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Indigenous Health Research
Increase in prevalence of obesity and diabetes and decrease in plasma
cholesterol in a central Australian Aboriginal community
Robyn McDermott, Kevin G Rowley, Amanda J Lee, Sabina Knight and Kerin
O'Dea
MJA 2000; 172: 480-484
Abstract -
Subject and Methods -
Results -
Discussion -
Acknowledgements -
References -
Authors' details
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-
More articles on Aboriginal health
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Abstract |
Objective: To document change in prevalence of
obesity, diabetes and other cardiovascular diease (CVD) risk
factors, and trends in dietary macronutrient intake, over an
eight-year period in a rural Aboriginal community in central
Australia.
Design: Sequential cross-sectional community surveys in
1987, 1991 and 1995.
Subjects: All adults (15 years and over) in the community
were invited to participate. In 1987, 1991 and 1995, 335 (87% of
eligible adults), 331 (76%) and 304 (68%), respectively, were
surveyed.
Main outcome measures: Body mass index and waist : hip ratio;
blood glucose level and glucose tolerance; fasting total and high
density lipoprotein (HDL) cholesterol and triglyceride levels; and
apparent dietary intake (estimated by the store turnover
method).
Intervention: A community-based nutrition
awareness and healthy lifestyle program, 1988-1990.
Results: At the eight-year follow-up, the odds ratios (95%
CIs) for CVD risk factors relative to baseline were obesity, 1.84
(1.28-2.66); diabetes, 1.83 (1.11-3.03); hypercholesterolaemia,
0.29 (0.20-0.42); and dyslipidaemia (high triglyceride plus low HDL
cholesterol level), 4.54 (2.84-7.29). In younger women (15-24
years), there was a trebling in obesity prevalence and a four- to
fivefold increase in diabetes prevalence. Store turnover data
suggested a relative reduction in the consumption of refined
carbohydrates and saturated fats.
Conclusion: Interventions targeting nutritional
factors alone are unlikely to greatly alter trends towards
increasing prevalences of obesity and diabetes. In communities
where healthy food choices are limited, the role of regular physical
activity in improving metabolic fitness may also need to be
emphasised.
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| |
The high rates of obesity, diabetes and other cardiovascular disease
(CVD) risk factors in Australian Aboriginal communities1-4 lead to high
rates of diabetic complications and excess mortality in relatively
young people.5-7 With often poor access to
appropriate, good quality secondary prevention
services,8,9 some communities have
sought to emphasise primary prevention of diabetes in
community-based health programs aimed at improving individual food
choices and the quality of the food supply.10,11 In the community described here, a community-based nutrition
awareness and healthy lifestyle program was commenced in 1988, after
a 1987 survey showed high rates of obesity, diabetes and other CVD risk
factors. The program continued for two years and culminated in a risk
factor survey and store turnover study in 1991, followed by a series of
family-based workshops to provide feedback on the results. A third
survey was carried out in 1995.
We describe the trends in CVD risk factors (anthropometry, lipid
levels, and glucose intolerance) and apparent dietary intake over
this eight-year period.
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| | Subjects and methods | |
Cross-sectional surveys were carried out in June 1987, May 1991 and
April 1995 at a rural Aboriginal community. The surveys were approved
by the Alice Springs Institutional Ethics Committee (which, in 1995,
had an Aboriginal subcommittee), and by the Deakin University Ethics
Committee, after consultation with the community council and health
council. All adult members of the community (those 15 years and over)
were invited to participate and volunteers gave written informed
consent. Pregnant or non-Indigenous community members were
excluded. Results were returned to individual participants and
summary reports presented to the community council. The resident
population at the time of each survey (excluding visitors from other
communities) was determined by household census.
Blood tests: Twelve millilitres of blood was taken after an overnight
fast and a second blood sample collected two hours after a 75 g glucose
drink. Blood samples were kept cold until centrifugation and the
plasma frozen immediately thereafter until analysis. Levels of
glucose, total cholesterol, high density lipoprotein (HDL)
cholesterol (after precipitation of other lipoproteins with 15% w/v
PEG 6000) and triglycerides were measured by standard enzymatic
techniques using commercial kits (Boehringer-Mannheim, Mannheim,
Germany).
