Social isolation and intrinsic capacity among left-behind older adults in rural China: The chain mediating effect of perceived stress and health-promoting behavior

Factors associated with intrinsic capacity impairment in hospitalized older adults: a latent class analysis

BACKGROUND

Intrinsic capacity (IC) is proposed by the World Health Organization (WHO) to promote healthy aging. Although some studies have examined the factors influencing IC, few studies have comprehensively confirmed lifestyle factors on IC, especially IC impairment patterns. The present study aimed to identify the patterns of IC impairment and explore the lifestyle and other factors associated with different patterns of IC impairment.

METHODS

This cross-sectional study was conducted in a Chinese geriatric hospital. IC was evaluated in five domains according to the recommendations of WHO: cognition, locomotion, vitality, sensory and psychological domains. The sociodemographic and health-related characteristics of participants were assessed.The health promoting lifestyle was evaluated using the Health-Promoting Lifestyle Profile-II scale, including nutrition, health responsibility, interpersonal relationships, physical activity, spiritual growth and stress management. We applied latent class analysis to identify IC impairment patterns and compared basic activities of daily living, instrumental activities of daily living, frailty, quality of life and falls among different IC impairment patterns. Multinomial logistic regression analysis was conducted to identify factors influencing the IC impairment patterns.

RESULTS

Among 237 participants included, the latent class analysis identified three patterns of IC impairment: 44.7% high IC (Class 1), 31.2% intermediate IC mainly locomotor impairment (Class 2) and 24.1% low IC mainly cognitive impairment (Class 3). Older adults in class 1 had the best function ability and quality of life, while class 3 had the highest levels of disability and frailty, the poorest quality of life and a higher prevalence of falls. Compared with class 1, older adults with advanced age (OR = 22.046, 95%CI:1.735-280.149), osteoporosis (OR = 3.377, 95%CI:1.161-9.825), and lower scores in physical activity (OR = 0.842, 95%CI:0.749-0.945), stress management (OR = 0.762, 95%CI:0.585-0.993) and social support (OR = 0.897, 95%CI:0.833-0.965) were more likely to belong to the class 2. Simultaneously, compared with class 1, older adults with advanced age (OR = 104.435, 95%CI:6.038-1806.410), stroke (OR = 3.877, 95%CI:1.172-12.823) and lower scores in physical activity (OR = 0.784, 95%CI:0.667-0.922) and social support (OR = 0.909, 95%CI:0.828-0.998) were more likely to be class 3. In addition, compared with class 2, older adults with a lower score in nutrition (OR = 0.764, 95%CI:0.615-0.950) were more likely to belong to the class 3.

CONCLUSIONS

This study provides evidence that there are heterogeneous IC impairment patterns in older adults and identifies various associated factors in each pattern, including age, stroke, osteoporosis, social support and lifestyle behaviors such as nutrition, physical activity and stress management. It informs stakeholders on which modifiable factors should be targeted through public health policy or early intervention to promote IC and healthy aging in older adults.

Social determinants of intrinsic capacity: A systematic review of observational studies

BACKGROUND

The World Health Organization defined healthy ageing as the maintenance of functional ability with ageing. Intrinsic capacity is a measurement of healthy ageing, and can be shaped by social determinants. However, an overall understanding of how multiple social determinants contribute to intrinsic capacity remains unclear. We aim to summarize observational studies investigating the relationships between social determinants and intrinsic capacity among community-dwelling adults.

METHODS

A systematic search was conducted through Medline, Embase, PsycInfo, Web of Science, and CINAHL until August 14, 2023.

RESULTS

After reviewing 813 articles, we included 21 studies from nine countries in Asia, Europe, and America. Seventeen studies used a cross-sectional design and the others were longitudinal studies. Social determinants related to intrinsic capacity can be classified into five domains, containing socioeconomic status (16, 76.2% of studies), lifestyles (14, 66.7%), psychosocial factors (9, 42.9%), material circumstances (4, 19.0%), and healthcare systems (1, 4.8%). Strong evidence supported that better intrinsic capacity was associated with higher education, higher wealth, more physical activities, no smoking, more social engagement, and being married or partnered. The relationships of intrinsic capacity with dietary patterns and alcohol drinking were contradictory across studies. Research on the associations of working status, housing environments, and healthcare accessibility with intrinsic capacity was insufficient to draw conclusions.

