Peak timing of slowest growth velocity among young children coincides with highest ambient temperatures in Burkina Faso: a longitudinal study

Background: Seasonal cycles in climatic factors affect drivers of child growth and contribute to seasonal fluctuations in undernutrition. Current growth seasonality models are limited by categorical definitions of seasons that rely on assumptions about their timing and fail to consider their magnitude. Objective: We disentangle the relationship between climatic factors and growth indicators, using harmonic regression to determine how child growth is related to peaks in temperature, precipitation, and vegetation. Methods: Longitudinal anthropometric data collected between August 2014 and December 2016 from 5039 Burkinabe children measured monthly from age 6 to 28 mo (108,580 observations) were linked with remotely sensed daily precipitation, vegetation, and maximum air temperature. Our models parsimoniously extract a cyclic signal with multiple potential peaks, to compare the magnitude and timing of seasonal peaks in climatic factors and morbidity with that of nadirs in growth velocity (cm/mo, kg/mo). Results: Length and weight velocity were slowest twice a year, coinciding both times with the highest temperatures, and peak fever incidence. Length velocity is slowest 13 d after the first temperature peak in April, and 5 d after the second. Similarly, weight velocity is slowest 13 d before the first temperature peak, and 11 d before the second. The statistical relationship between temperature and anthropometry shows that when the current temperature is higher, weight velocity is lower (beta = -0.0048; 95% CI: -0.0059, -0.0038), and length velocity is higher (beta = 0.0088; 95% CI: 0.0070, 0.0105). Conclusions: Results suggest that child health and development are more affected by high temperatures than by other aspects of climatic seasonality such as rainfall. Emerging shifts in climatic conditions will pose challenges to optimal growth, highlighting the importance of changes that optimize the timing of nutrition interventions and address environmental growth-limiting conditions.