Structure of self-rated health among the oldest old: Analyses in the total population and those living with dementia

Self-rated physical and mental health among older adults 80 years and older: cross-sectional results from a National community sample in Thailand

BACKGROUND

The aim of this study was to assess the self-reported physical health (SRPH) and self-reported mental health (SRMH) of older adults 80 years and older in Thailand.

METHODS

We analyze national cross-sectional data from the Health, Aging and Retirement in Thailand (HART) in 2015. Physical and mental health status was assessed by self-report.

RESULTS

The sample included 927 participants (excluding 101 proxy interviews), 80-117 years, median age 84 years [interquartile range (IQR) 81-86 years]. The median SRPH was 70.0 (IQR = 50.0-80.0), and median SRMH was 80.0 (IQR = 70.0 to 90.0). The prevalence of (good) SRPH was 53.3%, and the prevalence of (good) SRMH was 59.9%. In the final adjusted model, low or no income, living in the Northeastern, Northern and Southern region, daily activity limitations, moderate/severe pain, having one or two or more physical conditions, and low cognitive functioning were negatively associated, and higher physical activity was positively associated with good SRPH. No or low income, residing in the northern region of the country, daily activity limitations, low cognitive functioning, and probable depression were negatively associated with good SRMH, and physical activity was positively associated with good SRMH.

CONCLUSION

SRPH and SRMH was relatively high rated among the oldest old in Thailand, and influenced by various social, economic, and health-related factors. Special attention should be given to those with no or low income, those living in the non-central regions and those having no or low formal social engagement. Health care and other services should improve physical activity, financial support, and physical and mental care management to promote physical and mental well-being of older adults 80 years and older in Thailand.

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.

A machine learning approach to determine the influence of specific health conditions on self-rated health across education groups

BACKGROUND

Self-rated health, a subjective health outcome that summarizes an individual's health conditions in one indicator, is widely used in population health studies. However, despite its demonstrated ability as a predictor of mortality, we still do not full understand the relative importance of the specific health conditions that lead respondents to answer the way they do when asked to rate their overall health. Here, education, because of its ability to identify different social strata, can be an important factor in this self-rating process. The aim of this article is to explore possible differences in association pattern between self-rated health and functional health conditions (IADLs, ADLs), chronic diseases, and mental health (depression) among European women and men between the ages of 65 and 79 according to educational attainment (low, medium, and high).

METHODS

Classification trees (J48 algorithm), an established machine learning technique that has only recently started to be used in social sciences, are used to predict self-rated health outcomes. The data about the aforementioned health conditions among European women and men aged between 65 and 79 comes from the sixth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 27,230).

RESULTS

It is confirmed the high ability to predict respondents' self-rated health by their reports related to their chronic diseases, IADLs, ADLs, and depression. However, in the case of women, these patterns are much more heterogeneous when the level of educational attainment is considered, whereas among men the pattern remains largely the same.

CONCLUSIONS

The same response to the self-rated health question may, in the case of women, represent different health profiles in terms of the health conditions that define it. As such, gendered health inequalities defined by education appear to be evident even in the process of evaluating one's own health status.

Decomposition analysis of health inequalities between the urban and rural oldest-old populations in China: Evidence from a national survey

The number of Chinese oldest-old (aged 80+) is growing rapidly and some studies have shown that the health status is unequal among older persons in different regions. However, to the best of our knowledge, no study to date has analyzed health inequalities among the oldest-old in urban and rural areas in China. This study therefore aimed to examine the correlation between health inequalities among the oldest-old in urban and rural areas of China. From the 8th wave of the Chinese Longitudinal Health Longevity Survey (CLHLS), we selected 8124 oldest-old participants who met the requirements of the study. Chi-square tests were used to analyze the distribution characteristics of indicators and a logistic model was performed to determine the factors associated with different self-rated health (SRH). The Fairlie model was adopted to decompose the causes and related contributions to health inequality. Our results found that of the Chinese oldest-old, 46.57% were in good health. Urban residents reported significantly better SRH than rural residents (50.17% vs. 45.13%). Variables associated with good and poor SRH had different distribution characteristics. The logistic model suggested that marital status, alcohol consumption, and annual income were important factors underlying the SRH differences. Our decomposition analysis indicated that 76.64% of the SRH differences were caused by observational factors, and validated that the difference in SRH between urban and rural areas was significantly (P<0.05) associated with exercise status (45.44%), annual income (37.64%), social activity status (3.75%), age (-5.27%), and alcohol consumption (-2.66%). Therefore, socioeconomic status and individual lifestyle status were the main factors underlying the health inequality between urban and rural Chinese oldest-old.

