Background: While most epidemiological studies have assessed temperature–mortality associations at broad geographical scales, recent research highlights that temperature-related mortality risks are spatially heterogeneous due to local differences in exposure, vulnerability, and adaptive capacity. The aim of this study was to assess the impact of ambient air temperature on all-cause mortality at the district level in the Netherlands. Methods: A three-stage design was applied to assess the association between daily average air temperature and mortality across 3,116 districts and two age groups (0–74, 75+) for the period 2010–2019. First, a case time series design with distributed lag nonlinear models was used to estimate temperature–mortality associations for 355 Dutch municipalities. Second, municipality-level estimates were pooled using a multivariate meta-regression with municipality-level demographic, socioeconomic, climatological, and topographical predictors. Finally, the meta-regression model was used to downscale the risk estimates to the district level and to estimate standardized excess heat- and cold-related mortality rates. Results: Heat-related excess mortality was elevated in urban areas, whereas cold-related excess mortality was more pronounced in northern and southern districts compared with areas in the center of the Netherlands. During the study period, heat was associated with an average of 346 excess deaths per year (empirical 95% confidence intervals: 44–558), and cold with 11,988 excess deaths per year (7,554–15,609). This corresponds to standardized excess mortality rates of 2.2 (0.3–3.5) and 73.3 (46.8–94.7) per 100,000 person-years for heat and cold, respectively. The 75+ group showed more pronounced mortality risks compared with the younger age group. Conclusion: Our results indicate geographical heterogeneity in temperature-related standardized mortality rates, with high heat-related mortality in urban areas and more pronounced regional clustering of cold-related mortality. These findings can help local governments to implement climate adaptation measures to prevent heat- and cold-related excess mortality according to location-specific vulnerabilities.
Background: West Nile virus (WNV) and Lyme disease pose a growing public health threat in the United States. This study investigated spatial and temporal mortality trends of WNV and Lyme disease and evaluated associations with individual and county-level factors. Methods: We utilized National Center for Health Statistics data to identify WNV- and Lyme-related deaths (2003–2021), including demographics and the decedent’s county of residence. County-level insurance status was sourced from the U.S. Census Bureau, and urbanicity was defined using the 2013 National Center For Health Statistics classification. We applied negative binomial regression models to identify predictors of mortality. Results: Our analysis of 3694 deaths (WNV: 2,628 [71.2%]; Lyme: 1,066 [28.8%]) revealed WNV peaks occurred in 2003 (246 deaths, 9.4% of WNV deaths) and 2012 (281 deaths, 10.7%), and an increasing trend for Lyme (103 deaths, 9.7% in 2021). Overall, deaths were highest in 2012 (343, 9.3%) and lowest in 2009 (105, 2.6%). Age ≥65 (rate ratio [RR] = 1.5, confidence interval [CI] = 1.27, 1.48), male sex (RR = 1.2, CI = 1.04, 1.26), and White race (RR = 1.7, CI = 1.37, 1.73) were associated with increased mortality. Spatial analysis indicated high WNV mortality in California, Colorado, Arizona, and Texas, and states along the Mississippi River. In contrast, Lyme disease deaths were concentrated in the Northeast and the Upper Midwest. Conclusion: Our results suggest that age, sex, race, and urbanicity are important factors influencing mortality from WNV and Lyme disease. More research is needed to link exposures and incidence to mortality of WNV and Lyme to better understand the drivers of regional variation, given the spatial and temporal variability.
