Ethnic inequalities in mortality: Trends and explanations,

Transcription

1 Pharmac, Oct 2009 Professor Tony Blakely Ethnic inequalities in mortality: Trends and explanations, Acknowledgments: Tobias, Atkinson, Woodward, and too many more to name 1 Index

2 Structure of lecture 1. Indigenous health inequalities 2. Māori:non-Māori inequalities in mortality in Aotearoa: Trends in life expectancy since European contact Cause specific mortality trends in last 25 years 3. Explanations for ethnic inequalities: socioeconomic position health services risk factors (e.g. tobacco) racism 4. What might Pharmac do? Index 2

3 Indigenous health inequalities All colonised countries have health inequalities that favour the colonisers The size of Indigenous:non-Indigenous health inequalities vary by: history of each ethnic group and their relationship since contact power, resource acquisition/dispossession, socioeconomic resources, racism cultural dominance, subordination and intersection And they also vary due to proximal risk factors such as smoking 3

4 How do social factors get under the skin? WHO Commission on Social Determinants of Health 4

5 Simple causal framework The total contribution of changing variables >> 100% Socioeconomic position: Indigeneity History, colonisation, racism Education Income Class Health services: Health status: Access to.. and through Quality Morbidity Mortality Self-determined Risk factors: Smoking Diet Physical activity Alcohol 5

6 90 Non-Mäori (SNZ) Male 80 Non-Mäori (SNZ) Female Māori pre WWII Male 70 Māori pre WWII Female 60 Mäori (SNZ) Male n n n 30 Mäori (SNZ) Female Māori (correcting for undercount) Male Māori (correcting for undercount) Female Best country in the world Male 20 Best country in the world Female England & Wales Male England & Wales Female 6

7 90 Non-Mäori (SNZ) Male 80 Non-Mäori (SNZ) Female 70 Māori pre WWII Male 60 Māori pre WWII Female Mäori (SNZ) Male 30 Mäori (SNZ) Female 20 Māori (correcting for undercount) Male Māori (correcting for undercount) Female

8 NZCMS: method in one slide 1991 census cohort (0-74 yr olds) Anonymous and probabilistic record linkage Deaths

9 All-cause mortality rates by ethnicity, 1-74 yrs Males Females Percentage decline to Mäori Pacific Asian European/Other 25% 14% 58% 42% 22% 10% 50% 35% Index 9

10 Absolute & relative measures of inequality Rate ratio = 2.37 Rate difference = 403 per 100,000 10

11 All-cause mortality, 1-74 years Relative and absolute measures od inequality Māori Pacific Standardised Rate Ratios Males Females ( ) 1.94) 2.30 (1.85 ( ) 2.47) ( ( ) 2.27 ( ) ( ) 2.51 ( ) ( ) 2.78 ( ) ( ) 2.74 ( ) P (Trend) ( ) 1.41) ( ) ( ( ) 1.50 ( ) ( ) 1.57 ( ) ( ) 1.86 ( ) ( ) 1.82 ( ) P (Trend) ( ) ( ) Standardised Rate Differences Males Females ( ) 472) ( ) 397) 418 ( ( ( ) 320 ( ) 469 ( ) 336 ( ) 485 ( ) 347 ( ) 403 ( ) 311 ( ) ) (13-520) 201) 107 (44988 (22242 ( ) 127 (72-181) 164 ( ) 126 (83-170) 287 ( ) 167 ( ) 233 ( ) 145 ( ) (84-121) (78-110) 11

12 Māori compared to nmnpna - standardised rates differences and ratios (SRDs and SRRs) SRR SRD per 100,000 Ethnic disparities SRD, Males SRD, Females SRR, Males SRR, Females 12

13 13

14 Cardiovascular disease, 1-74 yr olds By what percentage has CVD mortality rates declined from to : a) for European; b) for Māori? 40% and 45% for male and female Māori 64% and 65% for male and female Europeans 14 Index

