Abstract
ObjectivesThis study aimed to demonstrate feasibility of a novel method for measuring resilience in dietary diversity (DD) and body mass index (BMI) of rural women of reproductive age (WRA) in Nepal and Bangladesh. Resilience is defined as the population’s ability to recover from adverse shocks, measured relative to statistical mean reversion. MethodsWe used regionally representative surveys from Nepal (n = 2187) and Bangladesh (n = 1715) collected annually in Nepal (four panels, 2013–2016) and every 6 months in Bangladesh (3 panels, 2016–2017), for BMI (kg/m2) and DD using 10 food groups (7-day qualitative diet recall, Nepal) and 6 food groups (24-hour diet recall, Bangladesh). We estimated where i is the woman, y is the outcome of interest, and z is a vector of controls. ∆yi, t+j denotes change in y between t + j-1 and t + j. Declinedi,t+1 equals 1 if the change between t and t + 1 is negative, zero otherwise. β2 measures the degree of reversal in decline controlling for mean reversion (β1) and other differences (age, age2, age cube, and socioeconomic status). β2 = 0 is our benchmark of mean reversion around the trend, i.e., recoveries after decline are not significantly different from declines after recovery. ResultsOur technique revealed significant (P < 0.01) resilience of DD in Nepal (Figure 1, Panel A). Among 1682 women in the Terai region, 47% (n = 784) experienced an initial decline in DD, and 61% of that initial decline was recovered. Mean reversion removed only 25% of the initial change among those who gained. We found no significant resilience in Bangladesh (Figure 1, Panel B) or for BMI in either country. ConclusionsThe resilience of DD in Nepal could reflect food aid responses to the 2015 earthquake or other interventions, while lack of resilience in BMI could reflect time lags, measurement errors or limits on the speed and timing of weight change. Lack of resilience of DD in Bangladesh could reflect shorter time intervals. Future work will apply this method to test for differences in resilience associated with exposure to programmatic interventions. Funding SourcesSupport provided by Feed the Future Innovation Lab for Nutrition, funded by the United States Agency for International Development (USAID). Supporting Tables, Images and/or Graphs▪
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