- Glucose tolerance was classified according to WHO
criteria.12
- Hypercholesterolaemia was defined as a plasma cholesterol
concentration ≥ 5.5 mmol/L; and
- Dyslipidaemia was defined as the combination of a low HDL
cholesterol level ( ≤ 0.9 mmol/L) plus hypertriglyceridaemia (a
fasting plasma triglyceride level ≥ 2.0 mmol/L).
Anthropometry: Measurements were made by trained staff using
standard techniques.13 Body weight was measured
to 0.1 kg, with the subject in light clothing, using digital
electronic scales; height was measured to 0.1 cm using a stadiometer;
and waist and hip circumferences were measured to 0.1 cm.
- Obesity was defined as a body mass index (BMI) > 30
kg/m2.
Smoking status: Current smoking status was ascertained in 1991 and
1995 using a yes/no questionnaire.
Dietary intake: Apparent dietary intake was measured using the store
turnover method14 for the three months
before each of the surveys. This method estimates general trends in
food consumption, as the local store is the main source of food for the
community. Expressing data as nutrient density (ie, as a proportion
of total energy intake) avoids estimating per capita intake and gives
a valid measure of dietary quality for the community.10,14
Intervention: A community-based nutrition awareness and healthy
lifestyle program was conducted from 1988 to 1990. The program, which
included a resident non-Aboriginal project officer and Aboriginal
coworker, concentrated mainly on raising awareness of diabetes in
the community, promoting healthy food-buying habits and improving
the quality of food purchased by the community store. Some details of
the intervention are given in Scrimgeour et al.15
Statistical analyses: Although some community members were
screened on more than one occasion (Box 1), analyses were performed
assuming purely cross-sectional data. Trends in continuous
variables were tested by linear regression using SPSS.16 Separate
analyses were performed for men and women. Regression models
included year of survey, age group and an interaction term of year of
survey with age group. Also included was a dummy variable indicating
whether that individual was screened once only or on more than one
occasion, the interaction terms of this dummy variable with year of
survey and age group, and a three-way interaction term. The latter two
variables were excluded from the final model if found to be
non-significant.
For categorical data, trends in prevalence were tested by a
χ2
test for linear association. Confidence intervals for prevalence
data were calculated assuming a binomial distribution and adjusted
using the finite sampling factor:
(N-n)/(N-1), where N is the
population size and n is the sample size. Mantel-Haenszel
age-weighted odds ratios and exact 95% confidence intervals for risk
factors were calculated using EpiInfo software.17 Sensitivity
analyses were performed to test for selection bias in the 1991 and 1995
survey samples.
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| | Results |
| | Response rates | |
Survey participation rates were 87% of the adults normally resident
and present at the time of the survey in 1987, 76% in 1991 and 68% in 1995
(Box 1). Participation rates by younger people were progressively
lower with each survey.
| | | | Anthropometry |
There was no statistically significant change in mean BMI among men
(Box 2A; the regression analysis had sufficient statistical power to
detect a difference in BMI over time of 0.15 kg/m2). Although mean
BMI rose in the two older age groups, this was because men returning for
repeat screenings tended to have a higher mean BMI than those screened
only once (P = 0.062). Similarly, there was no significant
change in waist circumference or waist : hip ratio among men (Box 2).
Among women, there was a significant increase in mean BMI,
particularly in those aged 15-24 years (Box 2A). The increase in mean
BMI (equivalent to about 10 kg in body weight) among women aged 15-24
years was accompanied by an increase in mean waist circumference, but
no significant change in waist : hip ratio. Among women 35 years and
older, mean BMI remained very high over the eight-year period.
For the community as a whole, the prevalence of obesity increased
significantly over the survey period: 1987 -- 22.8% (95%
CI, 22.2%-23.5%);
1991 -- 32.0% (95% CI, 30.6%-33.3%);
1995 -- 37.0% (95% CI, 35.1%-38.8%);
χ2
= 15.5, df = 1, P < 0.001.