CONCLUSION

These findings highlight roles of socioeconomic status, lifestyles, and psychosocial factors in improving intrinsic capacity thus promoting healthy ageing. Future research is needed to investigate causal relationships between social determinants and intrinsic capacity, especially material circumstances and healthcare systems.

Relationship Between eHealth Literacy and Healthy Aging in Older Chinese People: The Mediating Effect of Health Behaviors

OBJECTIVES

Healthy aging is an important means of promoting the well-being of older individuals. However, no studies have examined the relationship between eHealth literacy and healthy aging or its mechanism. Therefore, this study aimed to examine the relationship between eHealth literacy and healthy aging and the mediating effect of health behaviors in older Chinese individuals.

DESIGN

Cross-sectional study.

SETTING AND PARTICIPANTS

We recruited 2144 older individuals from Jinan, Shandong Province, China.

METHODS

We used the eHealth Literacy Scale to assess eHealth literacy. Healthy aging was evaluated based on multimorbidity, functional limitations, mild cognitive impairment, depressive symptoms, and social isolation. Moreover, health behaviors were assessed using the Health-Promoting Lifestyle Profile. Logistic and linear regression models were used to analyze the relationships between eHealth literacy, healthy aging, and its components. Finally, a structural equation model was used to analyze the mediation.

RESULTS

High eHealth literacy was associated with all healthy aging components (P < .05), including the absence of multimorbidity [odds ratio (OR), 1.014; 95% CI, 1.002-1.025], no functional limitation (OR, 1.035; 95% CI, 1.022-1.047), no mild cognitive impairment (OR, 1.042; 95% CI, 1.024-1.061), no depressive symptoms (OR, 1.049; 95% CI, 1.027-1.072), and no social isolation (OR, 1.033; 95% CI, 1.018-1.048). In the adjusted model, eHealth literacy (β = 0.174; 95% CI, 0.132-0.217) was positively correlated with healthy aging. Health behaviors had a partial mediating effect on the relationship between eHealth literacy and healthy aging.

CONCLUSIONS AND IMPLICATIONS

Higher eHealth literacy was associated with better healthy aging in older Chinese individuals, and health behaviors mediated this relationship. Improving eHealth literacy may be an effective intervention for achieving healthy aging.

Factors influencing the intention for lung cancer screening in high-risk populations for lung cancer

Objective

Utilizing low-dose computed tomography for lung cancer screening has proven effective in reducing lung cancer mortality among high-risk individuals. This study aimed to investigate the health beliefs, knowledge of lung cancer, and cancer prevention behaviors in adults at high risk for lung cancer, with the goal of identifying predictors influencing their intention to undergo lung cancer screening.

Methods

The study utilized a descriptive cross-sectional design. Online questionnaires, including assessments of lung cancer screening health beliefs, knowledge of lung cancer, cancer prevention behaviors, intention to undergo lung cancer screening, and participant characteristics, were distributed to 186 individuals at high risk of lung cancer through a survey link. The data collection period spanned from April 26 to May 3, 2023. Analytical procedures encompassed descriptive statistics, independent t-test, one-way ANOVA, Pearson's correlations, and hierarchical multiple regression.

Results

The mean score for the intention to undergo lung cancer screening in our study was 3.66 out of 5. The regression model explaining the intention to undergo lung cancer screening accounted for 34.7% of the variance. Significant factors identified included stress level (β = 0.20, P = 0.002), perceived risk (β = 0.13, P = 0.040), self-efficacy (β = 0.35, P < 0.001), and engagement in cancer prevention behavior (β = 0.26, P < 0.001).

Conclusions

Healthcare providers should implement psychological interventions and provide education about cancer screening for high-risk individuals, aiming to enhance their perceived risk and self-efficacy, thus promoting a higher likelihood of undergoing screening.