OBJECTIVE—The purpose of this study was to examine the natural history of peripheral arterial disease (PAD) complicating type 2 diabetes, in particular the influence of PAD on the risk of cardiac death and the adequacy of PAD risk factor management.

RESEARCH DESIGN AND METHODS—The Fremantle Diabetes Study (FDS) was a prospective community-based observational study of diabetic patients recruited between 1993 and 1996. The present sample comprised the 1,294 FDS type 2 diabetic patients and a subgroup of 531 of these who had valid data at baseline and five or more subsequent consecutive annual reviews. Assessments consisted of a range of clinical and biochemical variables including the ankle/brachial index (ABI). PAD was defined as an ABI ≤0.90 at two consecutive reviews or any PAD-related lower-extremity amputation.

RESULTS—The prevalence of PAD at study entry was 13.6% and the incidence of new PAD was 3.7 per 100 patient-years. Both prevalent and incident PAD was strongly and independently associated with increasing age, systolic blood pressure, total serum cholesterol, and especially smoking. Risk factor management improved but remained suboptimal during follow-up. An ABI of ≤0.90 was independently associated with an increased risk of cardiac death of 67%.

CONCLUSIONS—Measurement of the ABI is a simple means of identifying PAD in diabetic patients. PAD is common in diabetic patients and predicts cardiac death. These data further support the role of regular screening for PAD in diabetes so that intensive management of vascular risk factors can be pursued.

Studies in the general population indicate that peripheral arterial disease (PAD) is associated with increased risk of death from cardiovascular disease, and subgroup analyses suggest that PAD carries a particularly poor prognosis in diabetes (13). The role of the ankle/brachial index (ABI) in the detection of asymptomatic PAD, including that in diabetic individuals, is well established (4,5). Although screening for asymptomatic PAD using the ABI is recommended in diabetes, this recommendation has not been universally embraced. There is some evidence that PAD is underdiagnosed and that risk factor management is suboptimal in those most at risk (68).

Clinicians may underestimate the significance of PAD in diabetic patients because there are few data relating to its natural history. Early studies (1,9) relied on absent foot pulses or the presence of claudication to identify individuals with PAD. These indexes lack sensitivity for early and asymptomatic PAD, both of which have important prognostic implications (2). Although there have been a number of cross-sectional studies of PAD prevalence in diabetes based on the ABI (5,10,11), there is only one large study, the U.K. Prospective Diabetes Study (UKPDS) from which valid incidence and outcome data have been published (12). However, a limitation of the UKPDS was the exclusion of patients most at risk of prevalent and incident PAD, namely those with known coronary heart disease (CHD) (13).

The aims of the present study were to assess the prevalence, incidence, determinants, and prognosis of PAD in a large representative community-based cohort of type 2 diabetic patients. The main hypotheses to be tested were that 1) PAD increases the risk of cardiac death in diabetic patients and 2) PAD risk factor management is suboptimal in these patients.

The Fremantle Diabetes Study (FDS) was a prospective observational study of diabetic patients from a postcode-defined community of 120,097 people in Western Australia (14,15). The FDS protocol was approved by the Human Rights Committee, Fremantle Hospital, and all subjects gave informed consent before participation. We identified 2,258 eligible subjects between 1993 and 1996 using multiple sources (including hospital lists, general practitioners, specialists, allied health services, pharmacies, and advertisements) and recruited 1,426 (63%) to undergo annual assessments, of whom 1,294 (91%) had type 2 diabetes. Nonrecruited patients had age, sex, diabetes type, and ethnicity similar to those who were recruited (14). To obtain valid incidence data, we identified a 5-year subgroup comprising the 531 type 2 diabetic patients in the FDS with complete data at baseline and five or more subsequent consecutive annual reviews up to 1 November 2001.

