gtbr2024

5.3 TB determinants

The tuberculosis (TB) epidemic is strongly influenced by broader social and economic development as well as (often interrelated) risk factors more specifially linked to health, such as nutritional status, diabetes, HIV infection, alcohol use disorders and smoking. For example, the numbers of people developing TB and dying from the disease started to decline in western Europe, North America and some other parts of the world around the turn of the 20th century, as incomes grew, levels of poverty fell, and housing and nutrition improved (1, 2). The fastest declines in TB incidence and TB mortality in western Europe occurred in the 1950s and 1960s, in the context of progress towards universal health coverage (UHC), rapid social and economic development, and the availability of effective drug treatments. Achieving global targets for reductions in TB disease burden set in the United Nations (UN) Sustainable Development Goals (SDGs) and World Health Organization (WHO) End TB Strategy requires progress in addressing TB determinants. For this reason, WHO has developed a framework for monitoring SDG indicators related to TB in 2017; this comprises 14 indicators for which a relationship with TB incidence could be established, under seven SDGs (see Annex 5 of the core report document). Five are health-related risk factors for TB and six are broader socioeconomic determinants; the other three indicators, two for UHC and one related to current health expenditures, are covered in Section 5.1.

There is a particularly clear relationship between TB incidence and two SDG-related indicators: (i) the population prevalence of undernutrition and (ii) gross domestic product (GDP) per capita (Fig. 5.3.1).

Each dot represents a country or area.

(a) GDP per capitaa

Relationship between two SDG-related indicators and TB incidence per 100 000 population, 2023. DGP per capita

(b) Prevalence of undernutritiona,b

elationship between two SDG-related indicators and TB incidence per 100 000 population, 2023. Prevalence of undernutrition
a The year of data used for GDP per capita and the population prevalence of undernutrition is the latest year for which data are available from the World Bank (https://data.worldbank.org/) and in the WHO Global Health Observatory (https://www.who.int/data/gho), respectively.
b Data for undernutrition are for people aged ≥18 years. In this age group, undernutrition is defined as a body mass index (BMI) <18.5.


Estimates of the number of people with a new episode of TB (incident cases) attributable to alcohol use disorders, diabetes, HIV infection, smoking and undernutrition are shown in Fig. 5.3.2. Globally in 2023, an estimated 0.96 million incident cases of TB were attributable to undernutrition, 0.75 million to alcohol use disorders, 0.70 million to smoking, 0.61 million to HIV infection and 0.38 million to diabetes (Fig. 5.3.2).

Fig. 5.3.2 Global estimates of the number of people with a new episode of TB (incident cases) attributable to five risk factors,a 2023

a Undernutrition is defined as a low body mass index (BMI) for people aged ≥5 years. Underweight (low weight-for-age), wasting (low weight-for-height) and stunting (low height-for-age) are used to define undernutrition for people aged under five years.
Sources of data used to produce estimates included journal articles (3–6): the World Bank Sustainable Development Goals Database (http://datatopics.worldbank.org/sdgs/); the WHO Global Health Observatory (https://www.who.int/data/gho); the WHO World Health Data Hub (https://data.who.int/); and the WHO global TB database


At country level, there is considerable variation in the relative importance and contribution of the five health-related risk factors (Fig. 5.3.3, Fig. 5.3.4), and thus also variation in which of these factors need to be prioritized as part of national efforts to reduce the burden of TB disease.

Fig. 5.3.3 Estimated percentage of people with a new episode of TB (incident cases) attributable to five risk factors,a by country, 2023

(a) Alcohol use disorders

stimated percentage of people with a new episode of TB (incident cases) attributable to alcohol use risk factors, by country, 2023

(b) Diabetes

stimated percentage of people with a new episode of TB (incident cases) attributable to diabetes risk factors, by country, 2023

(c) HIV infection

stimated percentage of people with a new episode of TB (incident cases) attributable to HIV infection risk factors, by country, 2023

(d) Smoking

stimated percentage of people with a new episode of TB (incident cases) attributable to Smoking risk factors, by country, 2023

(e) Undernutritionb

stimated percentage of people with a new episode of TB (incident cases) attributable to Undernutrition risk factors, by country, 2023
a The percentages for alcohol use disorders, diabetes and smoking were calculated using TB incidence estimates restricted to adults aged ≥15 years.
b In 2024, WHO published a systematic review that included an updated estimate of the relative risk of TB associated with undernutrition (6).


Among the 30 high TB burden countries, undernutrition, alcohol use disorders and smoking are leading TB determinants in most countries, although HIV infection is the top contributor in several African countries, especially in southern and east Africa (Fig. 5.3.4).

Fig. 5.3.4 Estimated number of TB cases attributable to five risk factors, 30 high TB burden countries, 2023

Best estimates (in colour) and uncertainty intervals (black) are shown. Blank areas (missing bars) represent no data available.
Sources of data used to produce estimates included journal articles (3–6): the World Bank Sustainable Development Goals Database (http://datatopics.worldbank.org/sdgs/); the WHO Global Health Observatory (https://www.who.int/data/gho); the WHO World Health Data Hub (https://data.who.int/); and the WHO Global Tuberculosis Programme.


The status of TB determinants beyond those included under SDG 3 is shown in Fig. 5.3.5. Poor access to clean cooking fuels, a high percentage of the population living in poverty, low access to social protection and a high percentage of the urban population living in slums are most common in countries in the African Region. The percentage of the population with undernutrition is comparatively high in countries in the African and South-East Asia regions. Income inequality is highest in countries in the African Region and the Region of the Americas.

