1. Applied Epidemiology 304 Inequalities research Research involving Maori participants Adapted from slides from Dr Sue Crengle Sept 2013

2. What lecture will cover? Rationale for inequalities research What do you need to undertake inequalities research? Examples –Population based cross-sectional survey –Cohort study –Intervention trial

3. Rationale Why should we undertake inequalities research?

4. Rationale Why should we undertake inequalities research? –Social justice* Inequalities are unjust or unfair Ethical and moral dilemma for doctors Inequalities affect everyone Inequalities are expensive Inequalities are avoidable * Woodward and Kawachi JECH 2000; 54:923-929 * IOM Unequal Treatment 2003

5. Rationale Why should we undertake inequalities research? –Social justice –NZ Public Health and Disability Act reducing disparities between population groups

6. Rationale Why should we undertake inequalities research? –Social justice –NZ Public Health and Disability Act reducing disparities between population groups –Rights – human, Indigenous, Treaty rights

7. Rationale Why should we undertake inequalities research? –Social justice –NZ Public Health and Disability Act –Rights – human, Indigenous, Treaty rights –Health care that is not well-considered and responsive to Māori needs likely to increase inequalities –Move from simple description to understanding –Identify effective interventions

8. What do we need to do inequalities research? Sufficient explanatory power Accurate and complete exposure –Ethnicity data –SES data –Other exposures of relevance to outcome E.g. Cancer, CVD procedures Relevant questions Non-deficit approach

9. Appropriate explanatory power Māori statistical needs have equal status with those of the total NZ population Enables research to generate results that are as productive for Māori health development as for non- Māori Surveys and trials based on random samples of population produce non-Māori profiles of exposures, access to social determinants of health, health behaviours, health service access and outcomes

10. Appropriate explanatory power Findings based on this data will more closely reflect non-Māori than Māori realities Services, interventions, policy, and programmes developed from these research findings will be more likely to meet non-Māori than Māori needs

11. Appropriate explanatory power Appropriate numbers of non-Māori and Māori in surveys and trials will allow: –Equal statistical power for both population groups –Develop appropriate services, interventions, policy, and programmes for each group –Provide ethnic specific baseline estimates for subsequent surveys and trials

12. Ethnicity data collection “The term ethnic group has a wide meaning. It is not the same as nationality, race or place of birth. Ethnic groups are… …people who have culture, language, history or traditions in common. These people have a ‘sense of belonging’ to the group… It is possible to belong to more than one ethnic group. At different times of their life people may wish to identify with other groups”. (NZHIS, 1996)

13. Ethnicity data collection Why? –data analyses in research –planning and developing appropriate services –determining quality of services, tracking outcomes, monitoring inequalities –development of health policies –highlighting areas of clinical intervention e.g. sickle cell disease

14. Ethnicity data can… Introduce bias if same ethnicity question not used for numerator and denominators Change if person changes their ethnic affiliation over time – this is OK!

15. Validity of ethnicity data can be affected if… Wrong question used Data collector guesses rather than asks person to self-identify Only one ethnic group is allowed Changes are made to the question (response categories themselves or the order of the categories)

16. Collecting and using ethnicity data Self-identification essential –As many as applies to them Should be checked at each interaction Must use same question –NZ Census question –Same wording, layout Classification as per ethnicity data protocol

17. More information… ‘Ethnicity data protocols for the Health and Disability Sector’ Ministry of Health Feb 2004 Available on http://www.moh.govt.nz/moh.nsf/49ba80 c00757b8804c256673001d47d0/038aa 30b8a5ef30dcc256e7e007c98c4?OpenD ocument

18. 20012006

19. Some examples Cross-sectional survey – determinant of health and contribution to inequalities Exaimination of CVD procedures and inequalities in procedures Intervention trial

20. NZHS 2002/03 (Harris et al, 2006a and 2006b) National Health Survey August 2002 to January 2004 Adults aged 15 years and over Approx. 12,500 respondents –Māori 4000 –Pacific 1000 –Asian 1000 Response rate 72%

21. Racial Discrimination Questions (Harris et al, 2006) Have you ever been the victim of an ethnically motivated attack (verbal or physical abuse to the person or property) in New Zealand? Have you ever been treated unfairly (e.g. treated differently, kept waiting) by a health professional (e.g. doctor, nurse, dentist etc.) because of your ethnicity in New Zealand? Have you ever been treated unfairly at work or been refused a job because of your ethnicity in New Zealand? Have you ever been treated unfairly when renting or buying housing because of your ethnicity in New Zealand?

