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New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis

BACKGROUND: Increasing evidence from high-income countries suggests the risk of cognitive impairment has been declining recently. However, related studies in China have rarely been done, and the results are inconsistent. We analyze the trends in cognitive function among middle-aged and older adults...

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Autores principales: Guo, Shuai, Zheng, Xiao-Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440902/
https://www.ncbi.nlm.nih.gov/pubmed/37605117
http://dx.doi.org/10.1186/s12877-023-04166-9
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author Guo, Shuai
Zheng, Xiao-Ying
author_facet Guo, Shuai
Zheng, Xiao-Ying
author_sort Guo, Shuai
collection PubMed
description BACKGROUND: Increasing evidence from high-income countries suggests the risk of cognitive impairment has been declining recently. However, related studies in China have rarely been done, and the results are inconsistent. We analyze the trends in cognitive function among middle-aged and older adults in China between 2011 and 2018. METHODS: We used data from four waves of the China Health and Retirement Longitudinal Study (CHARLS), including 48918 individuals aged 45 years and older. Cognitive function was assessed using the CHARLS cognitive measures containing episodic memory, orientation, attention, and visuospatial abilities. The hierarchical age-period-cohort (APC) model was used to quantify the separate age, period, and cohort effects on trends in cognitive function. RESULTS: The study sample’s ages ranged from 45 to 105 years (Mean = 59.2, SD = 9.4). Cognitive function declined with age net of period and cohort effects, an apparent acceleration in the rate of cognitive decline after age 65 was found adjusting for individual characteristics. Although period effects on trends in cognitive function remained stable during the study period, hierarchical APC models demonstrated significant cohort variations. Independent of age and period effects, there was a fluctuating trend across cohorts before 1960 and an overall decline across successive cohorts. CONCLUSIONS: Our study indicates that the age effect remains the most crucial factor regarding cognitive decline. Moreover, results demonstrate that cohorts living in social upheaval leading to educational deprivation and/or nutritional deficiency in early life may face a higher risk for cognitive deterioration later in life. Such findings indicate that dementia prevention from a life course perspective and cohort-specific strategies are critical to alleviating the future public-health burdens related to cognitive aging. Ongoing attention should be paid to the role of cross-cohort differences in education on cohort trends in cognition in countries like China that are aging rapidly and have a late start in educational expansion compared to other countries. Other factors, such as environmental stimulation, need to be noticed in younger cohorts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-04166-9.
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spelling pubmed-104409022023-08-22 New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis Guo, Shuai Zheng, Xiao-Ying BMC Geriatr Research BACKGROUND: Increasing evidence from high-income countries suggests the risk of cognitive impairment has been declining recently. However, related studies in China have rarely been done, and the results are inconsistent. We analyze the trends in cognitive function among middle-aged and older adults in China between 2011 and 2018. METHODS: We used data from four waves of the China Health and Retirement Longitudinal Study (CHARLS), including 48918 individuals aged 45 years and older. Cognitive function was assessed using the CHARLS cognitive measures containing episodic memory, orientation, attention, and visuospatial abilities. The hierarchical age-period-cohort (APC) model was used to quantify the separate age, period, and cohort effects on trends in cognitive function. RESULTS: The study sample’s ages ranged from 45 to 105 years (Mean = 59.2, SD = 9.4). Cognitive function declined with age net of period and cohort effects, an apparent acceleration in the rate of cognitive decline after age 65 was found adjusting for individual characteristics. Although period effects on trends in cognitive function remained stable during the study period, hierarchical APC models demonstrated significant cohort variations. Independent of age and period effects, there was a fluctuating trend across cohorts before 1960 and an overall decline across successive cohorts. CONCLUSIONS: Our study indicates that the age effect remains the most crucial factor regarding cognitive decline. Moreover, results demonstrate that cohorts living in social upheaval leading to educational deprivation and/or nutritional deficiency in early life may face a higher risk for cognitive deterioration later in life. Such findings indicate that dementia prevention from a life course perspective and cohort-specific strategies are critical to alleviating the future public-health burdens related to cognitive aging. Ongoing attention should be paid to the role of cross-cohort differences in education on cohort trends in cognition in countries like China that are aging rapidly and have a late start in educational expansion compared to other countries. Other factors, such as environmental stimulation, need to be noticed in younger cohorts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-023-04166-9. BioMed Central 2023-08-21 /pmc/articles/PMC10440902/ /pubmed/37605117 http://dx.doi.org/10.1186/s12877-023-04166-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Guo, Shuai
Zheng, Xiao-Ying
New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis
title New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis
title_full New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis
title_fullStr New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis
title_full_unstemmed New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis
title_short New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis
title_sort new evidence of trends in cognitive function among middle-aged and older adults in china, 2011-2018: an age-period-cohort analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440902/
https://www.ncbi.nlm.nih.gov/pubmed/37605117
http://dx.doi.org/10.1186/s12877-023-04166-9
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