Non-response in a survey of cardiovascular risk factors in the Dutch population: Determinants and resulting biases

Boshuizen, H.C.; Viet, A.L.; Picavet, H.S.J.; Botterweck, A.; van Loon, A.J.M.

doi:10.1016/j.puhe.2005.09.008

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Volume 120, Issue 4 , Pages 297-308, April 2006

Non-response in a survey of cardiovascular risk factors in the Dutch population: Determinants and resulting biases

H.C. Boshuizen
- Department of Information Technology and Methodology, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands
- Corresponding author. Tel.: +31 30 274 2944; fax: +31 30 274 4456.
A.L. Viet
- Department of Prevention and Healthcare Research, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
H.S.J. Picavet
- Department of Prevention and Healthcare Research, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
A. Botterweck
- Statistics Netherlands, Division of Social and Spatial Statistics, Statistical Analysis, Heerlen, The Netherlands
A.J.M. van Loon
- Department of Prevention and Healthcare Research, National Institute for Public Health and the Environment, Bilthoven, The Netherlands

Received 4 November 2004; received in revised form 4 July 2005; accepted 26 September 2005.

Summary

Background

The aim of the research was to study the determinants of participation in a health examination survey (HES) which was carried out in a population that previously participated in a health interview survey (HIS) of Statistics Netherlands, and to estimate the effect of non-participation on both the prevalence of the main HES outcomes (risk factors for cardiovascular disease) and on relationships between variables.

Methods

Logistic regression was used to study the determinants of participation in the HES (n=3699) by those who had previously participated in the HIS (n=12 786). Linear models were used to predict the main outcomes in non-participants of the HES. Item non-response was handled by multiple imputation.

Results

HES participants had a higher socio-economic status and comprised more ‘worried well’, while the rural population were less likely to participate in the HES. Most predicted values of outcomes in HES non-participants differed from those in HES participants, but much of this was due to differences in the age and gender composition of both groups. Taking age and gender differences into account, most predicted values of outcomes in the entire HIS population were within the 95% confidence intervals of the HES values, with the exception of body height in men and high-density lipoprotein cholesterol, fasting glucose and body weight in women. These differences are most likely to be due to the higher socio-economic status of HES participants. Relationships between HIS variables did not change significantly when using HES participants alone compared with all HIS participants.

Conclusions

Despite a high rate of non-participation, some bias, mostly small, was seen in the prevalence rates of the main outcome variables. Bias in the relationships between variables was negligible.

Keywords: Health surveys, Population surveillance, Blood pressure, Cholesterol, Body height, Body weight