Global Health Observatory (GHO) data

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.

Mortality

Age- and sex-specific all-cause mortality rates were estimated for 2000-2012 from revised life tables, published in World Health Statistics 2014 (1). Total number of 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 2012 revision (2).

Causes of death were estimated for 2000-2012 using data sources and methods that were specific for each cause of death (3). Vital registration systems which record deaths with sufficient completeness and quality of cause of death information were used as the preferred data source. Mortality by cause was estimated for all Member States with a population greater than 250,000. These NCD mortality estimates are based on a combination of country life tables, cause of death models, regional cause of death patterns, and WHO and UNAIDS programme estimates for some major causes of death (not including NCDs). Detailed information on methods for mortality and causes of death estimates were published previously (3).

Age-standardized death rates for cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes were calculated using the WHO standard population (4). Proportional mortality (% of total deaths, all ages, and of both sexes) for communicable, maternal, perinatal and nutritional conditions; injuries; cardiovascular disease; cancer; chronic respiratory disease; diabetes; and other NCDs is reported for 2012 (5).

The 2012 probability of dying between ages 30 and 70 years from the four main NCDs was estimated using age-specific death rates (in 5-year age groups, e.g. 30-34… 65-69, for those between 30 and 70) of the combined four main NCD categories, for each Member State (5). Using the life table method, the risk of death between the exact ages of 30 and 70, from any of the four causes and in the absence of other causes of death, was calculated using the equation below. ‪The ICD codes used are: Cardiovascular disease: I00-I99, ‪Cancer: C00-C97, ‪Diabetes: E10-E14, ‪and Chronic respiratory disease: J30-J98.‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

Five-year death rates were then translated into the probability of death for each NCD using the following formula:

The unconditional probability of death, for the 30-70 age range, was calculated last:

Metabolic/biological risk factors *

Estimates for metabolic/biological risk factors (BMI, overweight and obesity, blood glucose/diabetes and blood pressure) were produced for the standard year 2010 to serve as baselines for reporting against the NCD global voluntary targets, and for the year 2014. The crude adjusted estimates are based on aggregated data provided to WHO and Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group and obtained through a review of published and unpublished literature. The inclusion criteria for estimation analysis included data that 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 so that the same indicator could be reported for a standard year (in this case 2010 and 2014) in all countries: standard risk factor definition, standard set of age groups for reporting; standard reporting year, and representativeness of population. Using regression modeling techniques, crude adjusted rates for each indicator were produced. To further enable comparison among countries, age-standardized comparable estimates were produced. This was done by adjusting the crude estimates to the WHO Standard Population (4) 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 analyzed by taking into account sampling error and uncertainty due to statistical modeling. The estimates included in the WHO Regional groupings and World Bank Income groupings are the age-standardized comparable estimates. Data reported as of October 2014 were included in the estimation process. Further detailed information on the methods and data sources used to produce these estimates is available from WHO.

* Data shown for cholesterol are currently the former estimates for 2008 ; updated cholesterol estimates will be available in due course.

Insufficient Physical Activity – Adults

For comparable estimates of insufficient physical activity for adults, surveys were included that presented sex- and age-specific prevalence with sample sizes (minimum: n=50), using the definition of not meeting the WHO recommendations on physical activity for health (6), or a similar specific definition. 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 (2010) and standard age groups, adjustments were made for definition of insufficient physical activity, over-reporting of the International Physical Activity Questionnaire (IPAQ) (7-9), 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 18+ 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 (4), 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.

Insufficient Physical Activity – School-going adolescents

For comparable estimates of insufficient physical activity for school going adolescents, surveys were included that presented sex- and age-specific prevalence with sample sizes (minimum: n=50), using the definition of not meeting the WHO recommendations on physical activity for health (6), or a similar definition (less than 60 minutes of activity on less than 5 days per week) . Data had to come from a random sample of the adolescent population, with clearly indicated survey methods.

In order to report comparable data for a standard year (2010) and standard age groups, adjustments were made for definition of insufficient physical activity, and coverage. Using regression modelling techniques, crude adjusted prevalence values were produced for the ages 11-17 years.

References
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