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Published in: BMC Medical Research Methodology 1/2021

Open Access 01-12-2021 | Research article

A framework for exploring non-response patterns over time in health surveys

Authors: Famke J. M. Mölenberg, Chris de Vries, Alex Burdorf, Frank J. van Lenthe

Published in: BMC Medical Research Methodology | Issue 1/2021

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Abstract

Background

Most health surveys have experienced a decline in response rates. A structured approach to evaluate whether a decreasing - and potentially more selective - response over time biased estimated trends in health behaviours is lacking. We developed a framework to explore the role of differential non-response over time. This framework was applied to a repeated cross-sectional survey in which the response rate gradually declined.

Methods

We used data from a survey conducted biannually between 1995 and 2017 in the city of Rotterdam, The Netherlands. Information on the sociodemographic determinants of age, sex, and ethnicity was available for respondents and non-respondents. The main outcome measures of prevalence of sport participation and watching TV were only available for respondents. The framework consisted of four steps: 1) investigating the sociodemographic determinants of responding to the survey and the difference in response over time between sociodemographic groups; 2) estimating variation in health behaviour over time; 3) comparing weighted and unweighted prevalence estimates of health behaviour over time; and 4) comparing associations between sociodemographic determinants and health behaviour over time.

Results

The overall response rate per survey declined from 47% in 1995 to 15% in 2017. The probability of responding was higher among older people, females, and those with a Western background. The response rate declined in all subgroups, and a faster decline was observed among younger persons and those with a non-Western ethnicity as compared to older persons and those with a Western ethnicity. Variation in health behaviours remained constant. Prevalence estimates and associations did not follow the changes in response over time. On the contrary, the difference in probability of participating in sport gradually decreased between males and females, while no differential change in the response rate was observed.

