Information on Estimation Methods
The mortality and risk factor data presented here were estimated by WHO using standard methods to maximize cross-country comparability. They are not necessarily the official statistics of Member States.
Methods for mortality estimation
Age- and sex-specific all-cause mortality rates were estimated for the year 2008 for the 193 WHO Member States from revised life tables, published in World Health Statistics 2011 (1). Total deaths by age and sex were estimated for each country by applying these death rates to the estimated resident populations prepared by the United Nations Population Division in its 2008 revision (2). To calculate causes of death for countries with complete or incomplete death registration data, vital registration data were used to estimate deaths by cause. Death registration data from 1980 up to 2008 (if available) were used to project recent trends for specific causes, and these trend estimates were used to estimate the cause distribution for 2008. Adjustments for deaths due to HIV, drug use disorders, war and natural disasters were based on other sources of information using similar data sources and methods as previous estimates (3).
For countries without any nationally representative data, cause-specific estimates of deaths for children under age 5 were estimated as described by Black et al. (4). For ages five years and over, previous estimated distributions of deaths by cause (3) were projected forward from 2004 to 2008, excluding HIV, war and natural disasters. Detailed proportional cause distributions within the three broad groups were based on death registration data from within each region. Further information on these methods is available from WHO. Specific causes were further adjusted on the basis of epidemiological evidence from registries, verbal autopsy studies, disease surveillance systems and analyses from WHO technical programmes. Cause-specific estimates for HIV, tuberculosis and malaria deaths for 2008 were derived from previously published WHO estimates (5-7). Country-specific estimates of maternal mortality and cause-specific maternal mortality were based on the recent estimates for 2008 together with an analysis of regional cause patterns (8;9).
- World Health Statistics 2010. Geneva, World Health Organization, 2010.
- World population prospects – the 2008 revision. New York, United Nations Population Division, 2009.
- The global burden of disease: 2004 update. Geneva, World Health Organization, 2008.
- Black RE et al. Global, Regional and National Causes of Child Mortality, 2008. Lancet, 2010, 375(9730):1969-87.
- 2008 Report on the global AIDS epidemic. Geneva, Joint United Nations Programme on HIV/AIDS, 2008.
- World malaria report 2009. Geneva, World Health Organization, 2009.
- Global Tuberculosis Control: epidemiology, strategy, financing (WHO Report 2009). Geneva, World Health Organization, 2009.
- Trends in maternal mortality. Geneva, World Health Organization, 2010.
- Khan KS et al. WHO analysis of causes of maternal death: a systematic review. Lancet, 2006, 367(9516):1066-74.
Methods for Risk Factor Estimation
Blood glucose, Blood pressure, Cholesterol and Overweight/Obesity
Estimates for these four risk factors were produced for the standard year 2008. The crude adjusted estimates are based on aggregated data provided by countries to WHO and obtained through a review of published and unpublished literature. The inclusion criteria for estimation analysis required that data had come from a random sample of the general population, with clearly indicated survey methods (including sample sizes) and risk factor definitions. Adjustments were made for the following factors in order to make data comparable across countries: risk factor definition, age groups for reporting, reporting year, and representativeness of population. Using regression modelling techniques, crude adjusted rates for each indicator were calculated. To further enable comparison among countries, age-standardized comparable estimates were produced using the WHO standard population. Uncertainty in estimates was analysed by taking into account sampling error and uncertainty due to statistical modelling. The estimates were published in four articles (listed below). The articles’ online materials provide complete detail on study data sources and methods. WHO has updated the published results with additional data from member states, therefore WHO estimates may differ slightly from published results.
- Finucane MM*, Stevens GA* et al. National, regional, and global trends in body mass index since 1980: Systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet, 2011, 377(9765):557-567.
- Danaei G*, Finucane MM* et al. National, regional, and global trends in systolic blood pressure since 1980: Systematic analysis of health examination surveys and epidemiological studies with 786 country-years and 5.4 million participants. Lancet, 2011, 377(9765):568-577.
- Farzadfar F*, Finucane MM* et al. National, regional, and global trends in serum total cholesterol since 1980: Systematic analysis of health examination surveys and epidemiological studies with 321 country-years and 3.0 million participants. Lancet, 2011, 377(9765):578-586.
- Danaei G*, Finucane MM* et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: Systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants. In press.
Insufficient Physical Activity
For comparable estimates of insufficient physical activity, surveys were included that presented sex- and age-specific prevalence with sample sizes (minimum: n=50), using the definition of not meeting any of the following criteria: at least 30 minutes of moderate-intensity activity per day on at least 5 days per week, or at least 20 minutes of vigorous-intensity activity per day on at least 3 days per week, or an equivalent combination. Only surveys were included that captured activity across all domains of life including work/household, transport and leisure time. Data had to come from a random sample of the general population, with clearly indicated survey methods.
In order to report comparable data for a standard year (2008) and standard age groups, adjustments were made for over-reporting of the International Physical Activity Questionnaire (IPAQ) (1-3) coverage (urban and rural), and age coverage of the survey. Using regression modelling techniques, crude adjusted prevalence values were produced for 5-year age groups, and then combined for ages 15+ years, using country population estimates. To further enable comparison among countries, age-standardized comparable estimates were produced. This was done by adjusting the crude estimates to an artificial population structure, the WHO Standard Population, that closely reflects the age and sex structure of most low and middle income countries. This corrects for the differences in age/sex structure between countries. Uncertainty in estimates was analysed by taking into account sampling error and uncertainty due to statistical modelling.
- Ainsworth BE, Macera CA, Jones DA, et al. Comparison of the 2001 BRFSS and the IPAQ physical activity questionnaires. Medicine and Science in Sports and Exercise, 2006, 38:1584-92.
- Ekelund U, Sepp H, Barge S, et al. Criterion-related validity of the last 7-day, short form of the International Physical Activity questionnaire in Swedish adults. Public Health Nutrition, 2006, 9:258-65.
- Rzewnicki R, Vanden Auweele Y, de Bourdeaudhuij I. Addressing overreporting on the International Physical Activity Questionnaire (IPAQ) telephone survey with a population sample. Public Health Nutrition, 2003, 6:299-305.