Associations between rainfall and leaf area index-LAI and nutritional and health indicators in two districts of Southern Madagascar: The HydroNut project

• First study linking climate variability through rainfall and vegetation and nutritional and health outcomes in the southern Madagascar • Lag time between hydroclimatic indicators and health/nutrition outcomes were identified, indicating that preventive actions should be prioritized within 0-3 months after rainfall peaks and within 0-2 months following LAI increases to mitigate health impacts • Early Warning Systems could support resilience with timely anticipatory actions Climate crises affect human health, including nutritional status. However, evidence on this association remains limited. We investigated the associations between hydroclimatic indicators (rainfall and Leaf Area Index (LAI)) and health and nutrition outcomes (Severe Acute Malnutrition (SAM), diarrhea, Acute Respiratory Infections (ARI), Malaria) as part of the HydroNut project led by Action contre la Faim. Time series data on monthly nutritional and health outcomes of children under five, along with hydroclimatic indicators, were collected for Amboasary (2014–2021) and Betioky (2016–2021) districts in Madagascar. Associations were assessed using negative binomial regression models adjusted for seasonality and trends providing the relative risk (RR) and its 95% confidence interval (95% CI). Lagged effects were also explored. Data covered 54–90 months, depending on the indicator and district. In Amboasary and Betioky respectively, crude models showed positive associations of rainfall with SAM (RR[95%CI]=1.005[1.002-1.007]; 1.003[1.000-1.005]), diarrhea (1.002[1.001-1.004]; 1.004[1.001-1.006]), and ARI only in Betioky (1.002[1.000-1.004]). Similar stronger associations were observed for LAI with SAM (3.138[2.174-4.530]; 2.122[1.504-2.994]), diarrhea (1.925[1.512-2.450]; 2.220[1.701-2.898]), and ARI in Betioky (1.813[1.368-2.401]). Overall, lag effects appeared within three months for rainfall and two months for LAI, showing a protective role between months 4–10 according to district and outcome. Malaria showed negative associations, turning positive after 4–7 months for rainfall and 2–6 months for LAI. In conclusion, SAM, ARI, and diarrhea increased within three months of rainfall or two months of LAI increases. Further research is needed to better understand the mechanisms underlying these relationships, thereby improving humanitarian response strategies.

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Journal
Environmental Advances
Published
2025-11-20
DOI
https://doi.org/10.1016/j.envadv.2025.100677
Primary Topic
Remote Sensing in Agriculture
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article
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article

Associations between rainfall and leaf area index-LAI and nutritional and health indicators in two districts of Southern Madagascar: The HydroNut project

Laure Ngabirano, Simon Carrière, Alan R. Patlán‐Hernández, Dieynaba S. N’Diaye et al.
Environmental Advances
Remote Sensing in Agriculture
article

Associations between rainfall and leaf area index-LAI and nutritional and health indicators in two districts of Southern Madagascar: The HydroNut project

Laure Ngabirano, Simon Carrière, Alan R. Patlán‐Hernández, Dieynaba S. N’Diaye, Jacques Gardon, Jean Lapègue, Tom Heath, Camille Ollivier, Fara Pascale Rakotomandrindra, Myriam Ait Aissa
article en

Abstract

• First study linking climate variability through rainfall and vegetation and nutritional and health outcomes in the southern Madagascar • Lag time between hydroclimatic indicators and health/nutrition outcomes were identified, indicating that preventive actions should be prioritized within 0-3 months after rainfall peaks and within 0-2 months following LAI increases to mitigate health impacts • Early Warning Systems could support resilience with timely anticipatory actions Climate crises affect human health, including nutritional status. However, evidence on this association remains limited. We investigated the associations between hydroclimatic indicators (rainfall and Leaf Area Index (LAI)) and health and nutrition outcomes (Severe Acute Malnutrition (SAM), diarrhea, Acute Respiratory Infections (ARI), Malaria) as part of the HydroNut project led by Action contre la Faim. Time series data on monthly nutritional and health outcomes of children under five, along with hydroclimatic indicators, were collected for Amboasary (2014–2021) and Betioky (2016–2021) districts in Madagascar. Associations were assessed using negative binomial regression models adjusted for seasonality and trends providing the relative risk (RR) and its 95% confidence interval (95% CI). Lagged effects were also explored. Data covered 54–90 months, depending on the indicator and district. In Amboasary and Betioky respectively, crude models showed positive associations of rainfall with SAM (RR[95%CI]=1.005[1.002-1.007]; 1.003[1.000-1.005]), diarrhea (1.002[1.001-1.004]; 1.004[1.001-1.006]), and ARI only in Betioky (1.002[1.000-1.004]). Similar stronger associations were observed for LAI with SAM (3.138[2.174-4.530]; 2.122[1.504-2.994]), diarrhea (1.925[1.512-2.450]; 2.220[1.701-2.898]), and ARI in Betioky (1.813[1.368-2.401]). Overall, lag effects appeared within three months for rainfall and two months for LAI, showing a protective role between months 4–10 according to district and outcome. Malaria showed negative associations, turning positive after 4–7 months for rainfall and 2–6 months for LAI. In conclusion, SAM, ARI, and diarrhea increased within three months of rainfall or two months of LAI increases. Further research is needed to better understand the mechanisms underlying these relationships, thereby improving humanitarian response strategies.

Environmental AdvancesVol. 22
Centre National de la Recherche Scientifique (FR), University of Antananarivo (MG), École Pratique des Hautes Études (FR), Université de Montpellier (FR), Sorbonne Université (FR), Milieux environnementaux, transferts et interactions dans les hydrosystèmes et les sols (FR), Institut des Géosciences de l'Environnement (FR), Institut de Recherche pour le Développement (FR), Université Grenoble Alpes (FR), Action Contre la Faim (FR)
Openalex Percentile: Top 66%
Remote Sensing in Agriculture
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