladesh, India, Nepal and Pakistan. We apply machine learning techniques to child marriage data and develop a prediction model that relies largely on regional and local inputs such as droughts, floods, population growth and nightlight data to model the incidence of child marriages. We find that our gradient boosting model is able to identify a large proportion of the true child marriage cases and correctly classifies 77% of the true marriage cases, with a higher accuracy in Bangladesh (92% of the cases) and a lower accuracy in Nepal (70% of cases). In addition, all countries contain in their top 10 variables for classification nighttime light growth, a shock index of drought over the previous and the last two years and the regional level of education, suggesting that income shocks, regional economic activity and regional education levels play a significant role in predicting child marriage. Given the accuracy of the model to predict child marriage, our model is a valuable tool to support policy design in countries where household-level data remains limited. [ABSTRACT FROM AUTHOR]

Access to adequate and nutritious food is important for the current and future health of adolescent girls. Interventions often focus on the individual as responsible for their own health ignoring the complex structural issues that underlie optimal nutrition. In South Asia gender inequalities have been noted as an important determinant of poor nutrition among women and their young children, but analysis of adolescent girls' diets and what influences these are rarely undertaken. Therefore, we sought to analyse the factors affecting what and where girls' eat and what affects their behaviour in the plains of Nepal, using a cultural-ecological approach. We analysed a secondary qualitative dataset of focus group discussions with adolescent girls aged 12–19 years old, young mothers, mothers-in-law, and older female key informants. Eating was heavily influenced by patriarchal norms. Boys had preferential access to food, money, and freedom of movement to appreciate their future role in providing for the family. Food was an investment, and boys were perceived to have more nutritional need than girls. Girls were not perceived to be a good return on investment of food, and eating practices sought to prepare them for life as a subservient daughter-in-law and wife. Obedience and sacrifice were valued in girls, and they were expected to eat less and do more housework than boys. Girls' eating and behaviour was constrained to maintain self and family honour. Interventions should acknowledge cultural influences on eating and engage multiple actors in addressing harmful gender norms which limit eating and prevent girls from reaching their potential. [ABSTRACT FROM AUTHOR]

Lentil (Lens culinaris Medik.) is a cool-season pulse grown in winter cropping cycle in South Asia and provides a major source of nutrition for many low-income households. Lentil productivity is perceived to be sensitive to high rainfall, but few studies document spatial and temporal patterns of yield variation across climate, soil, and agronomic gradients. Using farm survey data from Nepal, this study characterizes patterns of lentil productivity and efficiency for two cropping seasons. Additional insights were derived from on-farm trials conducted over a 5-year period that assess agronomic, drainage, and cultivar interventions. To contextualize the inferences derived from farm surveys and trials, the Stempedia model was used to simulate the severity of Stemphylium blight (Stemphylium botryosum) risk–the principal fungal disease in lentil–with 30 years of historical climate data. Although development efforts in Nepal have prioritized pulse intensification, results confirm that lentil remains a risky enterprise highlighting the prevalence of crop failures (16%), modest yields (353 kg ha-1), and low levels of profitability (US$ 33 ha-1) in wet winters. Nevertheless, site factors such as drainage class influence responses with upland sites performing well in wet winters and lowland sites performing well in dry winters. In wet winters, a phenomena perceived to be increasing, 76% of surveyed farmers reported significant disease pressure and simulations with Stempedia predict that conditions favoring Stemphylium occur in >60% of all years. Nevertheless, simulation results also suggest that these risks can be addressed through earlier planting. Based on the combined results, gains in yield, yield stability, and technical efficiency can be enhanced in western Nepal by: 1) ensuring timely lentil planting to mitigate climate-mediated disease risk, 2) evaluating new lentil lines that may provide enhanced resistance to diseases and waterlogging, and 3) encouraging the emergence of mechanization solutions to overcome labor bottlenecks. [ABSTRACT FROM AUTHOR]