Depressive symptoms and risk of incident cardiometabolic multimorbidity in community-dwelling older adults: The China Health and Retirement Longitudinal Study

Combined influence of depression symptoms and ratio of triglyceride to high-density lipoprotein cholesterol on cardiometabolic multimorbidity: Findings from the China Health and Retirement Longitudinal Study 2011-2018

BACKGROUND

Previous studies had reported depression symptoms and TG/HDLC ratio may share pathophysiological pathway. The aim was to investigate the combined effects of depression symptoms and TG/HDL-C ratio on the risk of CMM.

METHODS

This cohort study extracted data from 2011 to 2018 of CHARLS. The CMM event occurred from 2013 to 2018, defined as suffering from more than one of stroke, cardiac events, and diabetes mellitus. Cox proportional hazards regression models were used to assess the association between the baseline combined effects of depression symptoms and TG/HDL-C ratio with incidence of CMM, stroke, cardiac events, and diabetes mellitus.

RESULTS

A total of 8349 participants (3966 men and 4383 women) were included in the study, with a mean age of 58.5 years. During a 7-year follow-up survey, 370 (4.43 %) participants developed CMM. Compared to individuals with no depression symptoms and low TG/HDLC ratio, the multivariable-adjusted HRs (95%CI) for the new-onset CMM for patients with the depression symptoms alone, high TG/HDLC ratio alone, and depression symptoms and high TG/HDLC ratio were 1.37 (95 % CI = 0.95-1.98), 1.62 (95 % CI = 1.22-2.14), 1.94 (95 % CI = 1.39-2.72), respectively (P < 0.001).

LIMITATIONS

Firstly, potential confounding factors such as dietary intake and nutrition were not collected at the time of study design. Secondly, exposure to the outcome was self-reported, which may cause recall bias or misclassification. Finally, the population was aged ≥45 years, so the results cannot be generalized to all age groups.

CONCLUSION

Our findings indicated that patients with depression and high TG/HDLC ratio had a higher risk of developing CMM.

A predictive model for depression in Chinese middle-aged and elderly people with physical disabilities

BACKGROUND

Middle-aged and older adults with physical disabilities exhibit more common and severe depressive symptoms than those without physical disabilities. Such symptoms can greatly affect the physical and mental health and life expectancy of middle-aged and older persons with disabilities.

METHOD

This study selected 2015 and 2018 data from the China Longitudinal Study of Health and Retirement. After analyzing the effect of age on depression, we used whether middle-aged and older adults with physical disabilities were depressed as the dependent variable and included a total of 24 predictor variables, including demographic factors, health behaviors, physical functioning and socialization, as independent variables. The data were randomly divided into training and validation sets on a 7:3 basis. LASSO regression analysis combined with binary logistic regression analysis was performed in the training set to screen the predictor variables of the model. Construct models in the training set and perform model evaluation, model visualization and internal validation. Perform external validation of the model in the validation set.

RESULT

A total of 1052 middle-aged and elderly persons with physical disabilities were included in this study, and the prevalence of depression in the elderly group > middle-aged group. Restricted triple spline indicated that age had different effects on depression in the middle-aged and elderly groups. LASSO regression analysis combined with binary logistic regression screened out Gender, Location of Residential Address, Shortsightedness, Hearing, Any possible helper in the future, Alcoholic in the Past Year, Difficulty with Using the Toilet, Difficulty with Preparing Hot Meals, and Unable to work due to disability constructed the Chinese Depression Prediction Model for Middle-aged and Older People with Physical Disabilities. The nomogram shows that living in a rural area, lack of assistance, difficulties with activities of daily living, alcohol abuse, visual and hearing impairments, unemployment and being female are risk factors for depression in middle-aged and older persons with physical disabilities. The area under the ROC curve for the model, internal validation and external validation were all greater than 0.70, the mean absolute error was less than 0.02, and the recall and precision were both greater than 0.65, indicating that the model performs well in terms of discriminability, accuracy and generalisation. The DCA curve and net gain curve of the model indicate that the model has high gain in predicting depression.

CONCLUSION

In this study, we showed that being female, living in rural areas, having poor vision and/or hearing, lack of assistance from others, drinking alcohol, having difficulty using the restroom and preparing food, and being unable to work due to a disability were risk factors for depression among middle-aged and older adults with physical disabilities. We developed a depression prediction model to assess the likelihood of depression in Chinese middle-aged and older adults with physical disabilities based on the above risk factors, so that early identification, intervention, and treatment can be provided to middle-aged and older adults with physical disabilities who are at high risk of developing depression.

Temporary relationship between sleep duration and depression and its impact on future risk of cardiovascular disease

BACKGROUND

Although sleep duration and depression were correlated, their temporal sequence and how the sequence influence on future risk of cardiovascular disease (CVD) remained undetermined. This study aimed to explore the temporal relationship between sleep duration and depression, and its association with future CVD risk.

