Using Structure Coefficients and Multivariate Multiple Regression to Predict Psychosocial Outcomes with Health and Performance Variables in Older Adults

Peter D. Hart^{1, 2,}

¹Health Promotion Research, Havre, Montana, USA

²Kinesmetrics Lab, Tallahassee, Florida, USA

Cite this paper:
Peter D. Hart. Using Structure Coefficients and Multivariate Multiple Regression to Predict Psychosocial Outcomes with Health and Performance Variables in Older Adults. American Journal of Public Health Research. 2026; 14(4):103-112. doi: 10.12691/ajphr-14-4-4

Abstract

Background: Many psychosocial constructs are known predictors of longevity and health-related quality of life in older adult populations. Similarly, measures of health and performance have consistently shown positive influences on related outcomes among older adults. Less is known, however, if a set of health and performance measures can concurrently predict a set of psychosocial constructs. Purpose: The aim of this study was to use advanced statistical procedures to examine the extent to which several health and performance variables can predict multiple psychosocial outcomes simultaneously. Methods: Data from 2,561 adults 50+ years of age participating in the 2022 Health and Retirement Study were used. Three (3) psychosocial measures were created that included positive affect (POS), hostility (HOST), and anxiety (ANX). The psychosocial outcomes showed acceptable reliability (α values = 0.93, 0.80, 0.81, respectively) and were subsequently converted to factor T-scores using IRT. Five (5) health and performance predictor variables included physical activity (PA), grip strength (GS), balance test (BT), body mass index (BMI), and perceived general health (GH). Health-related covariates included AGE, SEX, and marital status (MS). The primary analysis consisted of univariate and multivariate multiple regression models along with calculated structure coefficients to examine the associations between sets of measured and synthetic variables. Results: Bivariate analyses showed that older adults with high levels (versus low levels) of PA or GH had significantly (p-values < 0.0001) greater POS and lower HOST and ANX. Additionally, those with high levels of GS or BMI showed significantly (p-values < 0.0001) greater HOST. While those with high levels of GS saw significantly (p = 0.0158) lower ANX. Univariate multiple regression models revealed all predictors 1) independently related to POS except GS, BT, and MS; 2) independently related to HOST except GS and MS; and 3) independently related to ANX except PA, GS, SEX, and MS. Multivariate multiple regression found that all predictors were independently related to the set of psychosocial outcomes except GS and MS. Finally, structure coefficients for the multivariate analysis indicated GH (r_S = 0.829, r_S = 0.382) and PA (r_S = 0.595, r_S = 0.274) were the strongest correlates of the explained variance found from the synthetic predictor and outcome variates, respectively. Conversely, GS (r_S = -0.101, r_S = -0.047) and BT (r_S = 0.140, r_S = 0.065) were the weakest correlates of the explained variance found from either the synthetic predictor or outcome variates, respectively. Conclusion: Results from this study support the ability of a health and performance construct to independently predict psychosocial wellness in older adults. Self-rated health and leisure activity may be stronger predictors of total psychosocial wellness than measures of performance in this population.

Keywords:
Psychosocial wellness Physical activity Self-rated health Performance Gerontology

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