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Background: Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States.Methods and Findings: We used vital registration and population data with information on sex, age, cause of death, and county of residence. We used four Bayesian spatiotemporal models, with different adjustments for other determinants of mortality, to directly estimate mortality and life expectancy loss due to current PM2.5 pollution and the benefits of reductions since 1999, nationally and by county. The covariates included in the adjusted models were per capita income; percentage of population whose family income is below the poverty threshold, who are of Black or African American race, who have graduated from high school, who live in urban areas, and who are unemployed; cumulative smoking; and mean temperature and relative humidity. In the main model, which adjusted for these covariates and for unobserved county characteristics through the use of county-specific random intercepts, PM2.5 pollution in excess of the lowest observed concentration (2.8 μg/m3) was responsible for an estimated 15,612 deaths (95% credible interval 13,248-17,945) in females and 14,757 deaths (12,617-16,919) in males. These deaths would lower national life expectancy by an estimated 0.15 years (0.13-0.17) for women and 0.13 years (0.11-0.15) for men. The life expectancy loss due to PM2.5 was largest around Los Angeles and in some southern states such as Arkansas, Oklahoma, and Alabama. At any PM2.5 concentration, life expectancy loss was, on average, larger in counties with lower income and higher poverty rate than in wealthier counties. Reductions in PM2.5 since 1999 have lowered mortality in all but 14 counties where PM2.5 increased slightly. The main limitation of our study, similar to other observational studies, is that it is not guaranteed for the observed associations to be causal. We did not have annual county-level data on other important determinants of mortality, such as healthcare access and quality and diet, but these factors were adjusted for with use of county-specific random intercepts.Conclusions: According to our estimates, recent reductions in particulate matter pollution in the USA have resulted in public health benefits. Nonetheless, we estimate that current concentrations are associated with mortality impacts and loss of life expectancy, with larger impacts in counties with lower income and higher poverty rate. [ABSTRACT FROM AUTHOR]

Background: No prior study to our knowledge has examined the joint contribution of a polygenic risk score (PRS), mammographic density (MD), and postmenopausal endogenous hormone levels-all well-confirmed risk factors for invasive breast cancer-to existing breast cancer risk prediction models.Methods and Findings: We conducted a nested case-control study within the prospective Nurses' Health Study and Nurses' Health Study II including 4,006 cases and 7,874 controls ages 34-70 years up to 1 June 2010. We added a breast cancer PRS using 67 single nucleotide polymorphisms, MD, and circulating testosterone, estrone sulfate, and prolactin levels to existing risk models. We calculated area under the curve (AUC), controlling for age and stratified by menopausal status, for the 5-year absolute risk of invasive breast cancer. We estimated the population distribution of 5-year predicted risks for models with and without biomarkers. For the Gail model, the AUC improved (p-values < 0.001) from 55.9 to 64.1 (8.2 units) in premenopausal women (Gail + PRS + MD), from 55.5 to 66.0 (10.5 units) in postmenopausal women not using hormone therapy (HT) (Gail + PRS + MD + all hormones), and from 58.0 to 64.9 (6.9 units) in postmenopausal women using HT (Gail + PRS + MD + prolactin). For the Rosner-Colditz model, the corresponding AUCs improved (p-values < 0.001) by 5.7, 6.2, and 6.5 units. For estrogen-receptor-positive tumors, among postmenopausal women not using HT, the AUCs improved (p-values < 0.001) by 14.3 units for the Gail model and 7.3 units for the Rosner-Colditz model. Additionally, the percentage of 50-year-old women predicted to be at more than twice 5-year average risk (≥2.27%) was 0.2% for the Gail model alone and 6.6% for the Gail + PRS + MD + all hormones model. Limitations of our study included the limited racial/ethnic diversity of our cohort, and that general population exposure distributions were unavailable for some risk factors.Conclusions: In this study, the addition of PRS, MD, and endogenous hormones substantially improved existing breast cancer risk prediction models. Further studies will be needed to confirm these findings and to determine whether improved risk prediction models have practical value in identifying women at higher risk who would most benefit from chemoprevention, screening, and other risk-reducing strategies. [ABSTRACT FROM AUTHOR]

Background: In many regions globally, buildings designed for harnessing heat during the cold exacerbate thermal exposures during heat waves (HWs) by maintaining elevated indoor temperatures even when high ambient temperatures have subdued. While previous experimental studies have documented the effects of ambient temperatures on cognitive function, few have observed HW effects on indoor temperatures following subjects' habitual conditions. The objective was to evaluate the differential impact of having air conditioning (AC) on cognitive function during a HW among residents of AC and non-AC buildings using a prospective observational cohort study.Methods: We followed 44 students (mean age = 20.2 years; SD = 1.8 years) from a university in the Greater Boston area, Massachusetts in the United States living in AC (n = 24) and non-AC (n = 20) buildings before, during, and after a HW. Two cognition tests were self-administered daily for a period of 12 days (July 9-July 20, 2016), the Stroop color-word test (STROOP) to assess selective attention/processing speed and a 2-digit, visual addition/subtraction test (ADD) to evaluate cognitive speed and working memory. The effect of the HW on cognitive function was evaluated using difference-in-differences (DiD) modelling.Findings: Mean indoor temperatures in the non-AC group (mean = 26.3°C; SD = 2.5°C; range = 19.6-30.4°C) were significantly higher (p < 0.001) than in the AC group (mean = 21.4°C; SD = 1.9°C; range = 17.5-25.0°C). DiD estimates show an increase in reaction time (STROOP = 13.4%, p < 0001; ADD = 13.3%, p < 0.001) and reduction in throughput (STROOP = -9.9%, p < 0.001; ADD = -6.3%, p = 0.08) during HWs among non-AC residents relative to AC residents at baseline. While ADD showed a linear relationship with indoor temperatures, STROOP was described by a U-shaped curve with linear effects below and above an optimum range (indoor temperature = 22°C-23°C), with an increase in reaction time of 16 ms/°C and 24 ms/°C for STROOP and ADD, respectively. Cognitive tests occurred right after waking, so the study is limited in that it cannot assess whether the observed effects extended during the rest of the day. Although the range of students' ages also represents a limitation of the study, the consistent findings in this young, healthy population might indicate that greater portions of the population are susceptible to the effects of extreme heat.Conclusions: Cognitive function deficits resulting from indoor thermal conditions during HWs extend beyond vulnerable populations. Our findings highlight the importance of incorporating sustainable adaptation measures in buildings to preserve educational attainment, economic productivity, and safety in light of a changing climate. [ABSTRACT FROM AUTHOR]

