Kenya

Proportional mortality

Percentage of total deaths due to NCDs 1) Cardiovascular diseases (CVDs) 2) Cancers 3) Chronic respiratory diseases (CRDs) 4) Diabetes 5) Other NCDs 6) Injuries and 7) Communicable, maternal, perinatal and nutritional conditions.

Latest year: 2019

NCDs are estimated to account for

43% of all deaths.

Total population

51 203 000

Percentage of total deaths due to NCDs

Percentage of total deaths due to NCDs overall and percentage of total deaths due to 7 main categories (5 different NCD categories plus 2 non-NCD categories which together total all deaths)

Latest year: 2019

43%

Total NCD deaths

Latest year: 2019

130 019

Probability of premature mortality from NCDs

Probability (%) of dying between age 30 and exact age 70 from any of cardiovascular diseases, cancer, diabetes, or chronic respiratory diseases (SDG indicator 3.4.1)

Latest year: 2019

19%

Diseases & Risk Factors

Noncommunicable Diseases (NCDs)

Mortality

In this geography, some NCD deaths were included in a separate category called “other pandemic-related mortality” in 2020 and 2021 due to incomplete or low-quality vital registration data. Because this may have affected trends between 2019 to 2021, only data through 2019 are displayed here.

19 %

Probability (%) of premature death

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Probability of premature mortality from NCDs

Probability (%) of dying between age 30 and exact age 70 from any of cardiovascular diseases, cancer, diabetes, or chronic respiratory diseases (SDG indicator 3.4.1)

Latest year: 2019

Probability (%) of premature death

43 %

% of all deaths

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Percentage of total deaths due to NCDs

Percentage of total deaths due to NCDs overall and percentage of total deaths due to 7 main categories (5 different NCD categories plus 2 non-NCD categories which together total all deaths)

Latest year: 2019

% of all deaths

59 %

% of NCD deaths

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Percentage of NCD deaths occurring under 70 years

Premature deaths due to noncommunicable diseases (NCD) as a proportion of all NCD deaths (%)

Latest year: 2019

% of NCD deaths

563 per 100 000 population

Deaths per 100 000 population

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

NCD age-standardized death rate

NCD age-standardized death rate per 100 000 population

Age-standardized death rate for NCDs

Latest year: 2019

Deaths per 100 000 population

Risk factors

2.9 litres

Title:

Total alcohol per capita (15+) consumption (in litres of pure alcohol) (SDG Indicator 3.5.2)

Definition:

Total APC is defined as the total (sum of three-year average recorded and three-year average unrecorded APC, adjusted for three-year average tourist consumption) amount of alcohol consumed per adult (15+ years) over a calendar year, in litres of pure alcohol. Recorded alcohol consumption refers to official statistics (production, import, export, and sales or taxation data), while the unrecorded alcohol consumption refers to alcohol which is not taxed and is outside the usual system of governmental control. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries. Positive figures denote alcohol consumption of outbound tourists being greater than alcohol consumption by inbound tourists, negative numbers the opposite. Tourist consumption is based on UN tourist statistics.

Estimation method:

Recorded alcohol per capita (15+) consumption of pure alcohol is calculated as the sum of beverage-specific alcohol consumption of pure alcohol (beer, wine, spirits, other) from different sources: the first priority in the decision tree is given to government statistics; second are country-specific alcohol industry statistics in the public domain based on interviews or field work (GlobalData (formerly Canadean), IWSR-International Wine and Spirit Research, Wine Institute, historically World Drink Trends), or data from the International Organisation of Vine and Wine (OIV); third is the Food and Agriculture Organization of the United Nations' statistical database (FAOSTAT); and fourth is data from alcohol industry statistics in the public domain based on desk review. For countries, where the data source is FAOSTAT the unrecorded consumption may be included in the recorded consumption. As from the introduction of the "Other" beverage-specific category, beer includes malt beers, wine includes wine made from grapes, spirits include all distilled beverages, and other includes one or several other alcoholic beverages, such as fermented beverages made from sorghum, maize, millet, rice, or cider, fruit wine, fortified wine.

