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| Journal of the New Zealand Medical Association,
05-November-2010, Vol 123 No 1325
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A comparative analysis of cardiovascular disease risk
profiles of five Pacific ethnic groups assessed in New Zealand primary care
practice: PREDICT CVD-13
Corina Grey, Sue Wells, Tania Riddell, Romana Pylypchuk,
Roger Marshall, Paul Drury, Raina Elley, Shanthi Ameratunga, Dudley Gentles,
Stephanie Erick-Peleti, Fionna Bell, Andrew Kerr, Rod Jackson
Studies since the 1990s have consistently shown that Pacific
peoples in New Zealand have higher incidence, mortality and case-fatality rates
from cardiovascular diseases (CVD) than New Zealand
Europeans.1–4 Research also suggests that
these outcomes are the result of a more adverse CVD risk factor profile among
Pacific peoples compared to
Europeans.5–10
However, Pacific peoples in New Zealand are not a
homogeneous population. The term ‘Pacific peoples’ is an umbrella
term describing about 7% of the New Zealand population who identify with at
least one of the ethnic groups originating from the Pacific Islands of
Polynesia, Melanesia and Micronesia.11 There
are over 12 nations represented in New Zealand’s Pacific community.
However most Pacific peoples identify with one or more of the four main ethnic
groups (Samoan, Tongan, Cook Island Māori and
Niuean).12
Most health-related surveys present aggregated data from
these different Pacific ethnic groups, in part because of the small samples of
each contributing ethnic group. Research into CVD has been no exception. Despite
recommendations to investigate each Pacific ethnic group
separately,13–15 only two previous
studies have attempted ethnic-specific analyses of the CVD risk profiles of
Pacific peoples in New Zealand, and both studies only had the statistical power
to find substantial differences between Pacific
groups.13,16 Also of note, the New Zealand
Census Mortality Study (NZCMS) reported much higher CVD mortality among Cook
Island Māori (RR 1.66 compared with Samoans), which was reproduced in both
1991–99 and 2001–04 cohorts.15 This
mortality differential is unexplained.
PREDICT is a clinical decision support programme aimed at
assisting primary care practitioners with CVD risk assessment and
management.17 Since 2002, it has been
implemented in nine PHOs throughout Auckland and Northland, representing about
65% of the population in these two regions. Over 10,000 Pacific participants
have now been recruited into the PREDICT programme, which has generated the
largest Pacific cohort ever assembled in New Zealand. This cohort does not
currently include a representative sample of people living in New Zealand as
only about 20% of the eligible population have been risk assessed to date.
However it seems unlikely that there would be any systematic differences in the
selection of patients from different Pacific groups for CVD risk assessment.
Therefore, we present a comparative analysis of CVD risk factor profiles in the
major Pacific populations living in New Zealand.
While the ethnic-specific risk factor profiles reported here
do not represent prevalence estimates for the Pacific populations in New
Zealand, the PREDICT study provides an opportunity to add to our very limited
knowledge on CVD risk factor differences between Pacific populations. Comparing
these risk profiles could help answer the question “Is it appropriate to
aggregate data on CVD risk profiles from different Pacific ethnic groups living
in New Zealand?”
MethodsPREDICT is a web-based clinical decision support
programme for CVD risk assessment and management in routine primary care
practice. Study methods and data definitions are described in full
elsewhere.17
The software programme has been integrated with several
of the most commonly used primary care patient management systems. This
integration allows uniform, systematically coded CVD risk data to be
automatically (and anonymously) extracted from a patient’s electronic
medical record. Gaps in the data required to undertake a formal CVD risk
assessment are then completed by either the GP or practice nurse on the PREDICT
templates, which are then automatically written back to the patient medical
record. Health data captured by PREDICT, including history of CVD, family
history of CVD, and total cholesterol/HDL ratio, have previously been shown to
be highly consistent with data held in electronic patient
records.18
Risk profiles are sent via a secure broadband internet
connection to a central server at the time of the assessment. Within seconds the
clinician receives the patient’s calculated 5-year CVD risk as well risk
management recommendations based on New Zealand CVD risk management
guidelines.19 The central server stores the CVD
risk factor profiles of each patient, and with permission from participating
PHOs, these are extracted anonymously and linked, via an encrypted National
Health Index (NHI) number, to national hospitalisation and mortality datasets.
