1. Effectiveness of diabetes and hypertension management by rural primary health-care workers (Behvarz workers) in Iran: a nationally representative observational study Farshad Farzadfar, MD, MPH, D.Sc Non Communicable Diseases Research Center Endocrinology and Metabolism Research Institute Tehran University of Medical Sciences July 13, 2012 1 SAPHIR Monthly Webinar

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3. Outline of the presentation Epidemiology of metabolic risk factors at global, regional, and country levels Objectives of the study Methodology and results of phase one of the study Methodology and results of phase two of the study Conclusion and take home messages 3

4. Global epidemiologic transition 4 Lopez et al. Lancet 2006

5. Age-standardized cardiovascular mortality trends in selected high- income countries Vital registration data from WHO MaleFemale

6. Regional FPG trends 6 North America Male Female North Africa and Middle East Danaei et al. Lancet 2011 North Africa and Middle East

7. Male Female FPG, BMI and SBP trends in Iran between 1980 and 2008 FPGBMISBP 7 Farzadfar et al. Lancet 2011, Finucane et al. Lancet 2011, Danaei et al. Lancet 2011

8. The effects of risk factors on life expectancy in 2005, by region Female Life expectancy SoutheastNorth-NortheastWestCentralNational Male Life expectancy SoutheastNorth-NortheastWestCentralNational 8 Farzadfar, et al, population Health metrics, 2011

9. Iran’s health system InputsRural areasUrban areas Population32%68% Primary healthcare systemWell-established High coverage rates Inefficient Low coverage rates Insurance coverage63% before 2005 and 94% in 2008 77% General practitioners6,25052,700 Specialists13514,300 Nurses/midwives4,47062,600 Behvarz32,0000 9 Annual report of MoH. 2005, Utilization study. 2005

10. The objectives of the study Phase one:  Estimating prevalence, diagnosis and coverage of treatment for diabetes and hypertension by residency area  Estimating the treatment effects of diabetes and hypertension by residency area Phase two:  Estimating the association of Behvarz density with levels of FPG (which has an integrated and well defined program in PHC) and SBP 10

11. 11 Data source and definitions Data source: Non-Communicable diseases surveillance survey (2005) Diabetic definition: Fasting plasma glucose (FPG) ≥ 126 mg/dl or on medication to control blood sugar (either oral anti-hyperglycemic agents or insulin) Hypertensive definition: Blood pressure (SBP/DBP) ≥ 140/90 mmHg or on medication to control blood pressure 11

12. Estimation of treatment effects Matching: –All treated individuals were matched to controls based on propensity score of their age, sex, BMI, education and wealth index Random intercept regression analysis with an instrumental variable: –A proxy for potentially unobserved confounders that could affect the use of treatment but not the distribution of risk factors 12

13. Age standardized prevalence of diabetes and hypertension by sex and urban and rural residence 13 Hypertension Age standardized prevalence RuralUrbanCountry Diabetes Age standardized prevalence RuralUrbanCountry

14. Diabetes and hypertension diagnosis in Iran 14

15. Coverage of treatments for diabetes and hypertension in Iran by sex and urban and rural residence 15 Diabetes Crude coverage of treatment (percent) RuralUrbanCountry Hypertension Crude coverage of treatment (percent) RuralUrbanCountry

16. Treatment coverage of diabetes and hypertension by wealth quintile Probability of receiving treatment 16 Wealth quintile

17. Coefficients of regression to estimate the effect of diabetes and hypertension treatment on fasting plasma glucose and systolic blood pressure of treated individuals 17

18. The average effect of treatment by area of residency 18 Treatment effects for hypertensive individuals (mmHg) RuralUrban Treatment effects for diabetics (mmol/L) RuralUrban

19. What could be the reason for the diabetes treatment effect differences between rural and urban areas? 19

20. Behvarz 20

21. 21 Data sources Risk factor exposure: Non-communicable diseases surveillance survey (2005) Behvarz : Census data (2006) Physician: Outpatient care center mapping (2005) ICU bed Ministry of health database (2005) Other socioeconomic indicators Census data (2006) 21

22. 22 Methods Propensity score matching: –Individuals living in districts falling in different Behvarz density quintiles were matched based on age, sex, body mass index (BMI), education, marital status, wealth index, physician density, ICU bed density and employment rate District level random intercept regression: –Adjust for age, sex, BMI, education, marital status, wealth index, physician density, ICU bed density and employment rate 22

23. The association between Behvarz and physician densities and district average wealth index 23

24. Coefficients of regression to estimate the effect of Behvarz-worker density on fasting plasma glucose and systolic blood pressure in Iran 24

25. Average effect of Behvarz-worker density on fasting plasma glucose (A) and systolic blood pressure (B) 25

26. Take home messages Risk factors with large burden but no current program to control Sub-national level policy making Primary healthcare as an effective management of chronic conditions such as diabetes Cost considerations 26

27. Acknowledgements Co-authors and colleagues Majid Ezzati Thomas Bossert Hengameh Namdari Siamak Alikhani Hamidreza Jamshidi Co-authors and colleagues Christopher Murray Emmanuela Gakidou Ghobad Moradi Alireza Delavari 27

28. Thank you comments/questions?