Combined impact of dynamic air pollution and transportation noise on cardiometabolic disorders in San Diego County.

Air pollution and noise exposure may synergistically contribute to increased cardiometabolic disorders; however, few studies have examined this potential interaction nor considered exposures beyond residential location. This study investigates the combined impact of dynamic air pollution and transportation noise on cardiometabolic disorders in San Diego County. Using the Community of Mine Study (2014-2017), 602 ethnically diverse participants were assessed for obesity, dyslipidemia, hypertension, and metabolic syndrome (MetS) using anthropometric measurements and biomarkers from blood samples. Time-weighted measures of exposure to PM2.5, NO2, road and aircraft noise were calculated using global positioning system (GPS) mobility data and Kernel Density Estimation. Generalized estimating equation models were used to analyze associations. Interactions were assessed on the multiplicative and additive scales using relative excess risk due to interaction (RERI). We found that air pollution and noise interact to affect metabolic disorders on both multiplicative and additive scales. The effect of noise on obesity and MetS was higher when air pollution was higher. The RERI of aircraft noise and NO2 on obesity and MetS were 0.13 (95%CI 0.03, 0.22) and 0.13 (95%CI 0.02, 0.25), respectively. This finding suggests that aircraft noise and air pollution may have synergistic effects on obesity and MetS.

Exploring the impact of environmental exposure changes on metabolic biomarkers: A 6-month GPS-GIS study among women with overweight or obesity.

BACKGROUND: Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements. METHODS: Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time. RESULTS: Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (ß -0.010, 95%CI -0.025, 0.005; ß -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (ß -1.001, 95%CI -1.888, -0.131). CONCLUSIONS: The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.

The role of cardiovascular health and vascular events in the relationship between excessive daytime sleepiness and dementia risk.

Many studies suggest a relationship between excessive daytime sleepiness (EDS) and dementia incidence, but the underlying mechanisms remain uncertain. The study aimed to investigate the role of cardiovascular burden in the relationship between EDS and dementia incidence over a 12-year follow-up in community-dwelling older adults. We performed analyses on 6171 subjects (aged ≥65 years) free of dementia and vascular disease at baseline. Participants self-reported EDS at baseline and an expert committee validated both prevalent and incident dementia. We defined cardiovascular burden by a low Cardiovascular Health score, constructed using the American Heart Association metrics, and incident vascular events. To explore the potential role of the cardiovascular burden in the relationship between EDS and dementia, we conducted mediation analyses with inverse odds ratio-weighted estimation, using multivariable-adjusted proportional hazard Cox and logistic regression models. Subjects with EDS had a higher risk of all-cause dementia (hazard ratio [HR] 1.39, 95% confidence interval [CI] 1.13-1.69) and dementia with vascular component (DVC) (HR 2.14, 95% CI 1.30-3.51), but not Alzheimer's disease (HR 1.18, 95% CI 0.93-1.51). Cardiovascular burden explained 5% (95% CI 4.1-5.2) and 11% (95% CI 9.7-11.3) of the relationship between EDS and all-cause dementia and DVC, respectively. These findings confirm that EDS may be implicated in the development of dementia and indicate a weaker than expected role of cardiovascular burden in the relationship between EDS and DVC.

Associations between environmental noise and myocardial infarction and stroke: Investigating the potential mediating effects of hypertension.

BACKGROUND: We investigated whether hypertension may be a mediator in the pathway linking environmental noise exposure to incident MI and stroke. METHODS: Separately for MI and stroke, we built two population-based cohorts from linked health administrative data. Participants were residents of Montreal (Canada) between 2000 and 2014, aged 45 years and older who were free of hypertension and MI or stroke at time of entry. MI, stroke and hypertension were ascertained from validated case definitions. Residential long-term environmental noise exposure, expressed as the annual mean level acoustic equivalent 24 h (LAeq24h), was estimated from a land use regression model. We performed mediation analysis based on the potential outcomes framework. We used a Cox proportional hazards model for the exposure-outcome model and a logistic regression for the exposure-mediator model. In sensitivity analysis we applied a marginal structural approach to estimate the natural direct and indirect effects. RESULTS: Each cohort included approximately 900 000 individuals, with 26 647 incident cases of MI and 16 656 incident cases of stroke. 36% of incident MI and 40% of incident stokes had previously developed hypertension. The estimated total effect per interquartile range increase (from 55.0 to 60.5 dB A) in the annual mean LAeq24h was 1.073 (95% confidence interval (CI): 1.070-1.077) for both MI for stroke. We found no evidence of exposure-mediator interaction for both outcomes. The relationships between environmental noise and MI and stroke was not mediated by hypertension. CONCLUSIONS: This population-based cohort study suggests that the main route by which environmental noise exposure may cause MI or stroke is not through hypertension.

Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics.

INTRODUCTION: Exposure to air pollution disproportionately affects racial/ethnic minorities that could contribute to health inequalities including metabolic disorders. However, most existing studies used a static assessment of air pollution exposure (mostly using the residential address) and do not account for activity space when modelling exposure to air pollution. The aim of this study is to understand how exposure to air pollution impacts metabolic disorders biomarkers, how this effect differs according to ethnicity, and for the first time compare these findings with two methods of exposure assessment: dynamic and static measures. METHODS: Among the Community of Mine study, a cross-sectional study conducted in San Diego County, insulin resistance, diabetes, hypertension, obesity, dyslipidemia, and metabolic syndrome (MetS) were assessed. Exposure to air pollution (PM2.5, NO2, traffic) was calculated using static measures around the home, and dynamic measures of mobility derived from Global Positioning Systems (GPS) traces using kernel density estimators to account for exposure variability across space and time. Associations of air pollution with metabolic disorders were quantified using generalized estimating equation models to account for the clustered nature of the data. RESULTS: Among 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM2.5 using dynamic measures. For all participants, higher dynamic exposure to PM2.5 and NO2 was associated with increased insulin resistance and cholesterol levels, and increased risk of obesity, dyslipidemia and MetS (RR 1.17, 95% CI: 1.07-1.28; RR 1.21, 95% CI: 1.12-1.30, respectively). The association between dynamic PM2.5 exposure and MetS differed by Hispanic/Latino ethnicity. CONCLUSION: These results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.

Air quality improvement and incident dementia: Effects of observed and hypothetical reductions in air pollutant using parametric g-computation.

INTRODUCTION: No evidence exists about the impact of air pollution reduction on incidence of dementia. The aim of this study was to quantify how air quality improvement leads to dementia-incidence benefits. METHODS: In the French Three-City cohort (12 years of follow-up), we used parametric g-computation to quantify the expected number of prevented dementia cases under different hypothetical interventions with particulate matter measuring <2.5 µm (PM2.5 ) reductions. RESULTS: Among 7051 participants, 789 participants developed dementia. The median PM2.5 reduction between 1990 and 2000 was 12.2 (µg/m3 ). Such a reduction reduced the risk of all-cause dementia (hazard ratio [HR], 0.85; 95% confidence interval [CI], 0.76 to 0.95). If all study participants were enjoying a hypothetical reduction of more than 13.10 µg/m3 (median reduction observed in the city of Montpellier), the rate difference was -0.37 (95% CI, -0.57 to -0.17) and the rate ratio was 0.67 (95% CI, 0.50 to 0.84). DISCUSSION: These findings highlight the possible substantial benefits of reducing air pollution in the prevention of dementia.

Socioeconomic inequalities in dementia risk among a French population-based cohort: quantifying the role of cardiovascular health and vascular events.

This study aimed to investigate the role of cardiovascular health (CVH) and vascular events as potential contributors to socioeconomic inequalities in dementia using causal mediation analyses. We used data from the Three-City Cohort, a French population-based study with 12 years of follow-up, with active search of dementia cases and validated diagnosis. Individual socioeconomic status was assessed using education, occupation and income. A CVH score as defined by the American Heart Association and incident vascular events were considered separately as mediators. We performed multi-level Cox proportional and Aalen additive hazard regression models to estimate the total effects of socioeconomic status on dementia risk. To estimate natural direct and indirect effects through CVH and vascular events, we applied two distinct weighting methods to quantify the role of CVH and vascular events: Inverse Odds Ratio Weighting (IORW) and Marginal Structural Models (MSM) respectively. Among 5581 participants, the risk of dementia was higher among participants with primary education (HR 1.60, 95%CI 1.44-1.78), blue-collar workers (HR 1.62, 95%CI 1.43-1.84) and with lower income (HR 1.23, 95%CI 1.09-1.29). Using additive models, 571 (95% CI 288-782) and 634 (95% CI 246-1020) additional cases of dementia per 100 000 person and year were estimated for primary education and blue-collar occupation, respectively. Using IORW, the CVH score mediate the relationship between education or income, and dementia (proportion mediated 17% and 26%, respectively). Yet, considering vascular events as mediator, MSM generated indirect effects that were smaller and more imprecise. Socioeconomic inequalities in dementia risk were observed but marginally explained by CVH or vascular events mediators.