PREDICT data can also be linked to the New Zealand Health Information Service
(NZHIS) NHI dataset that holds details of date of birth, gender, ethnicity and
socioeconomic status according to the NZDep01 Deprivation index.
Ethnicity data can therefore be collected from the
PREDICT template (originally from the patient’s electronic medical record,
or entered manually by the practitioner) or via linkage to the NHI dataset. Both
datasets have provision for up to three different ethnicities to be entered, so
that each patient in the PREDICT cohort could potentially have up to six
ethnicities.
Any person in the PREDICT cohort aged 35–74 years
with a Pacific ethnicity on any one of the six potential ethnicity fields was
included in these analyses. Pacific ethnicities were defined according to the
Ministry of Health’s Ethnicity Data Protocols for the Health and
Disability Sector as Level 2 codes 30 to
37.20 However, preliminary analyses revealed
that the Fijian group (code 36) was an anomaly, making up over 11% of the total
Pacific cohort but only 4% of Pacific peoples in official New Zealand
statistics.12 Furthermore, as the CVD risk
profile of the Fijian group was much closer to that of the Indian cohort than to
that of the other Pacific groups,21 we
suspected that some of those classified as Fijians were not ethnic Fijians, but
rather Fijian Indians. Therefore this group (n=1341) was excluded from these
analyses.
The Pacific groups included in this study were thus the
level 2 ethnicity codes 31 (Samoan), 32 (Cook Island Māori), 33 (Tongan),
34 (Niuean), and a combined group of both codes 37 (Other Pacific peoples,
including Tokelauans) and code 30 (Pacific peoples Not Further Defined,
NFD).
Less than 1% of patients in the Pacific cohort
identified with more than one Pacific ethnicity. Classification of ethnicity
prioritised the smaller Pacific groups over the larger ones, as was done in the
2001 New Zealand Census22 and the Diabetes,
Heart and Health Study 2002/03.16 This method
gave first priority to Niuean, followed by Cook Island Māori, Tongan and
lastly Samoan ethnicity. Only 70 people (0.7% of the Pacific cohort) identified
themselves as Tokelauan (code 35), therefore they were included in the
‘Other Pacific peoples’ ethnic group (code 37).
The data extracts for these analyses included all
PREDICT first risk assessments from August 2002 until January 2009. Data were
analysed using Stata v10.0 statistical software. Men and women were analysed
separately. Deprivation was assessed according to the NZDep01 index. NZDep01 is
a census based small area index of deprivation, which assigns a relative
deprivation score to each meshblock in New
Zealand.23 Each individual was assigned the
value according to their meshblock of residence. Risk ratios (RRs) with 95%
confidence intervals (CIs) were calculated for each ethnic group with Samoans as
the reference group, as they comprised the largest group, making up almost 50%
of the Pacific cohort. A binomial regression model was used to calculate risk
ratios (RR) adjusted for age. A post-regression test was used to test for any
overall differences in proportions between groups. A linear regression model
adjusting for age was used to calculate mean differences and 95% CIs for
continuous CVD risk factor data, again with Samoans as the reference group.
Mean differences in Framingham risk scores were also
calculated, using the original Framingham risk prediction
equation24 rather than the New Zealand
Guidelines Group-adjusted Framingham equation which adds a 5% 5 year risk
increment to high risk ethnic groups including Pacific
peoples.19 We decided not to adjust for
deprivation, as there were only small differences in NZDep between Pacific
groups and it is a relatively crude and indirect measure of deprivation which is
most useful when there are major differences between groups.
Ethical approval—The PREDICT
research project was approved by the Northern Region Ethics Committee Y in 2003
(AKY/03/12/314) and the national Multi Region Ethics Committee in 2007
(MEC/07/19/EXP).
ResultsBetween 2002 and June 2009, baseline PREDICT CVD risk
assessments were conducted on 10,301 people aged 35–74 identifying with at
least one Pacific ethnic group, after excluding those classified as Fijian (as
discussed in the Methods). Of these, 48% identified as Samoan, 17% as Tongan,
13% as Cook Island Māori, 8% as Niuean and 14% as Other Pacific or Pacific
NFD.
Table 1 shows the baseline demographic characteristics of
Pacific peoples in the PREDICT cohort by Level 2 ethnic group. In most Pacific
groups, there were similar proportions of men and women receiving CVD risk
assessments. The only exception to this was for the Tongan cohort (54% men).