Conclusions

Providing insights on non-response patterns over time is essential to understand whether declines in response rates may have influenced estimated trends in health behaviours. The framework outlined in this study can be used for this purpose. In our example, in spite of a major decline in response rate, there was no evidence that the risk of non-response bias increased over time.
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Literature
1.
go back to reference De Heer W, De Leeuw E. Trends in household survey nonresponse: a longitudinal and international comparison. Survey Nonresponse. 2002;41:41–54. De Heer W, De Leeuw E. Trends in household survey nonresponse: a longitudinal and international comparison. Survey Nonresponse. 2002;41:41–54.
2.
go back to reference Galea S, Tracy M. Participation rates in epidemiologic studies. Ann Epidemiol. 2007;17(9):643–53.CrossRef Galea S, Tracy M. Participation rates in epidemiologic studies. Ann Epidemiol. 2007;17(9):643–53.CrossRef
3.
go back to reference Mindell JS, Giampaoli S, Goesswald A, Kamtsiuris P, Mann C, Männistö S, et al. Sample selection, recruitment and participation rates in health examination surveys in Europe--experience from seven national surveys. BMC Med Res Methodol. 2015;15:78.CrossRef Mindell JS, Giampaoli S, Goesswald A, Kamtsiuris P, Mann C, Männistö S, et al. Sample selection, recruitment and participation rates in health examination surveys in Europe--experience from seven national surveys. BMC Med Res Methodol. 2015;15:78.CrossRef
4.
go back to reference Van Loon AJM, Tijhuis M, Picavet HSJ, Surtees PG, Ormel J. Survey non-response in the Netherlands: effects on prevalence estimates and associations. Ann Epidemiol. 2003;13(2):105–10.CrossRef Van Loon AJM, Tijhuis M, Picavet HSJ, Surtees PG, Ormel J. Survey non-response in the Netherlands: effects on prevalence estimates and associations. Ann Epidemiol. 2003;13(2):105–10.CrossRef
5.
go back to reference Tolonen H, Helakorpi S, Talala K, Helasoja V, Martelin T, Prättälä R. 25-year trends and socio-demographic differences in response rates: Finnish adult health behaviour survey. Eur J Epidemiol. 2006;21(6):409–15.CrossRef Tolonen H, Helakorpi S, Talala K, Helasoja V, Martelin T, Prättälä R. 25-year trends and socio-demographic differences in response rates: Finnish adult health behaviour survey. Eur J Epidemiol. 2006;21(6):409–15.CrossRef
6.
go back to reference Lynn P. Weighting for non-response. In: Survey and statistical computing; 1996. p. 205–14. Lynn P. Weighting for non-response. In: Survey and statistical computing; 1996. p. 205–14.
7.
go back to reference Little RJ, Vartivarian S. On weighting the rates in non-response weights. Stat Med. 2003;22(9):1589–99.CrossRef Little RJ, Vartivarian S. On weighting the rates in non-response weights. Stat Med. 2003;22(9):1589–99.CrossRef
8.
go back to reference Harvey JT, Charity MJ, Sawyer NA, Eime RM. Non-response bias in estimates of prevalence of club-based sport participation from an Australian national physical activity, recreation and sport survey. BMC Public Health. 2018;18(1):895.CrossRef Harvey JT, Charity MJ, Sawyer NA, Eime RM. Non-response bias in estimates of prevalence of club-based sport participation from an Australian national physical activity, recreation and sport survey. BMC Public Health. 2018;18(1):895.CrossRef
9.
10.
go back to reference Batty GD, Gale CR, Kivimäki M, Deary IJ, Bell S. Comparison of risk factor associations in UK biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis. BMJ. 2020;368:m131.CrossRef Batty GD, Gale CR, Kivimäki M, Deary IJ, Bell S. Comparison of risk factor associations in UK biobank against representative, general population based studies with conventional response rates: prospective cohort study and individual participant meta-analysis. BMJ. 2020;368:m131.CrossRef
11.
go back to reference Gustavson K, Røysamb E, Borren I. Preventing bias from selective non-response in population-based survey studies: findings from a Monte Carlo simulation study. BMC Med Res Methodol. 2019;19(1):120.CrossRef Gustavson K, Røysamb E, Borren I. Preventing bias from selective non-response in population-based survey studies: findings from a Monte Carlo simulation study. BMC Med Res Methodol. 2019;19(1):120.CrossRef
12.
go back to reference Ekelund U, Steene-Johannessen J, Brown WJ, Fagerland MW, Owen N, Powell KE, et al. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet. 2016;388(10051):1302–10.CrossRef Ekelund U, Steene-Johannessen J, Brown WJ, Fagerland MW, Owen N, Powell KE, et al. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet. 2016;388(10051):1302–10.CrossRef
13.
go back to reference Statistics Netherlands. Annual report on integration 2010 (in Dutch: Jaarrapport Integratie 2010). The Netherlands: Den Haag/Heerlen; 2010. Statistics Netherlands. Annual report on integration 2010 (in Dutch: Jaarrapport Integratie 2010). The Netherlands: Den Haag/Heerlen; 2010.
14.
go back to reference Gidlow C, Johnston LH, Crone D, Ellis N, James D. A systematic review of the relationship between socio-economic position and physical activity. Health Educ J. 2006;65(4):338–67.CrossRef Gidlow C, Johnston LH, Crone D, Ellis N, James D. A systematic review of the relationship between socio-economic position and physical activity. Health Educ J. 2006;65(4):338–67.CrossRef
