Kenny C F Kuok1, Lu Li2, Yu-Tao Xiang2, Bernice O C Lam Nogueira1,3, Gabor S Ungvari4,5, Chee H Ng6, Helen F K Chiu7, Linda Tran3, Li-Rong Meng1. 1. School of Health Sciences, Macao Polytechnic Institute, Macao SAR, China. 2. Unit of Psychiatry, Faculty of Health Sciences, University of Macau, Macao SAR, China. 3. Macao Sino-Portuguese Nurses Association, , Macao SAR, China. 4. School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, , Australia. 5. University of Notre Dame Australia/Marian Centre, , Perth, , Australia. 6. Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia. 7. Department of Psychiatry, Chinese University of Hong Kong, Hong Kong SAR, China, .
Abstract
AIM: There have been no previous studies of quality of life (QOL) in older adults in Macao. This study aimed to examine QOL in relation to the sociodemographic and clinical characteristics of adults aged ≥50 years in Macao. METHODS: A sample of 451 subjects (203 living in the community, 248 living in nursing homes) was interviewed using standardized instruments. Basic sociodemographic and clinical data including QOL were collected. RESULT: There were no significant differences between the community and nursing home groups in any of the QOL domains. Multiple linear regression analyses revealed that poor physical QOL was significantly predicted by severe depressive symptoms, insomnia, major medical conditions, unmarried status, and lower education ( F 11,438 = 26.2, P < 0.001), which accounted for 38.2% of the variance. Poor psychological QOL was significantly predicted by severe depressive symptoms and lower educational level ( F 11,438 = 24.3, P < 0.001), which accounted for 36.4% of the variance. Poor social QOL was significantly predicted by severe depressive symptoms, male gender, and unmarried status ( F 11,438 = 5.6, P < 0.001), which accounted for 12.5% of the variance. Poor environment QOL was significantly predicted by lower educational level, severe depressive symptoms, and younger age ( F 11,438 = 6.6, P < 0.001), which accounted for 12.1% of the variance. CONCLUSION: Older Macanese adults had poorer scores on physical and social QOL domains than the general Hong Kong Chinese population. Their QOL was more strongly related to severe depressive symptoms, major medical conditions, and insomnia.
AIM: There have been no previous studies of quality of life (QOL) in older adults in Macao. This study aimed to examine QOL in relation to the sociodemographic and clinical characteristics of adults aged ≥50 years in Macao. METHODS: A sample of 451 subjects (203 living in the community, 248 living in nursing homes) was interviewed using standardized instruments. Basic sociodemographic and clinical data including QOL were collected. RESULT: There were no significant differences between the community and nursing home groups in any of the QOL domains. Multiple linear regression analyses revealed that poor physical QOL was significantly predicted by severe depressive symptoms, insomnia, major medical conditions, unmarried status, and lower education ( F 11,438 = 26.2, P < 0.001), which accounted for 38.2% of the variance. Poor psychological QOL was significantly predicted by severe depressive symptoms and lower educational level ( F 11,438 = 24.3, P < 0.001), which accounted for 36.4% of the variance. Poor social QOL was significantly predicted by severe depressive symptoms, male gender, and unmarried status ( F 11,438 = 5.6, P < 0.001), which accounted for 12.5% of the variance. Poor environment QOL was significantly predicted by lower educational level, severe depressive symptoms, and younger age ( F 11,438 = 6.6, P < 0.001), which accounted for 12.1% of the variance. CONCLUSION: Older Macanese adults had poorer scores on physical and social QOL domains than the general Hong Kong Chinese population. Their QOL was more strongly related to severe depressive symptoms, major medical conditions, and insomnia.
Authors: Patricia Concheiro-Moscoso; Betania Groba; Francisco José Martínez-Martínez; María Del Carmen Miranda-Duro; Laura Nieto-Riveiro; Thais Pousada; Javier Pereira Journal: Digit Health Date: 2022-08-29