Time trends in the use of field-substitution in the Belgian health interview survey.

Data-collection Field-substitution Health surveys

Journal

Archives of public health = Archives belges de sante publique
ISSN: 0778-7367
Titre abrégé: Arch Public Health
Pays: England
ID NLM: 9208826

Informations de publication

Date de publication:
09 Nov 2022
Historique:
received: 12 05 2022
accepted: 13 10 2022
entrez: 8 11 2022
pubmed: 9 11 2022
medline: 9 11 2022
Statut: epublish

Résumé

Matched field-substitution has been applied in the Belgian Health Interview Survey (BHIS) since the first round. During data-collection, non-participating households are replaced by substitute households, if needed up to seven times. In this manuscript, the use of field-substitution in the six rounds of BHIS (1997-2018) is assessed. We investigated to what extent field-substitution contributes to obtaining the requested net-sample size and whether this has evolved throughout the successive BHIS's. Harmonized para-data gathered throughout de data-collection phases are used to define the final participation status of all households that could be contacted for participation to the survey. The share of the substituted households was calculated and possible trends in the use of field-substitution throughout the successive surveys was assessed using logistic regression. Finally, it was examined whether the application of field-substitution changed in terms of the position of the participating household in the clusters, using the ESTIMATE statement in the SAS procedure NLMIXED. Overall, four in ten participating households are substitute households. This proportion remains rather similar over the surveys. The probability of participating according to the position of the household within the cluster is evidently much higher in households at the first position of initial selected clusters. Over the survey-years, the share of participating household derived from substitute clusters in the total number of participating households has slightly increased. Field-substitution in BHIS plays a very substantial role in obtaining the requested net sample both in size and composition. Field-substitution, as applied in BHIS might inspire scientists to consider it when developing their surveys.

Sections du résumé

BACKGROUND BACKGROUND
Matched field-substitution has been applied in the Belgian Health Interview Survey (BHIS) since the first round. During data-collection, non-participating households are replaced by substitute households, if needed up to seven times. In this manuscript, the use of field-substitution in the six rounds of BHIS (1997-2018) is assessed. We investigated to what extent field-substitution contributes to obtaining the requested net-sample size and whether this has evolved throughout the successive BHIS's.
METHODS METHODS
Harmonized para-data gathered throughout de data-collection phases are used to define the final participation status of all households that could be contacted for participation to the survey. The share of the substituted households was calculated and possible trends in the use of field-substitution throughout the successive surveys was assessed using logistic regression. Finally, it was examined whether the application of field-substitution changed in terms of the position of the participating household in the clusters, using the ESTIMATE statement in the SAS procedure NLMIXED.
RESULTS RESULTS
Overall, four in ten participating households are substitute households. This proportion remains rather similar over the surveys. The probability of participating according to the position of the household within the cluster is evidently much higher in households at the first position of initial selected clusters. Over the survey-years, the share of participating household derived from substitute clusters in the total number of participating households has slightly increased.
CONCLUSION CONCLUSIONS
Field-substitution in BHIS plays a very substantial role in obtaining the requested net sample both in size and composition. Field-substitution, as applied in BHIS might inspire scientists to consider it when developing their surveys.

Identifiants

pubmed: 36348382
doi: 10.1186/s13690-022-00982-4
pii: 10.1186/s13690-022-00982-4
pmc: PMC9644564
doi:

Types de publication

Journal Article

Langues

eng

Pagination

229

Informations de copyright

© 2022. The Author(s).

Références

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pubmed: 24461932
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pubmed: 17958286

Auteurs

Stefaan Demarest (S)

Department of Epidemiology and public health, Sciensano, Rue Juliette Wytsmanstraat 14, 1050, Brussels, Belgium. stefaan.demarest@sciensano.be.

Geert Molenberghs (G)

L-Biostat, U Hasselt & KU Leuven, Leuven, Belgium.

Finaba Berete (F)

Department of Epidemiology and public health, Sciensano, Rue Juliette Wytsmanstraat 14, 1050, Brussels, Belgium.

Rana Charafeddine (R)

Department of Epidemiology and public health, Sciensano, Rue Juliette Wytsmanstraat 14, 1050, Brussels, Belgium.

Herman Van Oyen (H)

Department of Epidemiology and public health, Sciensano, Rue Juliette Wytsmanstraat 14, 1050, Brussels, Belgium.
Department of Public Health and Primary Care, Ugent, Ghent, Belgium.

Guido Van Hal (G)

b Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium.

Classifications MeSH