There was a trebling in prevalence of obesity among women in the age
group 15-24 years over the eight-year period (χ2 = 14.4,
df = 1, P < 0.001), but no change among men of the same
age group (χ2
= 0.2, df = 1, P = 0.636; Box 3).
For the older age groups, there was already a high prevalence of
obesity among women in 1987, which remained high (Box 3). The
prevalence of obesity increased significantly among men aged 25-34
years during the follow-up period (χ2 = 5.2, df = 1,
P = 0.022; Box 3). The increase among men aged 35 years and older
was not statistically significant (χ2 = 2.0, df = 1,
P = 0.155). The statistical power of analyses of prevalence
changes in age and sex subgroups was somewhat low because of sparse
data and, in some cases, low prevalence.
| | Glucose tolerance | |
For the community as a whole, there was a trend to an increasing
prevalence of diabetes: 1987 -- 11.6% (95% CI, 11.1%-12.0%);
1991 -- 18.6% (95% CI, 17.4%-19.7%);
1995 -- 20.7% (95% CI, 17.7%-22.2%);
χ2= 9.9, df = 1, P = 0.002; with significant
increases in prevalence among men aged 25-34 years (χ2 = 4.8, df
= 1, P = 0.029) and women aged 35 years and older
(χ2
= 3.9, df = 1, P = 0.048; Box 3).
However, the prevalence of impaired glucose tolerance (IGT) did not
change significantly: 1987 -- 8.4% (95% CI, 8.0%-8.8%);
1991 -- 9.4% (95% CI, 8.6%-10.3%);
1995 -- 7.5% (95% CI, 5.6%-8.5%).
χ2= 0.13, df = 1, P = 0.721.
| | Plasma lipids | |
There was a highly significant decrease in mean levels of plasma
cholesterol between 1987 and 1991 (Box 2B). This decrease occurred
across all ages and in both sexes. This fall in total cholesterol level
was partly due to decreases in HDL cholesterol levels, which also
occurred in all age- and sex-specific categories, with the largest
decrease among women aged 15-24 years (Box 2B). Conversely, among
both men and women, there was an increase of similar magnitude in mean
fasting plasma triglyceride level in all age groups (Box 2B). After
excluding subjects with diabetes from the analysis, these trends to
lower total and HDL cholesterol and higher triglyceride levels were
still apparent (data not shown).
| | Changes in CVD risk factor profile | |
Box 4 shows the changing prevalence of cardiovascular risk factors as
odds ratios compared with baseline. By 1995, community members were
more likely to be obese, diabetic and dyslipidaemic (high plasma
triglyceride and low plasma HDL cholesterol levels), whereas the
risk of hypercholesterolaemia declined.
| | Apparent dietary macronutrient intake | |
Box 5 summarises changes in apparent community intake of sugar, total
fat and saturated fat. As a proportion of total energy intake, there
was a decline in total and saturated fat and sugar intake. Complex
carbohydrate intake was 22%, 21% and 30% of total energy in 1987, 1991
and 1995, respectively. Store turnover data also suggested that,
compared with 1987, there were decreases in the approximate per
capita daily intake of sugar, fruit and vegetables and increases in
flour and bread consumption (data not shown).
| | Representativeness of the survey samples
| |
The sensitivity analyses performed assumed that the non-responders
in 1991 and 1995 were all non-diabetic and non-obese. With this
assumption, the linear trend to an increase in prevalence remained
for obesity (χ2
= 5.0, df = 1, P = 0.025) but not for diabetes
(χ2 =
1.0, df = 1, P = 0.320). A more realistic, but still
conservative, assumption is that the non-responders in the 1991 and
1995 surveys had the same prevalence of obesity and diabetes as in the
first survey sample. With this assumption, there were significant
increases in estimated prevalences of obesity (23%, 30% and 32% in
1987, 1991 and 1995, respectively; χ2 = 9.4; df = 1; P =
0.002) and diabetes (12%, 17% and 18%; χ2 = 6.1; df = 1; P =
0.014).