All FDS assessments were performed at Fremantle Hospital. At each annual FDS visit, a physical examination was performed, including ophthalmoscopy and application of the Michigan Neuropathy Screening Instrument (16), and fasting blood and urine samples were taken for automated biochemical analyses (14,15). Supine systolic pressure was measured in duplicate in the right brachial artery and both posterior tibial and dorsalis pedis arteries using a hand-held Doppler probe. The ABI was calculated by dividing the highest of the systolic blood pressures in the respective ankle by the highest systolic blood pressure in the arm. The lowest ABI obtained for either leg was used in statistical analysis. Patients were classified as having CHD if there was a self-reported history of or hospitalization for myocardial infarction, angina, coronary artery surgery, or angioplasty and/or definite myocardial infarction on a Minnesota-coded electrocardiogram (codes 1-1 and 1-2) (17).

Definition of PAD

The ABI cut point used conventionally to define PAD is 0.90 (4,5). Given the strong relationship between PAD and cardiac mortality (2), we assessed the predictive value of levels of ABI for this end point in our cohort using the receiver operator characteristic curve. An ABI of 0.88 was furthest from the diagonal, supporting 0.90 as a suitable diagnostic threshold for clinically significant PAD in type 2 diabetes.

We considered PAD to be present at study entry (prevalent cases) if there was either 1) an ABI ≤0.90 at both baseline and first review or 2) a history of any PAD-related lower-extremity (including toe) amputation (LEA). PAD was considered to have developed during follow-up in those without PAD at baseline (incident cases) if there was 1) an ABI ≤0.90 at two consecutive reviews or 2) a new PAD-related LEA. The definition was based on two ABI measurements to reduce the effects of measurement error and within-person variability.

Mortality and hospital morbidity

All deaths and hospital admissions in Western Australia are recorded in the Western Australia Data Linkage System (17), which was used to provide FDS patient outcomes from the beginning of the study until end of June 2003. Causes of death were reviewed independently by two authors (D.G.B. and T.M.E.D.) and classified as cardiac (CHD or heart failure) or otherwise under the same system as used in the UKPDS (13). Where discrepancies occurred, casenotes were consulted, and a consensus coding was obtained.

Statistical analysis

The computer package SPSS for Windows (version 11.5) was used for statistical analysis. Data are presented as proportions, means ± SD, or geometric mean (SD range), or, in the case of variables that did not conform to a normal or log-normal distribution, as median (interquartile range). Updated mean values of key variables were calculated at each review by averaging results from all annual visits between baseline and the review of interest. Crude PAD incidence was defined in the 5-year subgroup as the number who developed PAD during follow-up divided by the total patient-years of follow-up from study entry to fourth review. A best line of fit of prevalence against time from study entry was determined to estimate the annual increase in prevalence.

Two-sample comparison of independent samples was by Fisher’s exact test for proportions, by Student’s t test for normally distributed continuous variables, and by Mann-Whitney U test for non-normally distributed variables. Multiple logistic regression analysis was performed to determine independent associates of prevalent and incident PAD. Values at baseline and fourth review, as well as updated means, were used to identify associates of incident PAD. Other complications (including CHD, neuropathy, and retinopathy) were not entered into multivariate analyses to focus on modifiable risk factors for PAD. Survival curves defined by baseline ABI status were constructed using Kaplan-Meier estimates and compared by log-rank test. Cox proportional hazards modeling was used to determine independent baseline predictors of cardiac death.

The 1,294 FDS patients with type 2 diabetes were aged 64.1 ± 11.3 years; 48.8% were male, and their median duration of diabetes was 4.0 years (interquartile range 1.0–9.0). Treatment was by diet alone in 32.0%, oral hypoglycemic agents (OHAs) in 56.1%, and insulin with or without OHAs in 12.0%. The median HbA1c (A1C) was 7.4% (6.4–8.8). The majority (69.5%) had at least one non-PAD vascular complication (CHD, cerebrovascular disease [CVD], neuropathy, retinopathy, and/or microalbuminuria [urinary albumin-to-creatinine ratio {ACR} ≥3.0 mg/mmol].

When compared with the other 763 type 2 diabetic patients from the baseline cohort, the 531 patients in the 5-year subgroup were younger at entry (62.4 ± 9.4 vs. 65.2 ± 12.3 years), were more likely to be male (54.2 vs. 45.0%), had shorter diabetes duration (3.0 years [interquartile range 0.7–7.0] vs. 4.3 [1.2–10.0]), had a lower A1C (7.2% [6.3–8.5] vs. 7.6 [6.5–9.0]), and had fewer non-PAD vascular complications (64.0 vs. 73.3%). They were also less likely to have died during follow-up (10.0 vs. 41.4%; P ≤ 0.001 in each case).