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

litres
Total alcohol per capita (15+) consumption (in litres of pure alcohol) (SDG Indicator 3.5.2)

Latest year: 2019

11 %

Title:

Prevalence of current tobacco use among adults aged 15+ years (age-standardized estimate) (%)

Definition:

The percentage of the population aged 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), “e-cigars”, “e-hookahs”, JUUL and “e-pipes”.

Estimation method:

A statistical model based on a Bayesian negative binomial meta-regression is used to model prevalence of current tobacco use for each country, separately for men and women. A full description of the method is available as a peer-reviewed article in The Lancet, volume 385, No. 9972, p966–976 (2015). Once the age-and-sex-specific prevalence rates from national surveys were compiled into a dataset, the model was fit to calculate trend estimates from the year 2000 to 2025. The model has two main components: (a) adjusting for missing indicators and age groups, and (b) generating an estimate of trends over time as well as the 95% credible interval around the estimate. Depending on the completeness/comprehensiveness of survey data from a particular country, the model at times makes use of data from other countries to fill information gaps. When a country has fewer than two nationally representative population-based surveys in different years, no attempt is made to fill data gaps and no estimates are calculated. To fill data gaps, information is “borrowed” from countries in the same UN subregion. The resulting trend lines are used to derive estimates for single years, so that a number can be reported even if the country did not run a survey in that year. In order to make the results comparable between countries, the prevalence rates are age-standardized to the WHO Standard Population. Estimates for countries with irregular surveys or many data gaps will have large uncertainty ranges, and such results should be interpreted with caution.

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of current tobacco use among adults aged 15+ years (age-standardized estimate) (%)

Latest year: 2019

6 g/day

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

g/day
Mean daily salt intake among adults aged 25+ years (g/day)

Latest year: 2019

9 %

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of insufficient physical activity among adults aged 18+ years (age-standardized estimate) (%)

Latest year: 2019

87 %

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of insufficient physical activity among school-going adolescents aged 11-17 (crude estimate) (%)

Latest year: 2019

31 %

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of raised blood pressure (SBP≥140 mmHg OR DBP≥90 mmHg) among adults aged 30–79 years (age-standardized estimate) (%)

Latest year: 2019

33 %

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of hypertension among adults aged 30–79 years (age-standardized estimate) (%)

Latest year: 2019

Hypertension diagnosis, treatment and control

Total

Males

Females

30-79 have hypertension

(% of people aged 30-79)

12 %

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of obesity among adults (age-standardized estimate) (%)

Latest year: 2019

2 %

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of obesity among adolescents aged 10–19 years (crude estimate) (%)

Latest year: 2019

6 %

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

Prevalence of diabetes among adults aged 18+ years (age-standardized estimate)