Background: Extreme heat has detrimental effects on male fertility. Previous studies conducted mainly in temperate countries have reported an association between higher ambient temperatures and decreased sperm quality. These findings might not be applicable to populations in tropical regions, who are chronically exposed to high ambient heat. Objectives: To address this knowledge gap, we measured the association between extreme heat during the spermatogenic life cycle and sperm quality in a population of 914 males who are 21–43 years old residing in a tropical country, Singapore. Methods: Medical records from 2011 to 2022 were analyzed alongside daily weather station records. Linear regression was used to estimate the association between the occurrence of days with maximum temperature >34.7°C during the 90-day spermatogenic life cycle and indicators of sperm quality. Sensitivity analyses were conducted for participants exposed to extreme heat multiple times during spermatogenesis. Results: Adjusting for age, race, body mass index, and days of abstinence before sample collection, exposure to extreme heat during the late stage of spermatogenesis (0–33 days before collection) was associated with lower sperm concentration (β = −9.3 million/mL, 95% confidence interval: –17, –1.8, P = 0.015). This amounted to a 20% reduction from the mean sperm concentration in the sample. Multiple (≥2) days of exposure to extreme heat in the late stage of spermatogenesis were associated with a larger reduction in sperm concentration (β = −12 million/mL, 95% confidence interval: −22, −2, P = 0.019). Conclusion: Even in tropical regions, with high ambient temperatures year-round, the occurrence of extremely hot days during the late stages of spermatogenesis is associated with lower sperm concentration. The degree of risk increases with more frequent exposures to extreme heat.
Background: Smoking combustible cigarettes accelerates biological aging and contributes to subsequent aging-related cardiovascular decline. However, the aging-related health consequences of electronic cigarette (e-cigarette) use (vaping) remain largely unknown. This study aims to investigate whether e-cigarette use is associated with biological aging acceleration using a nationally representative sample. Methods: This cross-sectional study included 8,595 participants aged 20–79 from two cycles (2015–2016 and 2017–2018) of the National Health and Nutrition Examination Survey. Biological aging was measured using PhenoAge, a validated epigenetic biomarker of aging. Its acceleration (PhenoAgeAccel) was quantified by the residual of PhenoAge regressed on chronological age. E-cigarette use was categorized as current (N = 417), former (N = 1,253), or nonuse (N = 6,925). Linear regression models were used to assess the association between e-cigarette use and PhenoAgeAccel, adjusting for combustible cigarette use, sex, race/ethnicity, education, body mass index, alcohol use, other tobacco product use, and secondhand smoke exposure. Results: In the fully adjusted model, current e-cigarette use was associated with 1.20 (95% confidence interval: 0.41, 2.10) years higher PhenoAgeAccel than never use. Similarly, individuals with current cigarette use exhibited 1.50 (95% confidence interval: 1.00, 2.00) years higher PhenoAgeAccel than those who had never smoked at least 100 cigarettes in their lifetime. Conclusions: This work provides the first epidemiologic evidence revealing the association between e-cigarette use and accelerated biological aging, after adjusting for smoking status. The findings underscore the potential value of public health interventions targeting reduced tobacco product use. Future longitudinal studies are needed to elucidate the underlying mechanisms.
Background: Environmental factors, particularly temperature-related exposures, are increasingly recognized as important determinants of tuberculosis (TB) disease progression and symptom manifestation. However, the evidence regarding the associations of heat exposure, cold exposure, and diurnal temperature range (DTR) with newly diagnosed TB remains limited and inconsistent. Methods: Data from Anhui Province between 1 January 2015 and 31 December 2024 were analyzed using a two-stage analytical framework based on a time-stratified case-crossover study design. City-specific associations between temperature and TB were pooled using a random-effects meta-analysis. Effect estimates were presented as relative risks (RRs) with corresponding confidence intervals (CIs). Results: A total of 243,577 newly diagnosed TB cases were reported during the study period. Compared with the median daily mean temperature, extreme heat exposure (95th percentile of daily mean temperature) was positively associated with newly diagnosed TB (RR = 1.218, 95% CI = 1.171, 1.267). In contrast, extreme cold exposure (fifth percentile of daily mean temperature) was negatively associated with newly diagnosed TB (RR = 0.837, 95% CI = 0.784, 0.893). Additionally, a greater DTR (95th percentile) was positively associated with newly diagnosed TB compared with the median DTR (RR = 1.320, 95% CI = 1.153, 1.512). These associations remained robust across multiple sensitivity analyses. Conclusion: Environmental temperature conditions are significantly associated with TB diagnosis. These findings suggest that temperature variability may influence the timing of TB diagnosis and highlight the importance of incorporating meteorological information into climate-sensitive TB surveillance and public health preparedness.