15 CVD mortality rates by ethnicity Falling: 40-45% for Māori; 60-65% for European/Other 15 Index

16 IHD mortality rates by ethnicity, 1-74 yrs 16

17 Stroke mortality rates by ethnicity, 1-74 yrs 17

18 Cancer mortality rates by ethnicity, 1-74 yrs 18

19 All cancer, 1-74 yrs Relative and absolute measures od inequality Māori Pacific P (Trend) P (Trend) 0.71 Standardised Rate Ratios Males Females (1.73 ( ) 1.74) 1.67 (1.85 ( ) 1.91) ( ) 1.61 ( ) ( ) 1.69 ( ) ( ) 1.98 ( ) ( ) 2.02 ( ) 0.03 (1.73 ( ) 1.59) 0.95 (1.85 ( ) 1.36) ( ) 1.07 ( ) ( ) 0.93 ( ) ( ) 1.29 ( ) ( ) 1.38 ( ) 0.05 ( ) ( ) Standardised Rate Differences Males Females 96) 90) 70 (84( ) 68 (78( ) 71 (48-94) 62 (43-80) 96 (74-118) 69 (51-87) 102 (84-121) 94 (78-110) 93 (76-109) 90 (76-105) (84-121) (78-110) 70) 30) 22 (-25-5 (-39(-3-76) 36 7 (-22-36) 10 (-21-40) -7 (-29-15) (6-50) 60 (32-89) 28 (2-46) (15-52) (84-121) (78-110) 19

20 Lung cancer mortality rates by ethnicity 20 Index

21 Breast cancer incidence by ethnicity Incidence compared to mortality trends 21 Index

22 Cervical cancer incidence by ethnicity CancerTrends standardised rates per 100,000 Blakely, Shaw, Atkinson, Tobias, Sarfati, Cunningham. CancerTrends: Preliminary results. [Not for distribution] 22 Index

23 Chronic lung disease mortality rates by ethnicity 23

24 Injury mortality rates by ethnicity, 1-74 yrs 24

25 Suicide rates by ethnicity, 1-74 yrs 25

26 26

27 Suicide and injury death rates by ethnicity 27

28 Cause of death contribution to absolute inequality 28

29 Structure of lecture Indigenous health inequalities Māori:non-Māori inequalities in mortality in Aotearoa: Trends in life expectancy since European contact Cause specific mortality trends in last 25 years Explanations for ethnic inequalities: socioeconomic position health services risk factors (e.g. tobacco) racism What might Pharmac do? 29 Index

30 How much of the mortality gap due to SES? Socioeconomic position: Death rate per 100,000 Death rate per 100, Education Income Class Indigeneity non-māori non-pacific Māori non-māori Māori Total death rate non-pacific Health services: Health status: a. 10% Access to.. and through Quality b. 25% a. 10% c. 50% b. 25% d. 75% c. 50% Morbidity Mortality Self-determined e. 90% d. 75% e. 90% Gap attributable to SES Gap NOT attributable to SES Risk factors: History, Gap Smoking Total death rate attributable to SES Gap NOT attributable to SES colonisation, Diet Examine mortality rate trends by ethnicity and income racism cross-classified Physical activity Use regression analyses to adjust ethnic gaps in mortality for multiple socio Alcohol economic factors, labour force status and NZDep 30

31 All-cause mortality by ethnicity (Māori [black], European [orange]) by income 31

32 All-cause RR (Māori cf European), adjusting for socio-economic factors, PLM and NZDep Age Sex years Males Model A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D Females A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D years Males A: Adjusted for age and region B: Model A plus socio-economic factors * D: Model B plus NZDep % reduction excess rate ratio A to B % reduction excess rate ratio A to D Females A: Adjusted for age and region B: Model A plus socio-economic factors * D: Model B plus NZDep % reduction excess rate ratio A to B % reduction excess rate ratio A to D 32

33 All-cause RR (Māori cf European), adjusting for socio-economic factors, PLM and NZDep Age Sex years Males Model A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D Females A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D years Males A: Adjusted for age and region B: Model A plus socio-economic factors * D: Model B plus NZDep % reduction excess rate ratio A to B % reduction excess rate ratio A to D Females A: Adjusted for age and region B: Model A plus socio-economic factors * D: Model B plus NZDep % reduction excess rate ratio A to B % reduction excess rate ratio A to D 33

34 All-cause RR (Māori cf European), adjusting for socio-economic factors, PLM and NZDep Age Sex years Males Model A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D Females A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D A: Adjusted for age and region B: Model A plus socio-economic factors * years Males D: Model B plus NZDep % reduction excess rate ratio A to B % reduction excess rate ratio A to D Females A: Adjusted for age and region B: Model A plus socio-economic factors * D: Model B plus NZDep % reduction excess rate ratio A to B % reduction excess rate ratio A to D 34