Age-Friendly Communities and Older Adults’ Health in the United States

As age-friendly community (AFC) initiatives grow, it will be essential to determine whether older adults who live in an AFC have better health than those who live in other environments. This study uses data from the 2017 AARP AFC Surveys and the AARP Livability Index to assess whether AFCs promote the health of older adults. We analyze data for 3027 adults aged 65 and older who reside in 262 zip code areas. Following AARP guidelines, we allocated the sample into two groups: an AFC group (livability score of 51+; n = 2364) and a non-AFC (score ≤ 50, n = 663). The outcome variable was self-rated health (M = 3.5; SD = 1.1; range: 1–5). We used an inverse probability weighting approach to evaluate whether older adults who live in an AFC reported better self-rated health than those who live in a non-AFC. Findings showed that older adults who lived in an AFC had better self-rated health than those in a non-AFC (b = 0.08, p = 0.027). Compared to non-Hispanic Whites, Black and Hispanic older adults reported worse self-rated health. Inasmuch as living in an AFC can promote the well-being of older adults, policymakers and practitioners should continue to develop and sustain high-quality, accessible built and social environments.

Exploring the most important factors related to self-perceived health among older men in Sweden: a cross-sectional study using machine learning

OBJECTIVE

To evaluate which factors are the most strongly related to self-perceived health among older men and describe the shape of the association between the related factors and self-perceived health using machine learning.

DESIGN AND SETTING

This is a cross-sectional study within the population-based VAScular and Chronic Obstructive Lung disease study (VASCOL) conducted in southern Sweden in 2019.

PARTICIPANTS

A total of 475 older men aged 73 years from the VASCOL dataset.

MEASURES

Self-perceived health was measured using the first item of the Short Form 12. An extreme gradient-boosting model was trained to classify self-perceived health as better (rated: excellent or very good) or worse (rated: fair or poor) using self-reported data on 19 prevalent physician-diagnosed health conditions, intensity of 9 symptoms and 9 demographic and lifestyle factors. Importance of factors was measured in SHapley Additive exPlanations absolute mean and higher scores correspond to greater importance.

RESULTS

The most important factors for classifying self-perceived health were: pain (0.629), sleep quality (0.595), breathlessness (0.549), fatigue (0.542) and depression (0.526). Health conditions ranked well below symptoms and lifestyle variables. Low levels of symptoms, good sleep quality, regular exercise, alcohol consumption and a body mass index between 22 and 28 were associated with better self-perceived health.

CONCLUSIONS

Symptoms are more strongly related to self-perceived health than health conditions, which suggests that the impacts of health conditions are mediated through symptoms, which could be important targets to improve self-perceived health. Machine learning offers a new way to assess composite constructs such as well-being or quality of life.

Dizziness in older persons at high risk of future hospitalization: prevalence, differences between those with and without dizziness, and effect of a proactive primary care intervention

Background

Dizziness is a common reason for seeking care, and frequently affects older persons. The aims were to determine the prevalence of dizziness in older persons at high risk of hospitalization, to compare subjects with and without dizziness, and to examine the effects on dizziness of a proactive primary care intervention in comparison with conventional care after one year.

Methods

Data were derived from a prospective multicentre clinical trial in persons aged 75 and older and at high risk of hospitalization. A baseline questionnaire included demographic data, use of aids, questions about everyday physical activity and exercise, pain (intensity, frequency, and duration), activities of daily living measured using the ADL Staircase, and health-related quality of life measured using the EQ-5D-3L vertical visual analogue scale. Both at baseline and after one year, subjects were asked about dizziness, and those with dizziness answered the Dizziness Handicap Inventory – Screening version. Subjects in the intervention group were evaluated by a primary care team and when needed proactive care plans were established. Groups were compared using the Mann Whitney U-test or chi-squared test.

