Am J Epidemiol 2004; 159:1168-1179.
Copyright © 2004 by the Johns
Hopkins Bloomberg School of Public Health
ORIGINAL CONTRIBUTIONS |
Population Effects on Individual Systolic Blood Pressure: A Multilevel Analysis of the World Health Organization MONICA Project
1 Department of Community Medicine, Section of Preventive Medicine, Lund University, Malmö, Sweden.
2 Department of Medicine, Umeå University, Umeå, Sweden.
3 Department of Epidemiology, University of Michigan, Ann Arbor, MI.
4 School of Population Health, University of Queensland, Brisbane, Australia.
Individuals from the same population share a number of contextual circumstances that may condition a common level of blood pressure over and above individual characteristics. Understanding this population effect is relevant for both etiologic research and prevention strategies. Using multilevel regression analyses, the authors quantified the extent to which individual differences in systolic blood pressure (SBP) could be attributed to the population level. They also investigated possible cross-level interactions between the population in which a person lived and pharmacological (antihypertensive medication) and nonpharmacological (body mass index) effects on individual SBP. They analyzed data on 23,796 men and 24,986 women aged 35–64 years from 39 worldwide Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) study populations participating in the final survey of this World Health Organization project (1989–1997). SBP was positively associated with low educational achievement, high body mass index, and use of antihypertensive medication and, for women, was negatively associated with smoking. About 7–8% of all SBP differences between subjects were attributed to the population level. However, this population effect was particularly strong (i.e., 20%) in antihypertensive medication users and overweight women. This empirical evidence of a population effect on individual SBP emphasizes the importance of developing population-wide strategies to reduce individual risk of hypertension.
analysis of variance; antihypertensive agents; blood pressure; body mass index; education; hypertension; population; world health
Abbreviations: Abbreviations: BMI, body mass index; MONICA, Monitoring of Trends and Determinants in Cardiovascular Disease; SBP, systolic blood pressure; SBP-SD, standard deviation of SBP measurements in each population; VPC, variance partition coefficient.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  N. T. Tuan, L. S. Adair, K. He, and B. M. Popkin Optimal Cutoff Values for Overweight: Using Body Mass Index to Predict Incidence of Hypertension in 18- to 65-Year-Old Chinese Adults J. Nutr., July 1, 2008; 138(7): 1377 - 1382. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. MERLO and B. CHAIX Neighbourhood effects and the real world beyond randomized community trials: a reply to Michael J Oakes Int. J. Epidemiol., October 1, 2006; 35(5): 1361 - 1363. [Full Text] [PDF]
|
|
|
|
 |
|
 J. Merlo, B. Chaix, M. Yang, J. Lynch, and L. Rastam A brief conceptual tutorial on multilevel analysis in social epidemiology: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health J. Epidemiol. Community Health, December 1, 2005; 59(12): 1022 - 1029. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Merlo, M. Yang, B. Chaix, J. Lynch, and L. Rastam A brief conceptual tutorial on multilevel analysis in social epidemiology: investigating contextual phenomena in different groups of people J. Epidemiol. Community Health, September 1, 2005; 59(9): 729 - 736. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. H Leyland Socioeconomic gradients in the prevalence of cardiovascular disease in Scotland: the roles of composition and context J. Epidemiol. Community Health, September 1, 2005; 59(9): 799 - 803. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Merlo, B. Chaix, M. Yang, J. Lynch, and L. Rastam A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon J. Epidemiol. Community Health, June 1, 2005; 59(6): 443 - 449. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Chaix, J. Merlo, and P. Chauvin Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France J. Epidemiol. Community Health, June 1, 2005; 59(6): 517 - 526. [Abstract] [Full Text] [PDF]
|
|