Correlates of cognitive impairment in the elderly in China: A cross-sectional study

Fat mass in postmenopausal women with osteoporosis is associated with cognitive function

Postmenopausal women undergo significant changes in endogenous hormones, which lead to reduced bone mineral density (BMD) and alterations in body composition. However, the relationship between body composition and cognitive function in this demographic has not yet been explored. This study aims to examine this relationship in postmenopausal women with osteoporosis.This survey will involve 120 postmenopausal women with osteoporosis. Dual-energy X-ray absorptiometry (DXA) will be used to assess L1-L4 BMD, fat mass (FM), trunk fat mass (TFM), fat-free mass (FFM), and appendicular skeletal muscle mass (ASMM). The relationship between body composition and cognitive function will be analyzed using t-tests and multiple linear regression.Our findings suggest that in postmenopausal women with osteoporosis, cognitive function (MMSE score) is positively correlated with body composition indicators such as FM and BMD, and positively correlated with educational level, but negatively correlated with age. FM plays a significant role in influencing cognitive function and is a crucial indicator of body composition in postmenopausal women with osteoporosis.

Analysis of the Prevalence of Mild Cognitive Impairment and its Influencing Factors in the Elderly Population in Huzhou City

BACKGROUND

Mild cognitive impairment (MCI) is a critical stage in the development of Alzheimer's disease, and early intervention in patients during this stage may reverse or delay their disease progression. As one of the regions with severe aging in China, it is necessary to understand the prevalence of MCI in Huzhou and adopt effective intervention measures. The study was aimed to investigate the prevalence rate and influencing factors of MCI in the elderly population in Huzhou city.

METHODS

A cross-sectional study was conducted involving 800 elderly residents of Huzhou city. The Montreal Cognitive Assessment (MoCA) and the activity of daily living (ADL) were used to assess the occurrence of MCI in the elderly. The influencing factors of MCI were investigated by univariate analysis and multi-factor analysis.

RESULTS

A total of 800 questionnaires were sent out in this survey, and 778 were effectively collected, with an effective recovery rate of 97.25%. Among 778 elderly people in Huzhou city, 668 had normal cognitive function, 82 had MCI, and 28 had dementia, the prevalence rate of MCI was 10.54% (82/778). According to the presence or absence of MCI, the patients were divided into an MCI group (n = 82) and a non-MCI group (n = 668). Female (p = 0.026), high age (p = 0.009), low Community Screening Instrument for Dementia (CSI-D) score (p = 0.007), high Dementia Screening Questionnaire (AD8) score (p < 0.001), high Patient Health Questionnaire Depression Scale (PHQ-9) score (p = 0.037) were all risk factors for MCI in the urban elderly population of Huzhou City.

CONCLUSION

The prevalence of MCI in the elderly population in Huzhou City is high, and its occurrence is closely related to many factors. It is necessary to increase attention to the high-risk population of MCI and implement targeted intervention measures to improve their cognitive function and improve the quality of life of the elderly population.

Large inter-arm systolic blood pressure difference is associated with cognitive impairment in older adults: a cross-sectional study in rural southwest China

Background

Studies have shown that both inter-arm blood pressure difference (IABPD) and cognitive impairment are associated with vascular events. However, the relationship between IABPD and cognitive impairment among elderly individuals in rural China remains unclear. This study aims to investigate the association between IABPD and cognitive impairment in rural older adults in Guizhou, southwestern China.

Methods

The study data were obtained from the Cohort Study of the Health Status of Guizhou Rural Older Adults in China (SHGROC). A multi-stage cluster sampling method was employed to select 1,088 rural elderly individuals aged ≥ 60 years from Guizhou Province for questionnaire surveys, physical examinations, and biological sample collection. Cognitive function of participants was assessed using the Mini-Mental State Examination (MMSE). Bilateral blood pressure was measured simultaneously using an automated device, and the IABPD was calculated. Multivariable linear and logistic regression models were used to examine the relationship between IABPD and cognitive impairment.

Results

The overall prevalence of cognitive impairment in the study sample was 27.85%, and it was more common among participants with an IABPD ≥ 10 mmHg (P < 0.05). Multivariable regression analysis revealed that an inter-arm systolic blood pressure difference (IASBPD) ≥ 10 mmHg was independently associated with lower MMSE scores (β = -1.113; 95% CI: -2.120, -0.106; P = 0.030) and a higher risk of cognitive impairment (OR = 1.902; 95% CI: 1.189, 3.040; P = 0.007). Additionally, a dose-response relationship was observed between IASBPD and the risk of cognitive impairment, with a linear positive correlation. Further subgroup analysis indicated that the relationship between IASBPD and cognitive impairment was modified by sex, smoking, and regular exercise (P for interaction < 0.05).

