© International Epidemiological Association 1999
International Journal of Epidemiology 1999;28:846–852
Printed in Great Britain
Do simple prudent health behaviours protect
men from myocardial infarction?
Carole A Spencer, Konrad Jamrozik and Laurie Lambert
Background We tested whether behaviours such as discarding obvious fat on meat, cessation
of smoking, avoidance of passive smoking, habitual use of reduced fat milk,
prudent consumption of alcohol and regular but moderate physical exercise are
associated with a reduction of cardiovascular risk.
Methods
This was a population-based case-control study done in Perth, Western Australia.
The cases (n = 336) were men aged 27–64 years with a first-ever acute myocardial infarction (AMI) during the period 1992–1993, and who survived at least
28 days. The controls (n = 735) were participants in a population-based survey of
cardiovascular risk factors conducted during May–November 1994. Both groups
completed the same questionnaire and the data were analysed with multiple
logistic regression using backward elimination technique.
Results
Among men aged 27–64 years simple measures such as participation in nonvigorous exercise (odds ratio [OR] = 0.5, 95% CI : 0.4–0.7), and avoidance of added
salt (OR = 0.6, 95% CI : 0.4–0.9) are associated with significant and important
protection from AMI.
Conclusion
After 25 years of falling mortality in Australia, lifestyles can still be significantly
improved to reduce heart disease even further.
Keywords
Myocardial infarction, protective factors, case-control study, population-based,
Western Australia
Accepted
19 February 1999
Much of the epidemiological literature on the aetiology of
vascular disease is concerned with biological factors that are
associated with an increase in risk, rather than with aspects of
lifestyle and behaviour over which the individual has direct
control and that might reduce risk. Health promotion and
health education messages must address factors that the
audience can change.
The J-shaped relationship between average daily consumption of alcohol and both heart disease1 and stroke2 reminds us
that health promotion messages aimed at reducing risks that are
mirror images of epidemiological findings regarding increased
risk may be too simplistic. We therefore conducted a populationbased case-control study to measure the association between
coronary risk and a number of key or sentinel elements of a
prudent lifestyle that are simple, safe, and almost universally
applicable as goals for health promotion.
In addition, the data from healthy control subjects would also
reflect the extent to which the relevant health messages had
already been adopted in the general community and would
reveal the subgroups of the population that have been slowest
Department of Public Health, University of Western Australia.
Reprint requests to: Carole Spencer, Department of Public Health, University
of Western Australia, Nedlands, Western Australia 6907. E-mail: carole@
dph.uwa.edu.au
to respond to health promotion activities already in place. This
is important information for refining those activities in the
future.
Methods
Study population
Potentially eligible cases were male residents of the Perth
Statistical Division of Western Australia aged 27–64 years (mean
age = 54 years) who were admitted to the coronary care units
of the three adult teaching hospitals in Perth during 1992 and
1993.3 Only the 336 men with a first-ever AMI, as indicated by
their medical records, who survived for at least 28 days, were
eligible to participate in the study. These men completed a
postal questionnaire in 1995 covering aspects of their lifestyle
prior to having their AMI as well as demographic variables (see
below). Linkage of hospital records to official mortality statistics
showed that 135 men had died in the time between having
their AMI and the postal survey. The next-of-kin were identified for 100 of these men and were sent a shortened version of
the questionnaire to complete.
The response fraction was 85% (after adjustment for those for
whom current addresses could not be found) for the cases
thought to be alive at the beginning of the survey (313 men)
and 34% (after adjustment) for the deceased cases for whom
846
PRUDENT LIFESTYLE AND CORONARY RISK
the next-of-kin could be contacted (23 men). Previous studies3
indicate that 96% of cases of non-fatal AMI in males of working
age in Perth are managed in the three teaching hospitals from
which the present cases were identified.
