Dataset Information

Role of clinical, functional and social factors in the association between multimorbidity and quality of life: Findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).

ABSTRACT: OBJECTIVE:An increasing number of diseases is linked to deterioration of quality of life (QoL). Part of this association can be explained by socio-economic factors, which are most commonly accounted for. Our aim was to explore the potential contribution of other factors related to clinical burden, social interaction and functioning. METHODS:A cross-sectional analysis was conducted on wave 6 of the population-based Survey of Health, Ageing and Retirement in Europe (SHARE), among participants aged 50+ (n = 67 179). The Control, Autonomy, Self-Realization and Pleasure (CASP-12v1) questionnaire measured QoL. The association between number of diseases and QoL was tested in a mixed-effects linear regression model. The base model controlled for socio-economic characteristics. Factors of interest (symptoms, polypharmacy, unmet care needs, utilisation of care, social network, personal and financial help, loneliness and activities of daily living (ADL) with instrumental activities (IADL)) were added to the base model one at a time and tested for relevance (i.e. change in the ?-coefficient of the number of conditions of 15% or more). RESULTS:Symptoms, polypharmacy, loneliness and ADL/IADL appeared relevant and were retained in the final model. The association between number of conditions and QoL in the base model was -2.44 [95% CI: -2.72; -2.16], while this association was -0.76 [95%CI: -0.97; -0.54] after all relevant factors were included. CONCLUSION:Factors beyond the socio-economic circumstances play an important role in explaining the association between number of conditions and QoL. These factors should be considered to better estimate the impact of chronic diseases on QoL, and for improving patient care.

SUBMITTER: Makovski TT

PROVIDER: S-EPMC7575102 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Role of clinical, functional and social factors in the association between multimorbidity and quality of life: Findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).

Makovski Tatjana T TT Le Coroller Gwenaëlle G Putrik Polina P Choi Yun Hee YH Zeegers Maurice P MP Stranges Saverio S Ruiz Castell Maria M Huiart Laetitia L van den Akker Marjan M

PloS one 20201020 10

<h4>Objective</h4>An increasing number of diseases is linked to deterioration of quality of life (QoL). Part of this association can be explained by socio-economic factors, which are most commonly accounted for. Our aim was to explore the potential contribution of other factors related to clinical burden, social interaction and functioning.<h4>Methods</h4>A cross-sectional analysis was conducted on wave 6 of the population-based Survey of Health, Ageing and Retirement in Europe (SHARE), among pa ...[more]

PMID: 33079931

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Project description:PurposeThe increased burden of multimorbidity is restricting individuals' ability to live autonomously, leading to a poorer quality of life. This study estimated trajectories of functional limitation and quality of life among middle-aged (ages 50 to 64 years) and older (aged 65 years and older) individuals with and without multimorbidity. We also assessed differences in the relationship between these two trajectories by multimorbidity status and separately for each age cohort.MethodsData originated from the Survey of Health, Ageing, and Retirement in Europe (SHARE). In Luxembourg, data were obtained between 2013 and 2020, involving 1,585 respondents ≥ 50 years of age. Multimorbidity was defined as a self-reported diagnosis of two or more out of 16 chronic conditions; functional limitation was assessed by a combined (Instrumental) Activities of Daily Living (ADL/IADLI) scale; and to measure quality of life, we used the Control, Autonomy, Self-Realization, and Pleasure (CASP-12) scale. Latent growth curve modelling techniques were used to conduct the analysis where repeated measures of quality of life and functional limitation were treated as continuous and zero-inflated count variables, respectively. The model was assessed separately in each age cohort, controlling for the baseline covariates, and the estimates from the two cohorts were presented as components of a synthetic cohort covering the life course from the age of 50.ResultsMiddle-aged and older adults living with multimorbidity experienced poorer quality of life throughout the life course and were at a higher risk of functional limitation than those without multimorbidity. At baseline, functional limitation had a negative impact on quality of life. Furthermore, among middle-aged adults without multimorbidity and older adults with multimorbidity, an increase in the number of functional limitations led to a decline in quality of life. These results imply that the impact of multimorbidity on functional limitation and quality of life may vary across the life course.ConclusionUsing novel methodological techniques, this study contributes to a better understanding of the longitudinal relationship between functional limitation and quality of life among individuals with and without multimorbidity and how this relationship changes across the life course. Our findings suggest that lowering the risk of having multimorbidity can decrease functional limitation and increase quality of life.

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:AimsKnowledge on the link of individual social deprivation with dementia is incomplete. We thus aimed to see whether an association with dementia risk can be observed using a recently developed Social Deprivation Index (SoDep Index). Further, as deprivation is related to depression, we investigated the role of depression in the association.MethodsWe analysed data of 11 623 Survey of Health, Ageing and Retirement in Europe (SHARE) respondents. Social deprivation status was determined by SoDep Index score. Dementia was determined by self-reported diagnosis. Dementia risk by social deprivation status was estimated using Cox proportional hazard models, including relevant covariates (gender, marriage status, chronic conditions). Depressive symptom status was added in a second step. Further, we completed subgroup analyses by social deprivation status and analysed the relevance of depressive symptoms in dementia risk in each deprivation group. In an additional sensitivity analyses we corrected for mortality and used impaired cognitive testing performance as an alternative outcome.ResultsHigh (v. low) social deprivation status was associated with an increased dementia risk (hazard ratio (HR) = 1.79 [95% CI 1.31-2.45]) in the Cox analysis adjusted for covariates only. Further adjustment for depressive symptom status indicated a largely direct association between social deprivation status and dementia risk. Moreover, compared to not having experienced depressive symptoms in the past or at baseline, those with past (HR = 1.67 [95% CI 1.23-2.25]), baseline (HR = 1.48 [95% CI 1.04-2.10]) or stable depressive symptoms (HR = 2.96 [95% CI 2.12-4.14]) had an increased dementia risk. The association between stable depressive symptom status and dementia risk was in the high social deprivation subgroup particularly pronounced. Sensitivity analyses replicated results.ConclusionsResults add to a growing body of evidence indicating that a public health approach to dementia prevention must address socioeconomic inequity. Results suggest a largely direct association between social deprivation and dementia risk. Adults who experience high social deprivation appear particularly affected by detrimental effects of depressive symptomatology on dementia risk and need intervention.

Project description:BackgroundActive 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.MethodsThis 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.ResultsThe 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.ConclusionsOur 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.

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.

Dataset Information

Role of clinical, functional and social factors in the association between multimorbidity and quality of life: Findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).

Publications

Role of clinical, functional and social factors in the association between multimorbidity and quality of life: Findings from the Survey of Health, Ageing and Retirement in Europe (SHARE).

Similar Datasets

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