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Quantifying socioeconomic inequalities in health in absolute terms is of prime interest for decision-making and for international comparisons. The Slope Index of Inequality (SII), an index that quantifies absolute socioeconomic inequalities, was recently formalized, particularly in the context of mortality differences measured in the rate or hazard scale. However, absolute inequalities using either rates or hazards do not translate into a time dimension, which makes their interpretation difficult for policymakers. We propose an extension of the JOURNAL/epide/04.02/00001648-201907000-00015/math_15MM1/v/2019-06-06T035521Z/r/image-tiff in terms of the expected number of life years lost before an upper age, as well as its decomposition by cause of death. The JOURNAL/epide/04.02/00001648-201907000-00015/math_15MM2/v/2019-06-06T035521Z/r/image-tiff in the life years lost metric quantifies the extent to which life expectancy is shortened when comparing the higher and lower ends of the socioeconomic scale. The methodology proposed builds on recent developments in survival analysis for decomposing the number of life years lost according to cause of death using a pseudo-value approach. We illustrate our proposal using a representative 1% sample of the French population. On average, the least educated men lost 7 years of life from age 30 up to age 90 compared to the most educated. The loss for women is twice as much with 3.5 years. The JOURNAL/epide/04.02/00001648-201907000-00015/math_15MM3/v/2019-06-06T035521Z/r/image-tiff in the life years lost metric is easily understood, and the decomposition of the all-cause mortality JOURNAL/epide/04.02/00001648-201907000-00015/math_15MM4/v/2019-06-06T035521Z/r/image-tiff into parts attributable to given causes provides a sound estimation of the burden of different causes of death on absolute socioeconomic inequalities in mortality.
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Background: The All of Us Research Program is building a national longitudinal cohort and collecting data from multiple information sources (e.g., biospecimens, electronic health records, and mobile/wearable technologies) to advance precision medicine. Participant-provided information, collected via surveys, will complement and augment these information sources. We report the process used to develop and refine the initial three surveys for this program. Methods: The All of Us survey development process included: (1) prioritization of domains for scientific needs, (2) examination of existing validated instruments, (3) content creation, (4) evaluation and refinement via cognitive interviews and online testing, (5) content review by key stakeholders, and (6) launch in the All of Us electronic participant portal. All content was translated into Spanish. Results: We conducted cognitive interviews in English and Spanish with 169 participants, and 573 individuals completed online testing. Feedback led to over 40 item content changes. Lessons learned included: (1) validated survey instruments performed well in diverse populations reflective of All of Us; (2) parallel evaluation of multiple languages can ensure optimal survey deployment; (3) recruitment challenges in diverse populations required multiple strategies; and (4) key stakeholders improved integration of surveys into larger Program context. Conclusions: This efficient, iterative process led to successful testing, refinement, and launch of three All of Us surveys. Reuse of All of Us surveys, available at http://researchallofus.org, may facilitate large consortia targeting diverse populations in English and Spanish to capture participant-provided information to supplement other data, such as genetic, physical measurements, or data from electronic health records.
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Background: National, state, and local policies contributed to a 65% reduction in sulfur dioxide emissions from coal-fired power plants between 2005 and 2012 in the United States, providing an opportunity to directly quantify public health benefits attributable to these reductions under an air pollution accountability framework. Methods: We estimate ZIP code-level changes in two different—but related—exposure metrics: total PM2.5 concentrations and exposure to coal-fired power plant emissions. We associate changes in 10 health outcome rates among approximately 30 million US Medicare beneficiaries with exposure changes between 2005 and 2012 using two difference-in-difference regression approaches designed to mitigate observed and unobserved confounding. Results: Rates per 10,000 person–years of six cardiac and respiratory health outcomes—all cardiovascular disease, chronic obstructive pulmonary disorder, cardiovascular stroke, heart failure, ischemic heart disease, and respiratory tract infections—decreased by between 7.89 and 1.95 per JOURNAL/epide/04.02/00001648-201907000-00003/math_3MM1/v/2019-06-06T035521Z/r/image-tiff decrease in PM2.5, with comparable decreases in coal exposure leading to slightly larger rate decreases. Results for acute myocardial infarction, heart rhythm disorders, and peripheral vascular disease were near zero and/or mixed between the various exposure metrics and analyses. A secondary analysis found that nonlinearities in relationships between changing health outcome rates and coal exposure may explain differences in their associations. Conclusions: The direct analyses of emissions reductions estimate substantial health benefits via coal power plant emission and PM2.5 concentration reductions. Differing responses associated with changes in the two exposure metrics underscore the importance of isolating source-specific impacts from those due to total PM2.5 exposure.
