Danielson Jorge Delgado Neves

Background: Climate change is likely to affect health outcomes, particularly for vulnerable populations. Innovative research tools integrating environmental, climate, social, and health data are needed to better understand short and long-term impact of climate change on health and the impact of adaptive or mitigating interventions. Methods: Using social and health data from the Center for Data and Knowledge Integration for Health (CIDACS/Fiocruz) linked to climate and environmental data, we developed the CIDACS-Clima Platform, an innovative resource that integrates longitudinal, standardised environmental, climate, social, and health data for Brazil from 2000 to the present. Climate and environmental data are from different open-access sources, including weather and air quality stations, climate reanalysis, and Earth Observation satellite products, ensuring consistent data quality and fine spatial and temporal resolution across Brazil. Social and health data from two different resources: the open-access Deidentified Data Platform and the controlled-access 100 Million Brazilian and CIDACS Birth Cohorts, assembled with identified data and therefore secured with strict data protection requirements. Findings: The Platform provides environmental and climate exposures, including air temperature, humidity, rainfall, and PM2.5, as well as extreme event indicators, such as heatwaves and droughts. This allows studies of the effects of climate change on health outcomes across the social spectrum and the marked geographical and environmental variation observed in Brazil. The integration of data from social protection and adaptation policies enables evaluation of the impact on health of efforts to adapt to or mitigate climate change. Interpretation: By aligning open-access and controlled-access environmental, climate, social, and health data under a rigorous data protection framework, the CIDACS-Clima Platform provides an unprecedented infrastructure to investigate climate change-related health risks and their attribution, and to examine how structural inequalities and policies aimed at adaptation or mitigation could amplify or attenuate these risks.

Background We investigated the association between short-term exposure to heatwaves and infant and young child feeding practices in Brazil. Methods We obtained individual-level data from the Brazilian Food and Nutrition Surveillance System (SISVAN) and temperature data from the Brazilian Daily Weather Gridded Data for 2015–2022. Heatwaves were defined as periods of at least 2 consecutive days with daily mean ambient temperature above the municipality-specific 92·5th, 95th, or 97·5th percentile. Outcomes included minimum meal frequency (MMF), minimum dietary diversity (MDD), minimum acceptable diet (MAD), egg and/or flesh food consumption (EFF), sugar-sweetened beverage consumption (SwB), and unhealthy food consumption (UF). We used logistic regression combined with distributed lag non-linear models to estimate cumulative associations over 7 days. Findings Among 1,100,321 children aged 6–23 months, heatwave exposure was consistently associated with higher odds of not meeting MAD, with estimates increasing at higher temperature thresholds: OR 1·11 (95% CI 1·07–1·14), 1·16 (1·11–1·21), and 1·24 (1·15–1·33) at the 92·5th, 95th, and 97·5th percentiles, respectively. For MMF, corresponding ORs were 1·05 (1·02–1·09), 1·09 (1·05–1·14), and 1·09 (1·01–1·17). Heatwaves were also associated with higher odds of SwB consumption and non-consumption of EFF. No consistent associations were observed for MDD or UF. Associations were more pronounced in the Northeast and in municipalities with higher material deprivation. Interpretation Short-term exposure to heatwaves may disrupt complementary feeding practices, particularly in socially vulnerable settings. These findings may help inform public health strategies to support young children and caregivers during extreme heat events.

