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Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality
by
K. Robin Yabroff
, Timothy McNeel
, Hyunsoon Cho
, Benmei Liu
, Eric J. Feuer
, Angela B. Mariotto
, Zhuoqiao Wang
in
Adolescent
/ Adult
/ Adults
/ Age
/ Age groups
/ Aged, 80 and over
/ Biostatistics
/ Child
/ Child, Preschool
/ Comorbidity
/ Decision making
/ Demographics
/ Environmental Health
/ Epidemiology
/ Forecasts and trends
/ Hazards
/ Health Status
/ Humans
/ Life Expectancy
/ Life span
/ Life Tables
/ Male
/ Mass Screening
/ Medical prognosis
/ Medical screening
/ Medicine
/ Medicine & Public Health
/ Men
/ Mortality
/ Mortality, health survey
/ Mortality, Premature
/ National Health Interview Survey
/ Older people
/ Patient-centered care
/ Patients
/ Polls & surveys
/ Population
/ Prediction models
/ Public aspects of medicine
/ Public Health
/ RA1-1270
/ Research Article
/ Self-rated health status
/ Socioeconomic factors
/ Survival
/ Survival analysis
/ Tables (data)
/ United States
/ United States - epidemiology
/ Vaccine
/ White people
/ Womens health
2022
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Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality
by
K. Robin Yabroff
, Timothy McNeel
, Hyunsoon Cho
, Benmei Liu
, Eric J. Feuer
, Angela B. Mariotto
, Zhuoqiao Wang
in
Adolescent
/ Adult
/ Adults
/ Age
/ Age groups
/ Aged, 80 and over
/ Biostatistics
/ Child
/ Child, Preschool
/ Comorbidity
/ Decision making
/ Demographics
/ Environmental Health
/ Epidemiology
/ Forecasts and trends
/ Hazards
/ Health Status
/ Humans
/ Life Expectancy
/ Life span
/ Life Tables
/ Male
/ Mass Screening
/ Medical prognosis
/ Medical screening
/ Medicine
/ Medicine & Public Health
/ Men
/ Mortality
/ Mortality, health survey
/ Mortality, Premature
/ National Health Interview Survey
/ Older people
/ Patient-centered care
/ Patients
/ Polls & surveys
/ Population
/ Prediction models
/ Public aspects of medicine
/ Public Health
/ RA1-1270
/ Research Article
/ Self-rated health status
/ Socioeconomic factors
/ Survival
/ Survival analysis
/ Tables (data)
/ United States
/ United States - epidemiology
/ Vaccine
/ White people
/ Womens health
2022
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Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality
by
K. Robin Yabroff
, Timothy McNeel
, Hyunsoon Cho
, Benmei Liu
, Eric J. Feuer
, Angela B. Mariotto
, Zhuoqiao Wang
in
Adolescent
/ Adult
/ Adults
/ Age
/ Age groups
/ Aged, 80 and over
/ Biostatistics
/ Child
/ Child, Preschool
/ Comorbidity
/ Decision making
/ Demographics
/ Environmental Health
/ Epidemiology
/ Forecasts and trends
/ Hazards
/ Health Status
/ Humans
/ Life Expectancy
/ Life span
/ Life Tables
/ Male
/ Mass Screening
/ Medical prognosis
/ Medical screening
/ Medicine
/ Medicine & Public Health
/ Men
/ Mortality
/ Mortality, health survey
/ Mortality, Premature
/ National Health Interview Survey
/ Older people
/ Patient-centered care
/ Patients
/ Polls & surveys
/ Population
/ Prediction models
/ Public aspects of medicine
/ Public Health
/ RA1-1270
/ Research Article
/ Self-rated health status
/ Socioeconomic factors
/ Survival
/ Survival analysis
/ Tables (data)
/ United States
/ United States - epidemiology
/ Vaccine
/ White people
/ Womens health
2022
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Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality
Journal Article
Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality
2022
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Overview
Background
Life expectancy is increasingly incorporated in evidence-based screening and treatment guidelines to facilitate patient-centered clinical decision-making. However, life expectancy estimates from standard life tables do not account for health status, an important prognostic factor for premature death. This study aims to address this research gap and develop life tables incorporating the health status of adults in the United States.
Methods
Data from the National Health Interview Survey (1986–2004) linked to mortality follow-up through to 2006 (age ≥ 40,
n
= 729,531) were used to develop life tables. The impact of self-rated health (excellent, very good, good, fair, poor) on survival was quantified in 5-year age groups, incorporating complex survey design and weights. Life expectancies were estimated by extrapolating the modeled survival probabilities.
Results
Life expectancies incorporating health status differed substantially from standard US life tables and by health status. Poor self-rated health more significantly affected the survival of younger compared to older individuals, resulting in substantial decreases in life expectancy. At age 40 years, hazards of dying for white men who reported poor vs. excellent health was 8.5 (95% CI: 7.0,10.3) times greater, resulting in a 23-year difference in life expectancy (poor vs. excellent: 22 vs. 45), while at age 80 years, the hazards ratio was 2.4 (95% CI: 2.1, 2.8) and life expectancy difference was 5 years (5 vs. 10). Relative to the US general population, life expectancies of adults (age < 65) with poor health were approximately 5–15 years shorter.
Conclusions
Considerable shortage in life expectancy due to poor self-rated health existed. The life table developed can be helpful by including a patient perspective on their health and be used in conjunction with other predictive models in clinical decision making, particularly for younger adults in poor health, for whom life tables including comorbid conditions are limited.
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