SynthesisInternational journal of epidemiology2026
First global synthesis of heat-related mental health impacts in children and young people: a systematic review and meta-analysis.
Synthesis in International journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
backgroundClimate change is increasing the frequency and severity of non-optimal temperatures and heatwaves, posing risks to public health, especially for children and young people. We performed a systematic review and meta-analysis to assess the impacts of (i) non-optimal ambient temperatures and (ii) heatwaves on mental health outcomes in this group globally.
methodsWe searched five databases for studies published between 2000 and 2024. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we selected studies by using the population-exposure-comparison-outcome (PECO) framework (PROSPERO protocol ID CRD42024524650). We performed a random-effects meta-analysis, assessed the risk of bias, and examined variation by age, gender, income, and climate zones.
resultsOf 23 included studies, 19 examined ambient temperature and 4 examined heatwaves. A 1°C increase in daily ambient temperature was associated with a 0.9% increase in morbidity-related mental health outcomes across varied healthcare encounters and diagnoses (relative risk = 1.009; 95% confidence interval: 1.003-1.016). Children aged 5-18 years were most vulnerable, with a 1.5% increased risk associated with high temperatures (1.005-1.026) and 25% increased risk during heatwaves (1.006-1.561). Climate-zone analyses showed that children and young people in humid subtropical and hot-summer continental zones had the highest risks from high temperatures (1.004-1.036 and 1.004-1.038, respectively).
conclusionHigh temperatures and heatwaves were associated with adverse mental health risks in children and young people. Data were lacking for some of the hottest and most socio-economically disadvantaged regions globally. Future research should prioritize these regions, explore mechanistic pathways, and generate disaggregated data.
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