title: Measuring the speed of aging across population subgroups.
abstract: People in different subgroups age at different rates. Surveys containing biomarkers can be used to assess these subgroup differences. We illustrate this using hand-grip strength to produce an easily interpretable, physical-based measure that allows us to compare characteristic-based ages across educational subgroups in the United States. Hand-grip strength has been shown to be a good predictor of future mortality and morbidity, and therefore a useful indicator of population aging. Data from the Health and Retirement Survey (HRS) were used. Two education subgroups were distinguished, those with less than a high school diploma and those with more education. Regressions on hand-grip strength were run for each sex and race using age and education, their interactions and other covariates as independent variables. Ages of identical mean hand-grip strength across education groups were compared for people in the age range 60 to 80. The hand-grip strength of 65 year old white males with less education was the equivalent to that of 69.6 (68.2, 70.9) year old white men with more education, indicating that the more educated men had aged more slowly. This is a constant characteristic age, as defined in the Sanderson and Scherbov article "The characteristics approach to the measurement of population aging" published 2013 in Population and Development Review. Sixty-five year old white females with less education had the same average hand-grip strength as 69.4 (68.2, 70.7) year old white women with more education. African-American women at ages 60 and 65 with more education also aged more slowly than their less educated counterparts. African American men with more education aged at about the same rate as those with less education. This paper expands the toolkit of those interested in population aging by showing how survey data can be used to measure the differential extent of aging across subpopulations.
authors.affiliation: Department of Economics, Stony Brook University, Stony Brook, New York, United States of America; World Population Program, International Institute for Applied Systems Analysis, Laxenburg, Austria; Wittgenstein Centre for Demography and Global Human Capital (International Institute for Applied Systems Analysis, IIASA; Vienna Institute of Demography of the Austrian Academy of Sciences, VID/ÖAW; Vienna University of Economics and Business, WU), Laxenburg/Vienna, Austria.
authors.forename: Warren C
authors.initials: WC
authors.lastname: Sanderson
authors.affiliation: World Population Program, International Institute for Applied Systems Analysis, Laxenburg, Austria; Wittgenstein Centre for Demography and Global Human Capital (International Institute for Applied Systems Analysis, IIASA; Vienna Institute of Demography of the Austrian Academy of Sciences, VID/ÖAW; Vienna University of Economics and Business, WU), Laxenburg/Vienna, Austria.
authors.forename: Sergei
authors.initials: S
authors.lastname: Scherbov
mesh_terms: D001741:Black or African American / Q000706:statistics & numerical data; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000208:ethnology / Q000502:physiology*; D004522:Educational Status; D005260:Female; D018737:Hand Strength / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D012737:Sex Factors; D044465:White People / Q000706:statistics & numerical data