To develop and apply composite indices to assess immediate losses caused by hydrological disasters in Brazil between 2000 and 2023, with a focus on human losses and damages to health infrastructure. Data were obtained from the Integrated Disaster Information System, which consolidates national records of hydrological disasters. Seven indicators were selected for the Human Loss Index and four for the Health Infrastructure Loss Index. Indicators were normalized using Min-Max procedures and weighted through a combined Analytic Hierarchy Process and entropy method. The General Severity Index was calculated as the arithmetic mean of Human Loss Index and Health Infrastructure Loss Index, stratified into four levels of severity. Spatial and temporal analyses were conducted to identify critical regions and municipalities. The findings reveal significant heterogeneity in disaster impacts across time and space. Human losses exhibited greater variability than health infrastructure losses, with notable peaks in 2006, 2011, 2015, and 2019. Infrastructure damages were less frequent but highly disruptive, especially in 2012, 2019, and 2023. Municipalities in the Amazon region, particularly Japurá and Atalaia do Norte, registered the highest combined indices, reflecting compounded vulnerabilities from geographic isolation, fragile infrastructure, and socioeconomic inequalities. High General Severity Index scores were concentrated in the North, while human losses were more widely distributed, including along the densely populated southeastern coast. Results confirm that small and socioeconomically vulnerable municipalities are disproportionately affected, with limited institutional capacity to respond. Hydrological disasters in Brazil are strongly mediated by social inequalities, deficient urban planning, and weak preventive policies. Human and infrastructure losses disproportionately affect vulnerable populations, particularly in the North, where access to health services is precarious. The findings emphasize the need for territorially integrated strategies that combine climate adaptation, poverty reduction, and investments in resilient public health infrastructure.

Background: We investigated the association between short-term exposure to heatwaves and infant and young child feeding practices in Brazil.Methods: We obtained individual-level data from the Brazilian Food and Nutrition Surveillance System (SISVAN) and temperature data from the Brazilian Daily Weather Gridded Data for 2015–2022. Heatwaves were defined as periods of at least 2 consecutive days with daily mean ambient temperature above the municipality-specific 92·5th, 95th, or 97·5th percentile. Outcomes included minimum meal frequency (MMF), minimum dietary diversity (MDD), minimum acceptable diet (MAD), egg and/or flesh food consumption (EFF), sugar-sweetened beverage consumption (SwB), and unhealthy food consumption (UF). We used logistic regression combined with distributed lag non-linear models to estimate cumulative associations over 7 days.Findings: Among 1,100,321 children aged 6–23 months, heatwave exposure was consistently associated with higher odds of not meeting MAD, with estimates increasing at higher temperature thresholds: OR 1·11 (95% CI 1·07–1·14), 1·16 (1·11–1·21), and 1·24 (1·15–1·33) at the 92·5th, 95th, and 97·5th percentiles, respectively. For MMF, corresponding ORs were 1·05 (1·02–1·09), 1·09 (1·05–1·14), and 1·09 (1·01–1·17). Heatwaves were also associated with higher odds of SwB consumption and non-consumption of EFF. No consistent associations were observed for MDD or UF. Associations were more pronounced in the Northeast and in municipalities with higher material deprivation.Interpretation: Short-term exposure to heatwaves may disrupt complementary feeding practices, particularly in socially vulnerable settings. These findings may help inform public health strategies to support young children and caregivers during extreme heat events.

Exposure to high ambient temperatures near the time of delivery has been associated with adverse birth outcomes, but studies examining the impact on immediate newborn health remain limited. We used a time-stratified case-crossover design combined with a distributed lag nonlinear model to evaluate the short-term effects of ambient heat (0–1 day lag) on low 5-minute APGAR score (≤7; sub-categories: 6–7, 3–5, 0–2). Cases of low APGAR score among low-risk births (n = 34,980) in São Paulo state (274 municipalities), 2013–2019, were extracted from Brazil’s Live Birth Information System (Sistema de Informações Sobre Nascidos Vivos). Municipality-level daily mean temperatures were constructed from ERA5-Land reanalysis data and linked with case and control days by date and municipality of delivery. Models were adjusted for relative humidity and stratified by maternal age, race/ethnicity, education, parity, timing of prenatal care initiation, infant sex, municipality-level deprivation, and Köppen climate zone. Overall, exposure to high (95^th percentile: 26.1°C) versus moderate (50^th percentile: 20.9°C) temperature 0–1 days before delivery was associated with 8% higher odds (OR: 1.08, 95% CI: 1.02-1.14) of low APGAR score (≤7). In stratified analyses, heat-associated risks were elevated among infants born to women with Parda (1.10, 1.01-1.20). Associations were primarily driven by same-day (lag 0) exposure and were only observed in newborns with moderately low APGAR scores (6–7). Acute exposure to ambient heat may adversely impact newborns’ immediate health in low-risk live-births, highlighting the need for heat mitigation measures near the time of delivery.