| Titre : | Evaluating the impact of non-response bias in the Behavioral Risk Factor Surveillance System (BRFSS). (2012) |
| Auteurs : | Karen-L Schneider ; Melissa-A CLARK ; LAPANE (Kate-L) : USA. Department of Epidemiology. Virginia Commonwealth University. Richmond. VA. ; William RAKOWSKI |
| Type de document : | Article |
| Dans : | Journal of epidemiology and community health (vol. 66, n° 4, 2012) |
| Pagination : | 290-295 |
| Langues: | Anglais |
| Mots-clés : | Comportement ; Facteur risque ; Surveillance ; Biais |
| Résumé : | [BDSP. Notice produite par INIST-CNRS R0xHtlqq. Diffusion soumise à autorisation]. Background Response rates of national health surveys are decreasing, which potentially can bias obtained prevalence estimates. The purpose of this study is to evaluate the extent to which non-response impacts the representativeness of the 2000 Behavioral Risk Factor Surveillance System (BRFSS) sample compared to the 2000 Decennial Census. Methods The 2000 BRFSS had a median response rate of 48 %, while the 2000 Decennial Census had a response rate of 67 %. Representativeness of the BRFSS sample was evaluated on gender, race, ethnicity, age, household income and marital status. Prevalence of each factor in the BRFSS was compared to the prevalence found in the US Census on both the state and county levels. Prevalence differences between the BRFSS and Census were calculated and their association with response rates was evaluated using robust OLS regression and polytomous logistic regression. The relationship between prevalence differences and other survey design elements, such as data collection procedure and sampling fraction, was also explored. Results The BRFSS prevalence estimates diverged from the Census estimates on several sociodemographic factors even after adjustment for non-response/non-coverage. This was found on both the state and county levels ; however, smaller absolute differences between the BRFSS and Census prevalence estimates were found for factors included in the non-response/non-coverage adjustment weight. Lower response rates (<40 %) were associated with the under-representation of racial/ethnic minorities, women and younger individuals in the BRFSS survey. Conclusion Future research should examine alternative approaches to increase response rate (eg, mixed mode) and to adjust for non-response (eg, multiple imputation). |
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