Among men, regression analysis indicated that those who were
screened on more than one occasion had a greater increase in waist : hip
ratio with time (P = 0.014) and lower HDL cholesterol levels
(P = 0.004) compared with men screened only once. Among women,
those who were screened on more than one occasion had higher BMI (P =
0.020) compared with women screened only once. There were no
other significant differences apparent between these groups, nor
were there any other significant interactions with time.
Furthermore, a comparison of baseline data for subjects screened in
1987 and again at either or both of the subsequent surveys with those
who were not rescreened revealed no significant differences in mean
age, BMI, cholesterol and triglyceride levels or glucose tolerance
among either men or women. Together, these observations make it
unlikely that the observed trends in obesity, diabetes and plasma
lipids are artifacts due to sampling bias.
|
| | Discussion |
The community store intervention and education campaign in this
central Australian Aboriginal community was associated with a
decrease in apparent dietary intake of total and saturated fats and
refined carbohydrates and a corresponding increase in complex
carbohydrate intake. Associated with the change in dietary fat
intake, there were reductions in plasma cholesterol levels in all age
groups and both sexes. However, there were increases in the
prevalence of obesity (60% increase) and diabetes (80% increase)
over the survey period. While the study design does not allow us to
ascribe cause-and-effect relationships between the intervention
process and the trends in outcomes, the data imply that an attempt to
modify diet alone is insufficient to reverse trends to increasing
prevalence of obesity and diabetes.
Although the biochemical assays at baseline were performed on a
different instrument to that used in the two follow-up surveys, the
apparent changes in lipid profiles between the first and subsequent
surveys are unlikely to be due to methodological differences as the
same enzymatic methods were used for all three surveys and the kits
purchased from the same source; quality control samples were
routinely run and did not vary significantly over the study period;
and the changes observed are entirely consistent with the changes in
dietary fat intake.
Our results are similar to those reported after five years of a
non-communicable disease intervention program in
Mauritius:18 a major improvement in
circulating cholesterol levels, but rapidly increasing prevalence
of obesity and diabetes. The increase in prevalence of diabetes that
we found approaches the highest recorded.19 The trebling in the
prevalence of obesity among women aged 15-24 years was associated
with a four- to fivefold increase in prevalence of diabetes. In
contrast, there was no change in mean BMI for men in this age range.
Thus, weight gain and onset of diabetes in women was apparently
accelerated. Anecdotal evidence suggests this sex difference in
secular trends in body weight may be due to high participation by young
men in vigorous sporting activities such as football, whereas
regular exercise by young women is limited in this community.
Exercise has been shown to have protective effects against the
incidence of diabetes,20 even independently of
dietary change. Hence, community-directed interventions aimed at
increasing physical activity may improve health outcomes.
The prevalence of diabetes in older age groups was extremely high in
both men and women. Prior to 1991, diabetes was absent in men under 25
years and relatively uncommon among young women. By 1995, cases of
type 2 diabetes were beginning to appear even at this young age. The
decreasing age of onset of diabetes in this community has major public
health implications with respect to diabetic complications,
hyperglycaemia in pregnancy, and the subsequent intergenerational
amplification of diabetes risk.21
We have previously reported that body fat distribution, as indicated
by waist : hip ratio, among women in this community was unusual for an
Aboriginal population, with the central deposition of body fat being
less apparent than in other Aboriginal groups.2 Consistent with
this, there were no major changes in mean waist : hip ratio for women in
the subsequent surveys, even in the young women who had a large
increase in waist circumference.
Despite these adverse trends in obesity and diabetes, the community
has achieved significant improvements in dietary quality, as
indicated by the changes in the food supply at the store, and in plasma
cholesterol levels. However, a healthy diet consistent with
National Health and Medical Research Council (NHMRC)
guidelines22 has not been achieved.