22. Prevalence of physical and verbal attack (ever) by ethnic group

23. Prevalence of unfair treatment in institutional settings (ever) by ethnic group

24. Levels of self-reported exposure to any racial discrimination by ethnic group Level**MāoriPacific Asian European/Other * 2 only 21.1%1 only 3 or more 8.3% 4.5% 17.2% 4.4% 2.8% 21.1% 5.2% 1.6% 11.6% 2.5% 0.5% *Includes all non-Māori, non-Pacific, non-Asian **Number of racial discrimination variables to which respondents were exposed

25. Odds ratio of experience of racial discrimination with health outcomes* *Adjusted for sex, age, dep, ethnicity# not statistically significant at the 95% level Physical attack Verbal attack Unfair Treatment Health Work Housing Poor/fair self-rated health Poor physical functioning Poor mental health Current smoking CVD Overall discrim. 1.93 1.96 3.46 2.21 1.27 2.15 1.55 1.47 2.43 1.70 1.42 2.16 1.73 2.75 1.73 1.39 2.16 1.48 1.70 1.35 1.73 1.29 # 1.69 1.79 1.31 0.68 # 1.591.771.671.38

26. Odds ratios for increasing exposure to racial discrimination with health outcomes* *Adjusted for sex, age, dep, ethnicity # Not statistically significant at the 95% level None One Two Three+ Poor/fair self-rated health Poor physical functioning Poor mental health Current smoking CVD 1.00 2.02 2.26 3.60 1.00 1.48 1.91 2.15 1.00 1.56 2.47 2.95 1.00 1.61 1.59 2.93 1.00 1.17 # 2.36 1.41 #

27. Odds ratio of ethnicity (Māori vs European) on health outcomes

28. Harris R, Tobias M, Jeffreys M, Waldegrave K, Karlsen S, and Nazroo J Effects of self-reported racial discrimination and deprivation on Māori health and inequalities in New Zealand: cross-sectional study The Lancet 2006; 367:2005-2009. http://www.thelancet.com.ezproxy.auckland.ac.nz/journals/lancet/article/PII S0140673606688909/fulltext Harris R, Tobias M, Jeffreys M, Waldegrave K, Karlsen S, and Nazroo J Racism and health: The relationship between experience of racial discrimination and health in New Zealand Social Science & Medicine 63 (2006) 1428–1441

29. Ischaemic heart disease and intervention (Harwood et al 2006)  Follow 8,000 Māori and 90,000 non-Māori patients admitted to hospital for IHD between 1996 and 2004  From first admission and up to 9 years  Controlled for various factors including age, sex, disease and co-morbid condition

30. Data Sources Quality ethnicity data – Ever M ā ori New Zealand Health Information Service:  Public Hospital Discharges  All principal and secondary diagnoses (ICD-9 and ICD10)  All procedures (ICD-9 and ICD-10)  Demographic factors (age, sex, ethnicity, domicile code)  Mortality  Underlying cause of death, other contributing causes, other relevant conditions, cancer as a non-contributing cause of death  National Health Index

31. IHD procedure receipt during 1 st hospital admission Procedure Māori % n=8,224 Non-Māori % n=90,014 Relative Rate (95% CI) Angiography17.522.30.79 (0.75-0.83) Angioplasty3.26.00.53 (0.46-0.59) CABG1.31.90.68 (0.56-0.82)

32. Procedure Receipt during 1 st admission – Māori : non-Māori Ratios Procedure HR Age, sex adjusted HR Age, sex, diagnosis adjusted HR Age, sex, diagnosis, co- morbidity Angiography 0.60 Angioplasty 0.39 CABG 0.59

33. Procedure Receipt during 1 st admission – Māori : non-Māori Ratios Procedure HR Age, sex adjusted HR Age, sex, diagnosis adjusted HR Age, sex, diagnosis, co- morbidity Angiography 0.600.62 Angioplasty 0.39 CABG 0.590.58

34. Procedure Receipt during 1 st admission – Māori : non-Māori Ratios Procedure HR Age, sex adjusted HR Age, sex, diagnosis adjusted HR Age, sex, diagnosis, co- morbidity Angiography 0.600.620.68 (0.65-0.72) Angioplasty 0.39 0.43 (0.38-0.49) CABG 0.590.580.64 (0.53-0.79)

35. Māori/non-Māori ratios for IHD Procedure (Ever) Procedure Adjust for age, sex, diagnosis & Co-morbid as secondary diagnosis on index admission & Co-morbid as any diagnosis on index or earlier admission Angiography0.74 (0.71-0.76) 0.77 (0.74-0.79) 0.78 (0.76-0.81) PCI0.53 (0.50-0.57) 0.55 (0.52-0.59) 0.57 (0.54-0.61) CABG0.82 (0.77-0.88) 0.80 (0.75-0.86) 0.84 (0.79-0.90)

36. Māori/non-Māori ratios for deaths from IHD 1996 to 2003 Time HR Age, sex adjusted HR Age, sex, diagnosis adjusted HR Age, sex, diagnosis, co- morbidity First admission 1.40 (1.21-1.62) 1.40 (1.21-1.62) 1.35 (1.16-1.) After first admission 1.85 (1.69-2.02) 1.80 (1.65-1.97) 1.72 (1.57-1.88)

37. Possible interventions Focus on clinical audit and a web based clinical decision support programme…

38. Summary Inequalities research is important Explanatory power is essential Accurate, complete, valid exposure ascertainment important