Status quo bias and health behavior: findings from a cross-sectional study.
Background 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 SQ...
| Publicado en: | European Journal of Public Health Vol. 29; no. 5; pp. 992 - 998 |
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| Autores principales: | , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Oct2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=138940320&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 138940320 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11011262 BHW jtl: European Journal of Public Health issn: 11011262 maglogo: N pubinfo: dt: Oct2019 vid: 29 iid: 5 pid: 622 pub: Oxford University Press / USA artinfo: ui: 138940320 138940320 138940320 10.1093/eurpub/ckz017 138940320 ppf: 992 ppct: 6 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Status quo bias and health behavior: findings from a cross-sectional study. aug: au: Karl, Florian M Holle, Rolf Schwettmann, Lars Peters, Annette Laxy, Michael affil: Institute of Health Economics and Health Care Management, Helmholtz Zentrum München (GmbH), German Research Centre for Environmental Health, Neuherberg, Germany sug: subj: Health Behavior Evaluation Emotions Evaluation Health Promotion Human Cross Sectional Studies Insurance, Health Health Care Costs Physical Activity Diet Smoking Alcohol Drinking Body Mass Index Logistic Regression Age Factors Sex Factors Educational Status Income Morbidity Odds Ratio Confidence Intervals Life Style ab: Background 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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