Season of Data Collection of Child Dietary Diversity Indicators May Affect Conclusions About Longer-Term Trends in Peru, Senegal, and Nepal

Abstract

Background The WHO-UNICEF minimum dietary diversity (MDD) indicator for children aged 6–23 months is a global monitoring indicator used to track multi-year population-level changes in dietary quality, but the influence of seasonality on MDD estimates remains unclear. Objective Examine how seasonality of data collection may influence population-level MDD estimates and inferences about MDD change over multiple survey years. Methods Three countries were selected with three or more consecutive years of MDD data collection including continuous national Demographic Health Surveys in Senegal (2012–2017, N = 12,183) and Peru (2005–16, N = 35,272) and the PoSHAN sentinel site seasonal surveys (covering 3 seasons/year) in Nepal (2013–2016, N = 1309). MDD prevalence (≥5 of 8 food groups) and an 8-item continuous food group score (FGS) and 95% confidence intervals were estimated by month and compared for lean and non-lean seasons using Ordinary Least Squares (OLS) regression with dummy variables for year. Results The national prevalence of MDD was higher in Peru (75.4%) than in Nepal (39.1%) or in Senegal (15.7%). Children in Peru were 1.8% [coefficient: –0.0179 (–0.033, –0.002)] less likely to achieve MDD during the lean season. Similar seasonal magnitudes were observed in Senegal [–0.0347, (–0.058, –0.011)] and for Nepal [–0.0133 (–0.107, 0.081)]. FGS was about 0.1 item lower during the lean season in all three countries. In comparison, MDD increased by an average rate of only 4.2 and 4.4 percentage points per five years in Peru and Senegal respectively. Intake of specific food groups was stable across months in all countries with the provitamin-A rich food group exhibiting the most seasonality. Conclusions The magnitude of seasonal variation in MDD prevalence was smaller than expected but large relative to longer term changes. If large-scale surveys are not conducted in the same season, biased conclusions about trends are possible.

Seasonality and Day-to-Day Variability of Dietary Diversity: Longitudinal Study of Pregnant Women Enrolled in a Randomized Controlled Efficacy Trial in Rural Burkina Faso

“…Indeed, low dietary diversity has been attributed to a high dependence on tô , which is a stiff, cereal-based porridge served with a watery sauce containing green, leafy vegetables (e.g., sorrel and baobab leaves) and sporadically garnished with other vegetables (e.g., eggplant, tomato, and okra) or nuts and seeds (peanuts and néré seed), with or without meat, fish, or caterpillars ( 19 , 27 , 43 ). Moreover, in parallel to our findings, vitamin A–rich fruit and vegetable consumption [e.g., ripe mangoes ( 2 )] exhibited the most seasonality among under-5 children in Nepal, Peru, and Senegal ( 8 ), which was, however, buffered slightly by a higher consumption prevalence of flesh foods and other vegetables by women enrolled in MISAME-III. In contrast, the lack of intra-annual variability in the consumption of dark green, leafy vegetables, for example, might be explained by the different seasonal harvesting patterns of species and varieties within the same FG ( 61 ) or by processing techniques (e.g., dried compared with fresh foods).…”

“…Hence, mismatches in the timing of repeated cross-sectional surveys might exert spurious influences on inferences about changes in the FG diversity score or MDD-W prevalence among pregnant women over time, in particular if observational studies are not conducted in the same season. Thorne-Lyman et al ( 8 ) indicated that average annual rates of change (over ∼5 years) in children's 8-point FG score and a dichotomous indicator (≥5 FGs) were not markedly larger than the average seasonal changes observed, which suggests that seasonal fluctuations are large enough to introduce bias into inferences of change and trends in dietary diversity, particularly when data collection is annual and baseline levels are high. Furthermore, in MISAME-III, a dichotomous MDD-W (i.e., only crossing >5 FGs reflects change) resulted in only a slight loss of responsiveness to seasonality among MISAME-III participants, thus leading us to conclude that changes occur mainly amongst segments of our sample with FG diversity scores close to the 5-FG cutoff.…”

“…Prior analyses of the seasonality of individual- or household-level dietary diversity range from (fixed- or mixed-effects) regression ( 19 , 33–39 ) to time-series summaries of (bi)monthly ( 19 , 40 , 41 ) or seasonal values ( 34 , 39 , 42–52 ), followed by the fit of a regression model that takes a 12-month periodicity (annual model) into account ( 8 , 40 ), and models including an interaction term between dietary diversity indices and survey timing to assess effect modification on nutrient intake ( 47 , 54 , 55 ). However, those methods can lead to over-parameterization or may introduce abrupt changes by the arbitrary choice of seasonal cutoffs (e.g., lean compared with plenty).…”

“…Food group (FG) diversity scores, which consist of counting the number of FGs recalled over a defined period (e.g., 24 hours), are relatively straightforward to measure and are widely used as population-based indicators to assess dietary diversity in multitopic surveys (e.g., Demographic and Health Surveys) ( 8 ) and intervention studies ( 9 ). In 2016, the 5 out of 10 FG cutoff of the Minimum Dietary Diversity for Women (MDD-W) indicator was identified as the most accurate cutoff to predict a mean probability of adequacy (MPA) >0.60 of nonpregnant and lactating women's diets across 11 micronutrients ( 10 ).…”

Gender-common and gender-specific determinants of child dietary diversity in eight Asia Pacific countries

“…Third, our analysis model did not account for within-country seasonality of food availability. Types of affordable food and diversity of market-available food are season-dependent [ 59 ]. To alleviate the seasonal impacts on child’s food intake caused by various data collection periods between countries, we built a unique analysis model for each country.…”