tracking disparity: trends in ethnic and socio-economic inequalities in mortality, 1981 - 2004

1

Tracking Disparity: Trends in ethnic and socio-economic inequalities

in mortality, 1981 - 2004

Professor Tony Blakely, ASBHM 2008Martin Tobias, June Atkinson, Li-Chia Yeh, Ken Huang.

2

Overview• Some background on NZCMS• Part I: Ethnic results • Part II: Socio-economic results• Part III: Contribution of socioeconomic position to ethnic

inequalities• Part IV: Contribution of “behaviour” to ethnic and socio-

economic inequalities trends in mortality:– Behaviour of society, institutions and governments - structural– Behaviour of health services– Behaviour of individuals – tobacco (diet, PA)– Discriminatory behaviour – racism

There will be audience participation!

Keen to have your questions/challenges during, and comments at end (eg, other behavioural data from NZ, Australian comparisons)

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www.wnmeds.ac.nz/nzcms-info.html

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Main sources for this presentation

1. Blakely T, Tobias M, Atkinson J, Yeh L-C, Huang K. Tracking Disparity: Trends in ethnic and socioeconomic inequalities in mortality, 1981-2004. Wellington: Ministry of Health, 2007.

2. Blakely T, Tobias M, Robson B, Ajwani S, Bonne M, Woodward A. Widening ethnic mortality disparities in New Zealand 1981-99. Soc Sci Med 2005;61(10):2233-2251.

3. 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? The Lancet 2006;368(9529):44-52.

4. Blakely T, Tobias M, Atkinson J. Inequalities in mortality during and after restructuring of the New Zealand economy: repeated cohort studies, 2008:BMJ.39455.596181.25. (Appearing in hardcopy 16 Feb.)

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NZCMS: method in one slide

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1991 census cohort (0-74 yr olds)

DeathsAnonymous and probabilistic record linkage

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Method to calculate mortality rates

• Calculate rates directly off linked NZCMS data, using census ethnicity and income and standard cohort methods

• Ages 1-74, age-standardised to WHO world population

• Each of five ‘periods’ (ie, 1981-84, … 2001-04) are three years in duration – not full five-year intercensal

• What has NZCMS added to New Zealand information?– Now have correct trends in mortality by ethnicity

– Now have one of world’s largest cohort studies of smoking – active and passive

– Rates by many socio-economic factors, with ability for multivariable analyses

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Part I: Ethnic inequalities in mortality

8

All-cause mortality rates by ethnicity, 1-74 yrs

Percentage decline 1981-84 to 2001-04 Mäori Pacific Asian European/Other Males 25% 14% 58% 42% Females 22% 10% 50% 35%

9

Absolute and relative measures of inequality

Rate ratio = 2.37

Rate difference = 403 per 100,000

10

Ethnic disparities

Māori compared to nMnPnA - standardised rates differences and ratios (SRDs and SRRs)

200

300

400

500

600

700

800

1981-84 1986-89 1991-94 1996-99 2001-04

SR

D p

er 1

00,0

00

0

0.5

1

1.5

2

2.5

3

SR

R

SRD, Males SRD, Females

SRR, Males SRR, Females

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50

55

60

65

70

75

80

85

1950 1960 1970 1980 1990 2000

Lif

e e

xp

ec

tan

cy

in y

ea

rs

Non-Mäori (SNZ) Male Non-Mäori (SNZ) Female

Mäori (SNZ) Male Mäori (SNZ) Female

Mäori (NZMCS) Male Mäori (NZMCS) Female

12

Cardiovascular disease, 1-74 year olds combined

• By what percentge has CVD mortality rates declined from 1981-84 to 2001-04: a) for European; b) for Māori?– 64% and 65% for male and female Europeans

– 40% and 45% for male and female Māori

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CVD mortality rates by ethnicity, 1-74 yrs

15

IHD mortality rates by ethnicity, 1-74 yrs

17

All-cancer mortality rates by ethnicity, 1-74 yrs

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Lung cancer mortality rates by ethnicity

19

Colorectal cancer mortality rates by ethnicity

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Lung cancer, males

0

20

40

60

80

100

1980-84 1985-89 1990-95 1996-99

Prostate cancer

0

5

10

15

20

25

1980-84 1985-89 1990-95 1996-99

Colorectal cancer, males

0

5

10

15

20

25

1980-84 1985-89 1990-95 1996-99

Lung cancer, females

0

15

30

45

60

75

1980-84 1985-89 1990-95 1996-99

Breast cancer

0

10

20

30

40

50

1980-84 1985-89 1990-95 1996-99

Colorectal cancer, females

0

4

8

12

16

20

1980-84 1985-89 1990-95 1996-99

Colorectal cancer mortality rates:

