Abstract
Introduction: Older adulthood encompasses several decades of change and heterogeneity. Primary care providers need a geriatric comprehensive vision for defining older adult subpopulations.Methods: Using PubMed and Google searches, we reviewed the literature on epidemiology of age-related physiological changes, age-related diseases and geriatric syndromes, functional state, and emotional and social changes. We divided old age into strata based on chronological age and strata based on functional state, disease burden, and geriatric syndromes.Results: We describe 4 chronological-age strata beginning at age 60, and 4 functional-age strata based on frailty according to a modified clinical frailty scale. We provide clinical considerations and anticipatory guidance topics for each of the age strata and functional strata.Conclusion: Chronological age, functional status, chronic disease burden and geriatric syndromes, and life expectancy are all important domains that impact clinical care and appropriate anticipatory guidance for individual older adults. Better knowledge for differentiating subpopulations of older adults may improve clinical care, reduce medical overuse, improve personalized anticipatory guidance, and focus on the impact of functional state on the quality of life.
Highlights
Older adulthood encompasses several decades of change and heterogeneity
This study presents a model for the division of older age into stages, which are characterized by chronological age, functional status, chronic disease burden, and geriatric syndromes
We divided aging into four functional strata and explored clinical considerations and anticipatory guidance topics that might be appropriate for each stratum
Summary
Older adulthood encompasses several decades of change and heterogeneity. The proportion of older adults in the world will nearly double [1]. Older adults are a heterogeneous population, with many people over the age of 80 continuing to work and travel, while others might be weak, chronically ill, or disabled. A traditional framework for describing different populations of older adults is “young-old,” “old,” “old-old,” and/or “oldest old” [2]. Proteomic analysis finds large changes in gene expression at about the age of 40, 60, and 80 [4]. These frameworks are not adequate to describe the different stages of aging and subpopulations of older adults. Older age is a risk factor for normative physiological changes with aging and for cancer, heart disease, diabetes, dementia, and many
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