Approach to identifying hot spots for NCDs in South Africa

Transcription

1 Approach to identifying hot spots for NCDs in South Africa HST Conference 6 May 2016 Noluthando Ndlovu, 1 Candy Day, 1 Benn Sartorius, 2 Karen Hofman, 3 Jens Aagaard-Hansen 3,4 1 Health Systems Trust, Westville, KwaZulu-Natal, South Africa 2 University of KwaZulu-Natal, Durban, KwaZulu-Natal, South Africa 3 University of Witwatersrand, Johannesburg, Gauteng, South Africa 4 Steno Diabetes Center, Gentofte, Denmark

2 Hot Spot Analysis Statistically based methods to assess geographic clustering, pinpointing locations of high- and lowvalue clusters of a phenomenon of interest

3 Identifying NCD hot spots is important The burden of NCDs and risk factors is large and growing Yet receives lower prominence in budgets, priorities, M&E Harmonizing results from existing geo-referenced epidemiological surveys with data on relevant social determinants and environmental factors is essential to identify hot spots for NCDs. This can potentially guide public health planning and address inequity This presentation will demonstrate what already exists, what the gaps are and what can be done to address this

4 NCDs now leading cause of years of life lost in SA Source: Statistics South Africa Causes of death data as analysed for the District Health Barometer 2014/15.

5 Spatial distribution of relative premature mortality (YLLs) due to NCDs

6 High prevalence of NCDs (self-reported) increasing with age Heart problems Asthma Diabetes Hypertension Prevalence (%) Source: National Income Dynamics Study (NiDS) 2012 as reported in Wandai M, Day C. Trends in risk factors for non communicable diseases in South Africa. Durban: Health Systems Trust; 2015.

7 Strategic planning and resources for NCDs National Strategic Plan for the Prevention and Control of NCDs Very little done at provincial level Disease-specific budgeting is not used

8 NCDs with highest preventable disease burden (DALYs) from environmental risks Source: Preventing disease through healthy environments: a global assessment of the burden of disease from environmental risks. Geneva: World Health Organization; DALYs = disability-adjusted life years

9 Strategies for diet-related NCDs Poor diet now generates more disease than physical inactivity, alcohol and smoking combined International research has shown that environmental and policy interventions may be among the most effective strategies for creating population-wide improvements in eating. Source:Diet-related non-communicable diseases chapter in the South African Health Review 2016.

10 Methodology Review availability and granularity of data sources by creating a data matrix table Identify the lowest common level of geographic detail from datasets selected variables will be merged using the smallest unit of analysis Identify other gaps and limitations Promote harmonisation of data sources and harmonisation of methods for different levels of granularity as well as point-referenced (e.g. clinics) versus areal data Initiate supplementary data collection to fill gaps Validate predictions of hot spots on the ground

11 Results Available data: Epidemiological Social determinants Environmental factors Gaps and limitations Limited availability and use of environmental indicators in SA Granularity (level) of data sources Infrequent surveys or excessive delays in reporting Limited range of diseases measured and bias of self-reported data Causes of death - level, completeness, quality

12 Results Epidemiological data sources NCDs & Risk Factors Self-reported Measured Hypertension Diabetes Stroke NiDS SANHANES GHS SADHS NiDS, SANHANES, 1 SADHS, DHIS SANHANES, DHIS - Asthma Cancer DHIS Cancer Registry Overweight/Obesity - NiDS, SANHANES, SADHS Smoking NiDS, SANHANES, SADHS SANHANES Physical inactivity NiDS, SANHANES, SADHS SANHANES Alcohol consumption NiDS, SANHANES, SADHS - Unhealthy diet SANHANES, SADHS Causes of death (all causes) Vital registration (recorded) 1 SANHANES only reports raised blood pressure and does not consider medication use. DHIS = District Health Information System, GHS = General Household Survey, NiDS = National Income Dynamics Study, SADHS = South African Demographic & Health Survey, SANHANES = South African National Health and Nutrition Examination Survey

13 Results Social Determinants data sources Social Determinants Data Source South African Index of Multiple Deprivation (SAIMD) Noble et al. based on Census Quality of Life Index Gauteng City Region Observatory (GCRO) Socio-economic demographics GHS NiDS SADHS SANHANES GHS = General Household Survey, NiDS = National Income Dynamics Study, SADHS = South African Demographic & Health Survey, SANHANES = South African National Health and Nutrition Examination Survey

14 Social determinants: Quality of Life Index Source: Gauteng City Region Observatory (GCRO)

15 Results Environmental data sources Environmental Factors Air Quality Data Source South African Air Quality Information System (SAAQIS) National Aeronautics & Space Administration (NASA) Green Spaces/ Land Cover Main Mode of Transport South African National Biodiversity Institute (SANBI) GCRO Quality of Life Survey National Household Transport Survey Food Environment Index (composite measure) SANHANES GHS NiDS Data source on food outlets to be determined GHS = General Household Survey, NiDS = National Income Dynamics Study, SANHANES = South African National Health and Nutrition Examination Survey

16 Environment: Air Quality Ratings of Local Municipalities 8.2 million of 12.6 million deaths due to the environment are NCDs, mostly attributable to air pollution exposure Air-related health outcomes include lung cancer, stroke, chronic respiratory diseases (e.g. asthma & COPD) Sources: CSIR reported by SA Risk and Vulnerability Atlas Preventing disease through healthy environments: a global assessment of the burden of disease from environmental risks. Geneva: World Health Organization; 2016.

17 Environment: Proposed Food Environment Index Combines two measures of food access: % of low-income population with low access to a grocery store % of population with no access to reliable source of food during past year (food insecurity) Local food environments influence the options available to individuals and families

18 Gaps: Granularity of selected data sources Source National Provincial District Municipality Local Municipality Ward Cancer Registry SAAQIS SANHANES GHS SADHS NiDS National Transport Survey GCRO (Gauteng) DHIS (facility) SAIMD NASA SANBI

19 Gaps: Self-reported vs measured prevalence (2012) Hypertension prevalence (%) Self-reported Female Male Measured Source: National Income Dynamics Study (NiDS) as reported in Wandai M, Day C. Trends in risk factors for non communicable diseases in South Africa. Durban: Health Systems Trust; 2015.

20 Gaps: Causes of Death completeness, quality, level Age-standardised mortality rates by broad causes and single causes available for metro areas only Ill-defined and garbage codes range 15.6% % by district Source: Statistics South Africa Causes of death data as analysed for the District Health Barometer 2014/15.

21 Next steps for research Refine the analysis based on existing datasets combining epidemiology, social determinants and environmental data Begin in Gauteng due to the availability of diverse sources with small area data Initiate supplementary data collection to fill gaps especially on environmental risk indicators Validate hot spot predictions on the ground

22 Next steps for Public Health in South Africa Finalise Strategic NCD Plans and resource allocation at provincial levels Harmonise existing data sources and initiate data collection on gaps Utilise the potential of an approach combining the three domains to identify NCD hot spots that could guide public health planning and inform resource allocation

23 Contact Details Candy Day