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Prevalence and related factors of Active and Healthy Ageing in Europe according to two models: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE).

ABSTRACT: BACKGROUND:Active and Healthy Ageing (AHA) is the process of optimizing opportunities related to health, participation, and safety in order to improve quality of life. The approach most often used to measure AHA is Rowe and Kahn's Satisfactory Ageing model. Nonetheless, this model has limitations. One of the strategic objectives of the WHO Global Strategy and Action Plan (2016) is to improve Healthy Ageing measurement. Our objectives were to compare two models of assessing AHA and further compare the results by country and sociodemographic variables. METHODS:This was a cross-sectional, observational analysis of a representative sample of the general population aged 50 years and older in Europe. The data analysed were obtained by the Study of Health, Ageing and Retirement in Europe (SHARE). The dependent variable was AHA and its dimensions, measured using the Rowe and Kahn AHA model (AHA-B) and the authors' model based on the WHO definition (AHA-BPS). A descriptive analysis and multivariate models of binary logistical regression were developed. RESULTS:The sample consisted of 52,641 participants (mean age 65.24 years [SD = 10.18; Range = 50-104], 53.2% women). Healthy Ageing prevalence in the AHA-B model was 23.5% (95%CI = 23.1%-23.9%). In the AHA-BPS model, this prevalence was 38.9%. In both models, significant variations were observed between countries, and were distributed along a north-western to south-eastern gradient. The sociodemographic variables associated with the absence of AHA were advanced age, female sex, death of spouse, low educational level, lack of employment, and low financial status. Comparing the two models, the strength of association between absence of AHA and advanced age (85 years and older) was four times greater in the AHA-B model. CONCLUSIONS:Our results showing differences between these two models provide evidence that the AHA-BPS model does not penalize older age and is more likely to characterize AHA from a health promotion perspective.

SUBMITTER: Bosch-Farre C

PROVIDER: S-EPMC6205806 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Prevalence and related factors of Active and Healthy Ageing in Europe according to two models: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE).

Bosch-Farré Cristina C Garre-Olmo Josep J Bonmatí-Tomàs Anna A Malagón-Aguilera Maria Carme MC Gelabert-Vilella Sandra S Fuentes-Pumarola Concepció C Juvinyà-Canal Dolors D

PloS one 20181029 10

<h4>Background</h4>Active and Healthy Ageing (AHA) is the process of optimizing opportunities related to health, participation, and safety in order to improve quality of life. The approach most often used to measure AHA is Rowe and Kahn's Satisfactory Ageing model. Nonetheless, this model has limitations. One of the strategic objectives of the WHO Global Strategy and Action Plan (2016) is to improve Healthy Ageing measurement. Our objectives were to compare two models of assessing AHA and furthe ...[more]

PMID: 30372472

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Project description:BackgroundA frailty paradigm would be useful in primary care to identify older people at risk, but appropriate metrics at that level are lacking. We created and validated a simple instrument for frailty screening in Europeans aged ?50. Our study is based on the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE, http://www.share-project.org), a large population-based survey conducted in 2004-2005 in twelve European countries.MethodsSubjectsSHARE Wave 1 respondents (17,304 females and 13,811 males).Measuresfive SHARE variables approximating Fried's frailty definition. Analyses (for each gender): 1) estimation of a discreet factor (DFactor) model based on the frailty variables using LatentGOLD. A single DFactor with three ordered levels or latent classes (i.e. non-frail, pre-frail and frail) was modelled; 2) the latent classes were characterised against a biopsychosocial range of Wave 1 variables; 3) the prospective mortality risk (unadjusted and age-adjusted) for each frailty class was established on those subjects with known mortality status at Wave 2 (2007-2008) (11,384 females and 9,163 males); 4) two web-based calculators were created for easy retrieval of a subject's frailty class given any five measurements.ResultsFemales: the DFactor model included 15,578 cases (standard R2 = 0.61). All five frailty indicators discriminated well (p < 0.001) between the three classes: non-frail (N = 10,420; 66.9%), pre-frail (N = 4,025; 25.8%), and frail (N = 1,133; 7.3%). Relative to the non-frail class, the age-adjusted Odds Ratio (with 95% Confidence Interval) for mortality at Wave 2 was 2.1 (1.4 - 3.0) in the pre-frail and 4.8 (3.1 - 7.4) in the frail. Males: 12,783 cases (standard R2 = 0.61, all frailty indicators had p < 0.001): non-frail (N = 10,517; 82.3%), pre-frail (N = 1,871; 14.6%), and frail (N = 395; 3.1%); age-adjusted OR (95% CI) for mortality: 3.0 (2.3 - 4.0) in the pre-frail, 6.9 (4.7 - 10.2) in the frail.ConclusionsThe SHARE Frailty Instrument has sufficient construct and predictive validity, and is readily and freely accessible via web calculators. To our knowledge, SHARE-FI represents the first European research effort towards a common frailty language at the community level.

