Socioeconomic Status, Frailty, and All-Cause Mortality in Korean Older Adults: A 3-Year Population-Based Prospective Study

Wealth disparity and frailty among community-dwelling older adults in India

Background

Due to the vast socioeconomic diversity among its residents, studying health inequality in India is of particular interest. This study aimed to investigate the wealth-based inequalities in physical frailty and to quantify the contributions of potential predictors of frailty to this inequality.

Methods

Data were drawn from the first wave of the Longitudinal Ageing Study in India (LASI) conducted during 2017–18. Logistic regression analysis was used to examine the association between wealth status and frailty. We used the concentration index to measure the magnitude of wealth-related inequality in frailty. A decomposition analysis based on the logit model was used to assess the contribution of each predictor to the total inequality.

Results

The prevalence of physical frailty was significantly higher among the older adults in the poor group than in the non-poor group [Difference (poor vs. non-poor): 6.4%; p < 0.001]. Regression results indicated that older adults in the poorest group were 23% more likely to be physically frail than those in the richest category [Adjusted odds ratio (AOR) = 1.23; 95% confidence interval (CI): 1.11, 1.38]. The overall concentration index of frailty was 0.058 among the older adults, indicating that frailty is more concentrated among older adults with poor wealth status. Body mass index, wealth index, educational status, and region were the major and significant contributors to the socioeconomic status (SES) related inequalities in frailty.

Conclusions

Results suggest the need for formulating effective prevention and intervention strategies to decelerate the development of physical frailty among older adults in India, especially those with poor socioeconomic background.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14434-9.

The influence of multiple frailty profiles on institutionalization and all-cause mortality in community-living older adults

BACKGROUND

Frailty in older adults is associated with adverse geriatric outcomes. Physical frailty is often accompanied by problems in the cognitive, psychological, and social domains. This study investigated the ability of physical frailty combined with other health domains to predict institutionalization and mortality.

METHODS

A national sample of 9171 Koreans aged 65 years or older were surveyed at baseline in 2008 and 3 year follow-up. Those who were prefrail or frail according to the Fried criteria were conceived to have physical frailty. Psychological frailty, cognitive frailty, and social frailty were defined as having depressive symptoms, cognitive impairment, and social vulnerabilities, respectively, in addition to physical frailty. Using Cox proportional hazards and competing-risks regression, the risk of mortality and institutionalization by the number and profiles of different frailty domains was analysed.

RESULTS

At baseline, the 9171 participants were aged 73.1 (±6.8) years on average (median: 72, range: 65 to 103), and 59.2% were women. Multidomain frailty was highly prevalent (49.3%), with 6.1% concurrently displaying frailty in all four domains (mixed frailty). The risk of negative health outcomes increased with frailty in a higher number of domains with a subhazard ratio (SHR) of 3.48 (95% confidence interval [CI]: 1.83, 6.62; P < 0.001) for institutionalization and a hazard ratio (HR) of 3.95 (95% CI: 2.62, 5.93; P < 0.001) for mortality among those presenting mixed frailty. Psychological frailty (depressive symptoms combined with physical frailty) was strongly predictive of institutionalization (SHR = 2.85; 95% CI: 1.45, 5.59; P = 0.002) and mortality (HR = 2.47; 95% CI: 1.61, 3.78; P < 0.001). When combined with physical frailty and either depressive symptoms or social vulnerabilities, cognitive impairment also exhibited a significantly elevated risk of negative events. Physical frailty alone was not a strong predictor of adverse events, especially for mortality (HR = 1.13; 95% CI: 0.77, 1.67; P = 0.53).

CONCLUSIONS

Co-occurrence of physical frailty with other domains is common in late life. The presence of frailty in multiple domains raises the risk of adverse outcomes, with the effects varying by multidimensional profiles.

Prevalence and Factors Associated with Falls among Older Outpatients

Falls in older people are a major public health issue, as they are associated with increased risks of morbidity and mortality. This study aims to investigate the prevalence and factors associated with falls among older outpatients. A cross-sectional study was conducted in 539 outpatients aged 60 and over at the National Geriatric Hospital, Hanoi, Vietnam. Falls and their associated factors were analyzed by multivariable logistic regression. The prevalence of falls was 23.7% (single fall 17.9%, recurrent falls 5.8%). The majority of falls occurred at home (69.6%) and were caused by a slippery floor (51.6%). After falling, most patients sustained physical injuries (65.6%); notably, women suffered more severe injuries than men. Alcohol consumption, using psychotropic medications, having three or more comorbidities, hypertension, COPD, urinary incontinence, frailty, fear of falling, ADL/IADL limitation, slow walking speed and mobility impairment were significantly associated with falls. Overall, the data indicated that falls were prevalent among older outpatients. Behavior factors, comorbidities, geriatric syndromes and physical function were substantially associated with falls, suggesting that most falls are preventable. Further longitudinal studies of longer periods are needed to comprehensively investigate the risk factors for falls.

