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Cohort differences in psychological, social, and behavioural explanations of socioeconomic inequalities in health and mortality: Has policy been aiming at moving targets?

Projectomschrijving

Sociaal-economische gezondheidsverschillen: een bewegend doel voor beleid?

Doel

  • De verklaringen voor sociaaleconomische gezondheidsverschillen (SEGV) lijken duidelijk: mensen met een laag opleidingsniveau roken vaker, bewegen minder en eten ongezonder. Maar de samenleving verandert en misschien zijn andere factoren een rol gaan spelen.
  • Zijn de verklarende factoren van SEGV bij mensen van 55 tot 64 jaar oud in de afgelopen dertig jaar veranderd?

Aanpak/werkwijze

  • Analyse van gegevens van +/-6500 deelnemers aan de Longitudinal Aging Study Amsterdam en de Doetinchem Cohort Studie.
  • Kwantitatief onderzoek.

Resultaten

  • De verklarende factoren van SEGV veranderden tussen 1992 en 2012. Roken, alcoholgebruik, emotionele steun en ervaren regie werden steeds belangrijker. BMI, het sociale netwerk, persoonlijke effectiviteit en emotionele stabiliteit bleven even belangrijk.
  • Beleid en interventies gericht op het verkleinen van SEGV moeten zich aanpassen.
  • De kennis is verspreid naar beleidsmakers, GGD’s en onderzoekers.

Factsheet

Verklaringen van sociaal-economische gezondheidsverschillen. Richt beleid zich op een bewegend doel?
Bestand

Rapport Bewegend doel voor beleid

Verklaringen voor sociaal-economische gezondheidsverschillen: richt beleid zich op een bewegend doel?
Bestand

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Samenvatting van de aanvraag

This research project aims to derive a strategy for reducing socioeconomic inequalities in health (SEIH). This strategy is based on an examination of differences in socioeconomic, psychosocial, lifestyle, and health characteristics between three cohorts of middle-aged Dutch adults born in three distinct decades. The project answers the following research questions: 1) how has the composition of educational groups in terms of socioeconomic resources changed across cohorts; 2) which psychological, social, and behavioural factors have become more important for explaining SEIH over time?; and 3) to what extent have changes in socioeconomic groups and explanatory factors contributed to the persistence of SEIH over time? This project will provide major contributions to the evidence-base that informs policy makers and intervention specialists in their efforts to reduce and prevent excessive SEIH. Particularly, it addresses the following gaps in knowledge: First, a leading theoretical explanation for the persistence of SEIH states that due to wider societal developments, the mechanisms generating SEIH are changing over time (1). These developments include fundamental changes in the distribution of socioeconomic resources (e.g. education, prestige, income, and wealth), and in the psychological, social, and behavioural factors that link socioeconomic position (SEP) to health. Interventions based on the factors that once were dominant in explaining SEIH may thus become outdated, and be rendered ineffective. To date, despite its fundamental implications for public health policy if this theory were true, few studies have been able to test it with large scale observational data. This project employs a unique birth cohort-comparative design that provides crucial information needed to keep prevention and intervention programs up-to-date, and to anticipate future developments. Second, the mechanisms known to produce SEIH cross disciplinary boundaries, and include psychological, behavioural, and social pathways (2–4). Few studies have been able to single out from this multitude of factors the specific key mechanisms responsible for generating SEIH. Even less studies examined changes in the importance of these factors over time, which may be crucial to understand the persistence of SEIH. Therefore, this multidisciplinary project includes a wide range of explanatory factors: 1) intergenerational social mobility; 2) lifestyle, including smoking, alcohol use, physical activity and obesity; 3) personality characteristics, including mastery, self-efficacy, and neuroticism; 4) cognitive ability; and 5) social network size, composition, and support. Based on statistical analyses, this project shall identify which of these factors primarily account for observed health disparities and changes therein over time. These should receive priority in policies aimed at SEIH. Third, reviews suggest that previous life style interventions in the lower educated have largely failed to produce health improvement, and that generic health intervention programs have often benefited the high educated more than the low educated, thereby increasing rather than diminishing SEIH (5,6). This points to a lack of studies showing which factors could particularly benefit those with the lowest SEP. Therefore, this project analyses whether some explanatory factors are particularly important for the health of persons with a low SEP compared to an intermediate SEP. By examining the role of explanatory factors of SEIH across the socioeconomic gradient, this project can accurately indicate targets for prevention or intervention aimed at specific socioeconomic groups. Analyses for this project shall be conducted on available data from two Dutch prospective cohort studies: the Longitudinal Aging Study Amsterdam (LASA) and the Doetinchem Cohort Study (DCS) (7–9). These data sets provide the multidimensional and multi-cohort structure needed to examine explanations of the persistence of SEIH. The health outcomes included in this study are self-rated health, morbidity, depressive symptoms, and mortality. These outcomes show substantial socioeconomic inequalities (2,3,10) and cover key health aspects used by Statistics Netherlands to monitor changes in public health (11). The analytical procedures follow established guidelines for calculating SEIH. We examine inequalities using ‘measures of total impact’ primed to compare SEIH across cohorts (Relative Index of Inequality and Slope Index of Inequality), and ‘measures of effect’ primed to show the associations between belonging to a specific socioeconomic stratum and health (using fixed socioeconomic categories across cohorts). Statistical methods include Multi-group Structural Equation Modelling with parallel mediation models. Knowledge dissemination includes a workshop discussing strategies for reducing SEIH with representatives of the Ministry of Health, Welfare and Sports and the Netherlands Institute for Social Research.

Kenmerken

Projectnummer:
531003012
Looptijd: 100%
Looptijd: 100 %
2018
2022
Onderdeel van programma:
Gerelateerde subsidieronde:
Projectleider en penvoerder:
Prof. dr. M. Huisman
Verantwoordelijke organisatie:
Amsterdam UMC - locatie VUmc
Afbeelding
Kennisbundel gezonde wijk

In de kennisbundel Gezond leven in gemeente en regio vindt u een selectie van de meest bruikbare kennis uit onderzoek naar gezondheidsaanpakken in de wijk voor gemeenten en GGD’en. In ruim 4 jaar is de kennis opgedaan in 35 projecten, met subsidie uit ons Preventieprogramma.