Literature DB >> 20362610

Why should population attributable fractions be periodically recalculated? An example from cardiovascular risk estimation in southern Europe.

María Grau1, Isaac Subirana, Roberto Elosua, Montserrat Fitó, Maria-Isabel Covas, Joan Sala, Rafael Masiá, Rafel Ramos, Pascual Solanas, Ferran Cordon, F Javier Nieto, Jaume Marrugat.   

Abstract

OBJECTIVE: To determine the effect of age and study period on coronary heart disease (CHD) risk attributable to cardiovascular risk factors.
METHODS: A cohort of cardiovascular disease (CVD)-free randomly participants from Girona (Spain) aged 35-74 years recruited in 1995 and 2000 and followed for an average of 6.9 years. A survey conducted in the same area in 2005 was also used for the analysis. Smoking, hypertension, diabetes, sedentary lifestyle, obesity, total cholesterol > or = 240 mg/dl, low-density lipoprotein (LDL) cholesterol > or = 160 mg/dl, and high-density lipoprotein cholesterol <40 mg/dl were the risk factors considered. The composite end-point included myocardial infarction, angina pectoris, and CHD death.
RESULTS: LDL cholesterol had the highest potential for CHD prevention between 35 and 74 years [42% (95% Confidence Interval: 23,58)]. The age-stratified analysis showed that the population attributable risk (PAF) for smoking was 64% (30,80) in subjects < 55 years; for those > or = 55 years, the PAF for hypertension was 34% (1,61). The decrease observed between 1995 and 2005 in the population's mean LDL cholesterol level reduced that PAF in all age groups.
CONCLUSION: Overall, LDL cholesterol levels had the highest potential for CHD prevention. Periodic PAF recalculation in different age groups may be required to adequately monitor population trends. Copyright 2010. Published by Elsevier Inc.

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Year:  2010        PMID: 20362610     DOI: 10.1016/j.ypmed.2010.03.012

Source DB:  PubMed          Journal:  Prev Med        ISSN: 0091-7435            Impact factor:   4.018


  6 in total

1.  Assessment of the value of a genetic risk score in improving the estimation of coronary risk.

Authors:  Carla Lluis-Ganella; Isaac Subirana; Gavin Lucas; Marta Tomás; Daniel Muñoz; Mariano Sentí; Eduardo Salas; Joan Sala; Rafel Ramos; Jose M Ordovas; Jaume Marrugat; Roberto Elosua
Journal:  Atherosclerosis       Date:  2012-03-30       Impact factor: 5.162

2.  Shadow of diabetes over cardiovascular disease: comparative quantification of population-attributable all-cause and cardiovascular mortality.

Authors:  Mohammadreza Bozorgmanesh; Farzad Hadaegh; Farhad Sheikholeslami; Arash Ghanbarian; Fereidoun Azizi
Journal:  Cardiovasc Diabetol       Date:  2012-06-15       Impact factor: 9.951

3.  Age- and gender-specific population attributable risks of metabolic disorders on all-cause and cardiovascular mortality in Taiwan.

Authors:  Wuan-Szu Wang; Mark L Wahlqvist; Chih-Cheng Hsu; Hsing-Yi Chang; Wan-Chi Chang; Chu-Chih Chen
Journal:  BMC Public Health       Date:  2012-02-10       Impact factor: 3.295

4.  Population attributable fraction of leading non-communicable cardiovascular diseases due to leisure-time physical inactivity: a systematic review.

Authors:  Hashel Al Tunaiji; Jennifer C Davis; Mohammad Ali Mansournia; Karim M Khan
Journal:  BMJ Open Sport Exerc Med       Date:  2019-04-09

5.  [Impact of cardiovascular risk factors in the Extremadura population: HERMEX cohort contributions for a preventive strategy].

Authors:  Francisco Javier Félix-Redondo; Luis Lozano Mera; Paula Alvarez-Palacios Arrighi; Maria Grau Magana; Jose María Ramírez-Romero; Daniel Fernández-Bergés
Journal:  Aten Primaria       Date:  2019-01-10       Impact factor: 1.137

6.  Prevalence of obesity and associated cardiovascular risk: the DARIOS study.

Authors:  Francisco Javier Félix-Redondo; María Grau; José Miguel Baena-Díez; Irene R Dégano; Antonio Cabrera de León; Maria Jesús Guembe; María Teresa Alzamora; Tomás Vega-Alonso; Nicolás R Robles; Honorato Ortiz; Fernando Rigo; Eduardo Mayoral-Sanchez; Maria José Tormo; Antonio Segura-Fragoso; Daniel Fernández-Bergés
Journal:  BMC Public Health       Date:  2013-06-05       Impact factor: 3.295

  6 in total

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