Decades of Disparity I

21

Breast cancer rates by ethnicity

22

Suicide rates by ethnicity, 1-74 yrs

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Cause of death contributions to absolute inequality

25

Part II:Socio-economic inequalities in mortality

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Ethnicity, socio-economic position and health

SES

Ethnicity

Mortality

27

Method• Use NZCMS data: 81-84, 86-89, 91-94, 96-99, 01-04

• Treated equivalised (Jensen) household income as main socio-economic factor:– same fixed $ groups

(ie, real 1996 dollars)

• Calculate age-standardised mortality rates

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Low-medium income cut-point (1996 real dollars)

Medium-high income cut-point (1996 real dollars)

$15,000

$30,000

$45,000

$60,000

$75,000

1981 1986 1991 1996

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All-cause mortality rates by income

• Mostly parallel tracking in absolute terms• 30% and 41% decreases for low and high income males, respectively• 27% and 37% decreases for low and high income females, respectively

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Are inequalities increasing (81-84 to 96-99)?



Rate ratio = 1.44

Rate ratio = 1.72

Answer: Absolutely not, relatively yes

31

Income disparities

Low compared to high income - slope and relative indices of inequality (SIIs and RIIs)

0

100

200

300

400

500

600

700

800

1981-84 1986-89 1991-94 1996-99 2001-04

SII

per

100

,000

0

0.5

1

1.5

2

2.5

3

3.5

RII

Income SII, males Income SII, females

Income RII, males Income RII, females

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Cardiovascular disease, 1-74 year olds

34

CVD mortality, 1-74 years: relative and absolute measures of inequality

Sex Age Cohort SRR

Low:High Relative index of inequality (RII)

SRD Low:High

Slope index of inequality (SII)

Males 1-74 yrs 1981-84 1.50 1.9 (1.6 - 2.1) 101 150 (118 - 182) 1986-89 1.45 1.8 (1.5 - 2.1) 81 125 (76 - 174) 1991-94 1.54 2.1 (1.8 - 2.5) 78 129 (99 - 159) 1996-99 1.81 2.8 (2.3 - 3.4) 82 134 (114 - 154) 2001-04 1.84 2.9 (2.4 - 3.5) 66 103 (80 - 126) P (Trend) 0.04 0.03 0.04 0.11 Females 1-74 yrs 1981-84 1.43 1.8 (1.4 - 2.3) 42 68 (53 - 83) 1986-89 1.48 1.7 (1.3 - 2.1) 40 53 (51 - 54) 1991-94 1.69 2.3 (1.7 - 3.0) 41 65 (51 - 79) 1996-99 1.76 2.6 (2.0 - 3.5) 34 56 (43 - 69) 2001-04 1.66 2.8 (2.1 - 3.7) 26 46 (44 - 49) P (Trend) 0.08 0.03 0.02 0.07

35

All cancer, 1-74 year olds

36

Lung cancer, 1-74 year olds

37

Cause of death contributions to absolute inequality

38

Part III: Socio-economic mediation of ethnic

inequalities in mortality

39

Audience question: how much of the gap in mortality rates is due to differences in socio-economic position?

0

250

500

750

1000

1250

1500

1750

2000

non-Māorinon-Pacific

Māori a. 10% b. 25% c. 50% d. 75% e. 90%

Dea

th r

ate

pe

r 1

00,0

00

Total death rate Gap attributable to SES Gap NOT attributable to SES

40

Answering the question “What proportion (on average) of the Māori:European mortality inequality

was mediated by socioeconomic position?”

1. Examine mortality rate trends cross-classified by ethnicity and income

2. Use regression analyses to adjust ethnic gaps in mortality for multiple socio-economic factors, labour force status and NZDep

41

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

42

All-cause RR (Māori cf European), adjusting for socio-economic factors, PLM and NZDep

