Geohealth最新文献

{"title":"Predicting Daily Cardiovascular Emergencies Using Weather and Air Quality Data: A 23-Year Machine-Learning Analysis in Taiwan","authors":"Hsiang-Han Chen,&nbsp;Pei-Shan Tsai,&nbsp;Yu-Chia Chen,&nbsp;Cheng-Yu Li,&nbsp;Yu-Kai Lin,&nbsp;Wan-Ru Huang,&nbsp;Kate Huihsuan Chen","doi":"10.1029/2025GH001769","DOIUrl":"https://doi.org/10.1029/2025GH001769","url":null,"abstract":"<p>Short-term variability in weather and air quality is known to influence cardiovascular emergencies, yet its day-to-day predictive value at the population level remains insufficiently understood. Using 23 years of nationwide data from Taiwan (2000–2022), we evaluated how weather and air quality conditions shape daily cardiovascular disease (CVD) emergency visits across geographic regions. We first applied unsupervised learning methods, including UMAP and K-means clustering, to 184 environmental features to identify data-driven environmental regimes and examine the distribution of high-risk CVD days. We then trained eight supervised learning models to predict daily CVD emergency visits and used SHAP values to interpret key predictors. Unsupervised analyses revealed consistent seasonal and pollution-related patterns. High-risk days tended to cluster during cool conditions accompanied by elevated air pollution, with temperatures higher than in winter but substantially greater pollution levels. This pattern was particularly evident in northern Taiwan and among populations aged 65 years and older. Air-pollution variables produced more clearly defined high-risk clusters than meteorological variables alone, indicating a stronger pollution-related contribution to acute CVD risk. In the supervised framework, tree-based ensemble models (Random Forest, LightGBM, XGBoost) achieved the best performance, with <i>R</i>² values up to 0.67 and mean absolute percentage errors of 7%–8%. Predictability was highest for elderly populations and northern Taiwan. SHAP analyses identified NO_x-related metrics as dominant predictors of CVD emergency visits. These results demonstrate that high-resolution environmental data, combined with machine-learning methods, can effectively predict CVD emergencies, delineate high-risk environmental regimes, and support region-specific early-warning systems centered on air-pollution monitoring, particularly NO_x.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001769","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148238065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Natural Environment, Neighborhood Contexts, and Intra-Urban Suicidal Behavior","authors":"Yehua Dennis Wei,&nbsp;Yu Wang,&nbsp;Meitong Liu,&nbsp;Yue Zhang,&nbsp;Max Coleman,&nbsp;Ming Wen","doi":"10.1029/2025GH001567","DOIUrl":"https://doi.org/10.1029/2025GH001567","url":null,"abstract":"<p>High suicide rates remain a critical public health challenge in the United States. Using census block group-level data, we examine spatial clustering of suicidal behavior in Salt Lake City (SLC), Utah, and identify key environmental and socioeconomic determinants. We find that green space and walkability are associated with lower suicidal behavior, likely by promoting stress relief, physical activity, and social interaction. In contrast, greater access to hotels is linked to higher risk, as these spaces may offer privacy that limits timely intervention. Neighborhoods with higher incomes and larger families showed greater resilience, consistent with reduced financial strain and stronger emotional support. Areas with higher labor force participation face increased risk, possibly reflecting pressures from job competition and wage stagnation. Contextual factors further moderate these effects. The protective effect of green space is weaker in neighborhoods with larger shares of non-Hispanic African American residents and in higher-income or larger-family areas, but stronger where the jobs–housing mix is higher. Spatial heterogeneity analyses reveal that mixed land use near downtown is associated with higher risk, likely because of traffic noise, waste, and crime. Meanwhile, higher proportions of non-Hispanic African American residents are associated with lower risk in eastern SLC, where these populations tend to live in higher-income neighborhoods with better living conditions. Overall, this study highlights the interplay of environmental, socioeconomic, and contextual factors underlying suicidal behavior and offers a comprehensive understanding of how physical settings and neighborhood characteristics shape vulnerability. These insights inform the development of more targeted and effective suicide prevention strategies.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001567","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential Health Impacts of Short-Term Particulate Matter Exposure in Arid and Semi-Arid Regions: A Scoping Review","authors":"Emmet Norris,&nbsp;Jennifer Bailey,&nbsp;Yiqun Ma,&nbsp;Anusha Goswami,&nbsp;Sarah Aarons,&nbsp;Tarik Benmarhnia","doi":"10.1029/2025GH001359","DOIUrl":"10.1029/2025GH001359","url":null,"abstract":"<p>Particulate matter (PM) exposure is a leading risk factor for cardiovascular and respiratory morbidity and mortality across the world. While arid and semi-arid regions account for more than 40% of terrestrial land, there is a paucity of research investigating the relationship between PM exposure and health outcomes or how risk varies across different populations specific to these climate