Assessing the effect of drought severity on height-for-age z-score in Kenyan children: a secondary analysis
Notice bibliographique
Résumé
BackgroundGlobally, droughts are occurring more regularly and are having negative effects on population health, particularly in countries such as Kenya, where agriculture is a primary driver of the economy and a source of subsistence for many communities. Children are particularly susceptible to weather-related shocks. Previous research has shown an association between drought and cross-sectional indicators of malnutrition, such as stunting. In this study, we explored various longitudinal and spatial analysis approaches to evaluating the effect of drought on height-for-age z-scores (HAZ) over time and space among young children in Kenya.MethodsUsing anthropometric data from three georeferenced Kenyan Demographic and Health Surveys (KDHS) and the self-calibrated Palmer Drought Severity Index, we developed multivariate linear regression and spatial lag and error models (with Moran's I calculations) to investigate the association between drought severity and HAZ in children aged 0–5 years. Initial covariates included age of the child, sex, maternal age, height and education, wealth index, urban or rural location, and size at birth. We then did multilevel and geographically weighted regression modelling using frequentist or Bayesian methods and with inclusion of household-level covariates, such as livelihood zones. To assess the effect of changes in drought severity on child HAZ over time, KDHS data from 2003, 2008–09, and 2014 were analysed with spatiotemporal modelling.FindingsPreliminary results from the multivariate linear model showed a negative, non-significant association between drought severity and HAZ among Kenyan children in 2014 (β=0·033, p=0·101); however, there was a significant interaction between drought severity and age (β=–0·002, p<0·0007). The spatial lag model gave similar results. Other variables associated with HAZ included wealth index, age, sex, maternal education, and maternal height. Global Moran's I calculations indicated that there was a slight positive spatial autocorrelation across child HAZ (I=0·047, p<0·0001).InterpretationIncreased drought severity was associated with a non-significant decrease in HAZ among Kenyan children. However, a significant interaction between age and drought severity indicates that the effect of drought on HAZ varies by age. Findings from this study will help to inform the development of methodological approaches for improving understanding of the effects of climate change on child health. Expanding these analyses to other east-African countries will also contribute to the development of national adaptation strategies and planning in anticipation of increased climate variability.FundingCanadian Institutes of Health Research (Institute of Public and Population Health).
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| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
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