Association between occupational solvent exposure and cognitive performance in the French CONSTANCES study.

OBJECTIVE: The objective of this study was to evaluate the association between occupational exposure to solvents and cognitive performance in middle-aged and early-ageing participants, taking into account the working environment. METHODS: In the French Cohorte des consultants des Centres d'examens de santé (CONSTANCES) cohort, 41 854 participants aged 45-69 years completed a self-reported, lifetime occupational exposure questionnaire. Exposure to solvents (gasoline for hand washing, trichloroethylene, white spirit, cellulosic thinner) was first considered as a binary variable (exposed/not exposed). We computed number of solvent types to which participants were exposed, solvent exposure time and delay since last exposure. Cognitive performance was assessed and analysed in reference to norms of neuropsychological battery previously established in CONSTANCES according to age, sex and education. Multiple linear and modified Poisson regression were used to estimate the associations between solvent exposure and cognitive performance adjusting for individual and environmental characteristics, and working conditions (night shift, repetitive and noisy work). RESULTS: Men had a greater risk of global cognitive impairment when they were exposed to gasoline (relative risk (RR)=1.12, 95% CI 1.03 to 1.22), white spirit (RR=1.14, 95% CI 1.05 to 1.25) or cellulosic thinner (RR=1.17, 95% CI 1.06 to 1.31) at the workplace, even after adjusting for confounders. Women exposed to white spirit or exposed for more than 20 years had poorer global cognitive performance. CONCLUSION: These findings strengthen our understanding of the detrimental effect of solvent exposure on cognitive health not only in men but also in women for the first time, in a large general population middle-aged and early-ageing sample from France, taking into account working conditions.

Influence of activity space on the association between neighborhood characteristics and dementia risk: results from the 3-City study cohort.

BACKGROUND: Socioeconomic level of residential environment was found to influence cognitive performance. However, individuals from the same place of residence may be affected differently. We aim to investigate for the first time the influence of individual activity space on the association between neighborhood socioeconomic status (NSES) and the risk of dementia. METHODS: In the frame of the Three-City cohort, a French population-based study, we followed longitudinally (12 years) 7009 participants aged over 65. The activity space (i.e., the spatial area through which a person moves daily) was defined using two questions from Lawton's Instrumental Activities of Daily Living scale ("Goes shopping independently","Travels alone"), and one question about mobility restriction. The survival analysis was performed using a Cox marginal model that takes into account intra-neighborhood correlations and includes a large number of potential confounders. RESULTS: Among people with a limited activity space (n = 772, 11%), risk of dementia is increased in subjects living in a deprived area (characterized by high GINI index or low median income) compared to those living in more favored. CONCLUSION: This study shows that the individual activity space modifies the association between NSES and the risk of dementia providing a more complete picture of residential inequalities. If confirmed in different populations, these findings suggest that people with limited activity space and living in a deprived neighborhood are particularly at risk and should be targeted for prevention.

Sex-specific association between neighborhood characteristics and dementia: The Three-City cohort.

INTRODUCTION: The living environment affects general health and may influence cognitive aging; however, the relationships between neighborhood characteristics and dementia are still poorly understood. METHODS: We used data from a French population-based prospective study (the Three-City cohort) that included 7016 participants aged 65 years and older with a 12-year follow-up. We used principal components analysis of neighborhood composition indicators to construct the Three-City deprivation score. To study its impact on dementia incidence, we performed survival analyses using a marginal Cox model to take into account intraneighborhood correlations. As interaction with sex was significant, analyses were stratified by sex. RESULTS: Even after controlling on individual factors, women living in deprived neighborhoods were at higher risk of dementia (hazard ratio = 1.29, 95% confidence interval 1.00-1.67) and Alzheimer's disease (hazard ratio = 1.42, 95% confidence interval 1.09-1.84). No association was found for men. DISCUSSION: Living in a deprived neighborhood is associated with higher risk of dementia in women.

Effect of different heat wave timing on cardiovascular and respiratory mortality in France.