Age Sex Model 1981-84 1986-89 1991-94 1996-99 2001-04

25-59 years Males A: Adjusted for age and region 2.42 2.21 2.60 2.65 2.57

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 2.41 2.38 2.82 2.80 2.59


C: Model B plus position in labour market

D: Model C plus NZDep





D: Model B plus NZDep

% reduction excess rate ratio A to B




D: Model B plus NZDep



43


Age Sex Model 1981-84 1986-89 1991-94 1996-99 2001-04


B: Model A plus socio-economic factors * 2.04 1.89 2.03 2.09 2.00

C: Model B plus position in labour market 1.97 1.79 1.81 1.91 1.88

D: Model C plus NZDep . . 1.67 1.78 1.81











D: Model B plus NZDep . . 1.59 1.68 1.63








44


Age Sex Model 1981-84 1986-89 1991-94 1996-99 2001-04





% reduction excess rate ratio A to C 31% 35% 49% 45% 44%

% reduction excess rate ratio A to D - - 58% 53% 48%





% reduction excess rate ratio A to C 26% 29% 35% 32% 37%





% reduction excess rate ratio A to B 29% 41% 34% 28% 36%





% reduction excess rate ratio A to B 21% 24% 26% 22% 28%


45

What proportion (on average) of the Māori:European mortality inequality was

mediated by socioeconomic position?

• At least half for working age adults, and about one third for older adults.

• Small area deprivation contributed an extra 10%, over and above personal socio-economic factors.

• For 25-59 year olds position in the labour market contributed 10% to 15%.

• We have probably underestimated the contribution of socio-economic position in total (i.e. due to measurement error), BUT without doubt not all of ethnic inequalities in mortality are explained by socio-economic position.

46

Part IV: Contribution of “behaviour” to ethnic and socio-economic

inequalities trends in mortality:- Behaviour of society, institutions and governments

(structural)- Behaviour of health services

- Behaviour of individuals – tobacco (diet, PA)- Discriminatory behaviour – racism

49

1984 and all that ….

• 1970s and early 1980s:– subsidies, regulated economy, low unemployment, etc..

• 1984 to 1993:– deregulation of the financial sector

– reorganising the state sector

– ending of state support for industry

Resulting in:– flatter tax rates, targeted welfare, regressive consumption tax,

market rentals, privatisation, user charges, widening income inequalities, etc…

– health reform

50

Social determinants of health

Hui Taumata 1984:

‘shock absorbers in the economy’

51

Unemployment rates by ethnicity (Social Report, MSD; Source: Statistics New Zealand,

Household Labour Force Survey)

52

50

55

60

65

70

75

80

85

1950 1960 1970 1980 1990 2000

Lif

e e

xp

ec

tan

cy

in y

ea

rs

Non-Mäori (SNZ) Male Non-Mäori (SNZ) Female

Mäori (SNZ) Male Mäori (SNZ) Female

Mäori (NZMCS) Male Mäori (NZMCS) Female

53

Empirically 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

54

RR Māori cf European, decomposed by contribution from socio-economic factors and PLM

a) 25-59 yrs

1.0

1.5

2.0

2.5

3.0

1981

-84

1986

-89

1991

-94

1996

-99

2001

-04

1981

-84

1986

-89

1991

-94

1996

-99

2001

-04

Males Females

Rat

e ra

tio

fo

r M

aori

co

mp

ared

to

Eu

rop

ean

Component or RR attributable to socio-econmic factors

Component of RR attributable to position in labour market (PLM)

Component of RR NOT attributable to measured socio-economicfactors and PLM

b) 60-74 yrs

1.0

1.5

2.0

2.5

1981

-84

1986

-89

1991

-94

1996

-99

2001

-04

1981

-84

1986

-89

1991

-94

1996

-99

2001

-04

Males Females

Rat

e ra

tio

fo

r M

aori

co

mp

ared

to

Eu

rop

ean

Component or RR attributable to socio-econmic factors

Component of RR NOT attributable to measured socio-economic factorsand PLM

55

How much of the increase in inequality in mortality between Māori and non-Māori was attributable to

increasing socioeconomic inequality?

• Much of it for 25-59 year old males

• About half of it for 25-59 year old females

• Some of it 60-74 year olds. Other explanations for 60-74 year olds might include: – Cohort effects?

– Misclassification of socio-economic position?

– Socio-economic position earlier in life course more important?

56

Structural reform of 1980s and 1990s – impact on trends in socio-economic inequalities in mortality?

• Hypothesis: Inequalities in health may have increased in New Zealand as a result of structural reforms in 1980s and 1990s.

• Test: Compare trends in New Zealand with trends in other countries without such rapid changes.

57

11.5

22.5

33.5

44.5

1980

1985

1990

1995

Denmark

Finland

Norw ay

New Zealand(age andethnicitystandardised)

New Zealand(agestandardised)

Males, All Causes

1

1.5

2

2.5

3

3.5

4

4.5

1980 1985 1990 1995

Males, CVD

1

1.5

2

2.5

3

3.5

4

4.5

1980 1985 1990 1995

Males, Other Causes

1

1.5

2

2.5

3

3.5

4

4.5

1980 1985 1990 1995

Females, All Causes

1

2

3

1980 1985 1990 1995

Females, CVD

1

2

3

4

5

6

7

8

1980 1985 1990 1995

Females, Other Causes

1

2

3

1980 1985 1990 1995

RII by Education Level, by Time Period, Country and Cause of Death – 30-59 years

58

Possible explanations, I: Structural reform of 1980s and 1990s?