Prevalence of PAD

At baseline, 19 of 1,294 patients had a history of LEA including 15 (1.2%) attributed to PAD. Of the remaining 1,275, 113 (8.9%) could not have their baseline PAD status classified because they did not have a valid ABI measurement at either baseline or first review. There were 146 patients with an ABI ≤0.90 at both visits, which, when combined with the 15 cases of PAD-related amputations, gave a baseline PAD prevalence of 13.6% (95% CI 11.8–15.7). Compared with the 1,181 patients with assessable PAD status at baseline, the 113 unclassifiable patients were older (70.7 ± 13.2 vs. 63.4 ± 10.9 years, P < 0.001), had longer diabetes duration (5.0 years [interquartile range 2.0–11.0] vs. 4.0 [1.0–9.0], P = 0.008), higher A1C (7.9% [6.8–9.3] vs. 7.4 [6.4–8.8], P = 0.016), and lower ABI (0.70 ± 0.18 vs. 1.00 ± 0.21, P < 0.001). These data suggest that the estimated baseline prevalence is conservative. PAD was strongly associated with age, total serum cholesterol, systolic blood pressure, and smoking, and there were also associations with insulin treatment, antihypertensive therapy, and aspirin use (Table 1).

Incidence of PAD

The crude incidence of new PAD in patients in the 5-year cohort was 75 per 2,042 patient-years or 3.7 per 100 patient-years of follow-up. On average, net prevalence increased by 2.1% per year. Compared with patients in the 5-year cohort who remained PAD-free during follow-up (baseline values unless otherwise stated), those who developed PAD were older (67.4 ± 7.0 vs. 60.7 ± 9.3 years, P < 0.001), had longer diabetes duration (4.0 years [interquartile range 2.0–8.0] vs. 3.0 [0.6–6.0], P = 0.011), were more likely to smoke (24.0 vs. 12.6%, P = 0.018) and take aspirin (30.7 vs. 19.3%, P = 0.031), and had lower BMI (28.2 ± 4.5 vs. 29.7 ± 5.2 kg/m2, P = 0.022), higher systolic (155 ± 22 vs. 145 ± 21 mmHg, P < 0.001) and pulse (73 ± 17 vs. 64 ± 18 mmHg, P < 0.001) pressures, higher updated mean systolic (158 ± 19 vs. 144 ± 17 mmHg, P < 0.001) and pulse (81 ± 16 vs. 68 ± 15 mmHg, P < 0.001) pressures, and higher ACR at fourth review (3.7 [0.7–19.3] vs. 2.0 [0.4–9.8] mg/mmol, P = 0.002).

The independent risk factors for incident PAD are summarized in Table 1. Of those that were modifiable, smoking at study entry increased the risk of PAD more than fourfold, whereas increases in total serum cholesterol at baseline and systolic blood pressure at fourth review were also significant. There was greater use of aspirin in those with incident PAD, whereas those who did not develop PAD during follow-up were more likely to be diet treated. Nonsignificant associates of new PAD were diabetes duration, BMI, and glycemic control.

There were 23 patients in the 5-year cohort with PAD but no evidence of CHD or CVD at baseline. At study entry, 91% had systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, 35% had a total serum cholesterol >6.5 or >5.5 mmol/l with serum HDL cholesterol <1.0 mmol/l, and 17% smoked. Five years later, the equivalent percentages were 79, 14, and 18%. The proportion of these patients taking aspirin rose from 17% at baseline to 52% at 5 years.

Local complications of PAD

Of 357 patients in the total type 2 cohort with an ABI ≤0.90, 20 (5.6%) had a first LEA during follow-up compared with 16 of 897 (1.8%) with ABI >0.90 (P = 0.001). Similarly, 3.1% of those with an ABI ≤0.9 compared with 1.3% of those with an ABI >0.90 had a first episode of gangrene (defined by relevant ICD-9CM and ICD-10AM codes) during follow-up (P = 0.06).