This problem goes beyond the realm of individual choice and reflects
endemic poverty, high prices coupled with low incomes, often poor
quality of fruit and vegetables in community stores, household
economies which discourage the consumption of fresh foods, lack of
domestic refrigeration, and unavailability of many nutritious
foods.23 Reversal of obesity is
difficult even in the absence of such major environmental and social
barriers.24 Hence, early
intervention to prevent or delay the onset of excessive weight gain is
likely to be more effective in reducing diabetes and cardiovascular
risk in such communities.25
In conclusion, our results suggest that a focus on nutrition and
dietary habits alone may be insufficient to prevent excessive weight
gain and diabetes among adults in Aboriginal communities. Further
systematic studies of intervention processes, impacts and
associated outcomes are required to address this issue.
|
Acknowledgements
| |
This work was supported by grants from the NHMRC (No. 954605) and the
Commonwealth Department of Health and Family Services. Special
thanks to Fiona McLachlan, Sunil Piers, Nick Williams, Kathy Abbott
and the health workers and nursing staff of Territory Health Services
in Central Australia. We gratefully acknowledge the expert
technical assistance of Connie Karschimkus and Olga Strommer and
statistical advice of Elmer Villanueva.
|
| | References |
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populations. Aust J Public Health 1992; 16: 340-349.
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O'Dea K, Patel M, Kubisch R, et al. Obesity, diabetes and
hyperlipidemia in a central Australian Aboriginal community with a
long history of acculturation. Diabetes Care 1993; 16:
1004-1010.
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Gault A, O'Dea K, Rowley KG, et al. Abnormal glucose tolerance and
other coronary heart disease risk factors in an isolated Aboriginal
community in central Australia. Diabetes Care 1996; 19:
1269-1273.
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O'Dea K. Westernization and non-insulin-dependent diabetes in
Australian Aborigines. Ethnicity Dis 1991; 1: 171-187.
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Phillips CB, Patel MS, Weeramanthri TS. High mortality from renal
disease and infection in Aboriginal central Australians with
diabetes. Aust J Public Health 1995; 19: 482-486.
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Veroni M, Gracey M, Rouse I. Patterns of mortality in Western
Australian Aboriginals, 1983-1989. Int J Epidemiol 1994;
23: 73-81.
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Thomson NJ. Recent trends in Aboriginal mortality. Med J
Aust 1991; 154: 235-239.
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Phillips CB, Patel MS, Carbaron Y. Utilisation of health services
by Aboriginal Australians with diabetes. Diab Res Clin
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Deeble J, Mathers C, Smith L, et al. Expenditure on health services
for Aboriginal and Torres Strait Islander People. Canberra:
Australian Institute of Health and Welfare, 1998. (Catalogue No. HWE
6.)
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Lee AJ, Bonson APV, Yarmirr D, et al. Sustainability of a
successful health and nutrition program in a remote Aboriginal
community. Med J Aust 1995; 162: 633-635.
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Spinks M, White G. Looma, Western Australia: Diabetes Program.
In: Bear-Wingfield R, editor. Sharing good tucker stories. A guide
for Aboriginal and Torres Strait Islander communities. Canberra:
Commonwealth Department of Health and Family Services, 1996: 63-69.
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World Health Organization: Diabetes Mellitus: Report of a WHO
Study Group. World Health Organ Tech Rep Ser 1985; No. 727.
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Callaway CW, Chumlea WC, Bouchard C, et al. Circumferences. In:
Lohman TG, Roche AF, Masturell R, editors. Anthropometric
standardisation reference manual. Champaign, Ill: Human Kinetics
Books, 1988: 39-54.
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Lee AJ, O'Dea K, Mathews JD. Apparent dietary intake in remote
Aboriginal communities. Aust J Public Health 1994; 18:
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Scrimgeour D, Rowse T, Knight S. Food purchasing behaviour in an
Aboriginal community. 2. Evaluation of an intervention aimed at
children. Aust J Public Health 1994; 18: 67-70.
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SPSS [computer program], version 9.0. Chicago Ill: SPSS Inc,
1998.
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EpiInfo [computer program], version 6. Atlanta, Ga: Centers for
Disease Control and Prevention, 1993.
