Air pollution exposure and mammographic breast density in Tehran, Iran: a cross-sectional study

Ambient Air Pollution and Incident Cardiovascular Disease in People With Type 2 Diabetes Mellitus: A Cohort Study

OBJECTIVES

We aimed to assess the effect of air pollution on incident cardiovascular disease (CVD) in people with type 2 diabetes mellitus (T2DM).

METHODS

We tracked 486 T2DM patients from 2012 to 2021. Cox regression models were applied to assess the hazard of exposure to particulate matter, carbon monoxide (CO), ozone, nitrogen dioxide, and sulfur dioxide (SO 2 ) on incident CVD, revealing hazard ratios (HRs).

RESULTS

CVD incidents occurred in 73 individuals. Among men, each 1-ppm increase in CO levels raised the risk of CVD (HR: 2.66, 95% CI: 1.30-5.44). For women, a 5-ppb rise in SO 2 increased CVD risk (HR: 1.60, 95% CI: 1.11-2.30). No notable impact of particulate pollutants was found.

CONCLUSIONS

Persistent exposure to gaseous air pollutants, specifically CO and SO 2 , is linked to the development of CVD in men and women with T2DM.

Factors Associated with Abnormal Mammogram Results Among Low-Income Uninsured Populations in Medically Underserved And Rural Texas Regions

Background

This study investigated the potential associations between neighborhood characteristics, rurality, ethnicity/race, and breast cancer screening outcomes in designated Health Professional Shortage Areas in Central Texas. Limited access to preventive medical care can impact screening rates and outcomes. Previous research on the effects of factors such as rurality, neighborhood socioeconomic status, and education level on cancer prevention behaviors has yielded inconsistent results.

Materials and Methods

We analyzed data from a state-funded breast and cervical cancer screening programs for disadvantaged and medically underserved individuals. A mixed-effects logistic regression model was used to assess the impact of residency characteristics (rurality, educational attainment, unemployment, and poverty) on abnormal breast cancer screening outcomes, with individual level (age, ethnicity, race, and education) as control variables.

Results

During the studied time, there were 1,139 women screened and 134 abnormal mammograms found. Residency characteristics were not significantly associated with abnormal mammography outcomes at 0.05. However, individual factors are strongly associated with abnormal screening results. Non-Hispanic or Latino white women had increased odds of abnormal clinical outcomes compared with Hispanic or Latino women (OR = 2.03, CI 1.25-3.28; p = 0.004). Additionally, women residing in counties with more than 30% of the population completing college had increased odds of abnormal mammogram outcomes compared with counties with less than 15% college attainment (OR = 2.89, CI 0.99-8.38; p = 0.051).

Conclusions

This study found a significant correlation between area-level educational characteristics and abnormal mammography outcomes. Future research should explore the contextual risk factors influencing breast cancer occurrence and develop targeted interventions for this population.

Associations between Changes in Exposure to Air Pollutants due to Relocation and the Incidence of 14 Major Disease Categories and All-Cause Mortality: A Natural Experiment Study

BACKGROUND

Though observational studies have widely linked air pollution exposure to various chronic diseases, evidence comparing different exposures in the same people is limited. This study examined associations between changes in air pollution exposure due to relocation and the incidence and mortality of 14 major diseases.

METHODS

We included 50,522 participants enrolled in the UK Biobank from 2006 to 2010. Exposures to particulate matter with a diameter ≤ 2.5 μ m (PM 2.5 ), particulate matter with a diameter ≤ 10 μ m (PM 10 ), nitrogen oxides (NO x ), nitrogen dioxide (NO 2 ), and sulfur dioxide (SO 2 ) were estimated for each participant based on their residential address and relocation experience during the follow-up. Nine exposure groups were classified based on changes in long-term exposures due to residential mobility. Incidence and mortality of 14 major diseases were identified through linkages to hospital inpatient records and death registries. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incidence and mortality of the 14 diseases of interest.

