Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral Perspective
To unravel the combined effect of risk and protective factors that may contribute to preserve or impair cognitive status, this prospective cohort study systematically investigated a cluster of factors in elders aged 75 years and older from Guangxi Longitudinal Cohort (GLC) dataset. GLC has tracked 6...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-09-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fpsyg.2020.02217/full |
| _version_ | 1818934563508846592 |
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| author | Zhixiong Yan Xia Zou Xia Zou Xiaohui Hou |
| author_facet | Zhixiong Yan Xia Zou Xia Zou Xiaohui Hou |
| author_sort | Zhixiong Yan |
| collection | DOAJ |
| description | To unravel the combined effect of risk and protective factors that may contribute to preserve or impair cognitive status, this prospective cohort study systematically investigated a cluster of factors in elders aged 75 years and older from Guangxi Longitudinal Cohort (GLC) dataset. GLC has tracked 630 oldest-elders for two times within 2 years and will continue to follow two times in the next 4 years. At baseline geriatric assessment, sociodemographic information (e.g., education, Mandarin, marriage, and income), physical status [body mass index (BMI), chronic disease/medicine], lifestyle factors (smoking, alcohol, and exercise), and self-rated mental health (self-care, well-being, anxiety) were recorded by online interview. With 2 years’ follow-up, Mini-Mental State Examination (MMSE) and memory test were performed through person-to-person interview. The performance of MMSE was applied to represent the responder’s cognitive status which classified into cognitive impairment and normal group based on a cutoff point of 20. An age-related cognitive declining trend of 15 stratified factors was observed, though with a small effect size (R-square: 0.001–0.15). The odds of exposure or non-exposure on factors (memory, self-care, exercise, income, education, and literacy) had a significantly different effect on cognitive impairment through multivariate analysis after adjusting other confounding variables. Through stepwise multiple logistic regression analysis, the following 12 factors/index would be integrated to predict cognitive impairment: gender, physical health factors (BMI, chronic disease), socioeconomic and lifestyle factors (education, literacy, Mandarin, marriage, income, and exercise), and psychological health factors (memory, self-care cognition, and anxiety). Related clinical and nursing applications were also discussed. |
| first_indexed | 2024-12-20T05:06:16Z |
| format | Article |
| id | doaj.art-b8855b3507314fe2b7de6654ed8c09db |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-12-20T05:06:16Z |
| publishDate | 2020-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-b8855b3507314fe2b7de6654ed8c09db2022-12-21T19:52:24ZengFrontiers Media S.A.Frontiers in Psychology1664-10782020-09-011110.3389/fpsyg.2020.02217558683Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral PerspectiveZhixiong Yan0Xia Zou1Xia Zou2Xiaohui Hou3Psychology Department, Nanning Normal University, Nanning, ChinaGuangxi College for Preschool Education, Nanning, ChinaFaculty of Industrial Education and Technology, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, ThailandPsychology Department, Nanning Normal University, Nanning, ChinaTo unravel the combined effect of risk and protective factors that may contribute to preserve or impair cognitive status, this prospective cohort study systematically investigated a cluster of factors in elders aged 75 years and older from Guangxi Longitudinal Cohort (GLC) dataset. GLC has tracked 630 oldest-elders for two times within 2 years and will continue to follow two times in the next 4 years. At baseline geriatric assessment, sociodemographic information (e.g., education, Mandarin, marriage, and income), physical status [body mass index (BMI), chronic disease/medicine], lifestyle factors (smoking, alcohol, and exercise), and self-rated mental health (self-care, well-being, anxiety) were recorded by online interview. With 2 years’ follow-up, Mini-Mental State Examination (MMSE) and memory test were performed through person-to-person interview. The performance of MMSE was applied to represent the responder’s cognitive status which classified into cognitive impairment and normal group based on a cutoff point of 20. An age-related cognitive declining trend of 15 stratified factors was observed, though with a small effect size (R-square: 0.001–0.15). The odds of exposure or non-exposure on factors (memory, self-care, exercise, income, education, and literacy) had a significantly different effect on cognitive impairment through multivariate analysis after adjusting other confounding variables. Through stepwise multiple logistic regression analysis, the following 12 factors/index would be integrated to predict cognitive impairment: gender, physical health factors (BMI, chronic disease), socioeconomic and lifestyle factors (education, literacy, Mandarin, marriage, income, and exercise), and psychological health factors (memory, self-care cognition, and anxiety). Related clinical and nursing applications were also discussed.https://www.frontiersin.org/article/10.3389/fpsyg.2020.02217/fullcognitive impairmentprotective/risk factorselderly populationlifestylelogistic regression |
| spellingShingle | Zhixiong Yan Xia Zou Xia Zou Xiaohui Hou Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral Perspective Frontiers in Psychology cognitive impairment protective/risk factors elderly population lifestyle logistic regression |
| title | Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral Perspective |
| title_full | Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral Perspective |
| title_fullStr | Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral Perspective |
| title_full_unstemmed | Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral Perspective |
| title_short | Combined Factors for Predicting Cognitive Impairment in Elderly Population Aged 75 Years and Older: From a Behavioral Perspective |
| title_sort | combined factors for predicting cognitive impairment in elderly population aged 75 years and older from a behavioral perspective |
| topic | cognitive impairment protective/risk factors elderly population lifestyle logistic regression |
| url | https://www.frontiersin.org/article/10.3389/fpsyg.2020.02217/full |
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