35 All-cause RR (Māori cf European), adjusting for socio-economic factors, PLM and NZDep Half to two thirds of gap due to socioeconomic position Age Sex years Males Model A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D % % % 58% % 53% % 48% Females A: Adjusted for age and region B: Model A plus socio-economic factors * C: Model B plus position in labour market D: Model C plus NZDep % reduction excess rate ratio A to C % reduction excess rate ratio A to D % % % 44% % 43% % 48% A: Adjusted for age and region B: Model A plus socio-economic factors * D: Model B plus NZDep % reduction excess rate ratio A to B. 29%. 41% % % % % reduction excess rate ratio A to D % 39% 44% % % % 36% % 32% % 37% years Males Females A: Adjusted for age and region B: Model A plus socio-economic factors * D: Model B plus NZDep % reduction excess rate ratio A to B % reduction excess rate ratio A to D 35

36 Life expectancy trends by ethnicity Life expectancy in years Non-Mäori (SNZ) Male Mäori (SNZ) Male Mäori (NZMCS) Male Māori (MoH latest) Male Non-Mäori (SNZ) Female Mäori (SNZ) Female Mäori (NZMCS) Female Māori (MoH latest) Female Index

37 Trends in unemployment rates Life expectancy in years 85 (Social Report, MSD; Source: SNZ Household Labour Force Survey) Non-Mäori (SNZ) Male Mäori (SNZ) Male Mäori (NZMCS) Male Māori (MoH latest) Male Non-Mäori (SNZ) Female Mäori (SNZ) Female Mäori (NZMCS) Female Māori (MoH latest) Female

38 Mutton line at Westfield Freezing Works, Auckland 38

39 Saw-bench, Wanganui 39

40 40

41 Answering the question How much of the increase in inequality in mortality between Māori and non-māori was attributable to increasing socioeconomic inequality? Complex, but highly policy (& politically) relevant Lets look at the RRs over time, and see how much of the increase was due to increasing contributions from socio-economic factors and PLM 41

42 Males Females Males b) yrs Rate ratio for Maori compared to European a) yrs Rate ratio for Maori compared to European RR Māori cf European, decomposed by contribution from socio-economic factors and PLM Females Component or RR attributable to socio-econmic factors Component of RR attributable to position in labour market (PLM) Component or RR attributable to socio-econmic factors Component of RR NOT attributable to measured socio-economic factors and PLM Component of RR NOT attributable to measured socio-economic factors and PLM 42

43 CABG and PTCA rates per 100,000 Females Health services matter too Mäori Pacific Other CABG Angioplasty Source: Tukuitonga & Bindman,

44 Māori-nMnP 5-year cancer survival Ratio of Maori to non-maori non-pacific relative survivals Health services matter 1 Relative survival adjusted for age Relative survival adjusted for age and stage st ea r B i rv e C x m ra tu th c e r re r/u n/ e o l et Co ur / ey dn i K a m o an el M ry va O St h ac om id ro y Th d an l g u er t U s Source: Jeffreys M, Stevanovic V, Tobias M, Lewis C, Ellison-Loschmann L, Pearce N, Blakely T. Ethnic inequalities in cancer survival in New Zealand: linkage study. American Journal of Public Health 2005;95(5): (Restricted to cancers with more than 100 Mäori cases and greater than 65% with stated stage) 44

45 Hill S et al (in press). Māori:nonMaori disparities in colon cancer survival 45 Index

46 Hill S et al (in press). Māori:nonMaori disparities in colon cancer survival Adjusted for: Additional variables in model: Hazard Ratio 95% CI 0. Unadjusted Demographics Age, sex, year of diagnosis Disease factors + Stage Grade Site Emergency presentation Comorbidities* Smoking Definitive surgery Surgeon type Delay to surgery Adjuvant chemotherapy Treatment facility type Small area deprivation Rurality Patient factors 4. Treatment processes 5. Health care access 46 Index

47 Wider Determinants The Impacts of Racism on Health itutionalized Inst SES l tia en t fer en Dif eatm tr Health outcomes s es Str H beh ealth avi ors Access to health care Jones et al,

48 Racism one NZ research example Harris et al, Lancet 2006 New Zealand Health Survey Self-rated health, reduction due to adjusting for racial discrimination in last 12 months, ascertained with five questions: verbal attacks, physical attacks, and unfair treatment by a health professional, at work, or when buying or renting housing. 48

49 Trends in smoking by ethnicity Tobacco use survey Percent 60 Maori Pacific peoples European/Other Year Source: Ministry of Health Tobacco Trends 2007: A brief update on monitoring indicators. Wellington: Ministry of Health. 49

