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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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The study sample\u2019s 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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>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.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12877-023-04166-9","type":"journal-article","created":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T09:02:07Z","timestamp":1692608527000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["New evidence of trends in cognitive function among middle-aged and older adults in China, 2011-2018: an age-period-cohort analysis"],"prefix":"10.1186","volume":"23","author":[{"given":"Shuai","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Ying","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,8,21]]},"reference":[{"issue":"10248","key":"4166_CR1","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1016\/s0140-6736(20)30367-6","volume":"396","author":"G Livingston","year":"2020","unstructured":"Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. 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