Pathways through which health influences early retirement: a qualitative study

Background: Due to the aeging of the population, there is a societal need for workers to prolong their working lives. In the Netherlands, many employees still leave the workforce before the official retirement age of 65. Previous quantitative research showed that poor self-perceived health is a risk factor of (non-disability) early retirement. However, little is known on how poor health may lead to early retirement, and why poor health leads to early retirement in some employees, but not in others. Therefore, the present qualitative study aims to identify in which ways health influences early retirement. Methods. Face-to-face semi-structured interviews were conducted with 30 employees (60-64 years) who retired before the official retirement age of 65. Participants were selected from the Study on Transitions in Employment, Ability and Motivation. The interviews were transcribed verbatim, a summary was made including a timeline, and the interviews were open coded. Results: In 15 of the 30 persons, health played a role in early retirement. Both poor and good health influenced early retirement. For poor health, four pathways were identified. First, employees felt unable to work at all due to health problems. Second, health problems resulted in a self-perceived (future) decline in the ability to work, and employees chose to retire early. Third, employees with health problems were afraid of a further decline in health, and chose to retire early. Fourth, employees with poor health retired early because they felt pushed out by their employer, although they themselves did not experience a reduced work ability. A good health influenced early retirement, since persons wanted to enjoy life while their health still allowed to do so. The financial opportunity to retire sometimes triggered the influence of poor health on early retirement, and often triggered the influence of good health. Employees and employers barely discussed opportunities to prolong working life. Conclusions: Poor and good health influence early retirement via several different pathways. To prolong working life, a dialogue between employers and employees and tailored work-related interventions may be helpful

How Work Impairments and Reduced Work Ability are Associated with Health Care Use in Workers with Musculoskeletal Disorders, Cardiovascular Disorders or Mental Disorders

__Abstract__ Purpose the aim of this study was to explore how work impairments and work ability are associated with health care use by workers with musculoskeletal disorders (MSD), cardiovascular disorders (CVD), or mental disorders (MD). Methods in this cross-sectional study, subjects with MSD (n = 2,074), CVD (n = 714), and MD (n = 443) were selected among health care workers in 12 Dutch organizations. Using an online questionnaire, data were collected on in

<特集1>阪神・淡路大震災 第2部 体験談

<div><p>Background</p><p>The work ability index (WAI) is a frequently used tool in occupational health to identify workers at risk for a reduced work performance and for work-related disability. However, information about the prognostic value of the WAI to identify workers at risk for sickness absence is scarce.</p><p>Objectives</p><p>To investigate the prognostic value of the WAI for sickness absence, and whether the discriminative ability differs across demographic subgroups.</p><p>Methods</p><p>At baseline, the WAI (score 7-49) was assessed among 1,331 office workers from a Dutch financial service company. Sickness absence was registered during 12-months follow-up and categorised as 0 days, 0</p><p>Results</p><p>A lower WAI was associated with sickness absence (≥15 days vs. 0 days: per point lower WAI score OR=1.27; 95%CI 1.21-1.33). The WAI showed reasonable ability to discriminate between categories of sickness absence (ORC=0.65; 95%CI 0.63-0.68). Highest discrimination was found for comparing workers with ≥15 sick days with 0 sick days (AUC=0.77) or with 1-5 sick days (AUC=0.69). At the cut-off for poor work ability (WAI≤27) the sensitivity to identify workers at risk for ≥15 sick days was 7.5%, the specificity 99.6%, and the positive predictive value 82%. The performance was similar across demographic subgroups.</p><p>Conclusions</p><p>The WAI could be used to identify workers at high risk for prolonged sickness absence. However, due to low sensitivity many workers will be missed. Hence, additional factors are required to better identify workers at highest risk.</p></div

Pairwise AUCs: ability of the work ability index (WAI) to discriminate between categories of sickness absence.

<p>AUC: Area under the curve.</p

Univariate and multivariable multinomial regression analyses with odds ratios and 95% confidence intervals for the association between work ability, and individual factors with sickness absence among office workers (n = 1,331).

<p>*p-value <0.05; OR: odds ratio; 95% CI: 95% confidence interval; n: number of workers.</p><p>^a0 days of sickness absence is reference category.</p><p>^blower scores indicate better work ability.</p><p>Univariate and multivariable multinomial regression analyses with odds ratios and 95% confidence intervals for the association between work ability, and individual factors with sickness absence among office workers (n = 1,331).</p

Discriminative ability of the WAI dimensions in the prediction of different durations of sickness absence among office workers (n = 1,331).

<p>*p-value <0.05; ORC: ordinal c-index; 95% CI: 95% confidence interval; Dim: dimension.</p><p>^adiscriminative ability of the single WAI dimensions.</p><p>^bdiscriminative ability of the total WAI score minus a dimension.</p><p>Discriminative ability of the WAI dimensions in the prediction of different durations of sickness absence among office workers (n = 1,331).</p

Alcohol and Brain Development in Adolescents and Young Adults: A Systematic Review of the Literature and Advisory Report of the Health Council of the Netherlands

Young people, whose brains are still developing, might entail a greater vulnerability to the effects of alcohol consumption on brain function and development. A committee of experts of the Health Council of the Netherlands evaluated the state of scientific knowledge regarding the question whether alcohol negatively influences brain development in young people. A systematic literature search for prospective studies was performed in PubMed and PsychINFO, for longitudinal studies of adolescents or young adults ranging between 12 and 24 y of age at baseline, investigating the relation between alcohol use and outcome measures of brain structure and activity, cognitive functioning, educational achievement, or alcohol use disorder (AUD), with measures at baseline and follow-up of the outcome of interest. Data were extracted from original articles and study quality was assessed using the Newcastle-Ottawa Scale. A total of 77 studies were included, 31 of which were of sufficient quality in relation to the study objectives. There were indications that the gray matter of the brain develops abnormally in young people who drink alcohol. In addition, the more often young people drink or the younger they start, the higher the risk of developing AUD later in life. The evidence on white matter volume or quality, brain activity, cognitive function, and educational achievement is still limited or unclear. The committee found indications that alcohol consumption can have a negative effect on brain development in adolescents and young adults and entails a risk of later AUD. The committee therefore considers it a wise choice for adolescents and young adults not to drink alcohol

Health and prolonging working lives: an advisory report of the Health Council of The Netherlands

Objective This paper summarizes the main findings and recommendations of an advisory report on health and prolonging working life, which was requested by the Dutch Minister of Social Affairs and Employment. Methods The advisory report was compiled by a multidisciplinary committee of ten scientists appointed by the Health Council of The Netherlands. The committee's aims were to (i) describe the health of the ageing population, (ii) describe how prolonging working life influences health, (iii) describe determinants, besides health, for prolonging working lives, and (iv) review the literature on interventions aimed at retaining or improving employability of older workers. Results The report was presented to the Minister on 26 June 2018. As the likelihood of health problems increases with age, prolonging working life may be difficult. In general, life expectancy increases and gains in life years and health seem mainly attributable to people aged >75 years. Work is good for mental health. However, it may be beneficial for mental health to stop working around the retirement age. Besides health, financial factors, lifestyle, motivation to work, and working conditions play a role in prolonging working life. A systematic review of the evidence indicated that interventions such as worksite health promotion or career development workshops can support older workers in this matter. Conclusions The Health Council advised the Dutch Government to focus on worksite health promotion and career development interventions as well as the improvement of their implementation. This requires a tailored approach as there is a large diversity in health among older workers and particularly between low- and high-educated people. With this in mind, it was further recommended to explore whether flexible pension schemes might better suit this diversity