Reducing Bruzzi’s Formula to Remove Instability in the Estimation of Population Attributable Fraction for Health Outcomes
| العنوان: | Reducing Bruzzi’s Formula to Remove Instability in the Estimation of Population Attributable Fraction for Health Outcomes |
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| المؤلفون: | Alistair Vickery, Matthew Tuson, Berwin A. Turlach, David Whyatt |
| المصدر: | American Journal of Epidemiology. 187:170-179 |
| بيانات النشر: | Oxford University Press (OUP), 2017. |
| سنة النشر: | 2017 |
| مصطلحات موضوعية: | Adult, Male, Point prevalence survey, Biometry, Adolescent, Epidemiology, Statistics as Topic, Population, Health outcomes, 01 natural sciences, Young Adult, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Outcome Assessment, Health Care, Statistics, Humans, Medicine, Computer Simulation, 030212 general & internal medicine, 0101 mathematics, Child, education, Aged, Estimation, Likelihood Functions, education.field_of_study, business.industry, Infant, Newborn, Nonparametric statistics, Infant, Reproducibility of Results, Western Australia, Middle Aged, medicine.disease, Confidence interval, Logistic Models, Child, Preschool, Multivariate Analysis, Attributable risk, Cohort, Female, Medical emergency, business |
| الوصف: | The aim of this study was to reconcile 3 approaches to calculating population attributable fractions and attributable burden percentage: the approach of Bruzzi et al. (Am J Epidemiol. 1985;122(5):904-914.), the maximum-likelihood method of Greenland and Drescher (Biometrics. 1993;49(3):865-872.), and the multivariable method of Tanuseputro et al. (Popul Health Metr. 2015;13:5.). Using data from a statewide point prevalence survey (Western Australian Point Prevalence Survey, 2014) linked to an administrative database, we compared estimates of attributable burden percentage obtained using the contrasting methods in 6 logistic models of health outcomes from the survey, estimating 95% confidence intervals using nonparametric and weighted bootstrap approaches. Our results show that instability can arise from the fundamental algebraic construction of Bruzzi's formula, and that this instability may substantially influence the calculation of attributable burden percentage and associated confidence intervals. These observations were confirmed in a simulation study. The algebraic reduction of Bruzzi's formula to the 2 alternative methods resulted in markedly more stable estimates for population attributable fraction and attributable burden percentage in cross-sectional studies and cohort designs with fixed follow-up time. We advocate the widespread implementation of the maximum-likelihood approach and the multivariable method. |
| تدمد: | 1476-6256 0002-9262 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d2955d78d0b25e9c609ce9c15f2aec0Test https://doi.org/10.1093/aje/kwx200Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....7d2955d78d0b25e9c609ce9c15f2aec0 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14766256 00029262 |
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