Danielle N. Medgyesi

Climate-induced migration is increasingly recognized as a major demographic consequence of environmental change, yet projections vary widely due to differences in spatial scale, hazard coverage, and modeling approaches. This study introduces the First Street Global Climate Migration Model (FS-GCMM), a globally consistent, multi-hazard framework that estimates climate-driven population redistribution at a 12.5 km resolution across all countries through 2100. The model integrates high-resolution global climate hazard datasets, including flood (GloFAS), wind (IBTrACS and ERA5), drought (ERA5), wildfire (Global Fire Atlas), and extreme heat and cold (ERA5-LAND) datasets, with gridded population data from NASA SEDAC’s Gridded Population of the World (GPWv4) and Shared Socioeconomic Pathway (SSP) projections. To identify climate-related migration effects, we applied within-country propensity score matching to construct balanced samples of exposed and unexposed grid cells with similar socioeconomic, demographic, geographic, and governance characteristics. Hazard-specific impacts on annualized population change from 2000 to 2020 were then estimated using mixed-effects ridge regression with country-level random effects to account for cross-national heterogeneity and multicollinearity. These empirically derived coefficients were applied to SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios to project future climate-driven outmigration, which was subsequently redistributed using a spatial attractiveness framework incorporating economic opportunity, population density, climate safety, and geographic proximity. Results indicate statistically significant negative effects of all modeled hazards on population retention globally, with approximately 199.5 million people projected to experience climate-driven displacement by 2055 under SSP2-4.5.

Background: Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are persistent, widespread environmental contaminants, and some are endocrine disrupting. Studies of gynecologic cancers are limited; we evaluated ovarian cancer, a rare, often fatal malignancy. Methods: This nested case-control study included 318 ovarian cancer cases and 472 individually matched female controls in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, which recruited participants aged 55-74 years from 10 US study centers (1993-2001). We looked at cases through 2016 and quantitated 8 PFAS in prediagnostic serum samples. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for continuous (log2-transformed) and categorized PFAS concentrations by using conditional logistic regression models, implicitly adjusting for matching factors (age, center, year of random assignment, year of blood draw, race and ethnicity) and adjusting for smoking, body mass index, family history of cancer, menopausal hormone therapy and oral contraceptive use, parity, and number of freeze-thaw cycles. Results: We found a positive association with ovarian cancer for a doubling in 2-(N-methyl-perfluorooctane sulfonamido) acetic acid (MeFOSAA) concentrations (OR for log2 = 1.24, 95% CI = 1.03 to 1.49) and 62% greater risk among those in the highest quartile (OR for quartile 4 vs quartile 1 = 1.62, 95% CI = 1.03 to 2.54; P for trend = .02). Perfluorooctane sulfonic acid (PFOS) was associated with increased risk (OR for log2 = 1.47, 95% CI = 1.05 to 2.06), with no quartile trend (P for trend = .79). Associations with perfluorononanoic acid (OR for log2 = 1.36, 95% CI = 0.95 to 1.95) and perfluorodecanoic acid (OR for log2 = 1.35, 95% CI = 0.94 to 1.95) were suggested, with nonmonotonic quartile trends (P for trend = .12 to .21). The MeFOSAA associations were strongest in women aged 55-59 years (OR for log 2 = 1.60, 95% CI = 1.13 to 2.27), more moderate in women aged 60-64 years (OR for log2 = 1.31, 95% CI = 0.90 to 1.90), and null among women 65 years of age and older (OR for log2 = 1.02, 95% CI = 0.73 to 1.43; P for heterogeneity = .22). Associations persisted in cases diagnosed 8 years or more after blood collection. Conclusions: These findings offer novel evidence for PFAS as ovarian cancer risk factors, particularly PFOS and MeFOSAA, a PFOS precursor.

Importance: Over 90% of the US population relies on community water supplies (CWS), which generally use chlorine for disinfection. Trihalomethanes are regulated disinfection byproducts associated with bladder cancer and adverse birth outcomes. Animal studies report trihalomethanes, especially brominated compounds, may damage kidney function, but epidemiologic research is limited.Objective: To evaluate long-term exposure to trihalomethanes in residential CWS and its association with chronic kidney disease (CKD) risk.Design, Setting, and Participants: The California Teachers Study (CTS) is an ongoing prospective cohort of female teachers and administrators enrolled between 1995 and 1996 with data linked to mortality and health care records. This cohort study analyzed CTS data from January 1, 2005, once CKD diagnostic coding was adopted, through December 31, 2018. Statistical analysis was conducted from July 2023 to December 2024.Exposures: Residence time-weighted mean concentrations of 4 trihalomethanes, including 3 brominated trihalomethanes and chloroform, were calculated using annual measurements from CWS serving participants’ homes from 1995 to 2005. Uranium and arsenic (potentially nephrotoxic metals, previously evaluated in the cohort) from CWS were included as part of a g-computation mixture analysis.Main Outcomes and Measures: Cases of moderate (stage 3) to end-stage CKD were identified with diagnostic codes or dialysis-related procedures. Mixed-effects multivariable-adjusted Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% CIs for CKD by exposure to trihalomethane levels (US maximum contaminant level of 80 μg/L).Results: The study sample included 89 320 female participants (median age, 50 years [IQR, 43-61 years]) with 6242 CKD cases. Median concentrations were 5.5 μg/L (IQR, 0.5-24.1 μg/L; 95th percentile, 57.8 μg/L) for total trihalomethanes and 2.7 μg/L (IQR, 0.7-11.3 μg/L; 95th percentile, 30.0 μg/L) for brominated trihalomethanes. In flexible spline-based models, a clear exposure-response association was observed between trihalomethanes and CKD risk, with the highest risk for brominated trihalomethanes. The HRs for CKD risk associated with brominated trihalomethanes at the highest 2 exposure categories (75th percentile and at or above the 95th percentile) were 1.23 (95% CI, 1.13-1.33) and 1.43 (95% CI, 1.23-1.66), respectively (P < .001 for trend). Brominated trihalomethanes were the largest contributor (52.9%) to the association of the overall mixture with CKD risk, followed by uranium (35.4%), arsenic (6.2%), and chloroform (5.5%).Conclusions and Relevance: In this prospective cohort study of California female teachers, exposure to trihalomethane concentrations less than 80 μg/L (US current standard) increased CKD risk, particularly brominated trihalomethanes, which are not separately regulated in community water. The findings may have public health implications given the widespread use of water chlorination and growing burden of CKD.

