Physical activity trajectories and cognitive decline among older adults in China: a longitudinal cohort study.

We aimed to characterize physical activity (PA) trajectories across adulthood and to estimate their association with incident hypertension risk. Data were obtained from the China Health and Nutrition Survey (CHNS) conducted during 2004-2011. Group-based trajectory modeling (GBTM) was used to identify distinct groups of PA trajectories. The Cox proportional hazards model was used to investigate the association. A total of 11,162 participants whose PA was repeatedly estimated by self-report from questionnaires two to four times in the CHNS were included in our study. During the 5.4 years of follow-up, 3824 incident hypertension cases were identified. Five distinct PA trajectories were identified in men: light and slight decline, light and gradual decline then sharp rise, light to medium-heavy then decline, medium-heavy and gradual decline, and heavy and sharp decline. Two distinct PA trajectories were identified in women: light and stable, and medium and gradual decline. The PA trajectory of medium-heavy and gradual decline was significantly associated with decreased risk of hypertension in men, with the hazard ratios and 95% confidence intervals (CI) being 0.80 (0.63, 0.99), 0.74 (0.59, 0.93), 0.76 (0.60, 0.96), and 0.70 (0.55, 0.88) in models 1-4, respectively. Our study identified five distinct long-term PA trajectories in men and two distinct trajectories in women. The PA trajectory of medium-heavy PA in early adulthood followed by gradual decline was found to be significantly associated with a decreased risk of hypertension in later life in men.

Background: The impact of retirement on physical activity among older individuals remains ambiguous. This study aims to investigate the influence of retirement on physical activity and delineate the trajectories of physical activity changes during the retirement transition among elderly Chinese residents. Additionally, we endeavor to examine the factors that contribute to each trajectory. Methods: This longitudinal cohort study used data from four surveys of the China Health and Retirement Longitudinal Study and included a sample of 428 individuals who underwent formal retirement and provided information on physical activity. We employed generalized estimating equation to explore the impact of the retirement transition on physical activity among Chinese older adults. Latent class growth analysis was used to identify distinct trajectories of physical activity, and binary logistic regression was performed to identify pre-retirement factors influencing changes in physical activity. Results: Our findings indicate that retirement can lead to a decline in physical activity among older Chinese residents (OR=0.85, 95%CI 0.75~0.97). We identified three distinct trajectories of physical activity during the retirement transition: Trajectory 1 – “sustained low level of physical activity” (7.94%); Trajectory 2 – “middle level of physical activity with gradual decline” (69.16%); Trajectory 3 – “sustained high level of physical activity with significant fluctuations” (22.90%). Furthermore, we discovered that individuals in the “middle level of physical activity and gradual decline” trajectory were more likely to have an annual income exceeding 40,000 yuan (OR=9.69, 95%CI 1.12~83.63), reside in urban areas (OR=2.27, 95%CI 1.14~4.52), and have a fondness for playing Mahjong (OR=2.42, 95%CI 1.18~5.00) compared to those in the “sustained high level of physical activity with significant fluctuations” trajectory. Additionally, having an annual income exceeding 40,000 yuan (OR=19.67, 95%CI 1.30~298.61) predicted membership in the “sustained low level of physical activity” trajectory when compared to the “sustained high level of physical activity with significant fluctuations” trajectory. Conclusion: Retirement represents a substantial milestone in the life course and is associated with notable alterations in physical activity patterns. Among older Chinese residents, the trajectories of physical activity during the retirement transition exhibit diverse paths and are influenced by pre-retirement factors, including annual income, residential location, and hobbies. The findings of this study have important implications for the formulation of policies aimed at promoting healthy aging among individuals approaching retirement age.