15.
go back to reference Beenackers MA, Kamphuis CBM, Giskes K, Brug J, Kunst AE, Burdorf A, et al. Socioeconomic inequalities in occupational, leisure-time, and transport related physical activity among European adults: a systematic review. Int J Behav Nutr Phys Act. 2012;9:116.CrossRef Beenackers MA, Kamphuis CBM, Giskes K, Brug J, Kunst AE, Burdorf A, et al. Socioeconomic inequalities in occupational, leisure-time, and transport related physical activity among European adults: a systematic review. Int J Behav Nutr Phys Act. 2012;9:116.CrossRef
16.
go back to reference Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: a systematic review. Am J Prev Med. 2012;42(3):e3–e28.CrossRef Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: a systematic review. Am J Prev Med. 2012;42(3):e3–e28.CrossRef
17.
go back to reference Klumbiene J, Sakyte E, Petkeviciene J, Prattala R, Kunst AE. The effect of tobacco control policy on smoking cessation in relation to gender, age and education in Lithuania, 1994–2010. BMC Public Health. 2015;15(1):181.CrossRef Klumbiene J, Sakyte E, Petkeviciene J, Prattala R, Kunst AE. The effect of tobacco control policy on smoking cessation in relation to gender, age and education in Lithuania, 1994–2010. BMC Public Health. 2015;15(1):181.CrossRef
18.
go back to reference Tolonen H, Dobson A, Kulathinal S, Project WM. Effect on trend estimates of the difference between survey respondents and non-respondents: results from 27 populations in the WHO MONICA Project. Eur J Epidemiol. 2005;20(11):887–98.CrossRef Tolonen H, Dobson A, Kulathinal S, Project WM. Effect on trend estimates of the difference between survey respondents and non-respondents: results from 27 populations in the WHO MONICA Project. Eur J Epidemiol. 2005;20(11):887–98.CrossRef
19.
go back to reference Hotchkiss JW, Davies C, Gray L, Bromley C, Capewell S, Leyland AH. Trends in adult cardiovascular disease risk factors and their socio-economic patterning in the Scottish population 1995-2008: cross-sectional surveys. BMJ Open. 2011;1(1):e000176.CrossRef Hotchkiss JW, Davies C, Gray L, Bromley C, Capewell S, Leyland AH. Trends in adult cardiovascular disease risk factors and their socio-economic patterning in the Scottish population 1995-2008: cross-sectional surveys. BMJ Open. 2011;1(1):e000176.CrossRef
20.
go back to reference Ernstsen L, Strand BH, Nilsen SM, Espnes GA, Krokstad S. Trends in absolute and relative educational inequalities in four modifiable ischaemic heart disease risk factors: repeated cross-sectional surveys from the Nord-Trøndelag health study (HUNT) 1984-2008. BMC Public Health. 2012;12:266.CrossRef Ernstsen L, Strand BH, Nilsen SM, Espnes GA, Krokstad S. Trends in absolute and relative educational inequalities in four modifiable ischaemic heart disease risk factors: repeated cross-sectional surveys from the Nord-Trøndelag health study (HUNT) 1984-2008. BMC Public Health. 2012;12:266.CrossRef
21.
go back to reference Vikum E, Bjørngaard JH, Westin S, Krokstad S. Socio-economic inequalities in Norwegian health care utilization over 3 decades: the HUNT study. Eur J Pub Health. 2013;23(6):1003–10.CrossRef Vikum E, Bjørngaard JH, Westin S, Krokstad S. Socio-economic inequalities in Norwegian health care utilization over 3 decades: the HUNT study. Eur J Pub Health. 2013;23(6):1003–10.CrossRef
22.
go back to reference Abouzeid M, Wikström K, Peltonen M, Lindström J, Borodulin K, Rahkonen O, et al. Secular trends and educational differences in the incidence of type 2 diabetes in Finland, 1972–2007. Eur J Epidemiol. 2015;30(8):649–59.CrossRef Abouzeid M, Wikström K, Peltonen M, Lindström J, Borodulin K, Rahkonen O, et al. Secular trends and educational differences in the incidence of type 2 diabetes in Finland, 1972–2007. Eur J Epidemiol. 2015;30(8):649–59.CrossRef
23.
go back to reference Graff-Iversen S, Ariansen I, Naess O, Selmer RM, Strand BH. Educational inequalities in midlife risk factors for non-communicable diseases in two Norwegian counties 1974-2002. Scand J Public Health. 2019;47(7):705–12.CrossRef Graff-Iversen S, Ariansen I, Naess O, Selmer RM, Strand BH. Educational inequalities in midlife risk factors for non-communicable diseases in two Norwegian counties 1974-2002. Scand J Public Health. 2019;47(7):705–12.CrossRef
24.
go back to reference Johnson TP, Wislar JS. Response rates and nonresponse errors in surveys. JAMA. 2012;307(17):1805–6.CrossRef Johnson TP, Wislar JS. Response rates and nonresponse errors in surveys. JAMA. 2012;307(17):1805–6.CrossRef
25.
go back to reference Mohadjer L, West J. Effectiveness of Oversampling Blacks and Hispanics in the NHES Field Test. In: National Household Education Survey Technical Report; 1992. Mohadjer L, West J. Effectiveness of Oversampling Blacks and Hispanics in the NHES Field Test. In: National Household Education Survey Technical Report; 1992.
Metadata
Title
A framework for exploring non-response patterns over time in health surveys
Authors
Famke J. M. Mölenberg
Chris de Vries
Alex Burdorf
Frank J. van Lenthe
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2021
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-021-01221-0

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