Successful Aging as a Predictor of Long-Term Care Among Oldest Old: The Vitality 90+ Study

The Role of Life Satisfaction and Optimism for Successful Aging in Mid and Late Life

Guided by the Rowe and Kahn model, the current study examined the longitudinal association of objective and subjective components of successful aging (SA) with individuals' life satisfaction and level of optimism across adulthood aiming to validate the related scanty existing research. Data were from waves 2 and 3 (2004-14) of the Midlife in the United States (MIDUS) study. Using structural equation modeling, we examined (N = 2,040) whether subjective life satisfaction (wave 2) has any effect on a composite measure of SA (wave 3) while controlling for baseline sociodemographic and health factors. We also examined the mediation effects of optimism in the above associations. Findings revealed that life satisfaction has a significant positive effect on SA; also, this effect is bidirectional. Further, high optimism positively mediated the bidirectional association between life satisfaction and SA. This study identified life satisfaction and optimism as having potentially positive impacts on achieving SA in middle-aged and older adults.

Predicting successful ageing among older adults seems possible even as far as two decades ahead

BACKGROUND

Successful ageing is the term often used for depicting exceptional ageing and can be measured with multidimensional models including physical, psychological and social wellbeing. The aim of this study was to test multidimensional successful ageing models to investigate whether these models can predict successful ageing, and which individual subcomponents included in the models are most significantly associated with successful ageing.

METHODS

Successful ageing was defined as the ability to live at home without daily care at the age of 84 years or over. Data on the participants' physical, psychological and social wellbeing were gathered at baseline and the follow-up period was 20 years. Four successful ageing models were constructed. Backward stepwise logistic regression analysis was used to identify the individual subcomponents of the models which best predicted successful ageing.

RESULTS

All successful ageing models were able to predict ageing successfully after the 20-year follow-up period. After the backward stepwise logistic regression analysis, three individual subcomponents of four models remained statistically significant and were included in the new model: having no heart disease, having good self-rated health and feeling useful. As a model, using only these three subcomponents, the association with successful ageing was similar to using the full models.

CONCLUSIONS

Multidimensional successful ageing models were able to predict successful ageing after a 20-year follow-up period. However, according to the backward stepwise logistic regression analysis, the three subcomponents (absence of heart disease, good self-rated health and feeling useful) significantly associated with successful ageing performed as well as the multidimensional successful ageing models in predicting ageing successfully.

Cohort profile: The Vitality 90+ Study-a cohort study on health and living conditions of the oldest old in Tampere, Finland

PURPOSE

Vitality 90+ is an ongoing population-based study with repeated cross-sectional data collections. The study was designed to examine trends in health, functioning, living conditions, quality of life and care needs among the oldest old in Finland.

PARTICIPANTS

Nine mailed surveys have been conducted in the city of Tampere between 1995 and 2018. The first three surveys in 1995, 1996 and 1998 included all community-dwelling individuals aged 90 years or older; and the following six surveys in 2001, 2003, 2007, 2010, 2014 and 2018 covered all individuals in Tampere regardless of their living arrangements. In total, the surveys have included 5935 participants (8840 observations). Around 80% of the participants have been women. The participants' age range has been between 90 and 107 years.

FINDINGS TO DATE

The surveys have consistently asked the same questions over time, covering basic sociodemographic factors, morbidity, functioning, self-rated health (SRH), living arrangements, social relations, quality of life, care needs and providers of care. Survey data have been linked with national register data on health and social service use, mortality and medication. The main findings regarding the time trends show an increase in the proportion of people independent in activities of daily living and mobility. Along with improved functioning, the number of chronic conditions has increased, and SRH has shown a tendency to decline. In addition, we have found increasing occupational class inequalities in functioning and SRH over time.

FUTURE PLANS

The next round of data collection will be completed by the end of 2022. The Vitality 90+ Study welcomes research collaborations that fall within the general aims of the project. The research data 1995-2014 are archived at the Finnish Social Science Data Archive and the data for years 2018 and 2022 will be archived in 2023.

Association between car driving and successful ageing. A cross sectional study on the "S.AGES" cohort

BACKGROUND

Assessing successful ageing (SA) is essential to identify modifiable factors in order to enforce health promotion and prevention actions. SA comprises 3 dimensions: an active engagement with life, a low probability of disease and disease-related disability, and a high cognitive and physical functional capacity. Driving seems to be linked to SA as it is a mean to preserve social interactions and requires preserved functional and cognitive status. This study aims to investigate whether driving status can be considered a proxy of SA, by describing determinants associated with driving status in the 65+.

METHODS

This cross-sectional study is ancillary to the S.AGES (Sujets AGÉS-Aged Subjects) study, an observational prospective cohort study which included patients suffering from chronic pain, type-2 diabetes mellitus or atrial fibrillation from 2009 to 2014. SA was defined by the success of three dimensions: physiological comprised of comorbidity and autonomy scores, psychological comprised of cognitive status and emotional state, and a social dimension.