50 Trends in smoking

51 Trends in Māori smoking

52 Previous official Ministry estimates Use indirect, but internationally accepted, Peto method Uses Peto method, based on using lung cancer rates and standard relative risks, to infer total smoking-related mortality burden for total, Māori and European/Other Leads to ballpark conclusions like: a sixth of nmnp deaths due to tobacco, and a third of Māori deaths due to tobacco [all ages combined] These Peto estimates are (in my view) incorrect: do not allow for interaction of ethnicity and smoking (ie, the relative risks of smoking-mortality vary by ethnic group, as shown above) totally reliant on lung cancer rates. Interestingly, ethnic differences in lung cancer mortality greater than one would expect on basis of smoking rates 52

53 Lung cancer mortality rates by ethnicity 53 Index

54 Mortality by smoking status, males NZ Census-Mortality Study, Hunt et al, IJE 2005 CPS II ~

55 What is contribution of smoking to inequalities? Method: Standardise nmnp and Māori to Māori popn -1% % 3% 8% nmnp Mäori Men Women Age-Smok-stand Age-stand Age-Smok-stand Age-stand Age-Smok-stand Age-stand Age-Smok-stand 0 Age-stand Standardised mortality rate per 100, i.e. not as much as one might expect Source: Blakely T, Fawcett J, Hunt D, Wilson N. What is the contribution of smoking and socioeconomic position to ethnic inequalities in mortality in New Zealand? Lancet, 2006.

56 a) Males The contribution of active smoking Wilson N, Blakely T, Tobias M. What potential has tobacco control for reducing health inequalities? The New Zealand situation. International Journal for Equity in Health 2006;5(1):14. Gap attributable to smoking - B 2000 Mortality rate per 100,000 The contribution of smoking to ethnic gaps in mortality is larger if we model a counterfactual world where nobody ever smoked, compared to assuming that everyone smoked as Maori did in 1996 (i.e. PAR%, or scenario B on right) Gap attributable to smoking - A 5% 5% 90% Gap not attributable to smoking % 25% % Smoking-attributable rate 500 Never smoker rate 0 nmnp Mäori Ethnic gap Postschool Nil quals Educ gap b) Females Gap attributable to smoking - A 8% 17% 1500 Mortality rate per 100, yr gaps, Gap attributable to smoking - B 1200 Gap not attributable to smoking 75% % 20% 64% 600 Smoking-attributable rate 300 Never smoker rate 0 nmnp Mäori Ethnic gap Postschool Nil quals Educ gap 56

57 What really is the contribution of smoking? Summary, or my (expert) best guess Depends on the counterfacutal Māori population and distribution of smoking (Standardisation) World where no one had ever smoked (PAR%) Depends on time Now and in the future the contribution of smoking to ethnic gaps in mortality will probably be larger due to decrease in background mortality rates yet constant excess mortality due to tobacco Depends on amount of error in previous estimates Peto clearly too high But NZMCS direct method (both standardisation and PAR%) too low due to measurement error of smoking About 10 to 20% of Mäori to nmnp gap in mortality attributable to tobacco smoke, and a substantial contribution to deaths within each ethnic group And yes, I still believe that tobacco control is very important for reducing inequalities in health 57

58 Summary graph for 10% contribution Sexes combined, , year olds 2000 Death rate per 100, Amount NOT attributable to smoking Amount attributable to smoking non-māori nonpacific (nmnp) Māori Gap in death rates between Māori and nmnp 58

59 Simple causal framework The total contribution of changing variables >> 100% Socioeconomic position: Indigeneity History, colonisation, racism Education Income Class Health services: Health status: Access to.. and through Quality Morbidity Mortality Self-determined Risk factors: Smoking Diet Physical activity Alcohol 59

60 90 Non-Mäori (SNZ) Male 80 Non-Mäori (SNZ) Female Māori pre WWII Male 70 Māori pre WWII Female 60 Mäori (SNZ) Male 50 Mäori (SNZ) Female 40 Māori (correcting for undercount) Male Māori (correcting for undercount) Female 30 Projected non-māori 2.0% Male 20 Projected non-māori 2.0% Female Projected Māori 2.0% Male Projected Māori 2.0% Female 60

61 20/20 vision on 2040 Visioning the end of Māori-nonMāori inequalities in LE 90 Non-Mäori (SNZ) Male 80 Non-Mäori (SNZ) Female Māori pre WWII Male 70 Māori pre WWII Female 60 Mäori (SNZ) Male 50 Mäori (SNZ) Female 40 Māori (correcting for undercount) Male What do you think about this vision? 30 Projected non-māori 2.0% Male Feasible? 20 Projected non-māori 2.0% Female Would you/pharmac buy into it? Māori (correcting for undercount) Female Projected Māori 3.5% Male Projected Māori 3.5% Female 61 Index