As individuals age, they commonly experience reduced physical activity and cognitive decline. While evidence, there is limited trajectory research on their concurrent progression and interrelation in individuals over 55 years old. The data was collected from 5,765 individuals aged over 55 years who participated in the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2020. Physical activity was measured by IPAQ, cognitive function by episodic memory, and mental intactness score. Separate sets of group-based trajectory models were fitted to identify physical activity trajectories and cognitive function trajectories. Multivariate logistic regression was used to estimate the association between baseline characteristics and each set of trajectories. Group-based dual trajectory modeling (GBDTM) was applied to quantify these associations. GBDTM identified three distinct trajectory groups for physical activity and cognitive outcomes. The physical activity trajectories were classified as "Persistently low physical activity" (74.2%), "Decreasing physical activity" (13.7%), and "Rising physical activity" (12.1%). Similarly, cognitive function trajectories were categorized as "Persistently low cognitive function" (22.2%), "Persistently moderate cognitive function" (37.9%), and "Persistently high cognitive function" (39.9%). Notably, 15.6% of participants followed the trajectories of "Persistently low physical activity" and "Persistently low cognitive function." The presence of a severe decline in physical activity was associated with an increased likelihood of poor cognitive function and vice versa. Age, sex, education, residential status, BMI, and visual impairment were identified as significant predictors for physical activity and cognitive decline. This study found that the GBDTM can determine the consistent trajectories of physical activity and cognitive function trajectories that persistently decline in individuals over 55 years. Analyses of predictive factors can be instrumental in promoting physical activity and delaying cognitive decline.

Purpose: Relevant studies have shown that insufficient physical activity (PA) is associated with the risk of depression in middle-aged and elderly populations, but the relationship between different levels of PA and the risk of depression remains unexplored. Therefore, the objective of this study was to explore the relationship between different levels of PA and depression risk among middle-aged and older adults in China. Methods: The survey data of this study was based on the 2020 China Health and Retirement Longitudinal Study (CHARLS). A total of 13,316 middle-aged and elderly community residents aged 45 years or older with complete values of PA, depression assessment, and key variables were selected as the study subjects, and the PA levels and the prevalence of depression among middle-aged and elderly people were assessed based on the International Physical Activity Questionnaire (IPAQ) and the Center for Epidemiologic Studies Depression Scale (CESD), respectively. Multifactorial binary logistic regression models were developed to explore the effects of different levels of PA on the risk of depression in middle-aged and older adults, and sensitivity and stratification analyses were performed. Restricted cubic spline analysis was used to examine the possible non-linear relationship between physical activity and depression risk. Results: Multifactorial binary logistic regression analyses revealed that the odds of depression in middle-aged and older adults who participated in moderate and high levels of PA, using low levels of PA as a reference, was reduced by 15% [OR=0.85, 95% CI (0.73, 1), P=0.045] and 5% [OR=0.95, 95% CI (0.82, 1.11), P=0.541]. Sensitivity analyses showed that moderate levels of PA significantly reduced the risk of depression in middle-aged and older adults, indicating the robustness of the results. Stratified analyses showed that, compared with low levels of PA, moderate levels of PA significantly reduced the odds of depression in female middle-aged and older adults by 23% [OR=0.77, 95% CI (0.63, 0.95), P=0.013], and reduced the odds of depression by 30% in middle-aged and older adults living in inner-city areas [OR=0.7, 95% CI (0.54, 0.91), P=0.008], and reduced the odds of depression by 28% in 60- to 69-year-olds [OR=0.72, 95% CI (0.54, 0.94), P=0.017]. Restricted cubic spline plot results showed a non-linear dose relationship between PA levels and depression risk in middle-aged and older adults (P non-linearity=0.002). Conclusion: The study indicated that participation in moderate levels of PA associates with a reduction in the probability of depression in Chinese middle-aged and elderly people compared to low–high levels of PA.

It remains unclear whether sleep duration and physical activity (PA) trajectories in middle-aged and older adults are associated with different risks of cardiovascular diseases (CVDs). This study aimed to explore the trajectories of total sleep duration and PA among middle-aged and older Chinese adults and their impact on CVD risk. This study was based on the China Health and Retirement Longitudinal Study. 12009 adults aged 45 years and older from five waves were included. CVD events were measured by self-reports of heart disease and stroke. We first used group-based trajectory modeling to identify total sleep duration and PA trajectories from 2011 to 2020, and then employed logistic regression models to analyze their risk for CVD. We identified three sleep duration and PA trajectories. The risk of heart disease increased by 33% (OR = 1.31, 95% CI: 1.12-1.53) for the short sleep duration trajectory (vs. moderate sleep duration trajectory), by 40% (OR = 1.40, 95% CI: 1.06-1.84) for the high decreasing PA trajectory, and by 20% (OR = 1.20, 95% CI: 1.01-1.42) for the low stable PA trajectory (vs. high stable PA trajectory), respectively. Similar results for stroke and CVD as the outcomes were also observed, but the higher risk of stroke in the high decreasing PA trajectory group was not statistically significant. The joint effects of sleep and PA showed lower risks of heart disease and stroke in trajectories with moderate or long sleep duration and high stable PA compared with short sleep duration and a low stable PA trajectory. Short total sleep duration, high decreasing PA, and low stable PA trajectories could increase the risk of CVDs among middle-aged and older adults. Long-term moderate to long total sleep durations and high stable PA trajectories might be optimal for preventing CVDs.