regions. To address this, we performed a scoping review to assess the extent of literature in arid and semi-arid regions that consider such morbidity and mortality risks from short-term PM exposure. Our review identified 102 studies published after 2012 located within four arid climate classifications: hot arid, cold arid, semi-arid hot, and semi-arid cold. The meta-analysis found a pooled overall increased relative risk (RR) of both cardiovascular and respiratory mortality and morbidity, with an 8% higher risk of morbidity in hot arid regions (1.11, 95% confidence interval (CI): 1.05, 1.17) compared to cold semi-arid regions (1.02, 95% CI: 1.00, 1.03) for adults (18–64). Further, we assessed effect modification (age, sex, population density and season) and found weak evidence of increased risk for both males and adults. The studies included in this review highlighted compounding risks, such as dust storms, wildfire, and extreme temperature, however there was a significant lack of studies situated in highly populated arid regions, with none identified in Africa. Given the public health burden from PM exposure and the impact of climate change and anthropogenic activities which destabilize land-surfaces and increase dust emissions, additional focus is owed to demographic effect modifiers and the role of climate specific risks.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13250701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148228855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Intraurban Variation in Heat-Attributable Health Burden to Inform Local Interventions","authors":"K. Burley Farr,&nbsp;E. M. McInroe,&nbsp;W. L. Tsai,&nbsp;A. Hsu,&nbsp;A. G. Rappold","doi":"10.1029/2025GH001791","DOIUrl":"10.1029/2025GH001791","url":null,"abstract":"<p>Extreme heat exposure leads to excess cardiovascular morbidity and mortality among older adults, but misalignment in the geographic scales of health data and intraurban heat exposure make it challenging to inform local interventions. We introduce an adaptable framework for developing health burden estimates at finer geographic scales by connecting small area analysis (SAA) techniques with an epidemiologic model of heat related health risks in three steps: (a) estimating an exposure response function using individual level cardiovascular disease (CVD) hospitalizations for adults aged 65 and over; (b) downscaling daily CVD hospitalization incidence rates at the ZCTA-level to census block groups (CBG) using SAA, adjusting for individual- and community-level demographic factors, and (c) linking exposure-response with daily incidence rates to estimate heat-attributable burden at the CBG scale. Using the data for a metropolitan area in the southeastern United States for the summer of 2018, we estimated 1.8 to 22.0 excess hospitalizations per 10,000 people across CBG. We demonstrate the utility of this 3-step approach to help inform localized intervention strategies by classifying neighborhoods as one of four risk groups: Low, Health-driven, Heat-driven, and Dual-channel (driven by both heat and health). In comparison, using coarse-resolution temperature resulted in a significantly smaller heat-attributable health burden with different geographic distribution across the CBGs, highlighting the importance of using appropriately scaled exposure data. The findings from this study can support more effective heat interventions to address heat-health related outcomes, rather than exposure alone.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13250699/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148228868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Urban Heat-Related Illness Across U.S. Climate Regions and Demographics","authors":"S. E. Brown,&nbsp;V. Shandas","doi":"10.1029/2025GH001655","DOIUrl":"10.1029/2025GH001655","url":null,"abstract":"<p>We still know relatively little about how climate, demographics, built environment, and behaviors interact to drive hospitalizations during extreme heat events (EHEs). To address this paucity in understanding, we draw on extant literature to develop a transdisciplinary discrete event system dynamics (SD) modeling approach to address two research questions about the relationship between EHEs and heat-related illnesses (HRIs): (a) How will changes in EHE frequencies, intensities, and durations in major Metropolitan Statistical Areas (MSAs) across the contiguous United States (CONUS) Climate Regions drive HRI morbidity across demographic, health-status, and household groups over the coming decades? and (b) What are the anticipated HRI costs for these MSAs over the coming decades and how will the distribution of those costs evolve, across plausible low- and high-emissions scenarios? By employing a system dynamics simulation model on a sample of the 53 largest population MSAs in CONUS, we produced stratified HRI and cost projections across regions out to the year 2040. The results suggest that differences across regions and scenarios depend on changing EHE profiles combined with underlying changes in the geographic distribution of demographic and socioeconomic disparities in risk. By combining continuous and discrete event modeling, this approach makes possible the construction of models which can be empirically tested at discrete points, both structural and parametric, along their causal chains. Such models may help align specific interventions that address community vulnerabilities to extreme heat while improving the calibration, coordination, and timing of regional responses.