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Dowse GK, Gareeboo H, Alberti KGMM, et al, for the Mauritius
Non-communicable Disease Study Group. Changes in population
cholesterol concentrations and other cardiovascular risk factor
levels after five years of the non-communicable disease
intervention programme in Mauritius. BMJ 1995; 311:
1255-1259.
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Dowse GK, Spark RA, Mavo B, et al. Extraordinary prevalence of
non-insulin-dependent diabetes mellitus and bimodal plasma
glucose distribution in the Wanigela people of Papua New Guinea.
Med J Aust 1994; 16: 767-774.
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Pan X-R, Li G-W, Hu Y-H, et al. Effects of diet and exercise in
preventing NIDDM in people with impaired glucose tolerance. The Da
Qing IGT and diabetes study. Diabetes Care 1997; 20: 537-544.
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Pettit DJ, Nelson RG, Saad MF, et al. Diabetes and obesity in the
offspring of Pima Indian women with diabetes during pregnancy.
Diabetes Care 1993; 16: 310-314.
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National Health and Medical Research Council. Dietary
guidelines for Australians. Canberra: NHMRC/AGPS, 1992.
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Leonard D, Beilin R, Moran M. Whichway kaikai blo umi? Food and
nutrition in the Torres Strait. Aust J Public Health 1995; 19:
589-595.
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World Health Organization. Obesity: preventing and managing the
global epidemic. Geneva: WHO, 1998: 107-158.
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Macaulay AC, Paradis G, Potvin L, et al. The Kahnawake Schools
Diabetes Prevention Project: intervention, evaluation and
baseline results of a diabetes primary prevention program with a
native community in Canada. Prev Med 1997; 26: 779-790.
(Received 11 Oct 1999, accepted 20 Mar 2000)
|
Authors' details | |
Health Surveillance, Queensland Health, Tropical Public Health
Unit, Cairns, QLD.
Robyn McDermott, MPH, FAFPHM, Director.
Monash University, Centre for Population Health and Nutrition,
Monash Medical Centre, Melbourne, VIC.
Kevin G Rowley, BAppSci, PhD, Research Fellow; currently,
Research Fellow, Department of Medicine, St Vincent's Hospital,
Melbourne.
Kerin O'Dea, BSc, PhD, Head.
Menzies School of Health Research, Darwin, NT.
Amanda J Lee, GradDipDiet, PhD, Public Health Nutrition
Consultant.
Territory Health Services, Alice Springs, NT.
Sabina Knight, RN, MTH, Staff Development Officer (Remote).
Reprints will not be available from the authors.
Correspondence: Dr K
G Rowley, Department of Medicine, Clinical Sciences Building, St
Vincent's Hospital, Fitzroy, VIC 3065.
rowleykATmail.medstv.unimelb.edu.au
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2: Trends in anthropometric variables and plasma lipid levels, stratified by age and sex | | | | | 15-24 years | 25-34 years | 35 years and over | P* | P |