Results

Of the 779 subjects, 493 (63%) experienced dizziness. Persons with dizziness differed regarding sex, homecare service, aids, activities of daily living, health-related quality of life, physical activity, and pain. The intervention did not significantly reduce the level of dizziness.

Conclusions

Dizziness is common in vulnerable older persons, and individuals with dizziness differ in several respects. Further studies are needed employing more dizziness-specific assessment and individually tailored interventions.

Trial registration

ClinicalTrials.gov 170608, ID: NCT03180606.

Association between multimorbidity, self-rated health and life satisfaction among independent, community-dwelling very old persons in Japan: longitudinal cohort analysis from the Kawasaki Ageing and Well-being Project

OBJECTIVE

This study aimed to identify associations between multimorbidity and subjective health outcomes among the very old persons, after adjusting for coexisting conditions such as frailty and depression.

STUDY SETTING AND PARTICIPANTS

This was an observational cross-sectional study involving 1012 independent, community-dwelling very old persons (507 men, 505 women; aged 85-89 years) in Kawasaki city, Japan.

OUTCOME MEASURES

The primary outcome was the cross-sectional associations between multimorbidity and poor self-rated health (SRH) and life satisfaction using binary logistic regression. The secondary outcome was the association of subjective health with each chronic condition.

RESULTS

The prevalence of multimorbidity (≥2 conditions) was 94.7%, and the average number of chronic conditions was 4.47±1.9. Multimorbidity was significantly associated with poor SRH in the adjusted model only when six or more chronic conditions were present (OR 4.80; 95% CI 1.34 to 17.11; p=0.016). Cerebrovascular disease, heart disease, respiratory disease, connective tissue disease and arthritis showed significant associations with poor SRH after multivariate adjustment. Sex-specific analysis replicated associations between multimorbidity with six or more conditions and SRH in both men and women, while the diseases with the greatest impact on SRH differed between men and women. Most conditions were not associated with low satisfaction with life scale, with the exception of arthritis (OR 1.92, 95% CI 1.32 to 2.78, p=0.001).

CONCLUSIONS

Multimorbidity is prevalent in the independent, community-dwelling very old persons and is associated with poor SRH when six or more conditions are present; conditions causing mobility limitations, such as cerebrovascular disease, connective tissue disease and arthritis, have a negative impact on SRH.

TRIAL REGISTRATION NUMBER

UMIN000026053.

Self-Reported Sensory Impairments in Older Adults and their Association with Self-Rated Health and Mortality Outcomes

OBJECTIVES

This study assessed the relationship between self-reported impairments of vision, hearing, and dual sensory impairment, and change in self-rated health/mortality status over a 5-year period.

METHODS

Data came from the National Health and Aging Trends Study, a nationally representative survey of Medicare beneficiaries ages 65 and older. Analyses consisted of a series of ordinal logistic regressions stratified by sex.

RESULTS

For both women and men, self-reported sensory impairments were not statistical predictors of self-rated health/mortality, when other dimensions of health, such as physical functioning, participation, and activities of daily living functioning were included in models.

DISCUSSION

Understanding how self-reported sensory impairments impact self-rated health could assist in targeting rehabilitation strategies to older adults who experience sensory impairments.

What influences individual perception of health? Using machine learning to disentangle self-perceived health

Self-perceived health is a subjective health outcome that summarizes all the health conditions and is widely used in population health studies. Yet, despite its well-known relationship with survival, it is still unclear as to which health conditions are actually taken into account when making an individual assessment of one's own health. The aim of this paper is to assess the influence of four objective health conditions - IADLs, ADLs, chronic diseases, and depression - in predicting self-perceived health among Europeans by age group (50-64 and 65-79) and by sex. Classification trees (J48 algorithm), which pertains to the emerging Machine Learning techniques, were applied to predict self-perceived health according to the four abovementioned objective health conditions of European individuals in the sixth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) (n = 55,611). The four variables present different degrees of relevance in establishing predictions of self-perceived health values by age and by sex. Before the age of 65, chronic diseases have the greatest importance, while IADL limitations are more important in the 65-79 age group. Likewise, ADL limitations are more important for women free of chronic diseases in the 50-64 age group; however, these differences disappear among women in the older group. There is an evident degree of interplay between the objective health indicators of chronic diseases, ADLs, IADLs, and depression when predicting self-perceived health with a high level of accuracy. This interplay implies that self-perceived health summarizes different health conditions depending on age. Gender differences are only evident for the younger age group, whereas construction of self-perceived is the same for women and men among the older group. Therefore, none of these four indicators on its own is able to totally substitute self-perceived health.

