Literature DB >> 32844360

Does the selective attrition of a panel survey of older people affect the multivariate estimations of subjective well-being?

M Soledad Herrera1, Denisse Devilat2, M Beatriz Fernández2, Raúl Elgueta3.   

Abstract

PURPOSE: The increased population aging has resulted in a growing need for longitudinal studies about the quality of life among older people. Nevertheless, the results of these investigations could be biased because more disadvantaged people leave the original sample. The purpose of this study is to examine how the selective attrition observed in a panel survey affect multivariate models of subjective well-being (SWB). The question is if we could do reliable longitudinal investigations concerning the predictors of SWB in old age.
METHODS: This paper examines attrition in a panel of older people in Chile. Attrition was evaluated in the variables that affect elderly SWB. Probit models were fitted to compare dropouts with nondropouts. Then, multivariate probit models were estimated on satisfaction and depressive symptoms, comparing dropouts and nondropouts. Finally, we compared weighted and unweighted multivariate probit models on SWB.
RESULTS: The attrition rate in 2 years was 38.8%, including deaths and 32.9%, excluding them. Survey dropouts had lower satisfaction but not higher depressive symptoms. Among SWB predictors, people without a partner and with lower self-efficacy abandoned more the study. When applying the Becketti, Gould, Lillard, and Welch test, the probit coefficients of the predictor variables on SWB outcome variables were similar for dropouts and nondropouts. Finally, the comparison of multivariate models on SWB with weighting methods did not find substantial differences in the explanatory coefficients.
CONCLUSION: Although some predictors of attrition were associated with SWB, attrition did not produce biased estimates in multivariate models of life satisfaction life or depressive symptoms in old age.

Entities:  

Keywords:  Attrition; Elderly; Panel survey; Satisfaction; Subjective well-being

Year:  2020        PMID: 32844360     DOI: 10.1007/s11136-020-02612-4

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


  31 in total

1.  More than health: quality of life trajectories among older adults-findings from The Irish Longitudinal Study of Ageing (TILDA).

Authors:  M Ward; C A McGarrigle; R A Kenny
Journal:  Qual Life Res       Date:  2018-09-12       Impact factor: 4.147

2.  Quality of life attenuates age-related decline in functional status of older adults.

Authors:  Yuval Palgi; Amit Shrira; Oleg Zaslavsky
Journal:  Qual Life Res       Date:  2015-01-14       Impact factor: 4.147

3.  Prospective associations of social isolation and loneliness with poor sleep quality in older adults.

Authors:  Bin Yu; Andrew Steptoe; Kaijun Niu; Po-Wen Ku; Li-Jung Chen
Journal:  Qual Life Res       Date:  2017-11-30       Impact factor: 4.147

4.  Psychological attributes and changes in disability among low-functioning older persons: does attrition affect the outcomes?

Authors:  Gertrudis I J M Kempen; Eric van Sonderen
Journal:  J Clin Epidemiol       Date:  2002-03       Impact factor: 6.437

5.  Longitudinal Influences of Social Network Characteristics on Subjective Well-Being of Older Adults: Findings From the ELSA Study.

Authors:  Snorri Bjorn Rafnsson; Aparna Shankar; Andrew Steptoe
Journal:  J Aging Health       Date:  2015-03-24

Review 6.  A systematic literature review of attrition between waves in longitudinal studies in the elderly shows a consistent pattern of dropout between differing studies.

Authors:  Mark D Chatfield; Carol E Brayne; Fiona E Matthews
Journal:  J Clin Epidemiol       Date:  2005-01       Impact factor: 6.437

7.  Attrition and health in ageing studies: Evidence from ELSA and HRS.

Authors:  James Banks; Alastair Muriel; James P Smith
Journal:  Longit Life Course Stud       Date:  2011

8.  Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status?

Authors:  Rosie J Lacey; Kelvin P Jordan; Peter R Croft
Journal:  PLoS One       Date:  2013-12-30       Impact factor: 3.240

9.  Predicting change in quality of life from age 79 to 90 in the Lothian Birth Cohort 1921.

Authors:  Caroline E Brett; Dominika Dykiert; John M Starr; Ian J Deary
Journal:  Qual Life Res       Date:  2018-11-23       Impact factor: 4.147

10.  What is the difference between missing completely at random and missing at random?

Authors:  Krishnan Bhaskaran; Liam Smeeth
Journal:  Int J Epidemiol       Date:  2014-04-04       Impact factor: 7.196

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  1 in total

1.  A longitudinal study monitoring the quality of life in a national cohort of older adults in Chile before and during the COVID-19 outbreak.

Authors:  M Soledad Herrera; Raúl Elgueta; M Beatriz Fernández; Claudia Giacoman; Daniella Leal; Pío Marshall; Miriam Rubio; Felipe Bustamante
Journal:  BMC Geriatr       Date:  2021-02-26       Impact factor: 3.921

  1 in total

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