BACKGROUND: Previous epidemiological evidence suggests that the impact of heat waves on mortality may change over time within the summer season. The consideration of heat wave timing could help to optimize the implementation of heat alert systems. We explored the effect of the timing of extreme heat events on mortality risk during the summer season in France. METHODS: Summertime daily mortality data for 21 French cities from 2000 to 2015 were obtained from the French National Institute of Health and Medical Research. Heat waves were defined according to the official definition of Météo France. The order of heat wave over time, from June to August, was assessed. We also used ambient temperature and considered different summer periods. To quantify mortality risk (for cardiovascular and respiratory causes) for the first and second or later heat waves, quasi-Poisson models were performed. We used distributed lag non-linear models to estimate whether the non-linear exposure-response associations between temperature and mortality differ across different summer periods. RESULTS: Compared with non-heat wave days, the second and later heat waves of the summer season were associated with a higher relative risk (RR) for cardiovascular and respiratory mortality (RR, 95%CI: 1.38, 1.23-1.53; RR, 95%CI: 1.74, 1.45-2.08, respectively) as compared to first heat wave (RR, 95%CI: 1.30, 1.17-1.45, RR, 95%CI: 1.56, 1.33-1.83, respectively). Small increase from the median temperature was associated to an increased risk in mortality in the first stage of the summer (from June to mid-July), while only more extreme temperatures were harmful later in the summer. After the exclusion from the analysis of the August 2003 heat-wave, only results for earlier heat waves episodes and first-period exposures were confirmed. CONCLUSIONS: The timing of extreme temperatures modulates heat-related risks in France. Such information could be used to update local heat action plans to optimize health benefits.

The Burden of Wildfire Smoke on Respiratory Health in California at the Zip Code Level: Uncovering the Disproportionate Impacts of Differential Fine Particle Composition.

Wildfires constitute a growing source of extremely high levels of particulate matter that is less than 2.5 microns in diameter (PM2.5). Recently, toxicologic and epidemiologic studies have shown that PM2.5 generated from wildfires may have a greater health burden than PM2.5 generated from other pollutant sources. This study examined the impact of PM2.5 on hospitalizations for respiratory diseases in California between 2006 and 2019 using a health impact assessment approach that considers differential concentration-response functions (CRF) for PM2.5 from wildfire and non-wildfire sources of emissions. We quantified the burden of respiratory hospitalizations related to PM2.5 exposure at the zip code level through two different approaches: (a) naïve (considering the same CRF for all PM2.5 emissions) and (b) nuanced (considering different CRFs for PM2.5 from wildfires and from other sources). We conducted a Geographically Weighted Regression to analyze spatially varying relationships between the delta (i.e., the difference between the naïve and nuanced approaches) and the Centers for Disease Control and Prevention's Social Vulnerability Index (SVI). A higher attributable number of respiratory hospitalizations was found when accounting for the larger health burden of wildfire PM2.5. We found that, between 2006 and 2019, the number of hospitalizations attributable to PM2.5 may have been underestimated by approximately 13% as a result of not accounting for the higher CRF of wildfire-related PM2.5 throughout California. This underestimation was higher in northern California and areas with higher SVI rankings. The relationship between delta and SVI varied spatially across California. These findings can be useful for updating future air pollution guideline recommendations.

Aircraft and road traffic noise, insulin resistance, and diabetes: The role of neighborhood socioeconomic status in San Diego County.

Evidence linking traffic noise to insulin resistance and diabetes is limited and unanswered questions remain regarding the potential effect modification by neighborhood socioeconomic status (nSES). We aimed to assess socioeconomic inequalities in noise exposure, whether road and aircraft noise exposures were associated with insulin resistance or diabetes, and whether nSES modified these relationships. Among the Community of Mine Study in San Diego County, road and aircraft noise exposure at enrollment was calculated based on the static (participant's administrative boundary, and circular buffer around participant homes), and dynamic (mobility data by global positioning system, GPS) spatio-temporal aggregation methods. Associations of noise with insulin resistance (HOMA-IR) or type 2 diabetes (T2DM) were quantified using generalized estimating equation models adjusted for sex, age, ethnicity, individual income, and air pollution (nitrogen dioxide) exposure. Additive interaction between noise and nSES was assessed. Among 573 participants (mean age 58.7 y), participants living in low nSES were exposed to higher levels of aircraft and road noise using noise level at the census tract, circular buffer, or Kernel Density Estimation (KDE) of GPS data. Participants exposed to road noise greater or equal to the median (53 dB(A)) at the census tract and living in low nSES had an increased level of insulin resistance (ß = 0.15, 95%CI: -0.04, 0.34) and higher odds of T2DM (Odds Ratio = 2.34, 95%CI: 1.12, 4.90). A positive additive interaction was found as participants living in low nSES had higher odds of T2DM. The impact of noise exposure on insulin resistance and T2DM differs substantially by nSES. Public health benefits of reducing exposure to road or aircraft noise would be larger in individuals living in low nSES.

