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Ten-year incidence of diabetes in older Australians: the Blue Mountains Eye Study

Sudha Cugati, Jie Jin Wang, Elena Rochtchina and Paul Mitchell
Med J Aust 2007; 186 (3): 131-135. || doi: 10.5694/j.1326-5377.2007.tb00836.x
Published online: 5 February 2007

Abstract

Objective: To estimate the incidence of diabetes and impaired fasting glucose (IFG), and increased risk associated with the metabolic syndrome, in a representative population-based sample of older Australians.

Design, setting and participants: The Blue Mountains Eye Study examined 3654 residents aged 49 + years (82.4% response rate) during 1992–1994, and re-examined 2335 (75.1% of survivors) during 1997–1999 and 1952 (75.6% of survivors) during 2002–2004; 2123 participants with normal blood glucose levels at baseline were considered at risk of developing incident diabetes.

Main outcome measures: Incident diabetes (or IFG) was defined in participants at risk who were newly diagnosed by a physician during the follow-up or found to have a fasting blood glucose level ≥ 7.0 mmol/L (or 5.6–6.9 mmol/L). Kaplan–Meier cumulative 10-year incidence was calculated.

Results: The overall 10-year incidence of diabetes and IFG was 9.3% and 15.8%, respectively. Participants with metabolic syndrome at baseline had a higher risk of incident diabetes than those without metabolic syndrome (29.2% v 8.6%). Baseline factors associated with incident diabetes were elevated fasting glucose level (adjusted odds ratio [OR], 4.5; 95% CI, 3.4–6.1 per mmol/L), obesity (OR, 2.0; 95% CI, 1.3–2.8), diabetes family history (OR, 1.7; 95% CI, 1.2–2.5), current smoking (OR, 1.6; 95% CI, 1.0–2.7) and high density lipoprotein cholesterol level < 1.0 mmol/L (OR, 2.4; 95% CI, 1.5–3.8). Similar baseline factors were associated with incident IFG.

Conclusion: This population-based study provides data on the incidence of diabetes and IFG in an older, predominantly white population, and confirms that metabolic and lifestyle factors are major risk factors for diabetes.

Methods
Risk factor assessment

The 2003 WHO/International Society of Hypertension guidelines17 were used to classify participants as:

Obesity was defined as body mass index (BMI) ≥ 30 kg/m2. Participants were classified as smokers if they currently smoked or had stopped smoking less than 12 months before examination.

Total cholesterol, triglycerides and high density lipoprotein (HDL) were measured from fasting blood samples using a 747 Biochemistry Analyzer (Hitachi, Tokyo, Japan). Hypercholesterolaemia was defined as a serum cholesterol level ≥ 5.2 mmol/L, hypertriglyceridaemia as serum triglyceride ≥ 2.0 mmol/L, and abnormal HDL cholesterol as ≤ 1.0 mmol/L.

Renal function was estimated based on serum creatinine level and creatinine clearance (using the Cockcroft–Gault formula). Adjusted creatinine clearance was then calculated as creatinine clearance × 1.73/body surface area.18 Renal impairment was considered present if the adjusted creatinine clearance was < 60 mL/min/1.73 m2. All participants were asked about a history of angina, acute myocardial infarction, stroke or gout.

The metabolic syndrome was defined according to the new International Diabetes Federation definition19 as central obesity (defined as BMI > 30 kg/m2) plus any two of the following four factors:

A history of diabetes in the participant’s family was sought during the study interview. First-degree relatives included parents and siblings, while second-degree relatives included both maternal and paternal relatives. Participants with unknown family history of diabetes in both parents were considered to have no family history of diabetes.

Results
Incidence of diabetes and associations

Of the 3654 baseline participants, 2335 (75.1% of survivors) returned to the 5-year follow-up examination, and 1952 (75.6% of survivors) to the 10-year follow-up examination. Including participants seen at either or both of these examinations, 2564 participants were followed up after baseline. Surviving participants who did not return at either the 5- or 10-year follow-up examinations were more likely to have been younger than 60 years of age and current smokers at baseline.

Exclusions were 163 participants with diabetes at baseline, 52 with missing diabetes data or fasting blood samples at baseline, and 226 with no fasting blood tests at either the 5- or 10-year examinations. Thus, 2123 participants (1242 women and 881 men) had complete data available and were included in the assessment of 10-year incident diabetes.

The 10-year incidence of diabetes in the study population estimated by the Kaplan–Meier method was 9.3% (n = 165). Of these 165 participants, 52 (31.5%) were diagnosed solely on the basis of an elevated fasting plasma glucose level at examination. The remaining 113 (68.5%) gave a history of physician-diagnosed diabetes and were receiving treatment (insulin, oral therapy or diet).

More women (incidence, 10.0%, n = 105) than men (8.2%, n = 60) developed diabetes, although this difference was not statistically significant (P = 0.20). The age-specific incidence of diabetes was 9.1%, 8.6%, and 11.2%, in the age groups < 60, 60–69 and 70 + years, respectively (P for age-related trend = 0.73). After multivariate adjustment, baseline plasma glucose level, low HDL cholesterol, presence of obesity, current smoking and family history of diabetes were all significantly associated with an increased risk of diabetes, but presence of hypertension was not (Box 1). Past history of angina, acute myocardial infarction, stroke or gout were also not found to be associated with diabetes incidence, nor was body surface area-adjusted creatinine clearance (data not shown).