On average, Pacific women were approximately 3 years older
than their male counterparts. The distribution of age groups at first CVD risk
assessment was similar across Pacific groups, with approximately 25% aged
35–44, 35% aged 45–54 and 25% aged 55–64. All Pacific groups
were over-represented in areas of high deprivation, with approximately 75%
residing in the two most deprived NZDep01 quintiles (deciles 7–10).
Table 2 presents the gender-specific age-adjusted risk
ratios for three CVD risk factors (smoking, diabetes and a prior history of CVD)
for Pacific groups, using Samoans as the reference group. There were no overall
differences in the proportion of smokers among Pacific men (p=0.16). Cook Island
women had the highest proportion of smokers among women (21%) and were almost
60% more likely than Samoan women to smoke. Niuean men had the highest burden of
diabetes (almost 40%) among Pacific males.
Pacific women in all groups had a higher prevalence of
diabetes than their male counterparts, with over one-third of all Pacific women
having a diagnosis of diabetes. Tongan women were 26% more likely, and Niuean
women 17% more likely, than Samoan women to have diabetes. Overall differences
between Pacific groups in the proportion with a prior history of CVD were
small.
Table 1. Baseline demographic characteristics
of people in Pacific ethnic groups in the PREDICT cohort
Table 2. Age-adjusted estimates and risk
ratios, with 95% confidence intervals, for smoking, diabetes and prior history
of CVD for Pacific groups in PREDICT cohort by gender (reference group is
Samoan)
Table 3 shows the age-adjusted mean systolic and diastolic
blood pressures (BPs), total cholesterol/HDL ratio and Framingham 5-year CVD
risk scores of Pacific groups, by gender. Niuean men and women had the lowest
mean systolic and diastolic BPs of all groups (mean systolic and diastolic BPs 2
to 3 mmHg lower than Samoans). Tongan men had the highest mean total
cholesterol/HDL ratio (0.26 higher than Samoan men), and Niuean men the lowest
(0.16 lower than Samoan men). Tongan women had the highest mean total
cholesterol/HDL ratio (0.14 higher than Samoan women after adjusting for age and
deprivation).
Tongan men and women had the highest 5-year Framingham CVD
risk scores and while these were statistically significantly higher than the
Samoan reference categories, they only represented about a 10% relative
difference in risk.
Table 3. Age-adjusted mean values and mean
differences for systolic and diastolic blood pressures, total cholesterol/HDL
ratio and Framingham 5-year CVD risk score for Pacific groups in PREDICT cohort
by gender (Reference group is Samoan)
Body mass index (BMI) is not used in the Framingham risk
equation to calculate CVD risk and it is therefore not part of the risk
assessment template. BMI is only mandatory if clinicians wish to receive CVD
management recommendations based on New Zealand guidelines. Therefore, BMI was
only available for the 30% of this cohort whose general practitioner completed
both a risk assessment and risk management template. Mean BMI for this subset
did not differ significantly between different ethnic groups, with BMI ranging
from 32.6 to 33.9 in men and 34.3 to 36.7 in women.
DiscussionThis study presents a comparative analysis of CVD risk
profiles by the major Pacific ethnic groups living in New Zealand. The data were
generated from a web-based CVD risk assessment and management decision supported
system used in the majority of PHOs in the Northland and Auckland regions and
represents the largest cohort of Pacific people ever assembled in New Zealand.
As only about 20% of the eligible population has been risk assessed to date,
these findings cannot be used as population prevalence estimates. However we
assumed that there were unlikely to be important systematic differences in CVD
risk factor screening between the different Pacific populations, so that it was
reasonable to undertake comparative analyses. Interestingly, the age, gender and
NZDep01 profiles of the individual Pacific groups were remarkably similar.
