Airborne particulate matter with a diameter of 2.5 µm or less (PM_2.5) has often been reported to be associated with the cardiovascular toxic effects of air pollution mixtures and ozone (O₃) with respiratory illness.^1,2 However, there is increasing evidence that O₃, independent of PM_2.5, is also associated with cardiovascular mortality.^3,4 For example, O₃ has been associated with increases in mortality due to embolism and thrombosis,⁵ ischemic heart disease,³ heart failure,⁴ and stroke.⁶ However, not all studies reporting associations of O₃ with cardiovascular outcomes found that the associations were independent from particulate matter and other gaseous pollutants, such as nitrogen dioxide (NO₂) and sulfur dioxide (SO₂).^7,8 Other studies have found nonsignificant or seemingly “beneficial” associations between O₃ and cardiovascular outcomes.^9,10 The uncertainty in epidemiologic findings of O₃ cardiovascular effects is further enhanced by the limited understanding of biological mechanisms underlying the epidemiologic associations.¹¹

Exposome-wide association studies (EWAS) are a systematic and unbiased way to investigate multiple environmental factors associated with phenotype. We applied EWAS to study semen quality and queried the sample size requirements to detect modest associations in a reproductive cohort. We conducted 1) a multivariate EWAS of 128 endocrine disrupting chemicals (EDCs) from 15 chemical classes measured in urine/serum relative to 7 semen quality endpoints in a prospective cohort study comprising 473 men and 2) estimated the sample size requirements for EWAS etiologic investigations. None of the EDCs were associated with semen quality endpoints after adjusting for multiple tests. However, several EDCs (e.g., polychlorinated biphenyl congeners 99, 105, 114, and 167) were associated with raw p < 0.05. In a post hoc statistical power analysis with the observed effect sizes, we determined that EWAS research in male fertility will require a mean sample size of 2696 men (1795-3625) to attain a power of 0.8. The average size of four published studies is 201 men. Existing cohort studies with hundreds of participants are underpowered (<0.8) for EWAS-related investigations. Merging cohorts to ensure a sufficient sample size can facilitate the use of EWAS methods for assessing EDC mixtures that impact semen quality.

Objective: Prior studies examining diabetes prevalence in India have found that nearly 50% of the diabetes population remains undiagnosed; however, the specific populations at risk are unclear. Research design and methods: First, we estimated the prevalence of undiagnosed diabetes in India for 750 924 persons between the ages of 15 years and 50 years who participated in the National Family Health Survey (NFHS-4)/Demographic Health Survey (2015–2016), a cross-sectional survey of all 29 states and 7 union territories of India. We defined ‘undiagnosed diabetes’ as individuals who did not know about their diabetes status but had high random (≥200 mg/dL) or fasting (≥126 mg/dL) blood glucose levels. Second, using Poisson regression, we associated 10 different factors, including the role of healthcare access, and undiagnosed diabetes. Third, we examined the association of undiagnosed diabetes with other potential comorbid conditions. Results: The crude prevalence of diabetes for women and men aged 15–50 years was 2.9%, 95% CI 2.9% to 3.1%, with self-reported diabetes prevalence at 1.7%, 95% CI 1.6 to 1.8. The overall prevalence of undiagnosed diabetes for 15–50 year olds was at 1.2%, 95% CI 1.2% to 1.3%. Forty-two per cent, 95% CI 40.7% to 43.4% of the individuals with high glucose levels were unaware of their diabetes status. Approximately 45%, 95% CI 42.9% to 46.4% of undiagnosed diabetes population had access to healthcare. Men, younger individuals, and those with lower levels of education were most at risk of being undiagnosed. Geographically, the Southern states in India had a significantly higher prevalence of undiagnosed diabetes despite having nearly universal access to healthcare. Risk factors combined with random glucose could predict undiagnosed diabetes (area under the curve of 97.8%, 95% CI 97.7% to 97.8%), Nagelkerke R² of 66%). Conclusion: Close to half (42%) of the people with diabetes in India are not aware of their disease status, and a large subset of these people are at risk of poor detection, despite having health insurance and/or having access to healthcare. Younger age groups and men are the most vulnerable.