Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study
Background: Concepts of successful aging (SA), usual aging (UA), and mild cognitive impairment (MCI) have been developed to identify older adults at high risk of Alzheimer's diseases (AD), however, the predictors have rarely been investigated in a single study. Thus, this study aims to explore...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/62811/1/Predictors%20of%20poor%20cognitive%20.pdf |
| _version_ | 1825932518885425152 |
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| author | Vanoh, Divya Shahar, Suzana Che Din, Normah Omar, Azahadi Chin, Ai Vyrn Razali, Rosdinom Ibrahim, Rahimah Tengku Abdul Hamid, Tengku Aizan |
| author_facet | Vanoh, Divya Shahar, Suzana Che Din, Normah Omar, Azahadi Chin, Ai Vyrn Razali, Rosdinom Ibrahim, Rahimah Tengku Abdul Hamid, Tengku Aizan |
| author_sort | Vanoh, Divya |
| collection | UPM |
| description | Background: Concepts of successful aging (SA), usual aging (UA), and mild cognitive impairment (MCI) have been developed to identify older adults at high risk of Alzheimer's diseases (AD), however, the predictors have rarely been investigated in a single study. Thus, this study aims to explore the risk factors of MCI as compared to UA and SA among older adults, in a large community based cohort study in Malaysia. Method: 1993 subjects from four states in Malaysia were recruited. A comprehensive interview-based questionnaire was administered to determine socio-demographic information, followed by assessments to evaluate cognitive function, functional status, dietary intake, lifestyle and psychosocial status. Risk factors of cognitive impairment were assessed using the ordinal logistic regression (OLR). Result: The prevalence of SA, UA and MCI in this study was 11, 73 and 16 % respectively. OLR indicated that higher fasting blood sugar, hyperlipidemia, disability, lower education level, not regularly involved in technical based activities, limited use of modern technologies, lower intake of fruits and fresh fruit juices and not practicing calorie restriction were among the risk factors of poor cognitive performance in this study. Conclusion: This study will be a stepping stone for future researchers to develop intervention strategies to prevent cognitive decline. |
| first_indexed | 2024-03-06T09:43:16Z |
| format | Article |
| id | upm.eprints-62811 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:43:16Z |
| publishDate | 2016 |
| publisher | Springer |
| record_format | dspace |
| spelling | upm.eprints-628112022-11-09T03:40:56Z http://psasir.upm.edu.my/id/eprint/62811/ Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study Vanoh, Divya Shahar, Suzana Che Din, Normah Omar, Azahadi Chin, Ai Vyrn Razali, Rosdinom Ibrahim, Rahimah Tengku Abdul Hamid, Tengku Aizan Background: Concepts of successful aging (SA), usual aging (UA), and mild cognitive impairment (MCI) have been developed to identify older adults at high risk of Alzheimer's diseases (AD), however, the predictors have rarely been investigated in a single study. Thus, this study aims to explore the risk factors of MCI as compared to UA and SA among older adults, in a large community based cohort study in Malaysia. Method: 1993 subjects from four states in Malaysia were recruited. A comprehensive interview-based questionnaire was administered to determine socio-demographic information, followed by assessments to evaluate cognitive function, functional status, dietary intake, lifestyle and psychosocial status. Risk factors of cognitive impairment were assessed using the ordinal logistic regression (OLR). Result: The prevalence of SA, UA and MCI in this study was 11, 73 and 16 % respectively. OLR indicated that higher fasting blood sugar, hyperlipidemia, disability, lower education level, not regularly involved in technical based activities, limited use of modern technologies, lower intake of fruits and fresh fruit juices and not practicing calorie restriction were among the risk factors of poor cognitive performance in this study. Conclusion: This study will be a stepping stone for future researchers to develop intervention strategies to prevent cognitive decline. Springer 2016-03 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/62811/1/Predictors%20of%20poor%20cognitive%20.pdf Vanoh, Divya and Shahar, Suzana and Che Din, Normah and Omar, Azahadi and Chin, Ai Vyrn and Razali, Rosdinom and Ibrahim, Rahimah and Tengku Abdul Hamid, Tengku Aizan (2016) Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study. Aging Clinical and Experimental Research, 29 (2). 173 - 182. ISSN 1594-0667; ESSN: 1720-8319 https://link.springer.com/article/10.1007/s40520-016-0553-2 10.1007/s40520-016-0553-2 |
| spellingShingle | Vanoh, Divya Shahar, Suzana Che Din, Normah Omar, Azahadi Chin, Ai Vyrn Razali, Rosdinom Ibrahim, Rahimah Tengku Abdul Hamid, Tengku Aizan Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study |
| title | Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study |
| title_full | Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study |
| title_fullStr | Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study |
| title_full_unstemmed | Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study |
| title_short | Predictors of poor cognitive status among older Malaysian adults: baseline findings from the LRGS TUA cohort study |
| title_sort | predictors of poor cognitive status among older malaysian adults baseline findings from the lrgs tua cohort study |
| url | http://psasir.upm.edu.my/id/eprint/62811/1/Predictors%20of%20poor%20cognitive%20.pdf |
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