Latest year: 2019

4 mmol/l

Range Slider

2000
2005
2010
2015
2020
2025
2030

Total

Males

Females

Past trends

Projected Trends

Estimated projections for NCD indicators

Projections of NCD mortality and risk factor data

Latest year: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Projections were generated based on the methods used for the projections of the WHO Global Programme of Work (GPW13) indicators. For glucose, mortality, alcohol and salt projections, eight models were considered: random walk with trend (RW2), autoregressive (AR1), exponential smoothing, Holt’s linear trend, Holt’s linear trend (damped), flat extrapolation, linear extrapolation and annual average rate change extrapolation. As described in further detail in the GPW13 methodology document, models were tested using existing data, with part of these serving as test data. To determine which model performed best, the following statistical metrics were used: RMSE (root mean squared error), MAE (mean absolute error), MdAE (median absolute error), MASE (median absolute scaled error) and CBA (confidence bound accuracy: percentage of test points that lie within the predicted confidence intervals). Using all of these metrics, the best model was selected independently for each indicator and then used to project data to 2025 or 2030. For tobacco use, a Bayesian negative binomial meta-regression was used to fit trendlines and project to 2025. Projections are predominantly based on data from before the COVID-19 pandemic and are not adjusted for any possible impact on trends the pandemic may have had. Adult prevalence of obesity, prevalence of insufficient activity were projected assuming trends since 2010 continue. To do so, a regression was fit for each Bayesian model iteration, country and sex, with the probit of age-standardized prevalence as the dependent variable, and year as the independent variable. The regression was used to predict age-standardized prevalence for each model iteration, country, sex and projection year. The projected values shown are the mean of all Bayesian iterations for the country, sex and projection year. For obesity, on-track status was assessed based on the proportion of iterations for which the regression coefficient was less than or equal to zero, which is the posterior probability that the trend in age-standardized prevalence was flat or decreasing. Each country-sex was considered on track if the posterior probability of a flat or decreasing trend was greater than 0.5. For insufficient physical activity, each sex and country were considered on-track if the projected value for 2030 was less than 85% of the estimated value for 2010. For both obesity and insufficient physical activity, countries were further categorized by the likelihood that past trends were sufficient to meet the target. Raised blood pressure was projecting using a similar method, with the exception that regressions were fit for each country and sex.

Global Target

Country comparison

mmol/l
Mean total cholesterol (age-standardized estimate)

Latest year: 2019

Country response/ Progress monitor

Fully achieved

Partially achieved

Not achieved

Title:

Has an operational multisectoral national strategy/action plan that integrates the major NCDs and their shared risk factors

Definition:

Country has a multisectoral, national integrated NCD and risk factor policy/strategy/action plan that addresses the 4 main NCDs (cardiovascular diseases, diabetes, cancer, chronic respiratory disease) and their main risk factors (tobacco use, unhealthy diet, physical inactivity, harmful use of alcohol). “Multisectoral” refers to engagement with one or more government sectors outside of health. “Operational” refers to a policy, strategy or action plan which is being used and implemented in the country, and has resources and funding available to implement it. This is the fourth indicator from the NCD Progress Monitor (https://www.who.int/teams/ncds/surveillance/monitoring-capacity).

Estimation method:

Official country response to the WHO NCD country capacity survey (https://www.who.int/teams/ncds/surveillance/monitoring-capacity/ncdccs). This indicator is considered fully achieved if the country responds “Yes” to the questions “Does your country have a national NCD policy, strategy or action plan which integrates several NCDs and their risk factors?” and to the subquestion “ Is it multisectoral?”. Countries also have to respond “operational” to the subquestion “Indicate its stage” and “Yes” to all of the subquestions pertaining to the 4 main risk factors and 4 main NCDs: “Does it address one or more of the following major risk factors?” “Harmful use of alcohol” (optional for the Member States where there is a ban on alcohol), “Unhealthy diet”, “Physical inactivity”, “tobacco” (all 4 must have “Yes”) and “Does it combine early detection, treatment and care for:” “Cancer”, “Cardiovascular diseases”, “ Chronic respiratory diseases” and “Diabetes” (all 4 must have “Yes”). Country must also provide the needed supporting documentation. This indicator is considered partially achieved if the country responds “Yes” to the questions “Does your country have a national NCD policy, strategy or action plan which integrates several NCDs and their risk factors?” and to the subquestion “ Is it multisectoral?”. Countries also have to respond “operational” to the subquestion “Indicate its stage” and “Yes” to at least two of the 4 main risk factors and at least two of the 4 main NCDs.

Increased excise taxes and prices

Has implemented measures to reduce affordability by increasing excise taxes and prices on tobacco products

Latest year: 2023

Smoke-free policies

Has implemented measures to eliminate exposure to second-hand tobacco smoke in all indoor workplaces, public places and public transport

Latest year: 2023

Title:

Has implemented measures to eliminate exposure to second-hand tobacco smoke in all indoor workplaces, public places and public transport

Definition:

Country has all public places completely smoke-free (or at least 90% of the population covered by complete subnational smoke-free legislation).“Completely” means that smoking is not permitted, with no exemptions allowed, except in residences and indoor places that serve as equivalents to long-term residential facilities, such as prisons and long-term health and social care facilities such as psychiatric units and nursing homes. Ventilation and any form of designated smoking rooms and/or areas do not protect from the harms of second-hand tobacco smoke, and the only laws that provide protection are those that result in the complete absence of smoking in all public places. This is indicator 5b from the NCD Progress Monitor (https://www.who.int/teams/ncds/surveillance/monitoring-capacity).