(a) Access to clean cooking fuels

Map for selected SDG indicators beyond SDG 3 in high TB burden countries - Access to clean cooking fuels

(b) Income inequality

Map for selected SDG indicators beyond SDG 3 in high TB burden countries - Income inequality

(c) Living in poverty

Map for selected SDG indicators beyond SDG 3 in high TB burden countries - Living in poverty

(d) Access to social protection

Map for selected SDG indicators beyond SDG 3 in high TB burden countries - Access to social protection

(e) Living in slums

Map for selected SDG indicators beyond SDG 3 in high TB burden countries - Living in slums

(f) Undernutrition

Map for selected SDG indicators beyond SDG 3 in high TB burden countries - Undernutrition
Access to clean fuels: Percentage of population with access to clean fuels and technologies for cooking.
Income inequality: GINI index is shown where 0 is perfect equality and 100 is perfect inequality.
Living in poverty: Percentage of population living below the international poverty line, which is defined as living on $1.90 per day (at 2017 purchasing power parity).
Access to social protection: Percentage of population covered by social protection and labour programmes.
Living in slums: Percentage of urban population living in slums.
Undernutrition: Prevalence of BMI <18.5 among people aged ≥18 years.
Sources: World Bank Sustainable Development Goals Database (http://datatopics.worldbank.org/sdgs/); the WHO Global Health Observatory (https://www.who.int/data/gho).


The most recent data for undernutrition and five socioeconomic indicators associated with TB incidence are shown for the 30 high TB burden countries in Fig. 5.3.6. To facilitate comparisons with two indicators for which the ideal value is 100 (the percentage of the population with access to social protection and the percentage of the population with access to clean fuels), three of the other indicators (the percentage of the urban population living in slums, the percentage of the population with undernutrition and the percentage of the population living below the international poverty line) are represented as their inverse (i.e. the percentage of the urban population not living in slums, the percentage of the population with adequate nutrition and the percentage of the population living above the poverty line). An inverse of the GINI index (a measure of income inequality, which can take values from 0 to 100) is also shown. All indicator values in the figure are for the general population as opposed to people with TB; values for people with TB specifically (e.g. out-of-pocket expenditure and access to social protection) may differ from these general values.

Clean fuels: Percentage of population with access to clean fuels and technologies for cooking.
Income equality: An inverse GINI index is shown where 0 is perfect income inequality and 100 is perfect income equality.
Not in poverty: Percentage of population living above the international poverty line, which is defined as living on $1.90 per day (at 2017 purchasing power parity).
Social protection: Percentage of population covered by social protection and labour programmes.
Not in slums: Percentage of urban population not living in slums.
Adequate nutrition: Prevalence of BMI ≥18.5 among people aged ≥18 years.
Sources: World Bank Sustainable Development Goals Database (http://datatopics.worldbank.org/sdgs/); the WHO Global Health Observatory (https://www.who.int/data/gho).


Based on the latest available data in the World Bank database, some upper-middle-income and lower-middle-income countries (e.g. Brazil, China, India, Indonesia, Mongolia, South Africa, Thailand and Viet Nam) appear to be performing relatively well in terms of the selected SDG-related indicators. However, values for poor populations and other groups most at risk of developing TB are likely to be worse than national averages. Addressing the broader social and economic determinants of the TB epidemic requires multisectoral action and accountability. Global and national progress in adapting and using the WHO multisectoral accountability framework for TB (MAF-TB) is one of the featured topics of this report.

Further country-specific details for the 14 indicators related to TB incidence are available in the Global tuberculosis report app and Country profiles.

 

 

References

  1. Grange JM, Gandy M, Farmer P, Zumla A. Historical declines in tuberculosis: nature, nurture and the biosocial model. Int J Tuberc Lung Dis. 2001;5(3):208–12 (https://www.ncbi.nlm.nih.gov/pubmed/11326817).

  2. Styblo K, Meijer J, Sutherland I. [The transmission of tubercle bacilli: its trend in a human population]. Bull World Health Organ. 1969;41(1):137–78 (https://www.ncbi.nlm.nih.gov/pubmed/5309081).

  3. Imtiaz S, Shield KD, Roerecke M, Samokhvalov AV, Lönnroth K, Rehm J. Alcohol consumption as a risk factor for tuberculosis: meta-analyses and burden of disease. Eur Respir J. 2017;50 (http://doi.org/10.1183/13993003.00216-2017).

  4. Hayashi S, Chandramohan D. Risk of active tuberculosis among people with diabetes mellitus: systematic review and meta-analysis. Trop Med Int Health. 2018;23:1058-70 (https://doi.org/10.1111/tmi.13133).

  5. Jayes L, Haslam PL, Gratziou CG, Powell P, Britton J, Vardavas C et al. Tobacco Control Committee of the European Respiratory Society. SmokeHaz: Systematic Reviews and Meta-analyses of the Effects of Smoking on Respiratory Health. Chest. 2016 Jul;150(1):164-79. (https://doi.org/10.1016/j.chest.2016.03.060).

  6. Franco JVA, Bongaerts B, Metzendorf MI, Risso A, Guo Y, Pena Silva L et al. Undernutrition as a risk factor for tuberculosis disease. Cochrane Database of Systematic Reviews 2024, Issue 6. Art. No.CD015890. (https://doi.org/10.1002/14651858.CD015890.pub2).