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Identifying the impact of rainfall variability on conflicts at the monthly level.

ABSTRACT: Research on the relationship between rainfall variability and conflicts has yielded contradictory results. This study is the first to show that the significance of the impact of rainfall variability on conflicts depends on the temporal unit of analysis. We prove this point by comparing the statistical significance of the linkages between georeferenced conflicts and rainfall variabilities at the monthly and annual levels with panel data analyses from 1989 to 2020. We find that a 10 percent increase in monthly rainfall decreases the risk of conflict incidence by 0.0298 percent, but annual rainfall variability is not statistically linked to conflict outbreaks. These statistically significant disparities result from the aggregation of data dispersion and the disregard for the timing of the impact of rainfall on conflicts. These findings highlight the importance of information on monthly rainfall variation when estimating the impact of rainfall on conflicts.

SUBMITTER: Coulibaly TY

PROVIDER: S-EPMC9616923 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Identifying the impact of rainfall variability on conflicts at the monthly level.

Coulibaly Thierry Yerema TY Managi Shunsuke S

Scientific reports 20221028 1

Research on the relationship between rainfall variability and conflicts has yielded contradictory results. This study is the first to show that the significance of the impact of rainfall variability on conflicts depends on the temporal unit of analysis. We prove this point by comparing the statistical significance of the linkages between georeferenced conflicts and rainfall variabilities at the monthly and annual levels with panel data analyses from 1989 to 2020. We find that a 10 percent increa ...[more]

PMID: 36307515

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Project description:Background: Climate change and consequent increases in rainfall variability may have negative consequences for the food production of subsistence farmers in West Africa with adverse impacts on nutrition and health. We explored the pathway from rainfall through diet up to child undernutrition for rural Burkina Faso. Methods: The study used data of a dynamic cohort with 1,439 children aged 7-60 months from the Nouna Health and Demographic Surveillance Site (HDSS) for 2017 to 2019. We assessed data on diets, height, weight, household characteristics, and daily precipitation (from 1981 to 2019). Principal component analysis was used to identify distinct child dietary patterns (Dietary Pattern Scores, DPS). These were related to 15 rainfall indicators by area to obtain a precipitation variability score (PVS) through reduced rank regression (RRR). Associations between the PVS and anthropometric measures, height-for-age (HAZ), and weight-for-height (WHZ), were examined using multi-level regression analysis. Results: Stunting (HAZ < -2) and wasting (WHZ < -2) were seen in 24 and 6% of the children. Three main dietary patterns were identified (market-based, vegetable-based, and legume-based diets) and showed mixed evidence for associations with child undernutrition. The RRR-derived PVS explained 14% of the total variance in these DPS. The PVS was characterized by more consecutive dry days during the rainy season, higher cumulative rainfall in July and more extremely wet days. A 1-point increase in the PVS was associated with a reduction of 0.029 (95% CI: -0.06, 0.00, p < 0.05) in HAZ in the unadjusted, and an increase by 0.032 (95% CI: 0.01, 0.06, p < 0.05) in WHZ in the fully adjusted model. Conclusion: Rainfall variability was associated with dietary patterns in young children of a rural population of Burkina Faso. Increased rainfall variability was associated with an increase in chronic undernutrition, but not in acute undernutrition among young children.

Dataset Information

Identifying the impact of rainfall variability on conflicts at the monthly level.

Publications

Identifying the impact of rainfall variability on conflicts at the monthly level.

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