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13248521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148220160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of Emotional Divergence in Risk Communication With Forecast Error Type During Typhoon Khanun","authors":"Kiru Kim,&nbsp;Jonghun Kam","doi":"10.1029/2026GH001837","DOIUrl":"10.1029/2026GH001837","url":null,"abstract":"<p>Forecast errors of severe weather events aggravate economic damage and degrade public mental health. Whether forecast errors are underestimated or overestimated can shape public emotional responses differently, which remains unknown. In this study, we investigate the socio-psychological impacts of forecast errors during the landfall of Typhoon Khanun over the Korean Peninsula. We evaluate the predictive performance of multiple lead-hour precipitation forecasts against observational data and conduct a sentimental analysis of over 43,000 online discourses from the NAVER Weather Report Talk platform. Multiple lead-hour precipitation forecasts demonstrate underestimation in the eastern and southeastern regions of the Korean Peninsula and overestimation in the western and southwestern regions. The spatial discrepancies of precipitation forecasts are associated with distinct emotional responses: overestimation (underestimation) makes anxiety and worry (stress and confusion) the dominant emotion types in the discourses from the NAVER Report Talk platform. The findings of this study suggest that expectation–reality mismatch is a key mechanism in risk communication, and the direction of this mismatch differentiates public response. This study provides insights into the potential value of improved forecast accuracy on reducing emotional distress and strengthening public resilience during extreme weather events.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13243200/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148212743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term Impacts of PM2.5 Components on Schizophrenia Hospitalization: A Time-Series Analysis From Nanning, China","authors":"Zukang Gong,&nbsp;Baihua Chen,&nbsp;Bin Xu,&nbsp;Lan Lan,&nbsp;Shuiqing Qin,&nbsp;Li Su,&nbsp;Wenzhen Lin,&nbsp;Jianxiong Long","doi":"10.1029/2025GH001556","DOIUrl":"10.1029/2025GH001556","url":null,"abstract":"<p>Schizophrenia (SCZ) is a serious psychiatric condition. While PM_2.5 exposure has been linked to SCZ, the specific effects of its components remain poorly understood. This study aimed to explore the relationships between PM_2.5 constituents (including BC: black carbon, OM: organic matter, SO₄²⁻: sulfate, NH₄⁺: ammonium, and NO₃⁻: nitrate) and SCZ. It incorporated the hospitalization records of 16,082 SCZ patients from Nanning Fifth People's Hospital, spanning from 1 January 2014, to 31 December 2023. The daily concentration data of PM_2.5 and its five chemical components were sourced from Tracking Air Pollution in China (TAP). A distributed lag nonlinear model (DLNM) was employed to measure the dynamic correlation between PM_2.5 components and the risk of hospitalization for SCZ. Further analysis was conducted by stratifying based on gender, age, and cold/warm seasons to identify susceptible populations. Our study revealed that OM and BC demonstrated lagged effects on SCZ hospitalization, with significant associations observed at lag 3 day(lag3)and lag4. The strongest effect was identified at lag4, with OM showing an relative risks (RR) of 1.010 (95%CI: 1.001, 1.019) and BC exhibiting a higher RR of 1.010 (1.001, 1.019). And the lag effect of the OM relative percentage was identified at lag 3 (RR = 1.013, 95% CI: 1.005–1.022). PM_2.5, SO₄²⁻, and NH₄⁺ showed lagged response trends but no statistically significant effects (<i>p</i> &gt; 0.05). Subgroup analysis indicated that males, 45 years and younger, and those exposed during the warm season had higher risks associated with SO₄²⁻, OM, BC, and PM_2.5. Short-term exposure to OM is significantly related to SCZ hospitalization.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13243193/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148212763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heat, Humidity, and Adverse Birth Outcomes: Quantification of Projected Risks in the Contiguous United States","authors":"Megan Sheahan,&nbsp;Rupa Basu,&nbsp;Stefania Papatheodorou,&nbsp;Charles Fant,&nbsp;Benjamin Jeweler,&nbsp;Isabel Holland,&nbsp;James E. Neumann,&nbsp;Caitlin A. Gould","doi":"10.1029/2025GH001643","DOIUrl":"https://doi.org/10.1029/2025GH001643","url":null,"abstract":"<p>Research increasingly demonstrates relationships between higher apparent temperatures, inclusive of heat and humidity, and greater rates of preterm birth (PTB), term low birth weight (tLBW), and stillbirth cases. Through leveraging available epidemiological studies, we estimated the change in burden of these outcomes across the contiguous United States (CONUS) and throughout the 21st century during warm season months (i.e., May through September or October). We projected an additional 4,500 PTBs, 3,800 tLBWs, and 420 stillbirths annually at 1°C of CONUS warming attributable to changes in apparent temperature relative to baseline climatic conditions (1986–2005). These cases increased to 22,000 PTBs, 18,000 tLBWs, and 2,000 stillbirths annually with 4°C of warming relative to the baseline. We projected the most significant changes in per capita rates to occur in Gulf Coast states, where baseline risks of these birth outcomes currently are among the highest in CONUS. Across the three outcomes, we projected an increase in short-term healthcare costs following birth of approximately US$690 million annually at 1°C of warming, increasing to US$3.3 billion annually at 4°C (2023 dollars). When considering the economic burden of the infant deaths resulting from PTB and tLBW cases, we projected additional costs on the order of US$3.9 billion annually at 1°C, and US$35.8 billion annually at 4°C. Due to data availability, our valuation could not account for potential longer-term health and productivity implications or pain and suffering that families may experience following the adverse birth outcomes analyzed.