Conclusion

IASBPD ≥ 10 mmHg is associated with an increased risk of cognitive impairment in rural Chinese older adults. This suggested that IASBPD may provide a reference for early identification of individuals at risk of cognitive impairment.

Related factors of sarcopenia risk in Chinese older people - a cross-sectional study

Numerous factors, including age chronic disease, level of education, and depression, affect the health and function of skeletal muscles. However, it is still unclear which factors affect skeletal muscle health in older age groups across age range segments. Decision tree and logistic regression models were employed in this study to examine the factors that influence older adults' likelihood of developing sarcopenia. The database information of the China Health and Retirement Longitudinal Study (CHARLS) in 2015 was selected, and a sample of 2965 people who met the inclusion criteria was screened. Logistic regression research revealed that while height (p = 0.001, OR:0.979, 95%CI:0.967-0.992), triglycerides (p = 0.036, OR:0.999,95%CI:0.998-1.000), level of education (p = 0.004, OR:0.684,95%CI:0.530-0.883), and endowment insurance (p = 0.003, OR:0.598,95%CI: 0.427-0.839) were protective variables against sarcopenia in older adults, age (p < 0.001, OR:1.094,95%CI:1.079-1.110), depression (p = 0.003, OR:1.283,95%CI:1.089-1.512), and chronic disease(p < 0.012, OR:1.266,95%CI: 1.054-1.522) were risk factors for the condition. According to the decision tree model, the biggest determinant of an older person's chance of developing sarcopenia is age, which is followed by social communication, depression, chronic disease, level of education, and endowment insurance. In the aging Chinese population, sarcopenia risk is positively correlated with age, depression, and chronic disease, while it is adversely correlated with height, triglycerides, level of education, and endowment insurance. Level of education is the primary factor determining the risk of sarcopenia in older adults aged 60-69, while endowment insurance is the primary factor influencing the risk of sarcopenia in older adults aged 70-79. To prevent and intervene earlier in the beginning and progression of sarcopenia in the elderly, it is advised that knowledge of the condition be raised among the older population.

Establishment of a mild cognitive impairment risk model in middle-aged and older adults: a longitudinal study

BACKGROUND

Early identification individuals at high risk of mild cognitive impairment (MCI) is essential for prevention and intervention strategies of dementia, such as Alzheimer's disease. MCI prediction considering the interdependence of predictors in longitudinal data needs to be further explored. We aimed to employ machine learning (ML) to develop and verify a prediction model of MCI.

METHODS

In a longitudinal population-based cohort of China Health and Retirement Longitudinal Study (CHARLS), 8390 non-MCI participants were enrolled. The diagnosis of MCI was based on the aging-associated cognitive decline (AACD), and 13 factors (gender, education, marital status, residence, diabetes, hypertension, depression, hearing impairment, social isolation, physical activity, drinking status, body mass index and expenditure) were finally selected as predictors. We implemented a long short-term memory (LSTM) to predict the MCI risks in middle-aged and older adults within 7 years. The Receiver Operating Characteristic curve (ROC) and calibration curve were used to evaluate the performance of the model.

RESULTS

Through 7 years of follow-up, 1925 participants developed MCI. The model for all incident MCI achieved an AUC of 0.774, and its deployment to the participants followed 2, 4, and 7 years achieved results of 0.739, 0.747, and 0.750, respectively. The model was well-calibrated with predicted probabilities plotted against the observed proportions of cognitive impairment. Education level, gender, marital status, and depression contributed most to the prediction of MCI.

CONCLUSIONS

This model could be widely applied to medical institutions, even in the community, to identify middle-aged and older adults at high risk of MCI.

An analysis of factors influencing cognitive dysfunction among older adults in Northwest China based on logistic regression and decision tree modelling

BACKGROUND

Cognitive dysfunction is one of the leading causes of disability and dependence in older adults and is a major economic burden on the public health system. The aim of this study was to investigate the risk factors for cognitive dysfunction and their predictive value in older adults in Northwest China.

METHODS

A cross-sectional study was conducted using a multistage sampling method. The questionnaires were distributed through the Elderly Disability Monitoring Platform to older adults aged 60 years and above in Northwest China, who were divided into cognitive dysfunction and normal cognitive function groups. In addition to univariate analyses, logistic regression and decision tree modelling were used to construct a model to identify factors that can predict the occurrence of cognitive dysfunction in older adults.