The control subjects were 735 male participants in a survey of
cardiovascular risk factors conducted during May–November
1994 according to the protocol developed for the Risk Factor
Prevalence Study undertaken by the National Heart Foundation
of Australia.4 The sampling frame for this survey was all those
aged 25–69 years who were resident in the Perth Statistical
Division and were enrolled to vote. Enrolment to vote is compulsory for all citizens and permanent residents of Australia.
The small proportion (,5%) of male participants in the survey
who reported having sustained an AMI in the past was removed
from the control group. As well as having their weight, height,
waist, hips, blood pressure, cholesterol and triglycerides
measured, participants in the survey were asked to complete a
similar questionnaire to the cases (see below) whilst in the
survey clinic. The response fraction was 72% including 8% who
could not attend the clinic but agreed either to a home visit or
to complete a postal questionnaire.
Questionnaire
Cases and controls completed an almost identical self-administered
questionnaire. The controls were asked to relate the questions
to the time at which the questionnaire was answered while
the cases were asked about details just prior to their AMI.
The controls had the benefit of assistance from clinic staff, if
requested, whereas the cases were sent their questionnaires by
post but were supplied with a contact telephone number if they
had any queries.
Each man completed the Short Fat Questionnaire, a previously validated instrument5 that provides an estimate of the
proportion of calories obtained from saturated fat. Questionnaires concerning deceased men contained only two items for
which fat content could be calculated (removal of skin from
chicken and type of milk used), yielding scores from 0 to 5.
Therefore a pro-rata method was used to calculate the proportion of calories derived from saturated fat for the deceased
men. Categories for consumption of alcohol were created with
reference to the National Health and Medical Research Council
recommendations for ‘responsible drinking behaviour’.6
Vigorous exercise was defined as that causing the man to
breathe harder or to puff or pant.4 Present and past type and
level of smoking were sought, along with age of starting to
smoke, if relevant. Each man was also asked about the number
of years out of the previous ten that he had been exposed to
environmental tobacco smoke, and the number of hours of exposure in a usual week. In addition, the questionnaire covered
previous medical history, current heart-related treatment, selfreported height and weight and length of residence in Western
Australia.
Statistical methods
The data for all cases and controls were initially reviewed using
SAS software to produce frequency tables.7 To ensure that any
apparent differences between living cases and controls would be
minimized, missing values were identified and recoded to
values associated with the healthiest lifestyle.
847
Univariate comparisons, adjusting for 5-year age group,
and reverse stepwise multivariate logistic regression were then
performed using EGRET software.8
Population attributable proportions
Population attributable proportions were calculated by
determining the number of AMI in each group defined by age
that were mathematically attributable to a particular exposure,
on the assumption that the exposure caused the disease. The
figures for all strata of age were added and the total divided by
the total number of AMI observed. Algebraically, this may be
expressed as:
PAP (%) = 100 *
Σ {(ni pi (OR – 1))/(1 + pi (OR – 1))}
Σ ni
where ni is the number of AMI occurring in a particular age
group, pi is the proportion of control subjects in that group
reporting exposure, and OR is the age-adjusted odds ratio for
the risk factor derived from a multivariate logistic model. We
estimated the 95% CI for a population attributable proportion
by repeating this calculation using the 95% CI of the relevant
OR.2
Ethical considerations
The Committee for Human Rights of the University of Western
Australia and the Confidentiality of Health Information Committee of the Health Department of Western Australia approved
the protocol for the study.
Results
Univariate analyses
Data for 336 cases of AMI and 735 control subjects were
included in the univariate analysis of individual risk factors.
Differences in the distribution of ages of cases and control
subjects, related to the sampling strategy for the survey of the
latter, required that univariate analyses be adjusted for age
group (in six strata). Table 1 shows that, as expected, the risk of
AMI increased with age. There were significant protective
effects associated with infrequently or never adding salt to food
after cooking, eating less meat and trimming off the visible fat,
removing the skin from poultry, eating fish at least occasionally
and habitual use of reduced fat or skim milk. Men whose score
on the Short Fat Questionnaire was below the median for
control subjects had half the risk of AMI compared with the
remainder.