Objective sleep and cardiometabolic biomarkers: results from the community of mine study.

Study Objectives: Examining multiple dimensions of sleep health may better capture associations between sleep and health risks, including cardiometabolic disease (CMD). Hispanics have elevated risk for inadequate sleep and CMD biomarkers. Few studies have explored whether associations between sleep and CMD differ by Hispanic ethnicity. Methods: Leveraging data from the Community of Mine (CoM) study, a cross-sectional investigation of 602 ethnically diverse participants, we derived accelerometer-measured sleep duration and efficiency, and self-reported sleep quality. Accelerometer-measured sleep exposures were analyzed both as continuous and categorical variables. Multivariate and quantile regression models were used to assess associations between sleep and CMD biomarkers (insulin resistance, systolic blood pressure, and low-density-lipoprotein cholesterol), controlling for age, sex, ethnicity, education, smoking status, and body mass index. We examined the potential effect modification of Hispanic ethnicity. Results: We observed mixed results based on CMD biomarkers and sleep exposure. Increased sleep duration was significantly related to low-density lipoprotein cholesterol in adjusted models (estimate = 0.06; 95% CI: 0.02, 0.11). Poor sleep efficiency was associated with greater insulin resistance in the adjusted quantile (estimate = 0.20; 95% CI: 0.04, 0.36) model at the 90th percentile. Self-reported sleep quality was not associated with CMD outcomes. There was no evidence of effect modification by Hispanic ethnicity. Conclusions: In this cohort, sleep health measures were found to have mixed and at times opposing effects on CMD outcomes. These effects did not demonstrate an interaction with Hispanic ethnicity.

How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis.

Accumulating evidence links cardiometabolic health with social and environmental neighborhood exposures, which may contribute to health inequities. We examined whether environmental characteristics were individually or jointly associated with insulin resistance, hypertension, obesity, type 2 diabetes, and metabolic syndrome in San Diego County, CA. As part of the Community of Mine Study, cardiometabolic outcomes of insulin resistance, hypertension, BMI, diabetes, and metabolic syndrome were collected in 570 participants. Seven census tract level characteristics of participants' residential environment were assessed and grouped as follows: economic, education, health care access, neighborhood conditions, social environment, transportation, and clean environment. Generalized estimating equation models were performed, to take into account the clustered nature of the data and to estimate ß or relative risk (RR) and 95 % confidence intervals (CIs) between each of the seven environmental characteristics and cardiometabolic outcomes. Quantile g-computation was used to examine the association between the joint effect of a simultaneous increase in all environmental characteristics and cardiometabolic outcomes. Among 570 participants (mean age 58.8 ± 11 years), environmental economic, educational and health characteristics were individually associated with insulin resistance, diabetes, obesity, and metabolic syndrome. In the mixture analyses, a joint quartile increase in all environmental characteristics (i.e., improvement) was associated with decreasing insulin resistance (ß, 95 %CI: -0.09, -0.18-0.01)), risk of diabetes (RR, 95 %CI: 0.59, 0.36-0.98) and obesity (RR, 95 %CI: 0.81, 0.64-1.02). Environmental characteristics synergistically contribute to cardiometabolic health and independent analysis of these determinants may not fully capture the potential health impact of social and environmental determinants of health.

Association Between Occupational Exposure to Formaldehyde and Cognitive Impairment.