BackgroundAlthough physical activity (PA) in pregnancy benefits most women, not much is known about pregnancy-related changes in PA and its association with gestational diabetes mellitus (GDM) risk. The aim of this study was to identify the trajectory of PA during pregnancy and possible associations with the risk of GDM.MethodsThis was a prospective cohort study of 452 pregnant women recruited from 3 health clinics in a southern state of Peninsular Malaysia. PA levels at the first, second, and third trimester were assessed using the Pregnancy Physical Activity Questionnaire. GDM was diagnosed at 24–28 weeks of gestation following the Ministry of Health Malaysia criteria. Group-based trajectory modeling was used to identify PA trajectories. Three multivariate logistic models were used to estimate the odds of trajectory group membership and GDM.ResultsTwo distinct PA trajectories were identified: low PA levels in all intensity of PA and sedentary behavior (Group 1: 61.1%, n = 276) and high PA levels in all intensity of PA as well as sedentary behavior (Group 2: 38.9%, n = 176). Moderate and high intensity PA decreased over the course of pregnancy in both groups. Women in group 2 had significantly higher risk of GDM in two of the estimated logistic models. In all models, significant associations between PA trajectories and GDM were only observed among women with excessive gestational weight gain in the second trimester.ConclusionsWomen with high sedentary behavior were significantly at higher risk of GDM despite high PA levels by intensity and this association was significant only among women with excessive GWG in the second trimester. Participation in high sedentary behavior may outweigh the benefit of engaging in high PA to mitigate the risk of GDM.

BackgroundThe impact of retirement on physical activity among older individuals remains ambiguous. This study aims to investigate the influence of retirement on physical activity and delineate the trajectories of physical activity changes during the retirement transition among elderly Chinese residents. Additionally, we endeavor to examine the factors that contribute to each trajectory.MethodsThis longitudinal cohort study used data from four surveys of the China Health and Retirement Longitudinal Study and included a sample of 428 individuals who underwent formal retirement and provided information on physical activity. We employed generalized estimating equation to explore the impact of the retirement transition on physical activity among Chinese older adults. Latent class growth analysis was used to identify distinct trajectories of physical activity, and binary logistic regression was performed to identify pre-retirement factors influencing changes in physical activity.ResultsOur findings indicate that retirement can lead to a decline in physical activity among older Chinese residents (OR = 0.85, 95%CI 0.75 ~ 0.97). We identified three distinct trajectories of physical activity during the retirement transition: Trajectory 1 – “sustained low level of physical activity” (7.94%); Trajectory 2 – “middle level of physical activity with gradual decline” (69.16%); Trajectory 3 – “sustained high level of physical activity with significant fluctuations” (22.90%). Furthermore, we discovered that individuals in the “middle level of physical activity and gradual decline” trajectory were more likely to have an annual income exceeding 40,000 yuan (OR = 9.69, 95%CI 1.12 ~ 83.63), reside in urban areas (OR = 2.27, 95%CI 1.14 ~ 4.52), and have a fondness for playing Mahjong (OR = 2.42, 95%CI 1.18 ~ 5.00) compared to those in the “sustained high level of physical activity with significant fluctuations” trajectory. Additionally, having an annual income exceeding 40,000 yuan (OR = 19.67, 95%CI 1.30 ~ 298.61) predicted membership in the “sustained low level of physical activity” trajectory when compared to the “sustained high level of physical activity with significant fluctuations” trajectory.ConclusionRetirement represents a substantial milestone in the life course and is associated with notable alterations in physical activity patterns. Among older Chinese residents, the trajectories of physical activity during the retirement transition exhibit diverse paths and are influenced by pre-retirement factors, including annual income, residential location, and hobbies. The findings of this study have important implications for the formulation of policies aimed at promoting healthy aging among individuals approaching retirement age.

Long-term associations between the stability of physical activity trajectories and depressive symptom trajectories among middle-aged and older adults: A multi-trajectory modeling analysis using China Health and Retirement Longitudinal Study data.