Estimation method:

Legal instruments are analysed for the production of the WHO report on the global tobacco epidemic. Legislation (including implementing rules and regulations) is assessed to determine whether smoke-free laws adopted as of 31 December 2020 provided for a complete indoor smoke-free environment at all times, in all the facilities of each of the following eight places: health care facilities; educational facilities other than universities; universities; government facilities; indoor offices and workplaces not considered in any other category; restaurants or facilities that serve mostly food; cafes, pubs and bars or facilities that serve mostly beverages; public transport. This indicator is considered fully achieved if all eight categories of public places listed above are completely smoke-free in the country (or at least 90% of the population covered by complete subnational smoke-free legislation). This indicator is considered partially achieved if three to seven public places are completely smoke-free.

Large graphic health warnings/plain packaging

Has implemented plain/standardized packaging and/or large graphic health warnings on cigarettes packages

Latest year: 2023

Title:

Has implemented plain/standardized packaging and/or large graphic health warnings on cigarettes packages

Definition:

Country mandates plain/standardized packaging and/or large graphic warnings with all appropriate characteristics. Appropriate characteristics for large graphic warnings include: • specific health warnings mandated; • appearing on individual packages as well as on any outside packaging and labelling used in retail sale; • describing specific harmful effects of tobacco use on health; • are large, clear, visible and legible (e.g. specific colours and font style and sizes are mandated); • rotating health warnings and/or messages; • pictures or pictograms; and • written in (all) the principal language(s) of the country. Appropriate characteristics for plain/standardized packaging include: • restrictions or prohibitions on the use of logos, colours, brand images or promotional information on packaging other than brand names and product names displayed in a standard colour and font style; • standardized shape, size and materials of tobacco packaging; and • no advertising or promotion inside or attached to the package or tobacco product. This is indicator 5c from the NCD Progress Monitor (https://www.who.int/teams/ncds/surveillance/monitoring-capacity).

Estimation method:

Legislation (including implementing rules or regulations) adopted as of 31 December 2020 is assessed to determine the size of the warnings (the front and back of the cigarette pack are averaged to calculate the percentage of the total pack surface area covered by warnings) and warning characteristics. This indicator is considered fully achieved if the country has plain/standardized packaging and/or large graphic health warnings which are defined as covering on average at least 50% of the front and back of the package with all appropriate characteristics as detailed above. This indicator is considered partially achieved if there are medium-size warnings, which are defined as covering on average between 30 and 49% of the front and back of package, with some or all appropriate characteristics, or large warnings that are missing some appropriate characteristics. For countries with a law requiring plain/standardized packaging and/or large graphic warnings but with no implementing rules or regulations yet adopted as of 31 December 2020, this indicator will not be considered fully achieved.

Bans on advertising, promotion and sponsorship

Has enacted and enforced comprehensive bans on tobacco advertising, promotion and sponsorship

Latest year: 2023

Mass media campaigns

Has implemented effective mass media campaigns that educate the public about the harms of smoking/tobacco use and second-hand smoke

Latest year: 2023

Title:

Has implemented effective mass media campaigns that educate the public about the harms of smoking/tobacco use and second-hand smoke

Definition:

