Recommendation on unbiased estimation of population attributable fraction calculated in "prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study"

• 作者: Khosravi Ahmad Mansournia Mohammad Ali
• 来源期刊: 贫困所致传染病（英文）
• 关键词: Population attributable fraction Confounding Sample-weighted parametric g-formula
• 年，卷（期）: 2019,（4）
• 所属期刊栏目: Letter to the Editor
• 页码范围: 82-84
• 页数: 3页
• 语种: 中文
• DOI: 10.1186/s40249-019-0587-8

摘要

Population attributable fraction (PAF) refers to the proportion of all cases with a particular outcome in a population that could be prevented by eliminating a specific exposure. The authors of a recent paper evaluated the prevalence and estimated the PAFs for risk factors of TB among elderly people in China [Inf Dis Poverty. 2019;8:7]. Confounding is inevitable in observational studies and Levin's formula is of limited use in practice for unbiasedly estimating PAF. In a complex survey design, an unbiased estimation of the PAF can be calculated using a sample-weighted version of the Miettinen formula or a sample weighed parametric g-formula. With respect to causal interpretation of PAF in public health setting, computation of PAF is logical and practical when the exposure is amenable to intervention.