The Impact of Family Income on Body Mass Index and Self-Rated Health of Illiterate and Non-illiterate Rural Elderly in China: Evidence From a Fixed Effect Approach

Background: Rural communities worldwide are experiencing the most significant levels of aging. Most rural elderly have no stable pension, and leading family income plays an indispensable role in the life security of rural elderly. This study aims to investigate whether the association between annual family income per capita and body mass index (BMI) and self-rated health (SRH) in rural elderly is moderated by education during fast economic development.

Methods: We chose the fixed-effects model to analyze the impact of the annual family income per capita change on BMI and SRH based on a large, nationally representative longitudinal dataset of rural respondents aged above 60 of the China Family Panel Studies (CFPS) from 2010 to 2018.

Results: Six hundred and fifty-eight were eligible for inclusion in our analysis in CFPS. The median age of participants was 65 years in 2010, and 379 (57.60%) participants were male. Self-rated health increased with higher the logarithmized family income per capita among the rural illiterate elderly (β = 0.0770; 95% CI = 0.0065–0.1473). Body mass index increased with higher the logarithmized family income per capita among the rural elderly (β = 0.1614, 95% CI: 0.0325–0.2903), and it was more evident among the illiterate elderly (β = 0.2462, 95% CI: 0.05519–0.4372).

Conclusion: Family income has an impact on BMI and SRH moderated by education level among rural elderly in China. These results contribute to developing more targeted strategies in the context of a developing country. In addition, it also reminds us to consider the differences in the educational level of the elderly in rural areas when examining the relationship between family income and health.

Factors Associated With Positive Self-Rated Health: Comparing Older Adults in Brazil and in Portugal

Introduction: Self-rated health is a multidimensional health indicator and a predictor of adverse events in old age. Answers to this assessment are influenced by social, cultural and personality factors. Aim: Exploring common and distinctive characteristics of Brazilian and Portuguese older adults aged 70 and over regarding positive self-rated health according to sociodemographic variables, to functional capacity, to independent performance of basic activities of daily living and to neuroticism, as well as analyzing associations between positive self-rated health and these variables. Methods: The present paper is a comparative and cross-sectional study based on secondary data contained in the databases of the FIBRA (Frailty in Brazilian Older Adults) follow-up study, with 418 Brazilian older adults, and of the DIA (From Disability to Activity: The Challenge of Aging) study, with 380 Portuguese older adults. Both samples had higher percentages of women: 68.4% for Portugal and 69.9% for Brazil. The Brazilian sample had a higher average age (80.31 ± 4.67) than the Portuguese sample (76.80 ± 5.28). Results: The Portuguese older adults had better overall cognition scores, higher handgrip strength and higher neuroticism values than the Brazilian older adults. In the simple and multiple logistic regression analyses, it was found that among Brazilian older adults, subjects with higher scores in the MMSE (OR 1.16; 95% CI 1.08-1.24), regardless of ADL performance (OR 2.13; 95% CI 1.31-3.47) and with scores 24-29 (OR 1.92; 95% CI 1.07-3.43) or 11-23 (OR 2.09; 95% CI 1.15-3.79) in neuroticism were more likely to assess their health as very good/good. On the other hand, the Portuguese older adults with intermediate 24-9 (OR 2.38; 95% CI 1.31-4.33) or low 11-23 (OR 5.31; 95% CI 2.69-10.45) scores in neuroticism were more likely to evaluate their health as very good/good. Conclusion: Based on the findings of the present study and on the existing literature, it may be said that it is possible for people to age while keeping a positive perception of their own health, even in advanced old age; comparisons between the above-mentioned countries, however, point to the need for investments in healthcare systems so that older adults may enjoy greater physical independence and improved mental health.