METHODS

We included 10,629 middle-aged and elderly participants with repeated measurements of sleep duration and depressive symptoms (measured by Center for Epidemiological Studies-Depression scale [CESD]) at the first two visits from the China Health and Retirement Longitudinal Study. Cross-lagged analysis and mediation analysis were used to examine the temporal relationship between sleep duration and depression and its impact on future risk of CVD.

RESULTS

The adjusted cross-lagged path coefficient from baseline sleep duration to follow-up CES-D (β1 = -0.191; 95 % confidence interval [CI], -0.239 to -0.142) was significantly greatly than that from baseline CES-D to follow-up sleep duration (β2 = -0.031; 95 % CI, -0.031 to -0.024) (Pdifference < 0.0001). Similarly, the path coefficient from baseline sleep duration to annual changes in CES-D was significantly greater than that from baseline CES-D to annual changes in sleep duration (β1 = -0.093 versus β2 = -0.015, Pdifference < 0.0001). The path coefficient from baseline sleep duration to follow-up CES-D in CVD group was significantly greater than that in those without CVD (Pdifference of β1 = 0.0378). Furthermore, 27.93 % of the total association of sleep duration with CVD was mediated by depression symptoms.

CONCLUSIONS

The findings provide evidence that decrease in sleep duration probably precedes the increased in depressive symptoms, and depression partially mediated the pathway from sleep duration to incident CVD.

Internet use, cardiometabolic multimorbidity, and death in older adults: a multi-cohort study spanning developing and developed countries

BACKGROUND

Internet use is a double-edged sword for older adults' health. Whether internet use can prevent cardiometabolic diseases and death in older adults remains controversial.

METHODS

Four cohorts across China, Mexico, the United States, and Europe were utilized. Internet use was defined using similar questions. Cardiometabolic diseases included diabetes, heart diseases, and stroke, with 2 or more denoting cardiometabolic multimorbidity. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale and Europe-depression scale. The competing risk analysis based on subdistribution hazard regression, random-effects meta-analysis, and mediation analysis were utilized.

RESULTS

A total of 104,422 older adults aged 50 or older were included. Internet users (vs. digital exclusion) were at lower risks of diabetes, stroke, and death, with pooled sHRs (95% CIs) of 0.83 (0.74-0.93), 0.81 (0.71-0.92), and 0.67 (0.52-0.86), respectively, which remained significant in sensitivity analyses. The inverse associations of internet use with new-onset cardiometabolic diseases and death were progressively significant in Mexico, China, the United States, and Europe. For instance, older internet users in Europe were at 14-30% lower cardiometabolic risks and 40% lower risk of death. These associations were partially mediated by reduced depressive symptoms and were more pronounced in those with high socioeconomic status and women. Furthermore, patients with prior cardiometabolic conditions were at about 30% lower risk of death if they used the internet, which was also mediated by reduced depressive symptoms. However, certain cardiometabolic hazards of internet use in those aged < 65 years, with low socioeconomic status, men, and single ones were also observed.

CONCLUSION

Enhancing internet usage in older adults can reduce depressive symptoms and thus reduce the risks of cardiometabolic diseases and death. The balance of internet use, socioeconomic status, and health literacy should be considered when popularizing the internet in older adults.

Value of the short physical performance battery (SPPB) in predicting fall and fall-induced injury among old Chinese adults

BACKGROUND

The short physical performance battery (SPPB) is an easy-to-use tool for fall risk prediction, but its predictive value for falls and fall-induced injuries among community dwellers has not been examined through a large-sample longitudinal study.

METHODS

We analyzed five-round follow-up data (2, 3, 4, 5, 7 years) of the China Health and Retirement Longitudinal Study (CHARLS) (2011-2018). Data concerning falls and fall-induced injuries during multi-round follow-ups were collected through participant self-report. The Cochran-Armitage trend test examined trends in fall incidence rate across SPPB performance levels. Multivariable logistic regression and negative binomial regression models examined associations between SPPB performance and subsequent fall and fall-induced injury. The goodness-of-fit and area under the receiver operating curve (AUC) were used together to quantify the value of the SPPB in predicting fall and fall-induced injury among community-dwelling older adults.

RESULTS

The CHARLS study included 9279, 6153, 4142, 4148, and 3583 eligible adults aged 60 years and older in the five included follow-up time periods. SPPB performance was associated with fall and fall-induced injury in two and three of the five follow-up time periods, respectively (P < 0.05). The goodness-of-fit for all predictive models was poor, with both Cox-Snell R2 and Nagelkerke R2 under 0.10 and AUCs of 0.53-0.57 when using only SPPB as a predictor and with both Cox-Snell R2 and Nagelkerke R2 lower than 0.12 and AUCs of 0.61-0.67 when using SPPB, demographic variables, and self-reported health conditions as predictors together. Sex and age-specific analyses displayed highly similar results.

CONCLUSIONS

Neither use of SPPB alone nor SPPB together with demographic variables and self-reported health conditions appears to offer good predictive performance for falls or fall-induced injuries among community-dwelling older Chinese adults.