Country has implemented a national anti-tobacco mass media campaign designed to support tobacco control, of at least 3 weeks' duration with all appropriate characteristics. Appropriate characteristics include: • campaign was part of a comprehensive tobacco control programme; • before the campaign, research was undertaken or reviewed to gain a thorough understanding of the target audience; • campaign communications materials were pre-tested with the target audience and refined in line with campaign objectives; • air time (radio, television) and/or placement (billboards, print advertising, etc.) was obtained by purchasing or securing it using either the organization’s own internal resources or an external media planner or agency (this information indicates whether the campaign adopted a thorough media planning and buying process to effectively and efficiently reach its target audience); • the implementing agency worked with journalists to gain publicity or news coverage for the campaign; • process evaluation was undertaken to assess how effectively the campaign had been implemented; • an outcome evaluation process was implemented to assess campaign impact; and • the campaign was aired on television and/or radio. This is indicator 5e from the NCD Progress Monitor (https://www.who.int/teams/ncds/surveillance/monitoring-capacity).

Estimation method:

Eligible campaigns are assessed according to the appropriate characteristics to determine whether it signifies the use of a comprehensive communication approach. This indicator is considered fully achieved if the country has a campaign conducted with at least seven appropriate characteristics including airing on television and/or radio. This indicator is considered partially achieved if the country has a campaign conducted with one to six of the appropriate characteristics. WHO assessment is shared with national authorities for review and approval.

Restrictions on physical availability

Has enacted and enforced restrictions on the physical availability of retailed alcohol (via reduced hours of sale)

Latest year: 2019

Advertising bans or comprehensive restrictions

Has enacted and enforced bans or comprehensive restrictions on exposure to alcohol advertising (across multiple types of media)

Latest year: 2019

Increased excise taxes

Has increased excise taxes on alcoholic beverages

Latest year: 2019

Food reformulation policies

Has implemented measures to reformulate unhealthy foods and beverages

Latest year: 2023

Front-of-pack labelling policies

Has implemented front-of-pack labelling policies

Latest year: 2023

Public food procurement and service policies

Has implemented food procurement and service policies for various settings to improve food quality

Latest year: 2023

Mass media campaign on healthy diet

Has implemented at least one recent mass media campaign for healthy diets

Latest year: 2023

Marketing to children restrictions

Has implemented the WHO set of recommendations on marketing of foods and non-alcoholic beverages to children

Latest year: 2023

Marketing of breast-milk substitutes restrictions

Has legislation/regulations fully implementing the International Code of Marketing of Breast-milk Substitutes

Latest year: 2023

Title:

Has implemented at least one recent national public awareness programme and motivational communication for physical activity, including mass media campaigns for physical activity behavioural change

Definition:

Country has implemented at least one recent (within the past 2 years) national public awareness programme on physical activity. This is the eighth indicator from the NCD Progress Monitor (https://www.who.int/teams/ncds/surveillance/monitoring-capacity).

Estimation method:

Official country response to the WHO NCD country capacity survey (https://www.who.int/teams/ncds/surveillance/monitoring-capacity/ncdccs). This indicator is considered fully achieved if the country responds “Yes” to the following question: “Has your country implemented any national public education and awareness campaign on physical activity within the past 2 years?” and supporting documents provide clear evidence demonstrating that one or more of the following activities have been undertaken within the past 2 years: (1) national public-facing mass media education and awareness campaign on physical activity, AND/OR (2) national promotional initiatives supporting a regional or multi-country physical activity (sports) campaigns aimed at increasing awareness and encouraging participation in physical activity (e.g. European Sports Week, Caribbean Wellness Week), AND/OR (3) regular promotional days, held across the year, on physical activity either using the same theme (e.g. “car-free” Sundays) or a physical activity theme is clearly linked with the implementation of multiple health promotion days (e.g. World Heart Day, World Diabetes Day). Undertaking a single promotional day per year is not sufficient to fulfil this criteria. This indicator is considered partially achieved if the supporting documents provide evidence demonstrating that the country has implemented in the past 2 years one or more community-based initiatives or programmes promoting physical activity and/or increasing access to opportunities for physical activity in community settings (e.g. through schools, parks, workplace, health care) but without any evidence of a public-facing mass media education and awareness campaign.