RESULTS

During a median follow-up of 12.6 years, 29,869 participants were diagnosed with any disease of interest, and 3,144 died. Significantly increased risk of disease and all-cause mortality was observed among individuals who moved from a lower to higher air polluted area. Compared with constantly low exposure, moving from low to moderate PM 2.5 exposure was associated with increased risk of all 14 diseases but not for all-cause mortality, with adjusted HRs (95% CIs) ranging from 1.18 (1.05, 1.33) to 1.48 (1.30, 1.69); moving from low to high PM 2.5 areas increased risk of all 14 diseases: infections [1.37 (1.19, 1.58)], blood diseases [1.57 (1.34, 1.84)], endocrine diseases [1.77 (1.50, 2.09)], mental and behavioral disorders [1.93 (1.68, 2.21)], nervous system diseases [1.51 (1.32, 1.74)], ocular diseases [1.76 (1.56, 1.98)], ear disorders [1.58 (1.35, 1.86)], circulatory diseases [1.59 (1.42, 1.78)], respiratory diseases [1.51 (1.33, 1.72)], digestive diseases [1.74 (1.58, 1.92)], skin diseases [1.39 (1.22, 1.58)], musculoskeletal diseases [1.62 (1.45, 1.81)], genitourinary diseases [1.54 (1.36, 1.74)] and cancer [1.42 (1.24, 1.63)]. We observed similar associations for PM 10 and SO 2 with 14 diseases (but not with all-cause mortality); increases in NO 2 and NO x were positively associated with 14 diseases and all-cause mortality.

CONCLUSIONS

This study supports potential associations between ambient air pollution exposure and morbidity as well as mortality. Findings also emphasize the importance of maintaining consistently low levels of air pollution to protect the public's health. https://doi.org/10.1289/EHP14367.

Residential exposure to traffic pollution and mammographic density in premenopausal women

BACKGROUND

Mammographic density (MD) is the most important breast cancer biomarker. Ambient pollution is a carcinogen, and its relationship with MD is unclear. This study aims to explore the association between exposure to traffic pollution and MD in premenopausal women.

METHODOLOGY

This Spanish cross-sectional study involved 769 women attending gynecological examinations in Madrid. Annual Average Daily Traffic (AADT), extracted from 1944 measurement road points provided by the City Council of Madrid, was weighted by distances (d) between road points and women's addresses to develop a Weighted Traffic Exposure Index (WTEI). Three methods were employed: method-1 (1dAADT), method-2 (1dAADT), and method-3 (e1dAADT). Multiple linear regression models, considering both log-transformed percentage of MD and untransformed MD, were used to estimate MD differences by WTEI quartiles, through two strategies: "exposed (exposure buffers between 50 and 200 m) vs. not exposed (>200 m)"; and "degree of traffic exposure".

RESULTS

Results showed no association between MD and traffic pollution according to buffers of exposure to the WTEI (first strategy) for the three methods. The highest reductions in MD, although not statistically significant, were detected in the quartile with the highest traffic exposure. For instance, method-3 revealed a suggestive inverse trend (eβQ1 = 1.23, eβQ2 = 0.96, eβQ3 = 0.85, eβQ4 = 0.85, p-trend = 0.099) in the case of 75 m buffer. Similar non-statistically significant trends were observed with Methods-1 and -2. When we examined the effect of traffic exposure considering all the 1944 measurement road points in every participant (second strategy), results showed no association for any of the three methods. A slightly decreased MD, although not significant, was observed only in the quartile with the highest traffic exposure: eβQ4 = 0.98 (method-1), and eβQ4 = 0.95 (methods-2 and -3).

CONCLUSIONS

Our results showed no association between exposure to traffic pollution and MD in premenopausal women. Further research is needed to validate these findings.

Mammographic density and exposure to air pollutants in premenopausal women: a cross-sectional study

BACKGROUND

Mammographic density (MD) is a well-established risk factor for breast cancer. Air pollution is a major public health concern and a recognized carcinogen. We aim to investigate the association between MD and exposure to specific air pollutants (SO2, CO, NO, NO2, NOx, PM2.5, PM10, and O3) in premenopausal females.

METHODS

This cross-sectional study, carried out in Spain, included 769 participants who attended their gynecological examinations. Hourly concentrations of the pollutants were extracted from the Air Quality Monitoring System of Madrid City over a 3-year period. Individual long-term exposure to pollutants was assessed by geocoding residential addresses and monitoring stations, and applying ordinary kriging to the 3-year annual mean concentrations of each pollutant to interpolate the surface of Madrid. This exposure variable was categorized into quartiles. In a first analysis, we used multiple linear regression models with the log-transformed percent MD as a continuous variable. In a second analysis, we used MD as a dichotomous variable ("high" density (MD > 50%) vs. "low" density (MD ≤ 50%)) and applied multiple logistic regression models to estimate odds ratios (ORs). We also analyzed the correlation among the pollutants, and performed a principal component analysis (PCA) to reduce the dimensionality of this set of eight correlated pollutants into a smaller set of uncorrelated variables (principal components (PCs)). Finally, the initial analyses were applied to the PCs to detect underlying patterns of emission sources.