The prevalence of cognitive impairment among older adults remains high. It has been proven that social integration is related to cognitive function. However, limited research has examined the association of social integration and its different dimensions with cognitive function trajectories of older adults. The data were from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2013 (T1) to 2018 (T3). A total of 3,977 older adults were included in the final analysis. Cognitive function was measured with items from an adapted Chinese version of the Mini-Mini-Mental Mental State Examination (MMSE), while the measurement of social integration included three dimensions: economic integration, relational integration and community integration. A group-based trajectory model (GBTM) was used to identify cognitive trajectory groups among participants and an unordered multinomial logistic regression was employed to explore the association of baseline social integration and its three dimensions with cognitive function trajectories. Three cognitive function trajectory groups were identified: low-decline group (24.1%), medium-decline group (44.2%) and high-stable group (31.7%). Comparing to the medium-decline trajectory group, older adults with higher social integration scores were more likely to be in the high-stable trajectory group (OR = 1.087, 95%CI: 1.007 ~ 1.174), while less likely to be in the low-decline group (OR = 0.806, 95%CI: 0.736 ~ 0.882). Among the different dimensions of social integration, older adults with higher community integration scores were more likely to be in the high-stable trajectory group (OR = 1.222, 95%CI: 1.026 ~ 1.456); Older adults with higher relational integration scores were less likely to be in the low-decline trajectory group (OR = 0.816, 95%CI: 0.734 ~ 0.906). The economic integration was not found to correlate with the cognitive function trajectories. Stratified analyses revealed that the association between community integration and cognitive trajectories was only significant among older adults aged 60 to 69, and the association between relational integration and cognitive trajectories was only significant among older adults who was agricultural household registration. The developmental trajectories of cognitive function among Chinese older adults are heterogeneous. Social integration is significantly related to the trajectories of cognitive function in Chinese older adults. Measures should be taken to promote social integration of Chinese older adults to reduce the decline of cognitive function.

This study aims to identify and predict latent trajectories of depression and chronic disease among middle-aged and older adults in China using data-driven and interpretable machine learning methods, and to explore key factors that promote healthy aging. To achieve this, we analyzed longitudinal data from 13,073 middle-aged and older adults in the China Health and Retirement Longitudinal Study (CHARLS). Group-based multi-trajectory modeling (GBMTM) was applied to identify latent trajectory groups for depression and chronic disease statuses. Predictive factors included sociodemographic characteristics, health conditions, and lifestyle factors. Machine learning models and dynamic nomograms were used to predict trajectory groups, and model performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and decision curve analysis (DCA). As a result, three main trajectory groups were identified: a normal healthy trajectory group (26.9%), a potential depression and disease increase trajectory group (55.6%), and a high depression and disease burden trajectory group (17.5%). Additionally, the study found that older age, disability, shorter sleep duration, and poor self-reported health status were associated with a higher likelihood of belonging to the latent depression and disease increase trajectory group or the high disease burden trajectory group, particularly among urban women. In conclusion, this study demonstrates that the GBMTM and machine learning models can effectively identify and predict depression and chronic disease trajectories. The identified predictors are crucial for developing targeted interventions to promote healthy aging among the middle-aged and older adults.

Depressive symptoms among middle-aged and older adults in China: The interaction of physical activity and sleep duration.

25-Year Physical Activity Trajectories and Development of Subclinical Coronary Artery Disease as Measured by Coronary Artery Calcium: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

