Non-response bias in the analysis of the association between mental health and the urban environment: a cross-sectional study in Brussels, Belgium

BACKGROUND: This paper aims at analysing the impact of partial non-response in the association between urban environment and mental health in Brussels. The potential threats of the partial non-response are biases in survey estimates and statistics. The effect of non-response on statistical associati...

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Veröffentlicht in:ARCHIVES OF PUBLIC HEALTH 2023-07, Vol.81 (1)
Hauptverfasser: Guyot, Madeleine, Pelgrims, Ingrid, Aerts, Raf, Keune, Hans, Remmen, Roy, De Clercq, Eva M, Thomas, Isabelle, Vanwambeke, Sophie O
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container_issue 1
container_start_page
container_title ARCHIVES OF PUBLIC HEALTH
container_volume 81
creator Guyot, Madeleine
Pelgrims, Ingrid
Aerts, Raf
Keune, Hans
Remmen, Roy
De Clercq, Eva M
Thomas, Isabelle
Vanwambeke, Sophie O
description BACKGROUND: This paper aims at analysing the impact of partial non-response in the association between urban environment and mental health in Brussels. The potential threats of the partial non-response are biases in survey estimates and statistics. The effect of non-response on statistical associations is often overlooked and evidence in the research literature is lacking. METHODS: Data from the Belgian Health Interview Survey 2008 and 2013 were used. The association between non-response and potential determinants was explored through logistic regressions. RESULTS: Participants with low income, low educational levels, lower or higher age or in households with children were less likely to respond. When adjusting for socio-economic variables, non-response was higher in areas which are less vegetated, more polluted or more urbanised. Because the determinants of non-response and depressive disorders were similar, it is reasonable to assume that there will be more people with mental health problems among the non-respondents. And because more non-responses were found in low vegetation areas, the protective association between green spaces and mental health may be underestimated. CONCLUSION: Our capacity to measure the association between the urban environment and health is affected by non-response in surveys. The non-random spatial and socio-economic distribution of this bias affects the research findings.
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The potential threats of the partial non-response are biases in survey estimates and statistics. The effect of non-response on statistical associations is often overlooked and evidence in the research literature is lacking. METHODS: Data from the Belgian Health Interview Survey 2008 and 2013 were used. The association between non-response and potential determinants was explored through logistic regressions. RESULTS: Participants with low income, low educational levels, lower or higher age or in households with children were less likely to respond. When adjusting for socio-economic variables, non-response was higher in areas which are less vegetated, more polluted or more urbanised. Because the determinants of non-response and depressive disorders were similar, it is reasonable to assume that there will be more people with mental health problems among the non-respondents. And because more non-responses were found in low vegetation areas, the protective association between green spaces and mental health may be underestimated. CONCLUSION: Our capacity to measure the association between the urban environment and health is affected by non-response in surveys. 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title Non-response bias in the analysis of the association between mental health and the urban environment: a cross-sectional study in Brussels, Belgium
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