Prevalence and predictors of falls in a health-seeking older population: An outpatient-based study

BACKGROUND

Falls are one of the major causes of disability in older people. A wide range of risk factors for falls are described according to setting - inpatient, nursing homes and community. The aim of this study was to identify the risk factors for falls in an outpatient setting.

METHODS

In this cross-sectional observational study, 160 consenting subjects were enrolled randomly, from the Geriatric Medicine outpatient department, All India Institute of Medical Sciences, New Delhi, India. Non-ambulatory, seriously ill subjects were excluded. The subjects underwent brief evaluation including falls and geriatric assessment. They were grouped into fallers and non-fallers. A multivariable logistic regression analysis was used to identify the factors associated with falls.

RESULTS

The prevalence of falls was 23.75% (38/160). Women were proportionately higher (26.31%) in the fallers group vis-à-vis 19.67% in the non-fallers group. After multivariate analysis, opioids (odds ratio [OR] 5.24 [95% CI, 2.0 18-13.611]), vision impairment (OR 2.71 [95% CI, 1.050-07.011]), fear of falling (OR 3.17 [95% CI, 1.167-08.629]), instrumental activity of daily living (IADL) impairment (OR 3.41 [95% CI, 1.251-09.301]), anti-anginal medications (OR 8.90 [95% CI, 0.997-79.564]) and self-employment (OR 5.37 [95% CI, 1.058-27.329]) were associated with falls. Adequate nutrition (OR 0.82 [95% CI, 0.688-00.976]) and caregiver support (OR 0.46 [95% CI, 0.275-00.801]) were protective of falls.

CONCLUSION

We identified the multi-factorial etiology of falls. Patients having any of the above risk factors should undergo detailed fall risk assessment and preventive measures afterwards.

Creating a Culture of Health in Planning and Implementing Innovative Strategies Addressing Non-communicable Chronic Diseases

Ongoing demographic changes are challenging health systems worldwide especially in relation to increasing longevity and the resultant rise of non-communicable diseases (NCDs). To meet these challenges, a paradigm shift to a more proactive approach to health promotion, and maintenance is needed. This new paradigm focuses on creating and implementing an ecological model of Culture of Health. The conceptualization of the Culture of Health is defined as one where good health and well-being flourish across geographic, demographic, and social sectors; fostering healthy equitable communities where citizens have the opportunity to make choices and be co-producers of healthy lifestyles. Based on Antonovsky's Salutogenesis model which asserts that the experience of health moves along a continuum across the lifespan, we will identify the key drivers for achieving a Culture of Health. These include mindset/expectations, sense of community, and civic engagement. The present article discusses these drivers and identifies areas where policy and research actions are needed to advance positive change on population health and well-being. We highlight empirical evidence of drivers within the EU guided by the activities within the thematic Action Groups of the European Innovation Partnership on Active and Healthy Aging (EIP on AHA), focusing on Lifespan Health Promotion and Prevention of Age-Related Frailty and Disease (A3 Action Group). We will specifically focus on the effect of Culture on Health, highlighting cross-cutting drivers across domains such as innovations at the individual and community level, and in synergies with business, policy, and research entities. We will present examples of drivers for creating a Culture of Health, the barriers, the remaining gaps, and areas of future research to achieve an inclusive and sustainable asset-based community.

Social Interventions to Prevent Heat-Related Mortality in the Older Adult in Rome, Italy: A Quasi-Experimental Study

This study focuses on the impact of a program aimed at reducing heat-related mortality among older adults residing in central Rome by counteracting social isolation. The mortality of citizens over the age of 75 living in three Urban Areas (UAs) located in central Rome is compared with that of the residents of four adjacent UAs during the summer of 2015. The data, broken down by UA, were provided by the Statistical Office of the Municipality of Rome, which gathers them on a routine basis. During the summer of 2015, 167 deaths were recorded in those UAs in which the Long Live the Elderly (LLE) program was active and 169 in those in which it was not, implying cumulative mortality rates of 25‰ (SD ± 1.4; Cl 95%: 23–29) and 29‰ (SD ± 6.7; Cl 95%: 17–43), respectively. Relative to the summer of 2014, the increase of deaths during the summer of 2015 was greater in UAs in which the LLE program had not been implemented (+97.3% vs. +48.8%). In conclusion, the paper shows the impact of a community-based active monitoring program, focused on strengthening individual relationship networks and the social capital of the community, on mortality in those over 75 during heat waves.