Blood pressure and the global burden of disease 2000. Part II: estimates of attributable burden.
OBJECTIVE
To provide estimates of the global burden of disease attributable to non-optimal blood pressure by age and sex for adults aged > or = 30 years, by WHO subregion.


METHODS
Estimates of attributable burden were made using population impact fractions, which used data on mean systolic blood pressure levels, disease burden [in deaths and/or disability-adjusted life years (DALYs)] and relative risk corrected for regression dilution bias. Estimates were made of burden attributable to a population distribution of blood pressure with a mean systolic blood pressure of greater than 115 mmHg.


RESULTS
Globally, approximately two-thirds of stroke and one-half of ischaemic heart disease were attributable to non-optimal blood pressure. These proportions were highest in the more developed parts of the world. Worldwide, 7.1 million deaths (approximately 12.8% of the global total) and 64.3 million DALYs (4.4% of the global total) were estimated to be due to non-optimal blood pressure. Overall approximately, two-thirds of the attributable burden of disease occurred in the developing world, approximately two-thirds in the middle age groups (45-69 years) and approximately one-half occurred in those with systolic blood pressure levels between 130 and 150 mmHg.


CONCLUSIONS
The burden of non-optimal blood pressure is almost double that of the only previous global estimates, which is largely explained by the correction for regression dilution adopted in these analyses. High blood pressure is a leading cause of global burden of disease, and most of it occurs in the developing world.
Lawes
Carlene M M
CM
Clinical Trials Research Unit, University of Auckland, Auckland, New Zealand. c.lawes@ctru.auckland.ac.nz
Vander Hoorn
Stephen
S
Law
Malcolm R
MR
Elliott
Paul
P
MacMahon
Stephen
S
Rodgers
Anthony
A
D001794:Blood Pressure; D017281:Cost of Illness; D005260:Female; D006801:Humans; D006973:Hypertension / Q000191:economics / Q000453:epidemiology*; D008297:Male; D008962:Models, Theoretical; D017202:Myocardial Ischemia / Q000191:economics / Q000453:epidemiology*; D020521:Stroke / Q000191:economics / Q000453:epidemiology*