We found relatively small differences in overall CVD risk
factor profiles between the five Pacific groups assessed, suggesting that it is
reasonable to combine these data when describing the overall CVD risk profiles
of Pacific peoples living in New Zealand. However there were substantial
differences in the prevalence of some individual CVD risk factors. The largest
relative difference for a single risk factor was the almost 60% higher
proportion of smokers among Cook Island women compared to Samoan women, which is
consistent with results from previous
studies.16,25,26
Of note, smoking rates among Pacific groups in the PREDICT
cohort were lower than those reported by other studies, including the 2006 New
Zealand Census27 and the Pacific Drug and
Alcohol Survey (PDAS).26 However, the reported
Census data included all Pacific peoples aged 15 years and over, while our study
included those aged between 35 and 74 years, and the prevalence of smoking
decreases significantly with age.28 The PDAS
reported smoking rates for Pacific peoples aged 13 to 65 years, and had only
about one tenth the sample size of out study (n=338 Samoans, 228 Cook Island
Māori, 232 Tongans and 207 Niueans aged 13–65
years).26 The PDAS did not have the statistical
power and precision to provide meaningful comparisons between Pacific
groups.
In our study, Tongan women and Niuean men and women had the
highest burden of diabetes (approximately 40%), making them 20-30% more likely
to have diabetes than their Samoan counterparts. Tongan women have previously
been reported to have the highest prevalence of diabetes among Pacific groups in
the Diabetes Heart and Health Study (DHAHS)
2002/03,16 and Niuean men the highest
prevalence of diabetes among Pacific men in the Workforce Diabetes Survey (WDS)
1988-1990.13 However, our finding of a high
burden of diabetes among Niuean women has not been described
previously—possibly because of the small numbers of Niuean women included
in earlier studies (only 13 in the WDS and 60 in the
DHAHS).13, 16
Despite their high burden of diabetes, Niuean men and women
in our study had the lowest mean total cholesterol/HDL ratios and systolic and
diastolic blood pressures of the five Pacific groups (approximately 2-3 mmHg
lower than Samoan men and women). Our finding that Niueans had lower blood
pressure levels than other Pacific groups has not been reported previously.
However, Niuean men and women were reported to have significantly lower mean
total cholesterol:HDL ratios compared to other Pacific peoples in both the WDS
and the DHAHS, suggesting that the differences in this particular CVD risk
factor between Niueans and other Pacific groups are real.
The lower mean levels of systolic and diastolic BP and total
cholesterol:HDL ratio in Niueans compared to other Pacific groups in our study
may possibly be due to targeted risk management in people with diabetes, given
they also had the highest burden of diabetes in these analyses. We intend to
explore this hypothesis further once we have linked these data to national
pharmaceutical dispensing records. Comparing our data with all other New Zealand
surveys (except the Census) that have attempted to make comparisons of CVD risk
factors between the different Pacific populations living in New Zealand is
problematic because the largest of these other surveys was about one-tenth the
size of the PREDICT cohort. Therefore random error is likely to be a major
problem when considering the validity of comparative differences.
Unfortunately we were unable to provide any insights into
the observation by Blakely et al.15 of an
increased risk of CVD death among Cook Island Māori compared to other
Pacific peoples. While we identified some differences between groups for
individual risk factors, our summary measure of overall risk, using the
Framingham score, suggested that Tongan men and women had a small increased risk
compared to other Pacific groups, which had similar Framingham estimated risks.
However the Framingham risk score was developed to help improve the targeting of
risk factor management in individual patients and at best only explains about
one third the variability in CVD event rates in a population.
While it is possible there were systematic differences in
the selection criteria for risk assessing different Pacific groups which might
explain our inability to detect a higher overall risk among Cook Island
Māori, it is more likely that the tool was simply not sufficiently
sensitive. We plan to investigate the predicted risk versus the actual observed
event rate in this cohort, with a view to developing more accurate risk
prediction equations.
This study highlights the ongoing problems with the
collection of ethnicity data in the health sector. Prior to 2004, when the
Ministry of Health introduced Ethnicity Protocols for the Health and
Disability Sector,20 there were no
standards for the coding and recording of ethnicity data in primary care.
Consequently, inconsistencies in ethnicity recording have been noted in
hospital29 and primary care
records.30 A study by Riddell et al. involving
a sample (n=665) of people who had previously been risk assessed using PREDICT
also found that self-identified ethnicity was the same as that recorded in the
primary care record for only two-thirds of the
sample.31
Notably, this study found that only 37.5% of those recorded
as Fijian on the primary care record agreed with this when asked to
self-identify their ethnicity. This finding further supports our exclusion of
PREDICT participants classified as Fijian from the analyses. Furthermore,
Riddell’s study found zero agreement among those recorded as Pacific Not
Further Defined (NFD) on the primary care record with their self-identified
ethnicity—presumably because the majority of these people identify with a
specific Pacific ethnic group (for example, Samoan, Tongan
etc).31 Our finding that 959 people (9.3% of
our cohort) were only classified as Pacific NFD, rather than as a particular
Pacific ethnic group, suggests that there are still significant gaps in the
accuracy of recording of ethnicity in primary care.
