Elsevier

The Lancet

Volume 362, Issue 9380, 26 July 2003, Pages 271-280
The Lancet

Articles
Estimates of global and regional potential health gains from reducing multiple major risk factors

https://doi.org/10.1016/S0140-6736(03)13968-2Get rights and content

Summary

Background

Estimates of the disease burden due to multiple risk factors can show the potential gain from combined preventive measures. But few such investigations have been attempted, and none on a global scale. Our aim was to estimate the potential health benefits from removal of multiple major risk factors.

Methods

We assessed the burden of disease and injury attributable to the joint effects of 20 selected leading risk factors in 14 epidemiological subregions of the world. We estimated population attributable fractions, defined as the proportional reduction in disease or mortality that would occur if exposure to a risk factor were reduced to an alternative level, from data for risk factor prevalence and hazard size. For every disease, we estimated joint population attributable fractions, for multiple risk factors, by age and sex, from the direct contributions of individual risk factors. To obtain the direct hazards, we reviewed publications and re-analysed cohort data to account for that part of hazard that is mediated through other risks.

Results

Globally, an estimated 47% of premature deaths and 39% of total disease burden in 2000 resulted from the joint effects of the risk factors considered. These risks caused a substantial proportion of important diseases, including diarrhoea (92%–94%), lower respiratory infections (55–62%), lung cancer (72%), chronic obstructive pulmonary disease (60%), ischaemic heart disease (83–89%), and stroke (70–76%). Removal of these risks would have increased global healthy life expectancy by 9·3 years (17%) ranging from 4·4 years (6%) in the developed countries of the western Pacific to 16·1 years (43%) in parts of sub-Saharan Africa.

Interpretation

Removal of major risk factors would not only increase healthy life expectancy in every region, but also reduce some of the differences between regions. The potential for disease prevention and health gain from tackling major known risks simultaneously would be substantial.

Introduction

Reliable and comparable analysis of risks to health is key for prevention of disease and injury. Estimates of the burden of disease from individual health risks have been made for selected risk factors.1 Diseases and injuries are, however, almost always caused by multiple risk factors,2, 3 motivating the analysis of the health benefits of simultaneous reductions in multiple risks. Assessment of the combined effects of multiple distant risks is especially important because many factors act through intermediate factors,4, 5 or in combination with others. For example, education, occupation, and income can affect smoking, physical activity, and diet, which are risk factors for vascular diseases, both directly and through intermediate factors such as body-mass index (BMI), blood pressure, and cholesterol. Multicausality also means that various interventions can be used for disease prevention. The specific choice of interventions is determined by cost, technology availability, infrastructure, and preferences.

Previous research has estimated the joint effects of multiple risk factors in specific cohorts,6, 7, 8, 9 or for specific groups of diseases and risks.10, 11 Innovative methods have also been developed to quantify the effects of multiple risk factors, especially those that interact over time.12, 13 Effects of multiple risk factors beyond specific diseases or cohorts, however, remain almost unexplored in epidemiology and population health. We used comprehensive reviews of data for selected major risk factors to examine the joint health effects of these risks on healthy life expectancy (HALE). Because these risks make varying contributions to disease burden in different regions, we could also estimate how much of the crosspopulation health differentials-eg, differences in HALE—result from these risks. Through estimation of gains in HALE based on causes of disease, this work also contributes systematically to the continued debate on the potential limits to life expectancy.14

Section snippets

Estimation of joint population attributable fractions

Methods and data sources for estimation of the burden of disease attributable to individual risk factors have been described elsewhere.1 The contribution of a risk factor to disease or mortality, relative to some alternative exposure distribution (ie, population attributable fraction [PAF], defined as the proportional reduction in population disease or mortality that would occur if exposure to the risk factor were reduced to an alternative exposure distribution15, 16), is defined by the

Role of the funding source

The sponsors of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Results

Table 2, Table 3, Table 4, Table 5 show the individual and joint contributions of the selected risk factors for the ten leading diseases in the world and for three broad groups of subregions: high-mortality developing regions (38% of global population), lower-mortality developing regions (40% of global population), and demographically and economically developed regions (22% of global population). For most diseases, the joint effects of these risk factors were substantially less than the crude

Discussion

The estimates of the total effect of the 20 selected leading global risk factors showed that these risks jointly contributed to considerable loss of healthy life in different regions of the world. In particular, some leading global diseases—lower respiratory infection, diarrhoea, lung cancer, ischaemic heart disease, and stroke—were substantially a result of exposure to these risk factors. Removal of these risks would have not only increased global healthy life expectancy by 9·3 years (17%),

Comparative Risk Assessment Collaborating group

Members listed in previous report: M Ezzati, A D Lopez, A Rodgers et al. Selected major risk factors and global and regional burden of disease. Lancet 2002; 360: 1347–60.

Contributors

M Ezzati, S Vander Hoorn, A Rodgers, C J L Murray, and A D Lopez developed framework and methods for joint-effect analyses, and C D Mathers for HALE. S Vander Hoorn designed and conducted statistical analysis. A rodgers designed figures. Risk factor working groups reviewed scientific evidence and data sources for

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