TY - JOUR
T1 - Status quo bias and health behavior
T2 - Findings from a cross-sectional study
AU - Karl, Florian M.
AU - Holle, Rolf
AU - Schwettmann, Lars
AU - Peters, Annette
AU - Laxy, Michael
N1 - Publisher Copyright:
© 2019 The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
PY - 2019/10/1
Y1 - 2019/10/1
N2 - Status quo bias (SQB) has often been referred to as an important tool for improving public health. However, very few studies were able to link SQB with health behavior. Methods: Analysis were based on data from the population-based KORA S4 study (1999-2001, n = 2309). We operationalized SQB through two questions. The first asked whether participants switched their health insurance for financial benefits since this was enabled in 1996. Those who did were assigned a 'very low SQB' (n = 213). Participants who did not switch were asked a second hypothetical question regarding switching costs. We assigned 'low SQB' to those who indicated low switching costs (n = 1035), 'high SQB' to those who indicated high switching costs (n = 588), and 'very high SQB' to those who indicated infinite switching costs (n = 473). We tested the association between SQB and physical activity, diet, smoking, alcohol consumption, the sum of health behaviors, and body mass index (BMI) using logistic, Poisson and ordinary least square regression models, respectively. Models were adjusted for age, sex, education, income, satisfaction with current health insurance and morbidity. Results: SQB was associated with a higher rate of physical inactivity [OR = 1.22, 95% CI (1.11; 1.35)], a higher sum of unhealthy lifestyle factors [IRR = 1.05, 95% CI (1.01; 1.10)] and a higher BMI [β = 0.30, 95% CI (0.08; 0.51)]. Conclusion: A high SQB was associated with unfavorable health behavior and higher BMI. Targeting SQB might be a promising strategy for promoting healthy behavior.
AB - Status quo bias (SQB) has often been referred to as an important tool for improving public health. However, very few studies were able to link SQB with health behavior. Methods: Analysis were based on data from the population-based KORA S4 study (1999-2001, n = 2309). We operationalized SQB through two questions. The first asked whether participants switched their health insurance for financial benefits since this was enabled in 1996. Those who did were assigned a 'very low SQB' (n = 213). Participants who did not switch were asked a second hypothetical question regarding switching costs. We assigned 'low SQB' to those who indicated low switching costs (n = 1035), 'high SQB' to those who indicated high switching costs (n = 588), and 'very high SQB' to those who indicated infinite switching costs (n = 473). We tested the association between SQB and physical activity, diet, smoking, alcohol consumption, the sum of health behaviors, and body mass index (BMI) using logistic, Poisson and ordinary least square regression models, respectively. Models were adjusted for age, sex, education, income, satisfaction with current health insurance and morbidity. Results: SQB was associated with a higher rate of physical inactivity [OR = 1.22, 95% CI (1.11; 1.35)], a higher sum of unhealthy lifestyle factors [IRR = 1.05, 95% CI (1.01; 1.10)] and a higher BMI [β = 0.30, 95% CI (0.08; 0.51)]. Conclusion: A high SQB was associated with unfavorable health behavior and higher BMI. Targeting SQB might be a promising strategy for promoting healthy behavior.
UR - http://www.scopus.com/inward/record.url?scp=85072692901&partnerID=8YFLogxK
U2 - 10.1093/eurpub/ckz017
DO - 10.1093/eurpub/ckz017
M3 - Article
C2 - 30778558
AN - SCOPUS:85072692901
SN - 1101-1262
VL - 29
SP - 992
EP - 997
JO - European Journal of Public Health
JF - European Journal of Public Health
IS - 5
ER -