Cardiac death

There were 363 cardiac deaths during follow-up, 71 (50.7%) in the 140 patients with an ABI ≤0.90 compared with 292 (26.0%) in the remainder. The sensitivity (95% CI) of an ABI ≤0.90 to predict cardiac mortality was 50.7% (95% CI 42.2–59.2) and the specificity 74.0% (71.3–76.5). Within each 10-year age-group in the 5-year cohort, cardiac mortality was consistently twofold higher for the PAD group and the overall standardized cardiac mortality rate ratio was 2.59 (95% CI 2.38–2.80). The cumulative survival curves for patients remaining alive (or deceased from noncardiac causes) in the two groups defined by baseline ABI status are shown in Fig. 1. There was a significant difference between the curves (P < 0.0001, log-rank test).

The independent risk factors associated with cardiac mortality are summarized in Table 2. In view of the positive association between all-cause and cardiovascular mortality and both low and high ABI in the Strong Heart Study (18), we divided patients into three ABI groups, namely ≤0.90 (PAD), 0.91–1.40 (reference group), and >1.40. In Cox proportional hazards modeling, age, A1C, systolic blood pressure (negatively), natural logarithm (ln) ACR, neuropathy, retinopathy, CHD, CVD, current smoking, and indigenous background significantly predicted cardiac death, as did an ABI ≤0.90.

In our representative community-based sample of patients with type 2 diabetes, nearly 14% had PAD at study entry. The incidence of new PAD was 3.7% per year in a younger, healthier subset of patients. In both the baseline sample and 5-year subgroup, prevalent and incident PAD were strongly and independently associated with increasing age, systolic blood pressure, total serum cholesterol, and prior and current smoking. The patients with or developing PAD were taking aspirin more often than those without PAD and required more intensive blood glucose–lowering therapy. An ABI ≤0.90 at baseline was associated with an increased risk of cardiac death that approached 70%.

We used the ABI to detect PAD as it is a simple, noninvasive, and objective test with a proven role both in the diagnosis of PAD and in the baseline assessment of individuals at risk of cardiovascular disease (2,4). Even without symptoms, PAD is considered to be present when the ABI is ≤0.90 (4). Although the ABI may be less sensitive in diabetic patients because of an increased prevalence of calcified or incompressible arteries (19), the threshold of 0.90 is still used widely in this group (5,11,20,21). Our receiver operator characteristic curve analysis demonstrated that an ABI cut point of 0.88 was the best predictor of cardiac death, indicating that the threshold of 0.90 in diabetic patients has the same prognostic significance as in the general population.

Although the prevalence of PAD in diabetic subjects is typically double that seen in nondiabetic individuals (22,23), estimates vary considerably depending on the definition of PAD and the characteristics of the patient sample. For studies of type 2 patients that used a single ABI measurement and a threshold of 0.90, PAD prevalence ranged from 6.5% in Chinese subjects (21) to approaching 25% in U.K. studies (5,11). Using this definition, the prevalence in our patients was greater at 29.3%. With the use of two consecutive annual measurements, our prevalence estimate fell to 13.6%. PAD prevalence in the UKPDS was 1.2% at baseline, but only patients with newly diagnosed diabetes were recruited, and the investigators used a very conservative definition of PAD, namely two of ABI <0.80, absence of both foot pulses, and claudication (12). Over 4.3 years of follow-up, the prevalence in our patients increased to nearly 18%. This is higher than the 12.5% seen after double the duration of diabetes (18.5 years) in the UKPDS and is likely to reflect a variety of factors including the different definitions of PAD and the UKPDS exclusion criterion of CHD, which would have excluded subjects most at risk of PAD (12,13).

The strongest independent predictors of prevalent PAD in our subjects were age, hypertension, smoking status, insulin treatment, and total serum cholesterol. These have been reported in other studies involving type 2 diabetic patients (5,11,12). However, unlike the Hoorn Study (10) and the UKPDS (12), we did not find that glycemic control was an independent risk factor for prevalent PAD. This may be due to the use of more intensive blood glucose therapy, including greater use of insulin (19.2 vs. 10.1%), in those with PAD at baseline.

