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Samuel H. Preston
University of Pennsylvania
DemographyEconomicsMortality ratePopulationMedicine
286Publications
53H-index
11.1kCitations
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#1Samuel H. Preston (UPenn: University of Pennsylvania)H-Index: 53
George Orwell reportedly said that “Autobiography is only to be trusted when it reveals something disgraceful.” I've done my best to eliminate any disgraceful episodes from the following account, t...
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#1Yana C. Vierboom (MPG: Max Planck Society)H-Index: 2
#2Samuel H. Preston (UPenn: University of Pennsylvania)H-Index: 53
OBJECTIVES: To identify levels and trends in life expectancy at age 65 (e65) by geographic region and metropolitan status in the United States. METHODS: Using county-level data on population and deaths from the Census and National Center for Health Statistics, we consider spatial inequality in e65 across 4 metropolitan types and 10 geographic regions from 2000 to 2016. We examine whether changes in e65 are driven by mortality developments in metro types or geographic regions, and compare spatial...
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#1Andrew Stokes (BU: Boston University)H-Index: 18
#2Dielle J. Lundberg (BU: Boston University)
Last. Samuel H. Preston (UPenn: University of Pennsylvania)H-Index: 53
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INTRODUCTION: Prior studies have identified associations between obesity and numerous conditions that increase risks for chronic pain. However, the impact of obesity on prescription opioid use is not well known. This study investigates the association between obesity and incidence of long-term prescription opioid use. METHODS: Fifteen panels of the Medical Expenditure Panel Survey from 2000 to 2015 were pooled to generate a sample of civilian non-institutionalized adults aged 30-84 years who wer...
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The impact of rising drug use on US mortality may extend beyond deaths coded as drug-related to include excess mortality from other causes affected by drug use. Here, we estimate the full extent of drug-associated mortality. We use annual death rates for 1999-2016 by state, sex, five-year age group, and cause of death to model the relationship between drug-coded mortality-which serves as an indicator of the population-level prevalence of drug use-and mortality from other causes. Among residents ...
3 CitationsSource
#1Yana C. Vierboom (MPG: Max Planck Society)H-Index: 2
#1Yana C. Vierboom (MPG: Max Planck Society)
Last. Arun S. Hendi (Office of Population Research)H-Index: 4
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Abstract Objectives To examine trends in inequality in life expectancy and age-specific death rates across 40 US spatial units from 1990 to 2016. Methods We use multiple cause-of-death data from vital statistics to estimate measures of inequality in mortality across metropolitan status and geographic region. We consider trends for 5-year age intervals and examine inequality in cause-specific mortality. Results For both sexes, spatial inequality in life expectancy and all-cause mortality above ag...
1 CitationsSource
#1Irma T. EloH-Index: 35
#2Arun S. HendiH-Index: 4
Last. Samuel H. PrestonH-Index: 53
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3 CitationsSource
#1Yana C. VierboomH-Index: 2
#2Samuel H. PrestonH-Index: 53
Last. Andrew StokesH-Index: 18
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Background The incidence and/or diagnosis of a major disease may activate weight change. Patterns of weight change associated with diagnoses have not been systematically documented. Methods We use data on adults ages 30+ in the National Health and Nutrition Examination Survey (NHANES) from 1999–2014. Self-reported current weight and weight one year prior are used to estimate percent weight change in the last year. We use self-reported data on arthritis, diabetes, cancer, cardiovascular disease, ...
1 CitationsSource
by Thomas K. Burch Demographic Research Monographs Dordrecht: Springer, 2018 ISBN 978-3-319-65432-4. Softcover C$24.99, 200 pp. e-book DOI 10.1007/978-3-319-65433-1
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#1Andrew Stokes (BU: Boston University)H-Index: 18
#2Jason M. Collins (BU: Boston University)H-Index: 4
Last. Samuel H. Preston (UPenn: University of Pennsylvania)H-Index: 53
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OBJECTIVE Understanding how changes in weight over the life course shape risk for diabetes is critical for the prevention of diabetes. Using data from the National Health and Nutrition Examination Survey (NHANES), we investigated the association between self-reported weight change from young adulthood to midlife and incident diabetes. RESEARCH DESIGN AND METHODS We categorized individuals into four weight-change groups: those who remained nonobese (stable nonobese), those who moved from an obese...
5 CitationsSource
#1Samuel H. Preston (UPenn: University of Pennsylvania)H-Index: 53
#2Daesung Choi (UPenn: University of Pennsylvania)
Last. Andrew Stokes (BU: Boston University)H-Index: 18
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ABSTRACTWe investigated the impact of diabetes on US life expectancy by sex and race/ethnicity using a prospective cohort study design. Cohorts were drawn from 1997 to 2009 waves of the National Health Interview Survey and linked to death records through December 31, 2011. We combined data on the prevalence of diabetes among decedents with estimates of the hazard ratios of individuals diagnosed with diabetes to calculate population attributable fractions (PAFs) by age, sex, and race/ethnicity at...
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