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ORIGINAL ARTICLE
Active ageing among elderly community members: structural equation modeling analysis
Revista Brasileira de Enfermagem. 2020;73:e20200110
10-23-2020
Abstract
ORIGINAL ARTICLEActive ageing among elderly community members: structural equation modeling analysis
Revista Brasileira de Enfermagem. 2020;73:e20200110
10-23-2020DOI 10.1590/0034-7167-2020-0110
Views0See moreABSTRACT
Objective:
to propose a structural model of active ageing among elderly community members based on the World Health Organization’s theoretical framework and to identify the most relevant determinants of active ageing to the proposed model.
Methods:
a cross-sectional and analytical study conducted with 957 elderly community members. Confirmatory factor analysis and structural equation modeling were performed.
Results:
the final measurement model was composed of the six determinants of active ageing: behavioral (R²=0.66); personal (R²=0.74); physical environment (R²=0.70); social (R²=0.77); economic (R²=0.44); and social and health services (R²=0.95). The last one showed good quality of adjustment: χ2/gl=3.50; GFI=0.94; CFI=0.92; TLI=0.90; RMSEA=0.05. By analyzing the trajectories between determinants and active ageing, the most representative was social and health services active ageing (λ=0.97; p<0.001).
Conclusion:
satisfaction with access to health services and positive self-assessment of health status were the factors that most contributed to active ageing in this population.
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This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract
ORIGINAL ARTICLEActive ageing among elderly community members: structural equation modeling analysis
Revista Brasileira de Enfermagem. 2020;73:e20200110
10-23-2020DOI 10.1590/0034-7167-2020-0110
Views0See moreABSTRACT
Objective:
to propose a structural model of active ageing among elderly community members based on the World Health Organization’s theoretical framework and to identify the most relevant determinants of active ageing to the proposed model.
Methods:
a cross-sectional and analytical study conducted with 957 elderly community members. Confirmatory factor analysis and structural equation modeling were performed.
Results:
the final measurement model was composed of the six determinants of active ageing: behavioral (R²=0.66); personal (R²=0.74); physical environment (R²=0.70); social (R²=0.77); economic (R²=0.44); and social and health services (R²=0.95). The last one showed good quality of adjustment: χ2/gl=3.50; GFI=0.94; CFI=0.92; TLI=0.90; RMSEA=0.05. By analyzing the trajectories between determinants and active ageing, the most representative was social and health services active ageing (λ=0.97; p<0.001).
Conclusion:
satisfaction with access to health services and positive self-assessment of health status were the factors that most contributed to active ageing in this population.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 
Elderly Statistical Factor Analysis Archives - Revista Brasileira de Enfermagem