Background: Tobacco addiction is a complex, multicomponent phenomenon stemming from nicotine's pharmacology and the user's biology, psychology, sociology, and environment. After decades of public denial, the tobacco industry now agrees with public health authorities that nicotine is addictive. In 2000, Philip Morris became the first major tobacco company to admit nicotine's addictiveness. Evolving definitions of addiction have historically affected subsequent policymaking. This article examines how Philip Morris internally conceptualized addiction immediately before and after this announcement.Methods and Findings: We analyzed previously secret, internal Philip Morris documents made available as a result of litigation against the tobacco industry. We compared these documents to public company statements and found that Philip Morris's move from public denial to public affirmation of nicotine's addictiveness coincided with pressure on the industry from poor public approval ratings, the Master Settlement Agreement (MSA), the United States government's filing of the Racketeer Influenced and Corrupt Organizations (RICO) suit, and the Institute of Medicine's (IoM's) endorsement of potentially reduced risk products. Philip Morris continued to research the causes of addiction through the 2000s in order to create successful potentially reduced exposure products (PREPs). While Philip Morris's public statements reinforce the idea that nicotine's pharmacology principally drives smoking addiction, company scientists framed addiction as the result of interconnected biological, social, psychological, and environmental determinants, with nicotine as but one component. Due to the fragmentary nature of the industry document database, we may have missed relevant information that could have affected our analysis.Conclusions: Philip Morris's research suggests that tobacco industry activity influences addiction treatment outcomes. Beyond nicotine's pharmacology, the industry's continued aggressive advertising, lobbying, and litigation against effective tobacco control policies promotes various nonpharmacological determinants of addiction. To help tobacco users quit, policy makers should increase attention on the social and environmental dimensions of addiction alongside traditional cessation efforts. [ABSTRACT FROM AUTHOR]

Background: With the onset of prevention trials for individuals at high risk for Alzheimer disease, there is increasing need for accurate risk prediction to inform study design and enrollment, but available risk estimates are limited. We developed risk estimates for the incidence of mild cognitive impairment (MCI) or dementia among cognitively unimpaired individuals by APOE-e4 dose for the genetic disclosure process of the Alzheimer's Prevention Initiative Generation Study, a prevention trial in cognitively unimpaired APOE-e4/e4 homozygote individuals.Methods and Findings: We included cognitively unimpaired individuals aged 60-75 y, consistent with Generation Study eligibility criteria, from the National Alzheimer's Coordinating Center (NACC) (n = 5,073, 158 APOE-e4/e4), the Rotterdam Study (n = 6,399, 156 APOE-e4/e4), the Framingham Heart Study (n = 4,078, 67 APOE-e4/e4), and the Sacramento Area Latino Study on Aging (SALSA) (n = 1,294, 11 APOE-e4/e4). We computed stratified cumulative incidence curves by age (60-64, 65-69, 70-75 y) and APOE-e4 dose, adjusting for the competing risk of mortality, and determined risk of MCI and/or dementia by genotype and baseline age. We also used subdistribution hazard regression to model relative hazard based on age, APOE genotype, sex, education, family history of dementia, vascular risk, subjective memory concerns, and baseline cognitive performance. The four cohorts varied considerably in age, education, ethnicity/race, and APOE-e4 allele frequency. Overall, cumulative incidence was uniformly higher in NACC than in the population-based cohorts. Among APOE-e4/e4 individuals, 5-y cumulative incidence was as follows: in the 60-64-y age stratum, it ranged from 0% to 5.88% in the three population-based cohorts versus 23.06% in NACC; in the 65-69-y age stratum, from 9.42% to 10.39% versus 34.62%; and in the 70-75-y age stratum, from 18.64% to 33.33% versus 38.34%. Five-year incidence of dementia was negligible except for APOE-e4/e4 individuals and those over 70 y. Lifetime incidence (to age 80-85 y) of MCI or dementia for the APOE-e4/e4 individuals in the long-term Framingham and Rotterdam cohorts was 34.69%-38.45% at age 60-64 y, 30.76%-40.26% at 65-69 y, and 33.3%-35.17% at 70-75 y. Confidence limits for these estimates are often wide, particularly for APOE-e4/e4 individuals and for the dementia outcome at 5 y. In regression models, APOE-e4 dose and age both consistently increased risk, as did lower education, subjective memory concerns, poorer baseline cognitive performance, and family history of dementia. We discuss several limitations of the study, including the small numbers of APOE-e4/e4 individuals, missing data and differential dropout, limited ethnic and racial diversity, and differences in definitions of exposure and outcome variables.Conclusions: Estimates of the absolute risk of MCI or dementia, particularly over short time intervals, are sensitive to sampling and a variety of methodological factors. Nonetheless, such estimates were fairly consistent across the population-based cohorts, and lower than those from a convenience cohort and those estimated in prior studies-with implications for informed consent and design for clinical trials targeting high-risk individuals. [ABSTRACT FROM AUTHOR]