BACKGROUND AND OBJECTIVES: To our knowledge, no study has investigated the effect of exposure to formaldehyde on cognition in the general population. Our objective was to examine the association between occupational exposure to formaldehyde and cognitive impairment in middle-aged and young-old adults (≥45 years). METHODS: In the French CONSTANCES cohort, cognitive function was assessed with a standardized battery of 7 cognitive tests to evaluate global cognitive function, episodic verbal memory, language abilities, and executive functions (e.g., Digit Symbol Substitution Test [DSST]). A global cognitive score was created using principal component analysis. Cognitive impairment was assessed in reference to norms of neuropsychological battery according to age, sex, and education. Lifetime exposure to formaldehyde was assessed using a French Job Exposure Matrix created in the framework of the Matgéné project. After performing multiple imputation, separate modified Poisson regression models were used to evaluate the association between cognitive impairment (<25th percentile) and formaldehyde exposure (exposed/never exposed), exposure duration, cumulative exposure index (CEI), and combination of CEI and time of last exposure. RESULTS: Among 75,322 participants (median age 57.5 years, 53% women), 8% were exposed to formaldehyde during their professional life. These participants were at higher risk of global cognitive impairment (for global cognitive score: adjusted relative risk [aRR] 1.17; 95% confidence interval [CI] 1.11-1.23), after adjusting for confounders (age, sex, education, income, solvent exposure, Effort-Reward Imbalance, night shift, repetitive work, and noisy work). They were at higher risk of cognitive impairment for all cognitive domains explored. Longer exposure duration and high CEI were associated with cognitive impairment, with a dose-effect relationship for exposure duration. Recent exposure was associated with impairment in all cognitive domains. Time did not fully attenuate formaldehyde-associated cognitive deficits especially in highly exposed individuals (for DSST: high past exposure aRR 1.23; 95% CI 1.11-1.36; high recent exposure: aRR 1.24; 95% CI 1.13-1.35). DISCUSSION: Our findings highlight the long-term detrimental effect of formaldehyde exposure on cognitive health in a relatively young population.

The Role of Neighborhood Air Pollution Exposure on Somatic Non-Small Cell Lung Cancer Mutations in the Los Angeles Basin (2013-2018).

Limited previous work has identified a relationship between exposure to ambient air pollution and aggressive somatic lung tumor mutations. More work is needed to confirm this relationship, especially using spatially resolved air pollution. We aimed to quantify the association between different air pollution metrics and aggressive tumor biology. Among patients treated at City of Hope Comprehensive Cancer Center in Duarte, CA (2013-2018), three non-small cell lung cancer somatic tumor mutations, TP53, KRAS, and KRAS G12C/V, were documented. PM2.5 exposure was assessed using state-of-the art ensemble models five and ten years before lung cancer diagnosis. We also explored the role of NO2 using inverse-distance-weighting approaches. We fitted logistic regression models to estimate odds ratio (OR) and their 95% confidence intervals (CIs). Among 435 participants (median age: 67, female: 51%), an IQR increase in NO2 exposure (3.5 µg/m3) five years before cancer diagnosis was associated with an increased risk in TP53 mutation (OR, 95% CI: 1.30, 0.99-1.71). We found an association between highly-exposed participants to PM2.5 (>12 µg/m3) five and ten years before cancer diagnosis and TP53 mutation (OR, 95% CI: 1.61, 0.95-2.73; 1.57, 0.93-2.64, respectively). Future studies are needed to confirm this association and better understand how air pollution impacts somatic profiles and the molecular mechanisms through which they operate.

Outdoor air pollution exposure and cognitive performance: findings from the enrolment phase of the CONSTANCES cohort.

BACKGROUND: Air pollution exposure is one of the modifiable risk factors of cognitive decline. We aimed to test the association between exposure to several outdoor air pollutants and domain-specific cognitive performance. METHODS: In this cross-sectional study, we used data from the enrolment phase of the French CONSTANCES cohort. From the 220 000 people (aged 18-69 years) randomly recruited in the French CONSTANCES cohort, participants aged 45 years old or older (104 733 people) underwent a comprehensive cognitive assessment (verbal episodic memory, language skills, and executive functions). After exclusion of those who were not suitable for our analysis, 61 462 participants with available data were included in the analyses. We used annual mean concentrations at residential addresses, derived from land-use regression models, to assign exposure to particulate matter with aerodynamic diameters less than 2·5 µm (PM2·5), nitrogen dioxide (NO2), and black carbon. We used multiple linear regression models with different covariate adjustments to test the associations between each pollutant and cognitive outcomes. We did several sensitivity analyses, including multilevel modelling, meta-analysis by centre of recruitment, and exclusion of specific population groups. FINDINGS: We found significantly poorer cognitive function, especially on semantic fluency and domains of executive functions, with an increase in exposure to black carbon and NO2. Exposure to PM2·5 was mainly significant for the semantic fluency test. We found that decrease in cognitive performance with an increase of one interquartile range of exposure ranged from 1% to nearly 5%. The largest effect size (percentage decrease) for both PM2.5 and NO2 was found for the semantic fluency test (PM2.5 4·6%, 95% CI 2·1-6·9 and NO2 3·8%, 1·9-5·7), whereas for black carbon, the largest effect size was found for the digit symbol substitution test of the domains of executive functions (4·5%, 2·7-6·3). Monotonic and linear exposure-response associations were found between air pollution exposure and cognitive performance, starting from a low level of exposures. INTERPRETATION: Significantly poorer cognitive performance was associated with exposure to outdoor air pollution even at low levels of exposure. This highlights the importance of further efforts to reduce exposure to air pollution. FUNDING: The Caisse Nationale d'Assurance Maladie, and partly funded by Merck Sharp & Dohme and L'Oréal, the French National Research Agency, and Fondation de France. TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Long-term exposure to ambient air pollution and risk of dementia: Results of the prospective Three-City Study.

