Depressive symptoms increase the risk of falls and injurious falls in Chinese adults aged ≥ 45 years: A 3-year cohort study

Beyond the heart: The role of psychological factors and coping strategies in cardiovascular rehabilitation

BACKGROUND

Cardiovascular disease (CVD) is associated with several risk and protective factors, including psychological variables, such as anxiety and depressive symptoms, stress and coping strategies. These factors may be either a cause or a consequence of CVD and are thought to influence the cardiac rehabilitation (CR) process after acute cardiac event, a multifaceted intervention that is crucial for reducing rehospitalisation and mortality. The main aim of this study was to correlate such psychological components with cardiac outcomes in a sample of 315 CVD referred to an in-hospital CR program.

METHODS

Participants completed self-report questionnaires on perceived stress, anxiety and depressive symptoms, and coping styles.

RESULTS

Females (36.51 %) reported higher levels of depressive symptoms and turning to religion as a coping strategy compared to male. Perceived stress did not differ between male and female, but it was found to be significantly higher in heart failure patients, regardless of gender. Functional outcomes after a CR program were not predicted by any psychological variable, whereas clinical outcomes were predicted by depressive symptoms and coping strategies (social support and positive attitude). Finally, perceived health status was predicted by anxiety, depressive symptoms and avoidance.

CONCLUSIONS

These findings confirm the importance of conducting psychological screening in patients with CVD, as recommended by international guidelines, and highlight the need to provide them with adequate psychological support to reduce the adverse consequences of cardiac disease, and to promote protective attitudes and behaviours through tailored psychological interventions to improve outcomes after a CR program.

Utilizing machine learning to identify fall predictors in India's aging population: findings from the LASI

BACKGROUND

Depression has a detrimental effect on an individual's mental and musculoskeletal strength multiplying the risk of fall incidents. The current study aims to investigate the association between depression and falls in older adults using machine learning (ML) approach and identify its various predictors.

METHODS

Data for the study was derived from the Longitudinal Ageing Study in India, (LASI) conducted in 2017-18 for people aged 45-years and above. The study was carried out on 44,066 individuals. Depression was measured using the CIDI-SF scale. Bivariate cross-tabulations were used to study the prevalence of falls. And its association with depression and other independent factors were assessed using the novel ML, the Conditional inference trees (CIT) method.

RESULTS

Around 10.8 percent of older adults had fall incidents. CIT model predicted region to be a significant predisposing factor for an older adult to experience falls. Multimorbidity, depression, sleep problems, and gender were other prominent factors. The model predicted that, among depressed older adults, falls incidents were around 80 percent higher than non-depressed.

CONCLUSIONS

An association between falls and depression was observed. Depressive symptoms were associated with an increased risk of falls, even after controlling for other co-factors. The CIT method leveraged us to select the most important variables to predict falls with great precision. To prevent and manage falls among the expanding and diverse older-aged population, a multilevel and cross-sectoral approach is required. Mental health, especially depression, should be dealt with greater precautions. Public health enthusiasts should focus on the physical as well as mental health of the country's older adult population.

Causal associations between genetically determined common psychiatric disorders and the risk of falls: evidence from Mendelian randomization

BACKGROUND

The causal associations between psychiatric disorders and falls risk remains uncertain. Consequently, this study aimed to explore the causal relationship between genetically determined three common psychiatric disorders and the risk of falls based on Mendelian randomization (MR).

METHODS

The genome-wide association study (GWAS) data for schizophrenia (SCZ) (N = 320,404), major depressive disorder (MDD) (N = 480,359), and Alzheimer's disease (AD) (N = 63,926) were obtained as exposures. The GWAS data for falls risk (N = 451,179) was obtained as outcome. Univariate Mendelian randomization (UVMR) was used to evaluate the direct causal relationship between SCZ, MDD, AD, and risk of falls. Inverse variance weighting (IVW) was used as the primary analysis method. Sensitivity analysis was performed to assess the validity of the casualty. Multivariate Mendelian randomization (MVMR) analysis was conducted after adjusting body mass index and smoking initiation. Mediating MR was conducted to calculate the mediating effects of potential intermediaries.

RESULTS

UVMR analysis showed that SCZ (OR 1.02, 95% CI 1.01-1.04, p = 8.03E-03) and MDD (OR 1.15, 95% CI 1.08-1.22, p = 1.38E-05) were positively associated with the risk of falls. Sensitivity analysis results were reliable and robust. MVMR results indicated that the relationship between MDD and SCZ and falls risk remained significant. Mediating MR results demonstrated that smoking initiation mediated partial causal effect of SCZ (0.65%, P = 0.03) and MDD (14.82%, P = 2.02E-03) on risk of falls.

CONCLUSIONS

This study provides genetic evidence for a causal relationship of individuals with SCZ and MDD on an increased risk of falls. Healthcare providers should be aware of the risk of falls in MDD and SCZ patients and develop strategies accordingly.