RESULTS

The first analysis detected no association between MD and exposure to any of the pollutants. The second analysis showed non-statistically significant increased risks (ORQ4; IC95%) of high MD were detected in women with higher exposure to SO2 (1.50; 0.90-2.48), and PM2.5 (1.27; 0.77-2.10). In contrast, non-significant ORs < 1 were found in all exposure quartiles for NO (ORQ2 = 0.72, ORQ3 = 0.68, ORQ4 = 0.78), and PM10 (ORQ2 = 0.69, ORQ3 = 0.82, ORQ4 = 0.72). PCA identified two PCs (PC1: "traffic pollution" and PC2: "natural pollution"), and no association was detected between MD and proximity to these two PCs.

CONCLUSIONS

In general, our results show a lack of association between residential exposure to specific air pollutants and MD in premenopausal females. Future research is needed to confirm or refute these findings.

Mammographic density in the environs of multiple industrial sources

BACKGROUND

Mammographic density (MD), defined as the percentage of dense fibroglandular tissue in the breast, is a modifiable marker of the risk of developing breast cancer. Our objective was to evaluate the effect of residential proximity to an increasing number of industrial sources in MD.

METHODS

A cross-sectional study was conducted on 1225 premenopausal women participating in the DDM-Madrid study. We calculated distances between women's houses and industries. The association between MD and proximity to an increasing number of industrial facilities and industrial clusters was explored using multiple linear regression models.

RESULTS

We found a positive linear trend between MD and proximity to an increasing number of industrial sources for all industries, at distances of 1.5 km (p-trend = 0.055) and 2 km (p-trend = 0.083). Moreover, 62 specific industrial clusters were analyzed, highlighting the significant associations found between MD and proximity to the following 6 industrial clusters: cluster 10 and women living at ≤1.5 km (β = 10.78, 95 % confidence interval (95%CI) = 1.59; 19.97) and at ≤2 km (β = 7.96, 95%CI = 0.21; 15.70); cluster 18 and women residing at ≤3 km (β = 8.48, 95%CI = 0.01; 16.96); cluster 19 and women living at ≤3 km (β = 15.72, 95%CI = 1.96; 29.49); cluster 20 and women living at ≤3 km (β = 16.95, 95%CI = 2.90; 31.00); cluster 48 and women residing at ≤3 km (β = 15.86, 95%CI = 3.95; 27.77); and cluster 52 and women living at ≤2.5 km (β = 11.09, 95%CI = 0.12; 22.05). These clusters include the following industrial activities: surface treatment of metals/plastic, surface treatment using organic solvents, production/processing of metals, recycling of animal waste, hazardous waste, urban waste-water treatment plants, inorganic chemical industry, cement and lime, galvanization, and food/beverage sector.

CONCLUSIONS

Our results suggest that women living in the proximity to an increasing number of industrial sources and those near certain types of industrial clusters have higher MD.

The association of metformin and aspirin intake with mammographic breast density: A cross-sectional study

Background

Our purpose was to investigate the association between Mammographic breast density (MBD), a known strong marker for breast cancer and metformin and aspirin use and duration of use alone or simultaneously, in a sample of Iranian women considering other confounding factors.

Methods

In a cross-sectional study, 712 individuals were selected out of women referred to two university hospitals for screening mammography. Participants' information was collected with a questionnaire. Four-category density scale (a = almost entirely fatty, b = scattered fibroglandular densities, c= heterogeneously dense, and d = extremely dense) was categorized as low (a&b) and high (c&d) density.

Results

The mean age of the participants was 49.80 ± 7.26 years. Sixty-five percent of women belonged to the high and 35% to the low MBD category. Both aspirin and metformin had a significantly negative association with MBD, however, when confounding factors were entered into the models, only aspirin after adjustment for age and BMI had an inverse association with MBD (OR = 0.53, 95% CI: 0.35-0.94). Simultaneous use of metformin and aspirin (OR = 0.44, 95 %CI: 0.17-1.12) was associated with lower MBD. Furthermore, in women who used metformin (OR = 0.23, 95% CI: 0.09-0.62) and aspirin (OR= 0.35, 95% CI: 0.17-0.72) for 2 to 5 years, MBD was significantly lower. However, after the adjustment of confounding factors, these associations were not statistically significant.

Conclusion

It seems metformin and aspirin intakes are associated with MBD. However, further studies with more sample size are needed.