Table 2 shows that moderate consumption of alcohol, up to a
maximum of four drinks per day, was associated with a significant reduction in risk, and a protective relationship was
evident even in occasional drinkers. Current smokers had more
than double the risk of AMI compared with both ex-smokers
and lifelong non-smokers. Overall, men who had not been
exposed to environmental tobacco smoke at home, work,
socially or in cars in the previous 10 years had a risk of AMI that
was 30–40% lower than that of men who had been passive
smokers. When these analyses were limited to men who had
never smoked, those who had completely avoided environmental
tobacco smoke had a significantly reduced risk, but none of the
four setting-specific OR was significant. Regular participation
848
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Table 1 Results of univariate analysis of dietary risk factorsa
Cases
n = 336
%
Controls
n = 735
%
Odds ratio
25–39
2.4
30.5
1.0
40–44
7.1
13.1
7.0
3.0–16.1
45–49
15.2
15.4
12.6
5.8–27.5
50–54
21.1
12.8
21.2
9.8–45.7
55–59
23.5
14.0
21.5
10.0–46.1
60+
30.7
14.3
27.5
12.9–58.5
Always
43.2
28.2
1.0
Sometimes
25.3
30.2
0.6
0.4–0.8
Rarely or never
31.5
41.6
0.5
0.4–0.7
Above the median
58.0
49.8
1.0
Below the median
42.0
50.2
0.5
Rarely or never
19.0
10.3
1.0
Sometimes
28.6
29.0
0.5
0.4–0.8
Usually
52.4
60.7
0.4
0.3–0.7
Rarely or never
45.5
39.7
1.0
Sometimes
25.9
34.7
0.5
0.4–0.7
Usually
28.6
25.6
0.7
0.5–0.9
Factor
95% CI
Age group (years)
Adding salt to food
Score of the Short Fat Questionnaire
0.4–0.7
Removing fat from meat
Removing skin on chicken
Frequency of eating fish
Never
3.0
1.8
1.0
97.0
98.2
0.3
Always fullcream
44.6
40.0
1.0
Reduced fat milk or sometimes fullcream
40.0
45.0
0.7
0.5–0.9
Skim milk or none at all
15.4
15.0
0.7
0.4–0.9
3–6 times a week
25.0
12.4
1.0
1–2 times a week
38.1
43.4
0.3
Less than once a week
32.4
39.7
0.2
0.1–0.3
4.5
4.5
0.2
0.1–0.4
At least sometimes
0.1–0.8
Type of milk used
Frequency of eating meat
Never
0.2–0.5
a Odds ratios have been adjusted for age.
in either vigorous or non-vigorous exercise was significantly
protective—almost one-quarter (24%) of the cases did no exercise at all (leisure or work) in the month before their AMI,
compared with 14% of the controls being completely inactive in
the month before the survey.
Body mass index was calculated using self-reported weight
(in kg) divided by the square of self-reported height (in m).
Having a body mass index of less than 26.0 (classified as acceptable weight or underweight4) was associated with a significant
protective effect, compared with men who were overweight or
obese.
Multivariate model
The final multivariate model for all cases and controls is summarized in Table 3. As expected, not all of the significant relationships
apparent from the age-adjusted univariate analyses are still seen
here.
From the dietary factors, habitual removal of the skin from
chicken, eating fish at least sometimes, use of reduced fat or
skimmed milk and trimming the visible fat from meat all failed
to be retained in this model. By contrast, a low frequency of
adding salt to food after cooking, a low score for amount of
saturated fat in the diet and a low frequency of eating meat
were still associated with significant protective effects.