The 10-year cumulative diabetes incidence was substantially higher among the 203 participants who had metabolic syndrome at baseline (28.1%) than among those without metabolic syndrome (7.6%). Box 2 shows the effect of metabolic syndrome traits on the incidence of diabetes. The risk of diabetes increased with a greater number of metabolic syndrome traits, in addition to a BMI > 30 kg/m2. A two-, four- and eightfold increased risk of diabetes was associated with the presence of two, three and four metabolic syndrome traits, respectively, in addition to a BMI > 30 kg/m2.

The 10-year incidence of diabetes was higher in participants with IFG at baseline (30.0%) than in those with normoglycaemia (6.5%). Of the 194 participants with IFG at baseline who did not develop diabetes, 94 (48.5%) were normoglycaemic at the 5-year examination, and 15 (7.7%) at the 10-year examination, using the new ADA definition. Of the 94 who were normoglycaemic at the 5-year examination, nine (9.6%) reverted to IFG at the 10-year examination. The corresponding return rates from IFG at baseline to normoglycaemia at follow-up examinations using the previous ADA definition (6.1–6.9 mmol/L) were also assessed: 34/50 (68%) became normoglycaemic at the 5-year examination, and two (4%) at the 10-year examination. Of the 34 who returned to normoglycaemia after 5 years, three (9%) developed IFG at the 10-year examination.

A history of diabetes in first-degree relatives, or a paternal history of diabetes, was also a significant predictor of incident diabetes (Box 3).

Discussion

In this white Australian population aged 49 + years at baseline, we found that the 10-year cumulative incidence of type 2 diabetes was 9.3%, with only a weak age-related trend. Elevated fasting plasma glucose level, traits of the metabolic syndrome, current smoking and family history of diabetes were all independent predictors of type 2 diabetes. The 10-year incidence of IFG was 15.8%. We are unaware of other current large prospective population-based studies in Australia that have reported the long-term incidence of type 2 diabetes among non-Aboriginal Australians. Increasing age, current smoking and obesity were significant factors predicting higher risk of incident IFG. We found no apparent association between hypertension and diabetes incidence. An explanation for our finding that the age-related trend for incident diabetes, reported from many other studies, was only weak is not clear, but could reflect selective mortality in this older population sample. A clear age-related trend was found for incident IFG.

Notably, the 9.3% diabetes incidence over 10 years in this older, predominantly white Australian population is only slightly lower than the incidence of 9.9% over 8 years reported for an Australian Aboriginal population,8 a group well known to have higher diabetes prevalence, suggesting that the incidence of diabetes is rising. However, it is important to consider the differences between the two studies. The BMES was undertaken 5 years after the study in Australian Aboriginals, and the diagnostic criteria for diabetes differed: BMES used fasting plasma glucose level, while the study in Australian Aboriginals used 2-hour glucose tolerance. This is a major limitation of our study. The 2-hour oral glucose tolerance test and fasting plasma glucose level measure somewhat different metabolic abnormalities, and both have a certain degree of misclassification.22 Hence, we may have underestimated the incidence of diabetes.

A 60% higher risk of diabetes was found among current smokers compared with non-smokers or ex-smokers at baseline, independent of other risk factors. Our findings that smoking predicts both incident diabetes and IFG are comparable to those from other recent large population-based studies.23,24 This link could be the result of increased insulin resistance in smokers, either directly due to pancreatic damage, or indirectly due to increased hepatic lipase activity or impaired insulin-stimulated glucose transport in skeletal muscles, which has been observed in smokers.23,24 Efforts to encourage smoking cessation could thus be cost effective in reducing the burden of diabetes.

We observed that the presence of two or more metabolic syndrome traits in addition to a BMI > 30 kg/m2 significantly increased the risk of diabetes, in keeping with findings from other studies.2,25 Given that the metabolic syndrome now affects nearly a quarter of the adult population in developed countries,25 continued increases in both the prevalence and incidence of diabetes are likely.

The strengths of this study include its population-based sample and reasonable follow-up at both 5 and 10 years. Fasting plasma glucose level was measured in most participants, and incident diabetes was defined either by a physician diagnosis of diabetes or elevated fasting plasma glucose level. A major drawback of our study is the “surrogate” definition of central obesity. As other anthropometric measures of abdominal fatness were not taken at baseline examinations of our study cohort, we were unable to study the association between waist circumference and diabetes incidence. Although central obesity can be presumed in a middle-aged person with a BMI > 30 kg/m2,19 participants with increased waist circumference but normal BMI would have been misclassified in our analysis. Cross-sectional analytical data from the AusDiab Study indicated that, although waist circumference and waist/hip ratio were superior to BMI in terms of the diabetes association in men, no differences were found in these three measurements in women.26

In summary, in this population-based study of older Australians, incidence rates for diabetes and IFG over a 10-year period were 9.3% and 15.8%, respectively. Baseline cardiovascular risk factors, particularly traits of the metabolic syndrome, and family history of diabetes, were shown to predict incident diabetes. Addressing factors that predict the metabolic syndrome would help decrease the future incidence of diabetes. Preventive strategies should also focus on people with a first-degree family history of diabetes and those who smoke.

Received 6 June 2006, accepted 10 October 2006

  • Sudha Cugati1
  • Jie Jin Wang2
  • Elena Rochtchina3
  • Paul Mitchell4

  • Centre for Vision Research, Westmead Millennium Institute, University of Sydney, Sydney, NSW.


Correspondence: jiejin_wang@wmi.usyd.edu.au

Acknowledgements: 

The Blue Mountains Eye Study was supported by the National Health and Medical Research Council (Grant Nos. 974159, 991407, 211069).

Competing interests:

None identified.

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