Roman Romero-Ortuno1. 1. Department of Medical Gerontology, Trinity College Dublin, Trinity Centre for Health Sciences, St James's Hospital, Dublin, Ireland.
Abstract
AIM: The Frailty Index (FI) summarizes differences in health status within individuals, and the determinants of health drive that variability. The aim of the present study was to investigate the influence of education, income, smoking, alcohol intake and parental longevity on the FI variability in subjects of the same chronological age group. METHODS: Analyses were based on a 40-item FI based on the first wave of the Survey of Health, Aging and Retirement in Europe (SHARE, http://www.share-project.org/), including 29 905 participants aged ≥50 years from 12 countries. For each sex, the sample was divided into age categories (50s, 60s, 70s, 80s and ≥90), and FI quartiles within age categories were calculated. Multivariate ordinal regressions were computed to assess the relative contribution of the health determinants on the FI quartiles in each age group. RESULTS: In women, the most significant multivariate predictors were years of education (odds ratios [OR] around 0.9), and difficulties making ends meet (OR between 1.8 and 2.1). In men, the most significant multivariate predictors were years of education (OR around 0.9), difficulties making ends meet (OR between 1.6 and 2.1), mother's age at death (OR under 1), and father's age at death (OR under 1). CONCLUSIONS: Consistently with the literature, education and income explained, in both sexes, cross-sectional variability in FI in subjects of the same chronological age group. The influence of parental longevity seemed to be greater in men, which mirrors previous studies showing that genetic factors might have a higher impact on longevity in men.
AIM: The Frailty Index (FI) summarizes differences in health status within individuals, and the determinants of health drive that variability. The aim of the present study was to investigate the influence of education, income, smoking, alcohol intake and parental longevity on the FI variability in subjects of the same chronological age group. METHODS: Analyses were based on a 40-item FI based on the first wave of the Survey of Health, Aging and Retirement in Europe (SHARE, http://www.share-project.org/), including 29 905 participants aged ≥50 years from 12 countries. For each sex, the sample was divided into age categories (50s, 60s, 70s, 80s and ≥90), and FI quartiles within age categories were calculated. Multivariate ordinal regressions were computed to assess the relative contribution of the health determinants on the FI quartiles in each age group. RESULTS: In women, the most significant multivariate predictors were years of education (odds ratios [OR] around 0.9), and difficulties making ends meet (OR between 1.8 and 2.1). In men, the most significant multivariate predictors were years of education (OR around 0.9), difficulties making ends meet (OR between 1.6 and 2.1), mother's age at death (OR under 1), and father's age at death (OR under 1). CONCLUSIONS: Consistently with the literature, education and income explained, in both sexes, cross-sectional variability in FI in subjects of the same chronological age group. The influence of parental longevity seemed to be greater in men, which mirrors previous studies showing that genetic factors might have a higher impact on longevity in men.
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