Other behavioural risk factors shown to be significantly protective were drinking alcohol regularly and not being a current
smoker. However, avoidance of passive smoking failed to be retained in the model. Regular non-vigorous exercise undertaken
for health and fitness and not being overweight (body mass
index ,26.0) were associated with a significantly lower risk of
PRUDENT LIFESTYLE AND CORONARY RISK
849
Table 2 Results of univariate analysis of other behavioural risk factorsa
Factor
Cases
n = 336
%
Controls
n = 735
%
Odds ratio
95% CI
Alcohol
Lifelong abstainer
8.6
3.7
1.0
Occasional drink
16.1
13.5
0.5
0.3–0.9
1–2 drinks per day
48.5
55.4
0.5
0.3–1.0
3–4 drinks per day
13.1
18.5
0.4
0.3–0.9
.4 drinks per day
13.7
9.0
0.7
0.4–1.5
Current smoker
40.8
26.8
1.0
Ex-smoker
32.1
33.3
0.5
0.3–0.6
Lifelong non-smoker
27.1
39.9
0.4
0.3–0.6
Smoking status
Passive smoking last 10 years
Exposed at home
30.4
30.6
1.0
Not exposed at home
59.2
69.3
0.7
Unknown exposure at homeb
10.4
0.1
Exposed at work
57.1
58.0
1.0
Not exposed at work
33.0
41.8
0.6
9.8
0.3
Exposed in social venues
63.7
69.7
1.0
Not exposed in social venues
25.0
30.1
0.7
Unknown exposure in social venuesb
11.3
0.3
Exposed in cars
33.3
32.1
1.0
Not exposed in cars
55.9
67.2
0.7
Unknown exposure in carsb
11.0
0.7
None
81.3
66.9
1.0
Some
18.7
33.1
0.6
None
59.8
44.5
1.0
1–2 per week
11.3
20.0
0.4
0.2–0.5
5.1
9.7
0.3
0.2–0.7
4–5 per week
10.4
13.1
0.4
0.3–0.7
.5 per week
13.4
12.9
0.5
0.3–0.8
>26.0
64.6
54.7
1.0
,26.0
35.4
45.3
0.7
Unknown exposure at workb
0.5–0.9
0.5–0.9
0.5–1.0
0.4–0.9
Regular vigorous exercise
0.4–0.9
Sessions of non-vigorous exercise
3 per week
Self-reported BMIc
0.5–0.9
a Odds ratios have been adjusted for age.
b Men for whom passive smoking status was uncertain have been retained in the Table without odds ratios confidence intervals being calculated.
c BMI is body mass index (kg/m2).
AMI whereas a history of hypertension or diabetes, current
treatment for angina and following a diet to lower cholesterol
all marked significant increases in risk. From the demographic
factors, only age was associated with the risk of AMI.
A separate model that omitted control subjects who were currently being treated for angina yielded a similar pattern of results.
Population attributable proportions
Table 4 shows the prevalence in controls and the population
attributable proportions associated with each of the risk factors
in the final multivariate model. For example, in terms of
attributable proportion, the most important dietary variable was
the frequency of eating meat. One in eight of the control subjects reported eating meat at least three times per week, and this
was implicated in 18% of cases of AMI in the community.
Assessed in the same way, the most important behavioural
variable was lack of participation in non-vigorous exercise such
as walking. The risk associated with this exposure was modest,
but it was very widespread and therefore statistically was
associated with a greater proportion of the community-wide
incidence of AMI than were factors such as hypertension or
diabetes mellitus. By the same token, being overweight or obese
was found to be so common in the Australian community that
it was implicated in over one-fifth of AMI.