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001643","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Seasonal Meteorological Variability on Malaria Incidence in Côte d'Ivoire: A Retrospective Study (2021–2023)","authors":"Mawussé Bernice Corinne Akpovo,&nbsp;Adama Doumbia,&nbsp;Serge Paul Eholié,&nbsp;Wardatou Dine Mourtad,&nbsp;Sohee Park,&nbsp;Vasuki Rajaguru,&nbsp;Whiejong M. Han","doi":"10.1029/2025GH001728","DOIUrl":"https://doi.org/10.1029/2025GH001728","url":null,"abstract":"<p>Metrological variations strongly influence malaria transmission by affecting mosquito breeding and survival. Côte d'Ivoire, located within a tropical climate zone, is particularly vulnerable to metrological variations that can alter disease patterns. This study aimed to assess the relationship between meteorological variations of temperature, precipitation, relative humidity and malaria incidence in Côte d'Ivoire from 2021 to 2023. This was a retrospective ecological time-series study that used data from the National Malaria Control Program (NMCP) and meteorological data from SODEXAM. Monthly data was analyzed by ecological zones and age groups. Pearson's correlation and multiple linear regression models were used to examine associations between metrological variation factors and malaria incidence. Malaria incidence peaked during the rainy season (May–August) across all regions, with children under five representing 39% of total cases. Precipitation and relative humidity were positively and significantly correlated with malaria incidence (<i>r</i> = 0.583–0.698, <i>p</i> &lt; 0.05), while temperature showed a significant negative correlation (<i>r</i> = −0.539 to −0.600, <i>p</i> &lt; 0.05). Interaction analysis revealed that the effect of precipitation and humidity was strongest in the northern zone, where malaria transmission risk increased significantly (<i>β</i> = 22.51, <i>p</i> = 0.01). Malaria transmission in Côte d'Ivoire is strongly associated with metrological variability, particularly rainfall and humidity. Elevated precipitation and humidity increase malaria morbidity, whereas high temperatures above 28°C suppress transmission. Integrating meteorological surveillance into malaria early warning systems can improve prediction and control strategies, especially among vulnerable populations such as children under five.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001728","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence and Spatial Distribution of Chronic Respiratory Diseases in Dar es Salaam, Tanzania: Hydrological and Household Influences","authors":"Ibrahim Msuya,&nbsp;Francis Levira,&nbsp;Irene Moshi,&nbsp;Jean O'Dwyer,&nbsp;Gerry F. Killeen","doi":"10.1029/2025GH001764","DOIUrl":"https://doi.org/10.1029/2025GH001764","url":null,"abstract":"<p>Chronic Respiratory Diseases (CRDs) are a major global health burden, causing significant mortality and morbidity. The World Health Organization reports CRDs led to 4.1 million deaths in 2023, affecting 454.6 million people (5.54% globally). While tobacco smoking is the leading risk factor, others include air pollution, occupational hazards, childhood respiratory infections, and genetic predisposition. This study examines hydrology's role in CRD prevalence and spatial distribution, alongside household-level factors. Using remote sensing, the Topographical Wetness Index (TWI) was calculated at 30 m resolution and linked to CRD prevalence data from 1,533 households across 15 income-stratified neighborhoods in Dar es Salaam, Tanzania. Generalized linear mixed models, geovalidation, and ground truthing were employed for analysis. Results showed that CRD prevalence was significantly associated with higher TWI scores (OR = 1.18 [1.04, 1.33] per TWI unit increase, <i>p</i> = 0.009), with flood-prone areas (TWI ≥ 15) exhibiting a ninefold greater risk (OR = 8.63 [2.13, 35]). Other independent risk factors included household size (OR = 1.15 [1.05, 1.25] per person, <i>p</i> = 0.003) and communal skip bin use (OR = 4.04 [1.04, 15.80], <i>p</i> = 0.045). Conversely, air conditioning reduced CRD risk (OR = 0.22 [0.06, 0.77], <i>p</i> = 0.017). Notably, neighborhood income was not directly associated with CRD prevalence after adjusting for other factors, indicating poverty acts as an indirect, rather than proximal, determinant. These findings link moist, mold-prone environments to CRD risk, especially in urbanizing cities. Poor households often settle in flood-prone areas due to affordability, underscoring hydrology's role in CRD disparities.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001764","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}