Sayyedeh Sara Azimi1, Davood Khalili2, Farzad Hadaegh3, Parvin Yavari4, Yadollah Mehrabi5, Fereidoun Azizi6. 1. Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences and Center for Non-communicable disease Control, Deputy of Health, Ministry of health and medical Education, Tehran, Iran. 2. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. dkhalili@endocrine.ac.ir. 3. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 4. Department of Community Medicine, School of medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 5. Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 6. Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abstract
BACKGROUND: Population Attributable Fraction (PAF) is one of the most practical measures for estimating the burden of risk factors with some challenges in its calculation. Cardiovascular disease (CVD) is the first cause of death worldwide and the estimation of accurate PAFs for CVD risk factors is of great importance in conducting preventive strategies. Our aim was to estimate the PAFs of CVD risk factors via direct, i.e. based on regression models, and indirect, i.e. using related equations, methods. METHODS: Participants (3200 males and 4245 females aged ≥30 yr) without history of CVD were selected from the population-based cohort of Tehran Lipid and Glucose Study (TLGS). Hazard ratio (HR) and Odds ratio (OR) of conventional risk factors were calculated for CVD events after ten yr of follow-up. Levin's and Miettinen's equations were applied to indirectly estimate the PAFs and average PAF was directly derived from logistic regression model. RESULTS: The sum of PAFs resulted from indirect estimations reached to more than 100% (around 200% and 150% based on Levin's and Miettinen's formula respectively). The direct estimation attributed 80% and 86% of burden of CVD events to conventional risk factors in men and women respectively. The rank and pattern of PAFs of risk factors was somehow different among different methods. CONCLUSIONS: Estimating priorities of risk factors may differ in different methods for calculating PAF. This study provides evidence on the more expediency of direct method over indirect ways when individual data is available through a population-based cohort.
BACKGROUND: Population Attributable Fraction (PAF) is one of the most practical measures for estimating the burden of risk factors with some challenges in its calculation. Cardiovascular disease (CVD) is the first cause of death worldwide and the estimation of accurate PAFs for CVD risk factors is of great importance in conducting preventive strategies. Our aim was to estimate the PAFs of CVD risk factors via direct, i.e. based on regression models, and indirect, i.e. using related equations, methods. METHODS:Participants (3200 males and 4245 females aged ≥30 yr) without history of CVD were selected from the population-based cohort of Tehran Lipid and Glucose Study (TLGS). Hazard ratio (HR) and Odds ratio (OR) of conventional risk factors were calculated for CVD events after ten yr of follow-up. Levin's and Miettinen's equations were applied to indirectly estimate the PAFs and average PAF was directly derived from logistic regression model. RESULTS: The sum of PAFs resulted from indirect estimations reached to more than 100% (around 200% and 150% based on Levin's and Miettinen's formula respectively). The direct estimation attributed 80% and 86% of burden of CVD events to conventional risk factors in men and women respectively. The rank and pattern of PAFs of risk factors was somehow different among different methods. CONCLUSIONS: Estimating priorities of risk factors may differ in different methods for calculating PAF. This study provides evidence on the more expediency of direct method over indirect ways when individual data is available through a population-based cohort.
Authors: Domingo Orozco-Beltran; Vicente F Gil-Guillen; Josep Redon; Jose M Martin-Moreno; Vicente Pallares-Carratala; Jorge Navarro-Perez; Francisco Valls-Roca; Carlos Sanchis-Domenech; Antonio Fernandez-Gimenez; Ana Perez-Navarro; Vicente Bertomeu-Martinez; Vicente Bertomeu-Gonzalez; Alberto Cordero; Manuel Pascual de la Torre; Jose L Trillo; Concepcion Carratala-Munuera; Salvador Pita-Fernandez; Ruth Uso; Ramon Durazo-Arvizu; Richard Cooper; Gines Sanz; Jose M Castellano; Juan F Ascaso; Rafael Carmena; Maria Tellez-Plaza Journal: PLoS One Date: 2017-10-18 Impact factor: 3.240