RESULTS

2,098 patients were included of whom 1,226 (58.4%) reported being drivers. 351/2,092 (16.7%) were classified as successful agers: 292/1,266 (23.8%) in the driver group vs. 59/872 (6.8%) in the non-driver group; p < .001. In the final logistic model, after adjustment for relevant variables, SA was associated with driver status OR 1.94 [1.36-2.77].

CONCLUSION

Driving may be considered as a proxy to SA: it reflects elders' independence, cognitive ability and a means to maintain social interactions. To preserve their mobility and enable them to achieve SA, regular screening of driving skills, specific rehabilitation programs are needed. Moreover development and communication on special transports services, communal rides or even driverless car to avoid apprehension around older adults driving could be solutions.

Prediction of successful aging using ensemble machine learning algorithms

BACKGROUND

Aging is a chief risk factor for most chronic illnesses and infirmities. The growth in the aged population increases medical costs, thus imposing a heavy financial burden on families and communities. Successful aging (SA) is a positive and qualitative view of aging. From a biomedical perspective, SA is defined as the absence of diseases or disability disorders. This is distinct from normal aging, which is associated with age-related deterioration in physical and cognitive functions. From a social perspective, SA highlights life satisfaction and individual well-being, usually attained through socialization. It is an abstract and multidimensional concept surrounded by imprecision about its definition and measurement. Our study attempted to find the most effective features of SA as defined by Rowe and Kahn's theory. The determined features were used as input parameters of six machine learning (ML) algorithms to create and validate predictive models for SA.

METHODS

In this retrospective study, the raw data set was first pre-processed; then, based on the data of a sample of 983, five basic ML techniques including artificial neural network, decision tree, support vector machine, Naïve Bayes, and k-nearest neighbors (K-NN) with one ensemble method (that gathers 30 K-NN algorithms as weak learners) were trained. Finally, the prediction result was yielded using the majority vote method based on the output of the generated base models.

RESULTS

The experimental results revealed that the predictive system has been more successful in predicting SA with a 93% precision, 92.40% specificity, 87.80% sensitivity, 90.31% F-measure, 89.62% accuracy, and a ROC of 96.10%, using a five-fold cross-validation procedure.

CONCLUSIONS

Our results showed that ML techniques potentially have satisfactory performance in supporting the SA-related decisions of social and health policymakers. The KNN-based ensemble algorithm is superior to the other ML models in classifying people into SA and non-SA classes.

Physical activity and successful aging among middle-aged and older adults: a systematic review and meta-analysis of cohort studies

Background: We aimed to investigate the association between physical activity and successful aging among middle-aged and older adults and study how this association changes with age and time.

Results: The mean score of Newcastle-Ottawa Scale assessment was 8.0±0.8. Physically active middle-aged and older adults were more likely to age successfully than sedentary adults (OR=1.64, 95%CI: 1.40–1.94). The effect of physical activity was stronger in the younger group (OR=1.71, 95%CI: 1.41–2.08) than on the older group (OR=1.54, 95%CI: 1.13–2.08). However, the protective effect of physical activity reduced annually by approximately 3%.

Conclusions: Physical activity promotes successful aging among middle-aged and older adults especially in the younger population. Being physically active at middle and old age is beneficial to successful aging.

Methods: We searched for the relevant studies in three online databases: Pubmed, Web of Science, and Embase. Fifteen community-based cohort studies were included. The Newcastle-Ottawa Scale assessment Form was used for quality assessment. Overall, 189,192 participants aged 43.9-79.0 years were analyzed. The odds ratio for successful aging of the most physically active group compared with sedentary group was analyzed. Subgroup analysis was conducted by age group. Univariate Meta-regression was performed according to follow-up years.

Social support moderates D-dimer and self-rated successful aging within people with HIV and older adults

Many factors can influence perceptions of successful aging (SA), including social isolation and poor physical health. We hypothesized that social support attenuates the negative effect of plasma D-dimer, a correlate of HIV and aging, on SA. Participants included 230 adults (134 people with HIV; PWH, 96 HIV-), ages 36-65, segregated into age cohorts with up to 5 yearly visits. Multilevel modeling examined longitudinal within-person associations between D-dimer, social support, and SA. Social support moderated the relationship between D-dimer and SA and was significant among PWH and older individuals (ages 56-65), but not HIV- or younger cohorts. This association was significant only at extreme levels of social support, with significant decreases in social support potentiating the negative impact of D-dimer on SA and significant increases in social support facilitating increased SA. Despite declining health, high social support may improve SA in PWH and older adults, and low support may be especially problematic for older adults.