850
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Table 3 Results of multivariate analysis of risk factors
Factor
Odds ratio
95% CI
Age group (years)
Factor
Odds ratio
95% CI
Smoking status
25–39
1.0
Current smoker
1.0
40–44
7.3
3.0–17.8
Ex-smoker
0.5
0.3–0.8
45–49
15.1
6.6–34.7
Lifelong non-smoker
0.4
0.3–0.6
50–54
23.4
10.3–53.2
55–59
26.7
11.8–60.6
None
1.0
60+
36.3
16.0–82.4
Some
0.5
Regular non-vigorous exercise
0.4–0.7
Self-reported BMIa
Adding salt to food
Always
1.0
Sometimes
0.6
0.4–0.9
Rarely or never
0.7
0.5–1.0
Score of the Short Fat Questionnaire
Above the median
1.0
Below the median
0.7
0.5–1.0
Frequency of eating meat
>26.0
1.0
,26.0
0.7
No
1.0
Yes
1.5
1.0–2.1
Being treated for angina
No
1.0
Yes
3.9
3–6 times a week
1.0
1–2 times a week
0.4
0.2–0.6
Less than once a week
0.3
0.2–0.5
No
1.0
Never
0.3
0.1–0.6
Yes
6.0
Alcohol
0.5–0.9
History of hypertension
1.6–9.0
On a diet for cholesterol
2.8–13.0
Being treated for diabetes mellitus
Lifelong abstainer
1.0
Occasional drink
0.4
0.2–0.9
1–2 drinks per day
0.4
0.2–0.8
3–4 drinks per day
0.3
0.1–0.7
.4 drinks per day
0.4
0.2–0.8
No
1.0
Yes
2.4
1.2–4.8
a BMI is body mass index (kg/m2).
Discussion
It has been said that in an ageing community beset by chronic
degenerative diseases, it is at least as important to ‘add life to
years’ as to ‘add years to life’.9 The quest, therefore, is not only
to prevent premature deaths but also to prevent or at least to
delay the onset of impairment and disability in order to minimize handicap. Since a great deal is already known about the
effect of lifestyle factors on health, and about the biochemical
and physiological mechanisms that underlie these relationships,
the task facing us lies as much in applying what is already
known as it does in discovering more.
In Australia, mortality from ischaemic heart disease has
fallen more than 50% since 1968,10 but diseases of the heart
and arterial system still account for over 40% of deaths, and for
a considerable proportion of expenditure on health services, as
well as being a major cause of disability and handicap. For example, follow-up of the Perth MONICA register, a populationbased study of acute coronary events in people of working age,
showed that one-third of males who were in full-time employment at the time of their first-ever infarction and who survived
the initial episode, did not return to work. (Czarn A, unpublished observations, 1992). The aim of our study was to explore
the scope for further reduction in this burden of morbidity
and handicap, but instead of concentrating on intermediate and
potentially explanatory variables such as blood pressure and
serum cholesterol, our primary focus was on aspects of lifestyle
and behaviour that would translate directly into simple messages for health promotion and health education.
Broadly speaking, our results accord with previous observations regarding the association with AMI of dietary fat,11 alcohol,1 tobacco,1 exercise,12 hypertension,13 angina,14 cholesterol,15
diabetes16,17 and relative body mass.17 All these factors remained
in the final statistical model as well as the additional variables
relating to use of salt and the consumption of meat.
The consistency of our results with those in the literature
suggests that our methods were fundamentally valid. Indeed,
apart from the fact that our study was limited to men who
survived to at least 28 days after their AMI, it is unlikely that
there was any selection bias with regard to our cases of firstever infarction as these were obtained from a population-based
register of men attending any public hospital in the study area
and the original sampling frame for control subjects was also
population-based. Like many case-control studies, our results
might partly reflect recall bias but use, wherever possible, of
identical questionnaire items for cases and controls should
have minimized differential errors in measurement and wellestablished multivariate methods should have controlled
statistical confounding in our results.
