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Does selective migration bias the health impact assessment of urban regeneration programmes in cross-sectional studies? Findings from a Dutch case study

Bibliographic Data

ID12544209
AuthorsAnnemarie Ruijsbroek (0000-0001-7903-2272, National Institute for Public Health and the Environment, corresponding author), Albert Wong (National Institute for Public Health and the Environment), Carolien van den Brink (National Institute for Public Health and the Environment), Mariël Droomers (0000-0002-0867-8559), Hans Van Oers (0000-0003-4063-2240, National Institute for Public Health and the Environment), Hans A M Van Oers, Karien Stronks (0000-0002-0921-2232, Amsterdam UMC Location University of Amsterdam), Anton E Kunst (0000-0002-3313-5273, Amsterdam UMC Location University of Amsterdam)
Year2018
Volume55
Pages155-164
Publication date2018-12-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueHealth & Place (JOURNAL)
Journal identifiersISSN: 1353-8292 • E-ISSN: 1873-2054
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.healthplace.2018.11.007
PMID30591231
OpenAlexW2906177853
LanguageEN
References cited18

We examined if the assessment of the health impact of a national Dutch regeneration programme depends on using either a repeated cross-sectional or longitudinal study design. This is important as only the latter design can incorporate migration patterns. For both designs, we compared trends in medication use between target and control districts. We found differences in medication use trends to be modest under the longitudinal design, and not demonstrable under the repeated cross-sectional design. The observed differences were hardly influenced by migration patterns. We conclude that in the Netherlands migration patterns had little effect on the health impact assessment of this national urban regeneration programme, so either the cross-sectional or longitudinal evaluation study design will do

Cross-sectional study · Environmental health · Geography · Longitudinal study · Sociology · Demography · Environmental and Social Impact Assessments · Health disparities and outcomes · Health Systems, Economic Evaluations, Quality of Life · Medicine

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