Environmental Epidemiology最新文献

Introduction: Growing evidence exists that greenspace exposure can reduce metabolic syndrome risk, a growing public health concern with well-documented inequities across population subgroups. We capitalize on the use of g-computation to simulate the influence of multiple possible interventions on residential greenspace on nine metabolic biomarkers and metabolic syndrome in adults (N = 555) from the 2014-2017 Community of Mine Study living in San Diego County, California.

Methods: Normalized difference vegetation index (NDVI) exposure from 2017 was averaged across a 400-m buffer around the participants' residential addresses. Participants' fasting plasma glucose, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, systolic and diastolic blood pressure, hemoglobin A1c (%), waist circumference, and metabolic syndrome were assessed as outcomes of interest. Using parametric g-computation, we calculated risk differences for participants being exposed to each decile of the participant NDVI distribution compared to minimum NDVI. Differential health impacts from NDVI exposure by sex, ethnicity, income, and age were examined.

Results: We found that a hypothetical increase in NDVI exposure led to a decrease in hemoglobin A1c (%), glucose, and high-density lipoprotein cholesterol concentrations, an increase in fasting total cholesterol, low-density lipoprotein cholesterol, and triglyceride concentrations, and minimal changes to systolic and diastolic blood pressure, waist circumference, and metabolic syndrome. The impact of NDVI changes was greater in women, Hispanic individuals, and those under 65 years old.

Conclusions: G-computation helps to simulate the potential health benefits of differential NDVI exposure and identifies which subpopulations can benefit most from targeted interventions aimed at minimizing health disparities.

Background: Sudden cardiac death (SCD) is a major source of mortality and is the first manifestation of heart disease for most cases. Thus, there is a definite need to identify risk factors for SCD that can be modified on the population level. Short-term exposures to temperature have been implicated as a potential risk factor. Our objective was to determine if short-term temperature exposures were associated with increased risk of SCD in a US-based time-stratified case-crossover study.

Methods: A total of 465 cases of SCD were identified among participants of the prospective Nurses' Health Study (NHS). Control days were selected from all other matching days of the week within the same month as the case day. Average ambient temperature on the current day (Lag₀) and preceding 27 days (Lags_1-27) was determined at the residence level using 800-m resolution estimates. Conditional logistic distributed lag nonlinear models (DLNMs) were used to assess the relative risk (RR) of the full range of temperature exposures over the lag period.

Results: Warmer exposures in the days before event and colder temperatures 21-28 days prior were associated with increased risks of SCD. These results were driven by associations in regions other than the Northeast and among married women.

Conclusions: Both warm and cold ambient temperatures are suggestively associated with risks of SCD among middle-aged and older women living across the United States.

Background: Increased incidence of cancer has been reported among World Trade Center (WTC)-exposed persons. Aberrant DNA methylation is a hallmark of cancer development. To date, only a few small studies have investigated the relationship between WTC exposure and DNA methylation. The main objective of this study was to assess the DNA methylation profiles of WTC-exposed community members who remained cancer free and those who developed breast cancer.

Methods: WTC-exposed women were selected from the WTC Environmental Health Center clinic, with peripheral blood collected during routine clinical monitoring visits. The reference group was selected from the NYU Women's Health Study, a prospective cohort study with blood samples collected before 9 November 2001. The Infinium MethylationEPIC array was used for global DNA methylation profiling, with adjustments for cell type composition and other confounders. Annotated probes were used for biological pathway and network analysis.

Results: A total of 64 WTC-exposed (32 cancer free and 32 with breast cancer) and 32 WTC-unexposed (16 cancer free and 16 with prediagnostic breast cancer) participants were included. Hypermethylated cytosine-phosphate-guanine probe sites (defined as β > 0.8) were more common among WTC-exposed versus unexposed participants (14.3% vs. 4.5%, respectively, among the top 5000 cytosine-phosphate-guanine sites). Cancer-related pathways (e.g., human papillomavirus infection, cGMP-PKG) were overrepresented in WTC-exposed groups (breast cancer patients and cancer-free subjects). Compared to the unexposed breast cancer patients, 47 epigenetically dysregulated genes were identified among WTC-exposed breast cancers. These genes formed a network, including Wnt/β-catenin signaling genes WNT4 and TCF7L2, and dysregulation of these genes contributes to cancer immune evasion.

Conclusion: WTC exposure likely impacts DNA methylation and may predispose exposed individuals toward cancer development, possibly through an immune-mediated mechanism.

Background: Exposure to ambient PM_2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM_2.5 and distinct lipid profiles, is sparse.

Methods: Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM_2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders.

Results: The mean annual exposure in Chennai and Delhi was 40 and 102 μg/m³ respectively. Elevated ambient PM_2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m³ in both cities and beyond 125 µg/m³ in Delhi. TRIG levels in Chennai increased until 40 µg/m³ for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m³ in Delhi.

Conclusion: These findings demonstrate diverse associations between a wide range of ambient PM_2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

Background: Previous studies have indicated that renal disease mortality is sensitive to ambient temperatures. However, most have been limited to the summer season with inconclusive evidence for changes in population vulnerability over time.

Objective: This study aims to examine the association between short-term exposure to ambient temperatures and mortality due to renal diseases in Japan, and how this association varied over time.

Methods: We conducted a two-stage, time-stratified case-crossover study from 1979 to 2019 across 47 prefectures of Japan. We obtained the data of daily mortality counts for all renal diseases, acute renal failure, and chronic renal disease. We fitted a conditional quasi-Poisson regression model with a distributed lag nonlinear model. A random-effects meta-analysis was applied to calculate national averages. We performed additional analyses by four subperiods, sex, and age groups.

Results: We analyzed 997,590 renal mortality cases and observed a reversed J-shaped association. Lower temperatures were associated with increased mortality in all renal disease categories. The cumulative relative risks at 2.5th percentile compared to the minimum mortality temperature percentile were 1.34 (95% confidence interval [CI] = 1.29, 1.40), 1.51 (95% CI = 1.33, 1.71), and 1.33 (95% CI = 1.24, 1.43) for all renal, acute renal failure, and chronic renal disease mortality, respectively. The associations were observed in individuals of both sexes and aged 65 years and above. The associations of kidney mortality with low temperature remained consistent, while the associations with high temperature were pronounced in the past, but not in recent periods.

Conclusions: Protection for individuals with impaired renal function from exposure to low temperatures during cold seasons is warranted.

[This corrects the article DOI: 10.1097/EE9.0000000000000269.].