Overall, our data suggest that substantial further reductions
in morbidity from ischaemic heart disease could be seen in
Australia if larger proportions of the population could be persuaded to adopt and maintain a number of simple habits such
PRUDENT LIFESTYLE AND CORONARY RISK
851
Table 4 Estimated proportions of myocardial infarctions attributable to or prevented by particular exposures (n = 336) (values calculated from the
odds ratios and upper and lower CI)
Factor
Prevalence in controls
%
Attributable risk
%
95% CI
%
12.0
0–25.4
15.1
0–29.6
18.1
4.8–38.0
5.8
0.9–14.0
24.7
12.0–38.3
29.7
16.7–42.2
20.8
2.8–36.7
11.4
1.5–22.3
6.1
1.5–14.9
11.4
4.5–23.0
5.4
0.8–13.3
Adding salt to food
Rarely or never
41.6
Always
28.2
Score of the Short Fat Questionnaire
Below the median
50.2
Above the median
49.8
Frequency of eating meat
Never
3–6 times a week
4.5
12.4
Alcohol
1–2 drinks per day
55.4
Lifelong abstainer
3.7
Smoking status
Lifelong non-smoker
39.9
Current smoker
26.8
Regular non-vigorous exercise
Some
55.5
None
44.5
Self-reported BMIa
,26.0
45.3
>26.0
54.7
History of hypertension
No
78.9
Yes
21.1
Being treated for angina
No
98.8
Yes
1.2
On a diet for cholesterol
No
98.4
Yes
1.6
Being treated for diabetes mellitus
No
97.6
Yes
2.6
a BMI is body mass index (kg/m2).
as not adding salt to their food, reducing saturated fat in their
diet, eating meat less often, walking regularly and avoiding passive exposure to tobacco smoke. The increase in the proportion
of the population reporting that they did not add salt to food
was the single largest change observed in the series of three
surveys of risk factors for cardiovascular disease conducted by
the National Heart Foundation in Australian capital cities
during the 1980s.18–19 Assuming this did translate into a reduced intake of sodium, there are likely to have been small but
potentially important effects on average blood pressure in the
population.20 There are few data available on trends in consumption of meat in Australia, but meat is a principal source of
fat in the adult diet21 and our data show that many men are
also continuing to eat the fat on meat. Similarly, there are no
adequate longitudinal data on passive smoking, although downwards trends can be inferred from changes in the prevalence of
active smoking22 and from the adoption of smoke-free policies
in many workplaces and public places in Australia during the
1980s.23
For relevant individuals, giving up smoking and maintaining
weight within the acceptable range for one’s height stand to
make important contributions to one’s own coronary health as
well as to that of the community in general. Unfortunately, after
almost two decades of unbroken declines, the prevalence of
active smoking among Australian adults has remained static
during the 1990s,22 while average body mass index increased
throughout the 1980s.19
Many of the behaviours shown in our study to be associated
with a reduced risk of AMI are simple, inexpensive, most unlikely to cause harm and potentially could become permanent
features of the lifestyle of a very large proportion of the population. As Geoffrey Rose has pointed out,24 many people will
have to make small changes if the community as a whole is to
reap the very considerable potential benefits in terms of the
852
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
primary prevention of coronary disease that we have identified.
Encouraging these changes via health promotion campaigns
will assist this process, but progress in particular areas is likely
to be more certain and substantial if governments take an active
role in modifying environments such that they encourage
prudent behaviour. Relevant examples include provision of
well-designed and safe facilities for pedestrians and cyclists, subsidizing aids to cessation of smoking that are of proven efficacy,
and making smoke-free policies mandatory in all workplaces
and confined public places. Such initiatives require enlightened
leadership and some financial investment, but our results
suggest that even in a country where mortality from ischaemic
heart disease has fallen by half in the space of a generation,
there are very significant savings to be made in terms of both
personal suffering and reduced costs to the community.
6 National Health and Medical Research Council. Is There a Safe Level of
Daily Consumption of Alcohol for Men and Women? Canberra: Australian
Government Publishing Service, 1992.
7 SAS Institute Inc. SAS Users Guide, Version 6.12. Cary, North Carolina:
SAS Institute, 1997.
(EGRET)
Software, Version 0.19.6. Seattle: Statistics and Epidemiology Research
Corporation, 1991.
8 Epidemiological Graphic, Regression, Estimation and Testing
9 WHO Regional Strategy in Support of Health for All. Copenhagen: WHO
Regional Office for Europe, 1985.
10 National Heart Foundation of Australia. Heart and Stroke Facts—1995.
Canberra: NHF, 1997.
11 Ascherio A, Rimm EB, Giovannucci EL et al. Dietary fat and risk of
coronary heart disease in men: cohort follow up study in the United
States. Br Med J 1996;313:84–90.