• Hypothesis: Inequalities in health may have Hypothesis: Inequalities in health may have increased in New Zealand as a result of structural increased in New Zealand as a result of structural reforms in 1980s and 1990s.reforms in 1980s and 1990s.

• Test: Compare trends in New Zealand with trends Test: Compare trends in New Zealand with trends in other countries without such rapid changes.in other countries without such rapid changes.

• Answer: We do not find more rapidly increasing inequalities in NZ compared to Nordic countries

• Limitations: Time lags; other factors; detecting ‘period effect’ given lifecourse determinants of health and cohort effects; etc

59

Possible explanations, II: The role of health services?

• Hypothesis: Differential access, utilisation and quality of health services explains trends in health inequalities?

• Test: Determine parallel trends in access, utilisation and quality of health services. Problem - no data.

• Test: Determine trends in causes of death amenable to treatment. Problem - amenable diseases change over time, and nothing is absolute

• Speculate: We can draw on theory and other information

60

Trends in amenable mortality, 1981-84 to 2001-04

61

Inverse care law, and inverse equity law• It is well known that receipt of health care is often not best

matched with need• Social position is likely to predict access to, and quality and

receipt of, health services independent of ‘health need’• Therefore, health services are likely to contribute to

inequalities in health for diseases amenable to treatment:– CVD in the last 30 years– Cancer - less dramatically, but increasingly so

• The same argument can be extended to primary prevention, health promotion, screening, etc...

• But health services are also a tool to address inequalities, not just an inevitable cause of health inequalities

Hart JT. The inverse care law. Lancet 1971;1:405-12.Victora C, Vaughan J, Barros F, Silva A, Tomasi E. Explaining trends in inequities: evidence from Brazilian child health studies. Lancet 2000;356:1093-1098.

62

0

5

10

15

20

CABG Angioplasty

MäoriPacificOther

CABG and PTCA rates per 100,000 (1990 -1999) Females

Source: Tukuitonga & Bindman, 2002

63

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1997/98 1998/99 1999/00 2000/01 2001/02 2002/03

Sta

nd

ard

ise

d D

isc

ha

rge

Ra

tio

All surgery Coronary artery bypass graft operations

Source: Ministry of Health. Health and Independence Report: Director-General's annual report on the state of public health. Wellington: Ministry of Health, 2003.

Māori:non-Māori Standardised Discharge Ratios

64

Relative survival from cancerEthnic specific life tables

1.00

0.64

0.55

0.500.47

0.45

1.00

0.69

0.620.58 0.58 0.57

1.00

0.77

0.710.68

0.65 0.64

0.00

0.20

0.40

0.60

0.80

1.00

0 1 2 3 4 5

Time since diagnosis (years)

Re

lati

ve

su

rviv

al

(eth

nic

-sp

ec

ific

lif

e t

ab

les

)

Māori Pacific Non-Māori, non-Pacific

65

Ratio of Mäori to non-Mäori non-Pacific 5-year relative

cancer survival, before and after adjusting for stage

0

0.2

0.4

0.6

0.8

1

Breast

Cervix

Colon/

rectu

m

Kidne

y/ur

eter

/ure

thra

Melano

ma

Ovary

Stom

ach

Thyr

oid g

land

Uteru

sRa

tio

of

Ma

ori

to

no

n-M

ao

ri n

on

-Pa

cif

ic r

ela

tiv

e s

urv

iva

ls

Relative survivaladjusted for age

Relative survivaladjusted for ageand stage

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):834-7.

(Restricted to cancers with more than 100 Mäori cases and greater than 65% with stated stage)

66

Possible explanations (I)

DiagnosisDetection Treatment Death

Age Co-morbidities

Access to primary care

Breast: effect of screening

67

Possible explanations (II)

DiagnosisDetection Treatment Death

Age Co-morbidities

Access through care

Co-morbidities may limit treatment choices

68

Possible explanations, II: The role of health services?

• Hypothesis: Differential access, utilisation and quality of health services explains trends in health inequalities?

• Answer/concluding remarks:– traditionally, health services not thought to major contributor

to health inequalities

– improvements in treatments in recent decades and the inverse care law surely mean that health services are making an increasing contribution

– but, health services policy is also a tool to address inequalities - not just an inevitable cause of health inequalities

69

Possible explanations, III: Smoking?