RESULTS

A total of 12,494 valid questionnaires were collected, including 2617 from participants in the cognitive dysfunction group and 9877 from participants in the normal cognitive function group. Univariate analysis revealed that ethnicity, BMI, age, educational attainment, marital status, type of residence, residency status, current work status, main economic source, type of chronic disease, long-term use of medication, alcohol consumption, participation in social activities, exercise status, social support, total scores on the Balanced Test Assessment, total scores on the Gait Speed Assessment total score, and activities of daily living (ADL) were significantly different between the two groups (all P < 0.05). According to logistic regression analyses, ethnicity, BMI, educational attainment, marital status, residency, main source of income, chronic diseases, annual medical examination, alcohol consumption, exercise status, total scores on the Balanced Test Assessment, and activities of daily living (ADLs) were found to influence cognitive dysfunction in older adults (all P < 0.05). In the decision tree model, the ability to perform activities of daily living was the root node, followed by total scores on the Balanced Test Assessment, marital status, educational attainment, age, annual medical examination, and ethnicity.

CONCLUSIONS

Traditional risk factors (including BMI, literacy, and alcohol consumption) and potentially modifiable risk factors (including balance function, ability to care for oneself in daily life, and widowhood) have a significant impact on the increased risk of cognitive dysfunction in older adults in Northwest China. The use of decision tree models can help health care workers better assess cognitive function in older adults and develop personalized interventions. Further research could help to gain insight into the mechanisms of cognitive dysfunction and provide new avenues for prevention and intervention.

Association between disability and cognitive function in older Chinese people: a moderated mediation of social relationships and depressive symptoms

Objective

Many previous studies have found that disability leads to cognitive impairment, and in order to better understand the underlying mechanisms between disability and cognitive impairment, the present study aimed to investigate the moderating role of social relationships, including their role as mediators between disability and cognitive impairment in depressive symptoms.

Study design

This is a cross-sectional study.

Methods

A total of 5,699 Chinese older adults from the 2018 China Longitudinal Healthy Longevity Survey (CLHLS) were included in this study, and PROCESS macro was used to perform simple mediator and moderator mediator analyses, which were used to analyze the relationship between depressive symptoms and social relationships between disability and cognitive impairment.

Results

The results of this study showed significant correlations between disability, cognitive impairment, depressive symptoms, and social relationships, and that depressive symptoms mediated the relationship between disability and cognitive functioning [B = -0.232; 95% CI: (-0.304, -0.164)], and that social relationships mediated disability and cognitive functioning through pathway a (Disability-Depressive Symptoms) [B = 0.190; 95% CI: (0.020, 0.036)], path b (depressive symptoms-cognitive impairment) [B = 0.029; 95% CI: (0.015, 0.042)], and path c' (incapacitation-cognitive impairment) [B = 0.492; 95% CI: (0.298, 0.685)] to modulate the effect of incapacitation on cognitive impairment. In addition, social activities and social networks moderated the mediation model directly or indirectly, whereas social support moderated only the direct effect.

Conclusion

This study explains the intrinsic link between incapacitation and cognitive impairment in Chinese older adults, and that social relationships and depressive symptoms can directly or indirectly modulate the effects between them. This provides a basis for healthcare professionals to be able to better develop interventions that can be used to improve the level of cognitive functioning and mental health of older adults.

Exploring relevant factors of cognitive impairment in the elderly Chinese population using Lasso regression and Bayesian networks

Older adults are highly susceptible to developing cognitive impairment(CI). Various factors contribute to the prevalence of CI, but the potential relationships among these factors remain unclear. This study aims to explore the relevant factors associated with CI in Chinese older adults and analyze the potential relationships between CI and these factors.We analyzed the data on 6886 older adults aged≥60 from the China Health and Retirement Longitudinal Study (CHARLS) 2018. Lasso regression was initially used to screening variables. Bayesian Networks(BNs) were used to identify the correlates of CI and potential associations between factors. After screening with Lasso regression, 11 variables were finally included in the BNs. The BNs, by establishing a complex network relationship, revealed that age, education, and indoor air pollution were the direct correlates affecting the occurrence of CI in older adults. It also indicated that marital status indirectly influenced CI through age, and residence indirectly linked to CI through two pathways: indoor air pollution and education.Our findings underscore the effectiveness of BNs in unveiling the intricate network linkages among CI and its associated factors, holding promising applications. It can serve as a reference for public health departments to address the prevention of CI in the elderly.

Cognitive function and its associated factors among patients with cancer pain: a multicentre cross-sectional study in China

OBJECTIVE

This research aimed to assess the levels of cognitive function and its contributing factors among individuals experiencing cancer pain (CP) in mainland China.

DESIGN

A descriptive, cross-sectional study.

SETTING

The investigation was undertaken within three tertiary oncology hospitals.

PARTICIPANTS

We included 220 hospitalised individuals who reported experiencing cancer-related pain and consented to complete the research questionnaires.

OUTCOME MEASURES

The collected data encompassed sociodemographic and clinical variables, augmented by results from validated questionnaires. Cognitive impairment (CI) was evaluated using the Functional Assessment of Cancer Therapy-Cognitive (FACT-Cog) scale, with scores ranging from 0 to 148. Sleep quality, depression and anxiety were assessed through the Pittsburgh Sleep Quality Index, the Patient Health Questionnaire-9 and the Generalised Anxiety Disorder-7, respectively. A binary logistic regression model was used to identify factors associated with CI in individuals with CP.

