Associations between air pollution indicators and prevalent and incident diabetes in an African American cohort, the Jackson Heart Study

Associations of long-term exposure to air pollution and physical activity with the risk of systemic inflammation-induced multimorbidity in Chinese adults: results from the China multi-ethnic cohort study (CMEC)

OBJECTIVE

Previous studies proved the effect of long-term exposure to air pollution or physical activity (PA) on the risk of systemic inflammation-induced multimorbidity (SIIM), while the evidence regarding their joint effects was rare, especially in low- and middle-income countries. Therefore, we aimed to examine the extent of interaction or joint relations of PA and air pollution with SIIM.

METHODS

This study included 72,172 participants from China Multi-Ethnic Cohort.The average concentrations of ambient particulate matter pollutants (PM1, PM2.5, and PM10) were estimated using satellite-based random forest models. Self-reported information on a range of physical activities related to occupation, housework, commuting, and leisure activities was collected by an interviewer-administered questionnaire. A total of 11 chronic inflammatory systemic diseases were assessed based on self-reported lifetime diagnosis or medical examinations. SIIM was defined as having ≥ 2 chronic diseases related to systemic inflammation. Logistic regression models were used to assess the complex associations of air pollution particulate matter and PA with SIIM.

RESULTS

We found positive associations between long-term air pollution particulates exposure and SIIM, with odds ratios (95%CI) of 1.07 (1.03 to 1.11), 1.18 (1.13 to 1.24), and 1.08 (1.05 to 1.12) per 10 µg/m3 increase in PM1, PM2.5, and PM10. No significant multiplicative interaction was found between ambient air pollutant exposure and PA on SIIM, whereas negative additive interaction was observed between long-term exposure to PM2.5 and PA on SIIM. The positive associations between low volume PA and SIIM were stronger among those exposed to high-level air pollution particulates. Compared with individuals engaged in high volume PA and exposed to low-level ambient air pollutants, those engaged in low volume PA and exposed to high-level ambient air pollutants had a higher risk of SIIM (OR = 1.49 in PM1 exposure, OR = 1.84 in PM2.5 exposure, OR = 1.19 in PM10 exposure).

CONCLUSIONS

Long-term (3 years average) exposure to PM1, PM2.5, and PM10 was associated with an increased risk of SIIM. The associations were modified by PA, highlighting PA's importance in reducing SIIM for all people, especially those living in high-level air pollution regions.

Effects of Prolonged Exposure to Air Pollution and Neighborhood Disadvantage on Self-Rated Health among Adults in the United States: Evidence from the Panel Study of Income Dynamics

BACKGROUND

Although overall air quality has improved in the United States, air pollution remains unevenly distributed across neighborhoods, producing disproportionate environmental burdens for minoritized and socioeconomically disadvantaged residents for whom greater exposure to other structurally rooted neighborhood stressors is also more frequent. These interrelated dynamics and layered vulnerabilities each have well-documented associations with physical and psychological health outcomes; however, much remains unknown about the joint effects of environmental hazards and neighborhood socioeconomic factors on self-reported health status.

OBJECTIVES

We examined the nexus of air pollution exposure, neighborhood socioeconomic disadvantage, and self-rated health (SRH) among adults in the United States.

METHODS

This observational study used individual-level data from the Panel Study of Income Dynamics merged with contextual information, including neighborhood socioeconomic and air pollution data at the census tract and census block levels, spanning the period of 1999-2015. We estimated ordinary least squares regression models predicting SRH by 10-y average exposures to fine particulate matter [particles ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 )] and neighborhood socioeconomic disadvantage while controlling for individual-level correlates of health. We also investigated the interaction effects of air pollution and neighborhood socioeconomic disadvantage on SRH.

RESULTS

On average, respondents in our sample rated their health as 3.41 on a scale of 1 to 5. Respondents in neighborhoods with higher 10-y average PM 2.5 concentrations or socioeconomic disadvantage rated their health more negatively after controlling for covariates [β = - 0.024 (95% CI: - 0.034 , - 0.014 ); β = - 0.107 (95% CI: - 0.163 , - 0.052 ), respectively]. We also found that the deleterious associations of PM 2.5 exposure with SRH were weaker in the context of greater neighborhood socioeconomic disadvantage (β = 0.007 ; 95% CI: 0.002, 0.011).

DISCUSSION

Study results indicate that the effects of air pollution on SRH may be less salient in socioeconomically disadvantaged neighborhoods compared with more advantaged areas, perhaps owing to the presence of other more proximate structurally rooted health risks and vulnerabilities in disinvested areas (e.g., lack of economic resources, health access, healthy food options). This intersection may further underscore the importance of meaningful involvement and political power building among community stakeholders on issues concerning the nexus of environmental and socioeconomic justice, particularly in structurally marginalized communities. https://doi.org/10.1289/EHP11268.

Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 μg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 μg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Assessment of Disparities in Diabetes Mortality in Adults in US Rural vs Nonrural Counties, 1999-2018

IMPORTANCE

US rural vs nonrural populations have striking disparities in diabetes care. Whether rurality contributes to disparities in diabetes mortality is unknown.

OBJECTIVE

To examine rates and trends in diabetes mortality based on county urbanization.

DESIGN, SETTING, AND PARTICIPANTS

In this observational, cross-sectional study, the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database was searched from January 1, 1999, to December 31, 2018, for diabetes as a multiple cause and the underlying cause of death among residents aged 25 years or older in US counties. County urbanization was categorized as metro, medium-small, and rural. Weighted multiple linear regression models and jackknife resampling, with a 3-segment time component, were used. The models included exposures with up to 3-way interactions and were age standardized to the 2009-2010 population. The analyses were conducted from July 1, 2020, to February 1, 2022.

EXPOSURES

County urbanization (metro, medium-small, or rural), gender (men or women), age group (25-54, 55-74, or ≥75 years), and region (Midwest, Northeast, South, or West).

MAIN OUTCOMES AND MEASURES

Annual diabetes mortality rate per 100 000 people.

RESULTS

From 1999-2018, based on 4 022 238 309 person-years, diabetes was a multiple cause of death for 4 735 849 adults aged 25 years or older. As a multiple cause, diabetes mortality rates in 2017-2018 vs 1999-2000 were highest and unchanged in rural counties (157.2 [95% CI, 150.7-163.7] vs 154.1 [95% CI, 148.2-160.1]; P = .49) but lower in medium-small counties (123.6 [95% CI, 119.6-127.6] vs 133.6 [95% CI, 128.4-138.8]; P = .003) and urban counties (92.9 [95% CI, 90.5-95.3] vs 109.7 [95% CI, 105.2-114.1]; P < .001). In 2017-2018 vs 1999-2000, mortality rates were higher in rural men (+18.2; 95% CI, 14.3-22.1) but lower in rural women (-14.0; 95% CI, -17.7 to -10.3) (P < .001 for both). In the 25- to 54-year age group, mortality rates in 2017-2018 vs 1999-2000 showed a greater increase in rural counties (+9.4; 95% CI, 8.6-10.2) compared with medium-small counties (+4.5; 95% CI, 4.0-5.0) and metro counties (+0.9; 95% CI, 0.4-1.4) (P < .001 for all). Of all regions and urbanization levels, the mortality rate in 2017-2018 vs 1999-2000 was higher only in the rural South (+13.8; 95% CI, 7.6-20.0; P < .001).

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, US rural counties had the highest overall diabetes mortality rate. The determinants of persistent rural disparities, in particular for rural men and for adults in the rural South, require investigation.