Background: The association between blood pressure (BP) and the risk of cognitive impairment in older adults is limited. It is unclear at which thresholds BP increases the risk of cognitive decline. We aimed to investigate the association between BP and hypertension treatment status with cognitive decline in older adults. Methods: This study used data from the China Health and Retirement Longitudinal Study (CHARLS). Participants were categorized into five groups according to their visit measures of BP: 1) BP <120/80 mm Hg; 2) systolic BP (SBP) 120-129 mm Hg and diastolic BP (DBP) <80 mmHg; 3) BP ≥130/80 and <140/90 mmHg; 4) BP ≥ 140/90 mmHg; 5) and participants with anti-hypertensive medication treatment regardless of their BP levels. The global cognitive Z score was calculated as the average score of episodic memory and mental intactness. Linear mixed models were used to assess the longitudinal association between the BP group, SBP, pulse pressure (PP), and cognitive decline. Results: A total of 11,671 participants from CHARLS were included (47.3% men and mean age 58.6 ± 9.0 years). After adjusting for potential confounders, participants with BP ≥ 140/90 mm Hg but no anti-hypertensive medication were independently associated with accelerated cognitive decline ( β = -0.020, 95% CI -0.028 to -0.012; P <0.001). This trend was not significant for participants on anti-hypertensive treatment regardless of their BP levels. Elevated SBP and PP were found to be independently associated with accelerated cognitive decline ( P < 0.001 for both). However, participants on anti-hypertensive treatment for pre-existing hypertension, but with controlled SBP < 140 mm Hg and PP < 70 mm Hg did not have a significantly increased risk of cognitive decline. Conclusions: Uncontrolled hypertension was associated with subsequent cognitive decline. Effectively controlling BP with anti-hypertensive treatment can preserve cognitive health in older adults.

It has been shown that diabetes is associated with insufficient physical activity among middle-aged and older adults, but the association between different physical activity levels (PAL) and diabetes incidence needs to be further explored. This study aims to explore the correlation and dose-response relationship between different PAL and the diabetes incidence in middle-aged and older adults. Utilizing data from the 2018 China Health and Retirement Longitudinal Study (CHARLS), this cross-sectional analysis included 17,226 middle-aged and older adults aged 45 and above. Binary logistic regression models and restricted cubic spline (RCS) were used to explore the correlation and dose-response relationship between different PAL and the incidence of diabetes in the total middle-aged and older adults population as well as in subgroups. Sensitivity analyses were also performed to verify the robustness of the findings. In the entire study population, compared with the lowest PAL, participants in the third and fourth quartiles PAL saw diabetes incidence significantly reduced by 16% (p = 0.005) and 33% (p < 0.001), respectively (p for trend < 0.001). In subgroup analyses, the fourth quartile PAL significantly reduced the diabetes incidence among females, individuals aged 60-69, and rural residents by 25% (p = 0.011), 38% (p < 0.001) and 28% (p < 0.001), respectively. For males, middle-aged (45-59 years), and urban residents, the third quartile PAL reduced diabetes incidence by 22% (p = 0.004), 24% (p = 0.012), 21% (p = 0.013), respectively. When the fourth quartile PAL was reached, the diabetes incidence was significantly reduced in these populations by 41% (p < 0.001), 39% (p < 0.001), and 41% (p < 0.001), respectively. There was a negative dose-response relationship between physical activity and diabetes incidence in specific Chinese middle-aged and older adults population. In addition, sensitivity analyses indicated the robustness of the findings. Higher PAL was associated with lower diabetes incidence in specific Chinese middle-aged and older adults population. It is feasible to use physical activity to predict diabetes incidence in this demographic, and high PAL may be an effective means of preventing and controlling diabetes.

In 2015, intrinsic capacity (IC) was proposed by the WHO as a new measure for healthy aging. Evidence has shown that physical activity (PA) benefits the physical and mental health of older adults. However, the association between PA and IC among older adults was not well evaluated or reported. This study aims to investigate the association between PA and general and specific IC among Chinese older adults. The study included individuals aged 60 and above from the China Health and Retirement Longitudinal Study in 2015. The IC scores were constructed based on the WHO concept of five domains: psychological capacity, cognition, locomotion, vitality, and sensory abilities. Total PA and leisure PA were measured based on different activity purposes. Linear mixed-effects models and generalized linear mixed-effects models were developed to assess the associations between PA and IC. A total of 3359 participants were included in this study. Older adults who reported some PA were associated with a higher composite IC score, with a mean difference of 0.14 (95% CI: 0.09-0.18, p < 0.001) compared to those who reported no PA. In terms of leisure PA, physically active adults had a higher composite IC score with a mean difference of 0.06 (95% CI: 0.03-0.09, p < 0.001). Older adults with a high level of leisure PA also had a significantly higher composite IC score (diff. in mean = 0.07, 95% CI: 0.01-0.13, p < 0.05) compared to those with low-level leisure PA. In addition, PA was positively and significantly associated with three specific IC domains: locomotion, cognition, and vitality. Improving both general and leisure PA can be an effective way to prevent the decline in IC among older adults, thus reducing the personal and public load of primary healthcare for aging countries such as China.