| A: Anthropometric variables
Body mass index (BMI), kg/m2 | Men
1987
1991
1995 | 24.5 (23.4-25.6)
24.1 (22.9-25.4)
24.8 (23.3-26.3) | 26.3 (24.7-28.0)
27.0 (25.0-29.0)
28.7 (27.2-30.2) | 26.0 (24.7-27.3)
27.8 (26.2-29.5)
28.2 (26.6-29.9) |
0.514
|
0.992
| Women
1987
1991
1995 | 24.5 (23.2-25.7)
24.6 (23.1-26.1)
29.1 (27.3-31.0) | 27.8 (26.0-29.7)
28.8 (26.9-30.7)
29.7 (27.7-31.8) | 30.2 (28.3-32.1)
31.8 (30.0-33.6)
30.4 (28.7-32.1) |
<0.001
|
0.004
| | Waist circumference, cm | Men
1987
1991
1995 | 86.2 (83.0-89.4)
85.3 (82.0-88.7)
84.8 (81.2-88.4) | 91.0 (87.3-94.6)
93.9 (89.4-98.4)
95.1 (91.1-99.2) | 97.9 (93.4-102.5)
99.0 (95.2-102.8)
98.2 (93.1-103.3) |
0.834
|
0.340
| Women
1987
1991
1995 | 81.5 (78.7-84.4)
82.3 (79.3-85.4)
90.0 (86.7-93.4) | 92.0 (87.8-96.2)
95.4 (90.5-100.2)
92.2 (88.2-96.3) | 98.3 (94.1-102.4)
99.9 (96.3-103.5)
94.0 (90.9-97.2) |
<0.001
|
<0.001
| | Waist:hip ratio | Men
1987
1991
1995 | 0.87 (0.85-0.88)
0.87 (0.86-0.89)
0.88 (0.87-0.90) | 0.92 (0.90-0.94)
0.94 (0.92-0.96)
0.94 (0.93-0.96) | 0.97 (0.96-0.98)
0.99 (0.97-1.01)
1.00 (0.98-1.02) |
0.293
|
0.160
| Women
1987
1991
1995
| 0.82 (0.80-0.83)
0.85 (0.82-0.87)
0.85 (0.83-0.88) | 0.85 (0.83-0.87)
0.89 (0.85-0.92)
0.85 (0.84-0.87) | 0.85 (0.84-0.87)
0.89 (0.87-0.91)
0.86 (0.84-0.88) |
0.134
|
0.095
|
| | Data are means (95% confidence interval). *P-value for change over time. P-value for interaction of change over time with age group. | | Back to text | B: Plasma lipids
Total cholesterol, mmol/L | Men
1987
1991
1995 | 5.3 (5.0-5.6)
4.5 (4.3-4.8)
4.5 (4.3-4.8) | 6.0 (5.7-6.3)
4.8 (4.6-5.1)
5.3 (5.0-5.6) | 6.2 (5.7-6.6)
5.5 (5.1-5.9)
5.5 (5.2-5.8) |
0.034
|
0.571
| Women
1987
1991
1995 | 5.2 (4.9-5.4)
4.3 (4.1-4.5)
4.5 (4.3-4.8) | 5.7 (5.3-6.1)
4.8 (4.5-5.0)
4.8 (4.5-5.1) | 5.5 (5.3-5.8)
5.0 (4.7-5.3)
5.0 (4.8-5.3) |
0.001
|
0.317
| | HDL cholesterol, mmol/L | Men
1987
1991
1995 | 1.17 (1.10-1.24)
0.88 (0.82-0.94)
0.83 (0.76-0.90) | 1.23 (1.10-1.36)
0.84 (0.77-0.91)
0.79 (0.73-0.85) | 1.05 (0.96-1.14)
0.78 (0.72-0.84)
0.76 (0.70-0.81) |
<0.001
|
0.180
| Women
1987
1991
1995 | 1.45 (1.33-1.57)
0.98 (0.91-1.05)
0.88 (0.81-0.95) | 1.25 (1.12-1.38)
0.81 (0.75-0.87)
0.86 (0.81-0.92) | 1.18 (1.10-1.27)
0.84 (0.79-0.89)
0.82 (0.78-0.86) |
<0.001
|
0.011
| | Triglycerides, mmol/L | Men
1987
1991
1995 | 1.1 (1.0-1.3)
1.6 (1.4-1.9)
1.7 (1.5-1.9) | 1.6 (1.3-2.0)
2.3 (1.9-2.7)
2.1 (1.8-2.5) | 2.1 (1.8-2.5)
3.0 (2.5-3.6)
2.9 (2.4-3.6) |
0.004
|
0.419
| Women
1987
1991
1995 | 1.0 (0.9-1.1)
1.2 (1.1-1.4)
1.6 (1.4-1.8) | 1.3 (1.2-1.6)
1.8 (1.6-2.1)
1.8 (1.5-2.0) | 1.6 (1.4-1.8)
2.2 (2.0-2.5)
2.2 (2.0-2.4) |
<0.001
|
0.248
|
Data are means (95% confidence interval), except triglycerides, which are geometric means (95% CI). *P-value for change over time. P-value for interaction of change over time with age group.
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