RESULTS

Of the 225 individuals approached, 220 (97.8%) participated in the study. The mean FACT-Cog score for those with CP was 101.29 (SD=25.24; range=25-148). The prevalence of CI among these individuals was 35.90%. Sleep quality was rated below medium in 45% of participants with CP. More than moderate pain was reported by 28.2%, with 64.6% experiencing depression and 38.6% experiencing anxiety. Increased odds of developing CI were observed in those with CP (OR 1.422, 95% CI 1.129 to 1.841), depression (OR 1.119, 95% CI 1.029 to 1.2117), anxiety (OR 1.107, 95% CI 1.005 to 1.220), advancing age (OR 1.042, 95% CI 1.013 to 1.073), poor sleep quality (OR 1.126, 95% CI 1.013 to 1.252) and a history of smoking (OR 3.811, 95% CI 1.668 to 8.707).

CONCLUSIONS

CI associated with CP is notably prevalent in China. Those older, with a smoking history, inadequate sleep, more severe pain, depression and anxiety, have a heightened risk of CI. Consequently, interventions need to be personalised, addressing these key determinants.

Relationship Between Physical Exercise and Cognitive Impairment Among Older Adults with Type 2 Diabetes: Chain Mediating Roles of Sleep Quality and Depression

Objective

Although physical exercise has been shown to boost physical, psychological, and psychiatric conditions in older adults, there is a relative lack of research on the mechanisms involved in this process for older adults with type 2 diabetes mellitus (T2DM). We thus evaluated whether sleep quality and depression mediated the relationship between physical exercise and cognitive impairment in older adults with T2DM by focusing on the exercise-physiology-psychology and psychiatry connection.

Methods

Self-reported data were collected from 2646 older adults with T2DM in Weifang, Shandong, China. Regression and bootstrap analyses were conducted to explore the chain mediator model including physical exercise, cognitive impairment, sleep quality, and depression.

Results

Engaging in physical exercise (coefficient = -0.6858, p < 0.001), high levels of sleep quality (coefficient = -0.3397, p = 0.015), and low levels of depression (coefficient = 0.3866, p < 0.001) were significantly associated with a low level of cognitive impairment. Sleep quality and depression mediated the chain effect between physical exercise and cognitive impairment (total effect = -1.0732, 95% CI [-1.3652, -0.7862]; direct effect = -0.6858, 95% CI [-0.9702, -0.3974]; indirect effect = -0.3875, 95% CI [-0.5369, -0.2521]).

Conclusion

Physical exercise may improve sleep quality in older adults with T2DM, alleviating depression and delaying the development of cognitive impairment. Physical exercise can enhance patients' ability to resist depression and cognitive impairment, and creating comfortable sleep environments can also reinforce the effects of this process. These findings have important implications for promoting healthy aging in older adults with T2DM.

High-risk population and factors of stroke has changed among middle-aged and elderly Chinese-Evidence from 1989 to 2015

Background

Stroke is an acute cerebrovascular disease with high mortality and disability. This study aimed to investigate the trend of stroke prevalence from 1989 to 2015 in China, explore the transition of high-risk population and high-risk factors, and provide some evidence to develop more targeted stroke intervention strategies.

Material and methods

We derived the baseline data from China Health and Nutrition Survey (CHNS). Participants responded to face-to-face interviews and examinations containing demographic information, behavioral health information, disease history, and physical examination. We applied chi-square test, shapley value decomposition model, and decision tree model to evaluate the changes of high-risk population and high-risk factors of stroke.

Results

Across 42,419 middle-aged and elderly residents, the prevalence of stroke was decreasing from 1989 to 2015. Hypertension was the leading risk factor of stroke, while its contribution rate was weakened with the increasing of medicine taking rate. As the second risk factor of stroke, the contribution of age decreased either. Meanwhile, the contribution rate of historical health factors, lifestyle factors, and regional factors, such as body mass index, diabetes, and living area to the impact of stroke was increasing. In addition, the first high-risk population of stroke changed from hypertension patients aged 75 years and above to without spouse residents living in stroke belt such as Beijing and Liaoning. The second risk population of stroke transformed from male hypertensive patients under 75 years old into male hypertensive patients living in urban. The third high-risk group turned from the elderly aged 75 and above into the female patients with hypertension and diabetes.

Conclusions

This study demonstrated that the high-risk population and high-risk factors of stroke changed in China and revealed the direction and internal mechanism of transition of stroke. Targeted stroke intervention strategies should be renewed. Health education for the high-risk population of stroke should be carried out, healthy living habits need be advocated, and the use of antihypertensive drugs for the hypertensive patients should be standardized.