BACKGROUND: Volatile organic compounds (VOCs) are ubiquitous environmental pollutants. Exposure to VOCs is associated with cardiovascular disease risk factors, including elevated blood pressure in susceptible populations. However, research in the general population, particularly among nonsmoking adults, is limited. We hypothesized that higher VOC exposure is associated with higher blood pressure and hypertension, among nonsmokers. METHODS: We included 4 cycles of data (2011–2018) of nonsmoking adults (n=4430) from the National Health and Nutrition Examination Survey. Urinary VOC metabolites were measured by ultraperformance liquid chromatography-mass spectrometry, adjusted for urine dilution, and log-transformed. We estimated mean differences in blood pressure using linear models and prevalence ratio of stage 2 hypertension using modified Poisson models with robust standard errors. Models were adjusted for age, sex, race and ethnicity, education, body mass index, estimated glomerular filtration rate, and National Health and Nutrition Examination Survey cycle. RESULTS: Participants were 54% female, with a median age of 48 years, 32.3% had hypertension, and 7.9% had diabetes. The mean differences (95% CI) in systolic blood pressure were 1.61 (0.07–3.15) and 2.46 (1.01–3.92) mm Hg when comparing the highest with the lowest quartile of urinary acrolein (N-acetyl-S-[2-carboxyethyl]-L-cysteine) and 1,3-butadiene (N-acetyl-S-[3,4-dihydroxybutyl]-L-cysteine) metabolites. The prevalence ratios for hypertension were 1.06 (95% CI, 1.02–1.09) and 1.05 (95% CI, 1.01–1.09) when comparing the highest with lowest quartiles of urinary acrolein (N-acetyl-S-[2-carboxyethyl]-L-cysteine) and 1,3-butadiene (N-acetyl-S-[3,4-dihydroxybutyl]-L-cysteine), respectively. CONCLUSIONS: Exposure to VOCs may be a relevant yet understudied environmental contributor to cardiovascular disease risk in the nonsmoking, US population.

Climate change intensifies the frequency and severity of extreme weather events, profoundly altering demographic landscapes globally and within the United States. This study investigates their impact on migration patterns, using propensity score matching and LASSO techniques within a larger regression modeling framework. Here, we analyze historical population trends in relation to climate risk and exposure metrics for various hazards. Our findings reveal nuanced patterns of climate-induced population change, including “risky growth” areas where economic opportunities mitigate climate risks, sustaining growth in the face of observed exposure; “tipping point” areas where the amenities are slowly giving way to the disamenity of escalating hazards; and “Climate abandonment” areas experiencing exacerbated out-migration from climate risks, compounded by other out-migration market factors. Even within a single county, these patterns vary significantly, underscoring the importance of localized analyses. Projecting population impacts due to climate risk to 2055, flood risks are projected to impact the largest percentage of areas (82.6%), followed by heatwaves (47.4%), drought (46.6%), wildfires (32.7%), wildfire smoke (21.7%), and tropical cyclone winds (11.1%). The results underscore the importance of understanding hyperlocal patterns of risk and change in order to better forecast future patterns.

Environmental epidemiologic studies using geospatial data often estimate exposure at a participant’s residence upon enrollment, but mobility during the exposure period can lead to misclassification. We aimed to mitigate this issue by constructing residential histories for participants in the California Teachers Study through follow-up (1995–2018). Address records have been collected from the US Postal Service, LexisNexis, Experian, and California Cancer Registry. We identified records of the same address based on geo-coordinate distance (≤250 m) and street name similarity. We consolidated addresses, prioritizing those confirmed by participants during follow-up questionnaires, and estimating the duration lived at each address using dates associated with records (e.g., date-first-seen). During 23 years of follow-up, about half of participants moved (48%, including 14% out-of-state). We observed greater mobility among younger women, Hispanic/Latino women, and those in metropolitan and lower socioeconomic status areas. The cumulative proportion of in-state movers remaining eligible for analysis was 21%, 32%, and 41% at 5, 10, and 20 years post enrollment, respectively. Using self-reported information collected 10 years after enrollment, we correctly identified 94% of movers and 95% of non-movers as having moved or not moved from their enrollment address. This dataset provides a foundation for estimating long-term environmental exposures in diverse epidemiologic studies in this cohort. Impact Our efforts in constructing residential histories for California Teachers Study participants through follow-up (1995–2018) benefit future environmental epidemiologic studies. Address availability during the exposure period can mitigate misclassification due to residential changes, especially when evaluating long-term exposures and chronic health outcomes. This can reduce differential misclassification among more mobile subgroups, including younger women and those from lower socioeconomic and urban areas. Our approach to consolidating addresses from multiple sources showed high accuracy in comparison to self-reported residential information. The residential dataset produced from this analysis provides a valuable tool for future studies, ultimately enhancing our understanding of environmental health impacts.