In conclusion, this study has highlighted several
differences in CVD risk factors between five Pacific ethnic groups assessed in
routine primary care, including higher proportions of smoking in Cook Island
women, a higher burden of diabetes among Tongan women and Niuean men and women,
and slightly higher estimates of 5-year absolute CVD risk in Tongan men and
women. These differences suggest that Pacific peoples should not necessarily be
treated as a single entity when designing community-based health promotion and
disease prevention programmes, and that a targeted ethnic-specific approach to
the reduction of some CVD risk factors may be appropriate.
Research is currently limited in this area, however, and
studies will need to be conducted to evaluate whether ethnic-specific Pacific
interventions are more effective than general Pacific interventions. In
contrast, overall (absolute) CVD risk, as estimated by the Framingham equation,
is remarkably similar between the Pacific ethnic groups, suggesting that the
current practice of aggregating CVD risk data is reasonable for describing the
overall risk factor burden for Pacific peoples living in New Zealand.
Competing interests: None.
Author information: Corina Grey, Public
Health Medicine Registrar, Section of Epidemiology & Biostatistics, School
of Population Health, University of Auckland; Sue Wells, Senior Lecturer
Clinical Epidemiology, Section of Epidemiology & Biostatistics, School of
Population Health, University of Auckland; Tania Riddell, Senior Research
Fellow, Section of Epidemiology & Biostatistics, School of Population
Health, University of Auckland; Romana Pylypchuk, Research Analyst, Section of
Epidemiology & Biostatistics, School of Population Health, University of
Auckland; Roger Marshall, Associate Professor in Epidemiology &
Biostatistics, Section of Epidemiology & Biostatistics, School of Population
Health, University of Auckland; Paul Drury, Clinical Director, Auckland Diabetes
Centre; Raina Elley, Senior Lecturer, Clinical General Practice, School of
Population Health, University of Auckland; Shanthi Ameratunga, Deputy Head
– School of Population Health, Section of Epidemiology &
Biostatistics, School of Population Health, University of Auckland; Dudley
Gentles, Research Fellow, Section of Epidemiology & Biostatistics, School of
Population Health, University of Auckland; Stephanie Erick-Peleti, National
Pacific Tobacco Control Coordinator, National Heart Foundation; Fionna Bell,
Clinical Director, Ta Pasefika Pacific PHO; Andrew Kerr, Clinical Head of
Cardiology, Middlemore Hospital and Clinical Senior Lecturer, University of
Auckland; Rod Jackson, Professor of Epidemiology, Section of Epidemiology &
Biostatistics, School of Population Health, University of Auckland
Acknowledgements: The authors would like to
thank the following PHOs, as well as their affiliated general practitioners,
practice nurses and patients, for providing the data for analysis: ProCare
Network North, Auckland and Manukau, HealthWest, Te Tai Tokerau, Manaia,
Kaipara Care, Tihewa Mauriora and Whangaroa PHOs.
PREDICT was developed by a collaboration of clinical
epidemiologists at the University of Auckland, IT specialists at Enigma
Publishing Ltd (a private provider of online health knowledge systems), primary
health care organisations, non-governmental organisations (New Zealand
Guidelines Group, National Heart Foundation, Diabetes New Zealand, Diabetes
Auckland), several district health boards and the Ministry of Health.
PREDICT software platform is owned by Enigma Publishing Ltd
(PREDICT is a trademark of Enigma Publishing Ltd).
Funding: The PREDICT research project has
support by HRC grants 03/183 and 08/121 from the Health Research Council. CG
received a training endowment from the New Zealand College of Public Health
Medicine. SW has been, and TR is currently, a recipient of a National Heart
Foundation Research Fellowship.
Correspondence: Corina Grey, Section of
Epidemiology & Biostatistics, School of Population Health, University of
Auckland, PO Box 92019, Auckland, New Zealand. Fax: +64 (0)9 3737624; email: corinagrey@gmail.com
References:
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