Project description:BackgroundThe validity of self-reported chronic conditions has been assessed by comparing them with medical records or register data in several studies. However, the reliability of self-reports of chronic diseases has less often been examined. Our aim was to assess the proportion and determinants of inconsistent self-reports of diabetes in a long panel study.MethodsSHARE (Survey of Health, Ageing and Retirement in Europe) includes 140,000 persons aged ≥ 50 years from 28 European countries and Israel. We used data from waves 1 to 7 (except wave 3) collected between 2004 and 2017. Diabetes was assessed by self-report. An inconsistent report for diabetes was defined as reporting the condition in one wave, but denying it in at least one later wave. The analysis data set included 13,179 persons who reported diabetes, and answered the question about diabetes in at least one later wave. Log-binomial regression models were fitted to estimate crude and adjusted relative risks (RR) with 95% confidence intervals (CI) for the associations between various exposure variables and inconsistent report of diabetes.ResultsThe proportion of persons with inconsistent self-reports of diabetes was 33.0% (95% CI: 32.2%-33.8%). Inconsistencies occurred less often in persons taking antidiabetic drugs (RR = 0.53 (0.53-0.56)), persons with BMI ≥ 35 kg/m2 versus BMI < 25 kg/m2 (RR = 0.70, (0.64-0.77)), and poor versus excellent subjective health (RR = 0.87 (0.75-1.01)). Inconsistencies occurred more often in older persons (RR = 1.15 (1.12-1.18) per 10 years increase of age), and persons not reporting their age at diabetes onset (RR = 1.38 (1.31-1.45)).ConclusionIn SHARE, inconsistent self-report of diabetes is frequent. Consistent reports are more likely for persons whose characteristics make diabetes more salient, like intake of antidiabetic medication, obesity, and poor subjective health. However, lack of attention in answering the questions, and poor wording of the items may also play a role.

Project description:AimsDepression is among the main contributors to older adults' mental health burden. Retirement, one of the major life transitions, has been claimed to influence mental health substantially. Following up on a previous meta-analysis, the study aims to assess from a longitudinal perspective short- and long-term impacts of transitioning to retirement on depression risk and suicidality in older adults across Europe.MethodsWe conducted a longitudinal study using data from the Survey of Health, Ageing and Retirement in Europe (SHARE), collected between 2004 and 2020 in 27 European countries plus Israel. To estimate relative risks (RR) and 95% confidence intervals (95% CIs) for depression and suicidality at seven time intervals before and after retirement, we fitted adjusted generalized estimating equation models for repeated measures.ResultsWe included 8,998 individuals employed at baseline and retired at follow-up (median follow-up time: 9 years; maximum: 16 years). Compared to the year of retirement, the risk of depression was 11% lower in the following year (RR 0.89; 95% CI 0.81-0.99), 9% lower after 2 years (RR 0.91; 95% CI 0.82-1.00) and after 3 years (RR 0.91; 95% CI 0.81-1.01). Significant estimates remained among females, married individuals, those with an intermediate or higher level of education, former manual workers and those who retired at or before their country's median retirement age. A significant increase in depressive symptoms emerged from the tenth year after retirement among former non-manual workers (RR 1.21; 95% CI 1.05-1.40) and late retirees (RR 1.37; 95% CI 1.16-1.63). No heterogeneity emerged among strata. As for suicidality, we reported an increase in risk only 5 years or more after retirement, namely +30% 5-9 years after retirement (RR 1.30; 95% CI 1.04-1.64) and +47% 10 or more years after retirement (RR 1.47; 95% CI 1.09-1.98). Sensitivity analyses excluding subjects who reported a diagnosis of depression over the study period and those retirees who declared to receive a disability pension confirmed the results obtained in the overall analysis.ConclusionsLongitudinal adjusted data suggest an independent effect of retiring associated with a reduction in depression and suicidality risk in the short run, with its effect decreasing in the long run. Such trends are particularly evident among selected subgroups of elderly populations. If greater flexibility in pensionable age may help prevent depression late in life, the transition to retirement is to be accompanied by targeted health promotion interventions. In an ageing society, welfare policies should be evaluated, considering their long-term impact on mental health.

Dataset Information

Prevalence and related factors of Active and Healthy Ageing in Europe according to two models: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE).

Publications

Prevalence and related factors of Active and Healthy Ageing in Europe according to two models: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE).

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