Seasonality of underweight among infants 1–11 months old in Niger
An exploratory analysis of data from a cluster-randomised trial
Bibliographic Data
INTRODUCTION: Malnutrition is a risk factor for child mortality, with around 45% of deaths in children under 5 globally linked to malnutrition. Seasonality of malnutrition has important implications for the timing of child health programme activities, but evidence is mixed on the nature of such patterns. Moreover, the bulk of the existing evidence is focused on wasting and stunting in children 6-59 months, despite increasing evidence that younger children also face a high risk, and that underweight alone is an important predictor of mortality. METHODS: This study used data from the cluster-randomised AVENIR trial which compared the effect of biannual distribution of azithromycin vs placebo on mortality in children 1-59 months old in Niger. AVENIR included a biannual census conducted on a rolling basis over 2 years. A subset of 133 781 infants aged 1-11 months from 2904 communities were included in this study, and weight-for-age z-score (WAZ) was calculated at each census. The exposure for this analysis is the day of the year weight was captured. Harmonic regression was used to determine primary and secondary peaks and nadirs of WAZ over time. RESULTS: Overall, the primary peak of WAZ occurred in late February and the primary nadir occurred in mid-May, aligning with a seasonal temperature increase before the rainy season. A secondary peak in August and a secondary nadir in November were also seen, aligning with the postrainy season. CONCLUSION: The seasonality of WAZ of infants 1-11 months in Niger may have implications for the timing of programmes aiming to decrease malnutrition
Body mass index · Cluster randomised controlled trial · Data science · Environmental health · Exploratory analysis · Overweight · Randomized controlled trial · Seasonality · Sociology · Statistics · Underweight · Birth, Development, and Health · Child Nutrition and Water Access · Climate Change and Health Impacts · Demography · Medicine · Internal Medicine · Pediatrics
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