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Background: An increasing number of studies have linked air pollution to decreased fertility. Whether this is due to an effect on ovarian reserve is unknown. Method: Our study included 632 women attending the Massachusetts General Hospital Fertility Center (2004–2015) who had a measured antral follicle count. Validated spatiotemporal models estimated daily particulate matter
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Background: Occupational exertion is associated with a higher risk of preterm delivery, although studies of leisure time activities generally document reduced risks. Less is known about the risk of preterm delivery immediately following episodes of moderate or heavy physical exertion. Methods: We conducted a case–crossover study of 722 women interviewed during their hospital stay for early preterm delivery, defined by a gestational age before 34 weeks, and after 20 weeks. Interviews occurred between March 2013 and December 2015 in seven hospitals in Lima, Peru. Results: The incidence rate ratio (RR) of early preterm delivery was 5.82-fold higher (95% confidence interval [CI] = 4.29, 7.36) in the hour following moderate or heavy physical exertion compared with other times and returned to baseline in the hours thereafter. The RR of early preterm delivery within an hour of physical exertion was lower for exertion at moderate intensity (RR = 2.43; 95% CI = 1.50, 3.96) than at heavy intensity (RR = 23.62; 95% CI = 15.54, 35.91; P-homogeneity 3 times per week in the year before pregnancy (RR = 1.56; 95% CI = 0.81, 3.00) compared with more sedentary women (RR = 6.91; 95% CI = 3.20, 14.92; P-homogeneity = 0.003). Conclusions: Our study showed a heightened risk of early preterm delivery in the hour following moderate or heavy physical exertion.
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Background: Evidence linking long-term exposure to particulate air pollution to blood pressure (BP) in high-income countries may not be transportable to low- and middle-income countries. We examined cross-sectional associations between ambient fine particulate matter (PM2.5) and black carbon (BC) with BP (systolic [SBP] and diastolic [DBP]) and prevalent hypertension in adults from 28 peri-urban villages near Hyderabad, India. Methods: We studied 5531 participants from the Andhra Pradesh Children and Parents Study (18–84 years, 54% men). We measured BP (2010–2012) in the right arm and defined hypertension as SBP ≥130 mmHg and/or DBP ≥80 mmHg. We used land-use regression models to estimate annual average PM2.5 and BC at participant’s residence. We applied linear and logistic nested mixed-effect models stratified by sex and adjusted by cooking fuel type to estimate associations between within-village PM2.5 or BC and health. Results: Mean (SD) PM2.5 was 33 µg/m3 (2.7) and BC was 2.5 µg/m3 (0.23). In women, a 1 µg/m3 increase in PM2.5 was associated with 1.4 mmHg higher SBP (95% confidence interval [CI]: 0.12, 2.7), 0.87 mmHg higher DBP (95% CI: −0.18, 1.9), and 4% higher odds of hypertension (95% CI: 0%, 9%). In men, associations with SBP (0.52 mmHg; 95% CI: −0.82, 1.8), DBP (0.41 mmHg; 95% CI: −0.69, 1.5), and hypertension (2% higher odds; 95% CI: −2%, 6%) were weaker. No associations were observed with BC. Conclusion: We observed a positive association between ambient PM2.5 and BP and hypertension in women. Longitudinal studies in this region are needed to corroborate our findings.
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