BACKGROUND: Emerging epidemiological evidence suggests a relationship between exposure to air pollution and dementia. However, most of the existing studies relied on health administrative databases for the diagnosis of dementia. In a large French population-based cohort (the 3C Study), we assessed the effects of particulate matter ≤2.5 µm (PM2.5), nitrogen dioxide (NO2) and black carbon (BC) on the risk of dementia diagnosed with reliable tools. METHODS: Participants aged ≥65 years were recruited between 1999 and 2001 and followed for 12 years. At baseline and every 2 years, dementia was suspected on the basis of the neuropsychological and neurological examination and confirmed by an independent committee of clinicians. Exposure to NO2, BC and PM2.5 at the participants' residential address was estimated using land use regression models. For each pollutant and year of follow-up, the 10-year moving average of past exposure was estimated. Multilevel spatial random-effects Cox proportional hazards models were used in which exposure was included as a time-varying variable. Analyses were adjusted for individual (age, sex, education, APOE4 genotype, health behaviours) and contextual (neighbourhood deprivation index) confounders. RESULTS: At baseline, the median age of the 7066 participants was 73.4 years, and 62% were women. The median follow-up duration was 10.0 years during which 791 participants developed dementia (n = 541 Alzheimer's disease (AD) and n = 155 vascular/mixed dementia (VaD)). The 10-year moving average of PM2.5 concentrations ranged from 14.6 to 31.3 µg/m3. PM2.5 concentration was positively associated with dementia risk: HR = 1.20, 95% CI (1.08-1.32) for all-cause dementia, 1.20 (1.09-1.32) for AD, and 1.33 (1.05-1.68) for VaD per 5 µg/m3 PM2.5 increase. No association was detected between NO2 or BC exposure and dementia risk. CONCLUSION: In this large cohort of older adults, long-term PM2.5 exposure was associated with increased dementia incidence. Reducing PM2.5 emissions might lessen the burden of dementia in aging populations.

Occupational Exposures to Organic Solvents and Asthma Symptoms in the CONSTANCES Cohort.

Solvents are used in many workplaces and may be airway irritants but few studies have examined their association with asthma. We studied this question in CONSTANCES (cohort of 'CONSulTANts des Centres d'Examens de Santé'), a large French cohort. Current asthma and asthma symptom scores were defined by participant-reported respiratory symptoms, asthma medication or attacks, and the sum of 5 symptoms, in the past 12 months, respectively. Lifetime exposures to 5 organic solvents, paints and inks were assessed by questionnaire and a population-based Job-Exposure Matrix (JEM). Cross-sectional associations between exposures and outcomes were evaluated by gender using logistic and negative binomial regressions adjusted for age, smoking habits and body mass index. Analyses included 115,757 adults (54% women, mean age 47 years, 9% current asthma). Self-reported exposure to ≥1 solvent was significantly associated with current asthma in men and women, whereas using the JEM, a significant association was observed only in women. Significant associations between exposures to ≥1 solvent and asthma symptom score were observed for both self-report (mean score ratio, 95%CI, women: 1.36, 1.31-1.42; men: 1.34, 1.30-1.40) and JEM (women: 1.10, 1.07-1.15; men: 1.14, 1.09-1.18). Exposure to specific solvents was significantly associated with higher asthma symptom score. Occupational exposure to solvents should be systematically sought when caring for asthma.