12 Berlin JA, Colditz GA. A meta-analysis of physical activity in the
prevention of coronary heart disease. Am J Epidemiol 1990;132:612–28.
Acknowledgements
This work was supported by grants from the National Health
and Medical Research Council of Australia, the National Heart
Foundation of Australia and the Western Australian Health
Promotion Foundation (Healthway). The authors are indebted
to the Perth MONICA team and the staff involved with the 1994
Risk Factor Prevalence Survey. The study would not have been
possible without co-operation received from the patients, their
next of kin and the control subjects, and from the Australian
Bureau of Statistics, the Registrar General of Births, Deaths
and Marriages, the State Electoral Commission, the Health
Department of Western Australia, and numerous hospitals in
Perth.
13 Al-Roomi KA, Heller RF, Wlodarczyk J. Hypertension control and the
risk of myocardial infarction and stroke: a population-based study.
Med J Aust 1990;153:595–99.
14 Murabito JM, Anderson KN, Kannel WB, Evans JC, Levy D. Risk of
coronary heart disease in subjects with chest discomfort: the
Framingham Heart Study. Am J Med 1990;89:297–302.
15 Stampfer MJ, Sacks FM, Salvini S, Willett WC, Hennekens CH. A
prospective study of cholesterol, apolipoproteins, and the risk of
myocardial infarction. N Engl J Med 1991;325:373–81.
16 Knuiman MW, Welborn TA, Whittall DE. An analysis of excess
mortality rates for persons with non-insulin-dependent diabetes in
Western Australia using the Cox proportional hazards regression
model. Am J Epidemiol 1992;135:638–48.
17 Fraser GE, Lindsted KD, Beeson WL. Effect of risk factor values on
lifetime risk of and age at first coronary event. Am J Epidemiol 1995;
142:746–58.
References
1 English DR, Holman CDJ, Milne E et al. The Quantification of Drug
Caused Morbidity and Mortality in Australia, 1995 Edition. Canberra:
Department of Human Services and Health, 1995.
2 Jamrozik K, Broadhurst RJ, Anderson CS, Stewart-Wynne EG. The
role of lifestyle factors in the aetiology of stroke: a populationbased case-control study in Perth, Western Australia. Stroke 1994;
25:51–59.
3 Dobson AJ, Jamrozik K, Hobbs MST et al. Medical care and case
fatality from myocardial infarction and coronary death in Newcastle
and Perth. Aust NZ J Med 1993;23:12–18.
4 National Heart Foundation of Australia and Australian Institute of
Health and Welfare. Risk Factor Prevalence Study—Survey Number 3—
1989. Canberra: NHF, 1991.
5 Dobson AJ, Blijlevens R, Alexander HM et al. Short fat questionnaire:
a self-administered measure of fat-intake behaviour. Aust J Public
Health 1993;17:144–49.
18 Hobbs MST, Jamrozik K, Hockey RL et al. Mortality from coronary
heart disease and incidence of acute myocardial infarction in
Auckland, Newcastle and Perth. Med J Aust 1991;155:436–42.
19 Bennett SA, Magnus P. Trends in cardiovascular risk factors in
Australia. Med J Aust 1994;161:519–27.
20 Intersalt Cooperative Research Group. Intersalt: an international study
of electrolyte excretion and blood pressure. Br Med J 1988;297:319–28.
21 Cashel KM, Greenfiels H. Principal sources of dietary fat in Australia:
evidence from apparent consumption data and the national dietary
survey of adults. Br J Nutr 1994,71:753–73.
22 Hill DJ, White VM, Scollo MM. Smoking behaviours of Australian
adults in 1995: trends and concerns. Med J Aust 1998;168:209–13.
23 NHMRC Working Party. The Health Effects of Passive Smoking—Draft
Report of the NHMRC Working Party on Passive Smoking. Canberra:
NHMRC, 1995.
24 Rose G. The Strategy of Preventive Medicine. Oxford: Oxford University
Press, 1992.