• Hypothesis: The contribution of tobacco smoking to socio-economic inequalities in mortality may have increased over time?

• Test: Compare rate ratios for mortality by education over time, before an after adjusting for smoking.

Blakely T, Wilson N. The contribution of smoking to inequalities in mortality by education varies over time and by sex: two national cohort studies, 1981-84 and 1996-99. Int. J. Epidemiol. 2005;34(5):1054-1062.

70

Rate ratios of 45-74 year old mortality for nil cf. post-school education, before and after adjusting for smoking

1

1.1

1.2

1.3

1.4

1.5

Females1981-84

Males1981-84

Females1996-99

Males1996-99

RR Age &Ethnicityadjusted

Plus adjustedfor smoking

3%

16%

11%

21%

Reduction in ‘excess RR’ (ie RR-1) due to adjusting for smoking

71

Possible explanations, III: Smoking?

• Hypothesis: The contribution of tobacco to socio-Hypothesis: The contribution of tobacco to socio-economic inequalities in mortality may have increased economic inequalities in mortality may have increased over time?over time?

• Test: Compare rate ratios for mortality by education Test: Compare rate ratios for mortality by education over time. over time.

• Answer: Yes, contribution of smoking does increase over time

• Limitations: Accuracy of smoking data; contribution of passive smoking. (It seems highly likely that we underestimate the contribution of smoking, and possibly its increasing contribution over time.)

72

Tobacco consumption by ethnicity

1981 1996

Māori 51.9% 40.5%

Pacific 31.6% 28.0%

Non-Mäori non-Pacific 30.9% 21.5%

Source: Borman, Wilson, Mailing. NZ Med J 1999: 112:460-3.

73

Audience question: how much of the ethnic gap in mortality rates is due to differences in smoking?

0

250

500

750

1000

1250

1500

1750

2000

non-Māorinon-Pacific

Māori a. 10% b. 25% c. 50% d. 75% e. 90%

Dea

th r

ate

per

100,

000

Total death rate Gap attributable to smoking Gap NOT attributable to smoking

74

Contribution of smoking to mortality within ethnic groups, and to the gap in mortality rates between ethnic

groups: highly summarised, 45-74 yrs, 1996-99

275400

125

0

250

500

750

1000

1250

1500

1750

2000

non-Māori non-Pacific (nMnP)

Māori Gap in death ratesbetween Māori and

nMnP

Dea

th r

ate

per

100,

000 Amount NOT

attributableto smoking

Amountattributableto smoking

75

Trends in %Fat intake

32

34

36

38

40

42

44

Mäori Males Non-MäoriMales

Mäori Females Non-MäoriFemales

%FatLINZ: 1989

NNS: 1997

32

34

36

38

40

42

44

Males LINZ-89

Males NNS-97

FemalesLINZ-89

FemalesNNS-97

%Fat Mäori

Non-Mäori

76

Trends in BMI

22

24

26

28

30

Mäori Males Non-MäoriMales

MäoriFemales

Non-MäoriFemales

BMI

LINZ: 1989

NNS: 1997

22

24

26

28

30

Males LINZ-89

Males NNS-97

FemalesLINZ-89

FemalesNNS-97

BMI

Mäori

Non-Mäori

77

SES

Access tohealth care

Healthoutcom es

The Impacts of Racism on Health

Wider Determinants

Jones et al, 2001

78

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.

79

Conclusions• Social inequalities in mortality in New Zealand have widened:

– In relative terms for socio-economic inequalities– In both relative and absolute terms for ethnic inequalities– But, inequalities may have peaked in last decade – good news!

• Determining drivers of trends over time challenging• ‘Behaviour’ at many levels matters:

– Structural reforms probably important driver of widening inequalities– Health services matter – at any one point in time, more so for ethnic

inequalities, and probably increasingly over time– Tobacco matters – but not as big a driver of ethnic inequalities as most

people thought due to so many other factors behind ethnic inequalities– Diet/obesity probably matters, role of PA uncertain– Racism probably matters – at many levels – Role of neighbourhoods unclear and complex

• Changing disease profile over time important (falling CVD, increasing cancer; obesity epidemic)

tracking disparity: trends in ethnic and socio-economic inequalities in mortality, 1981 - 2004

Documents

ethnic mortality disparities

ethnic results

socioeconomic inequalities

contribution of behaviour

ethnic inequalitiespart

mortality ratescalculate

martin tobias

atkinson j