Publications

Tackling NCDs: best buys and other recommended interventions for the prevention and control of noncommunicable diseases, 2nd ed

30 April 2024

Invisible numbers

21 September 2022

World mental health report: Transforming mental health for all

16 June 2022

Toolkit for developing a multisectoral action plan for noncommunicable diseases: overview

19 April 2022

Saving lives, spending less: the case for investing in noncommunicable diseases

13 December 2021

Global Action Plan for the Prevention and Control of NCDs 2013-2020

14 November 2013

Percentage of total deaths due to NCDs

Percentage of total deaths due to NCDs

Latest data available: 2019

Title:

Percentage of total deaths due to NCDs overall and percentage of total deaths due to 7 main categories (5 different NCD categories plus 2 non-NCD categories which together total all deaths)

Definition:

Estimation method:

Total NCD deaths

Total NCD deaths

Latest data available: 2019

Title:

Total NCD deaths

Definition:

Number of deaths due to all noncommunicable diseases.

Estimation method:

Probability of premature mortality from NCDs

Probability of premature mortality from NCDs

Latest data available: 2019

Title:

Probability (%) of dying between age 30 and exact age 70 from any of cardiovascular diseases, cancer, diabetes, or chronic respiratory diseases (SDG indicator 3.4.1)

Definition:

Estimation method:

Probability of death between exact age 30 and exact age 70 was calculated using cause-specific mortality rates in each 5-year age group and standard life table methods. The estimates are derived from the WHO Global Health Estimates (GHE) (https://www.who.int/data/global-health-estimates).

Probability of premature mortality from NCDs

Probability of premature mortality from NCDs

Latest data available: 2019

Title:

Probability (%) of dying between age 30 and exact age 70 from any of cardiovascular diseases, cancer, diabetes, or chronic respiratory diseases (SDG indicator 3.4.1)

Definition:

Estimation method:

Probability of death between exact age 30 and exact age 70 was calculated using cause-specific mortality rates in each 5-year age group and standard life table methods. The estimates are derived from the WHO Global Health Estimates (GHE) (https://www.who.int/data/global-health-estimates).

Range Slider

Estimated projections for NCD indicators

Estimated projections for NCD indicators

Latest data available: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Probability of premature mortality from NCDs

Percentage of total deaths due to NCDs

Percentage of total deaths due to NCDs

Latest data available: 2019

Title:

Percentage of total deaths due to NCDs overall and percentage of total deaths due to 7 main categories (5 different NCD categories plus 2 non-NCD categories which together total all deaths)

Definition:

Estimation method:

Range Slider

Estimated projections for NCD indicators

Estimated projections for NCD indicators

Latest data available: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Percentage of total deaths due to NCDs

Percentage of NCD deaths occurring under 70 yearserror_outline Percentage of NCD deaths occurring under 70 years Premature deaths due to noncommunicable diseases (NCD) as a proportion of all NCD deaths (%) Latest year: 2019 Full description

Percentage of NCD deaths occurring under 70 years

Percentage of NCD deaths occurring under 70 years

Latest data available: 2019

Title:

Premature deaths due to noncommunicable diseases (NCD) as a proportion of all NCD deaths (%)

Definition:

Deaths due to noncommunicable diseases (NCDs) among people aged below 70 years, as a percentage of NCD deaths among all ages.

Estimation method:

Range Slider

Estimated projections for NCD indicators

Estimated projections for NCD indicators

Latest data available: 0

Title:

Projections of NCD mortality and risk factor data

Definition:

Projections of NCD mortality and risk factor indicators with time-series data for estimating future country attainment of targets.

Estimation method:

Percentage of NCD deaths occurring under 70 years

NCD age-standardized death rateerror_outline NCD age-standardized death rate per 100 000 population Age-standardized death rate for NCDs Latest year: 2019 Full description

NCD age-standardized death rate per 100 000 population

NCD age-standardized death rate (per 100 000 population)

litres
Total alcohol per capita (15+) consumption (in litres of pure alcohol) (SDG Indicator 3.5.2)

Latest year: 2019