The independent risk factors for new PAD were similar to those for prevalent cases, with age, smoking status, systolic blood pressure, and total serum cholesterol level increasing the risk. The positive association with aspirin use is likely to be a consequence of the significantly higher prevalence of CHD observed in patients developing PAD. Likewise, diet-treated patients are likely to have shorter diabetes duration and lower levels of A1C and thus lower risk of chronic vascular complications including PAD. Of the risk factors identified in our cohort, age and smoking status have been the most consistently reported in other samples of diabetic patients (12,24,25). The UKPDS also showed that glycemic control was an independent risk factor for incident PAD (12). None of the glycemic control measures in the present study were independent predictors of prevalent or incident PAD. The greater range of potential explanatory variables available in the FDS, more intensive contemporary management of glycemia, and/or the older age of the FDS cohort compared with UKPDS subjects might help to explain this discrepancy (14,15).

An ABI <0.90 is associated with increased cardiovascular mortality irrespective of diabetic status (2). However, the only community-based data relating to the prognostic significance of PAD in diabetes have been from subgroup analyses of 344 Framingham subjects (1) and 48 patients in the “Men born in 1914” study from Malmo (3). Both studies indicated that PAD increases cardiovascular mortality in diabetes. A study from the Mayo Clinic found that, in 424 patients with both PAD and diabetes, there was an adjusted risk of death that was 1.55 times that of patients with diabetes alone (26). Our larger study confirms this, with a low ABI (≤0.90) at baseline associated with a 67% increase in the risk of cardiac death compared with an ABI of >0.9–1.4. Albeit in a small number of subjects (n = 20), we also found a trend toward increased risk of cardiac death in patients with an ABI >1.4, consistent with studies in the general population (18). The relatively weak inverse association between systolic blood pressure and cardiac death may reflect a combination of relatively aggressive antihypertensive therapy and poor left ventricular function in at-risk patients.

One of the reasons for identifying PAD in patients with diabetes is to facilitate vascular risk management. There is evidence, for example, that intensive blood pressure control in diabetic patients with PAD reduces cardiovascular events (27). Despite recommendations from the American Diabetes Association that all diabetic patients >50 years of age should be screened for PAD (7), there are indications that this has not been embraced (28). There is also evidence from the National Health and Nutrition Examination Survey that the vascular risk factor management in diabetic patients remains suboptimal (29).

In our 5-year cohort, use of cardiovascular therapies intensified during follow-up, reflecting the increasing evidence base for such practice. Of patients with PAD but no evidence of CHD or CVD at baseline, the proportion taking aspirin tripled during follow-up. However, 48% were still not taking aspirin at 5 years. The use of antihypertensive and lipid-lowering medication also increased (data not shown), but we could not determine whether this was in response to the presence of PAD, alternative manifestations of atherosclerosis, or other patient- and physician-specific factors. Unfortunately, the proportion of patients with PAD who had inadequately treated hypertension remained high, whereas there was no reduction in smoking or increase in exercise during 5 years of follow-up. Nevertheless, the 67% increase in cardiac death in our cohort is likely to have been greater had there been no overall increase in use of cardiovascular therapies.

Our data indicate that the measurement of ABI is a simple means of identifying diabetic patients at increased risk of future cardiovascular disease and that the conventional 0.90 cut point is appropriate in diabetes. Importantly, more than half of our patients with PAD did not have CHD at baseline, yet, as a group, they were at substantially increased risk of cardiac death. PAD is relatively common in diabetic patients, even when stringent criteria for the diagnosis of prevalent and incident disease are used. This further supports the American Diabetes Association’s recommendation for regular screening in the context of optimized vascular risk management (7).

Figure 1—

Survival probability curves derived from Kaplan-Meier analysis of percentages of patients remaining alive (or deceased from noncardiac causes) in two groups of subjects defined by baseline ABI (P < 0.0001, log-rank test). In each case, censored data points are indicated by crosses.

Figure 1—

Survival probability curves derived from Kaplan-Meier analysis of percentages of patients remaining alive (or deceased from noncardiac causes) in two groups of subjects defined by baseline ABI (P < 0.0001, log-rank test). In each case, censored data points are indicated by crosses.

Close modal
Table 1—

Independent risk factors for prevalent and incident PAD as identified by multiple logistic regression analysis

Odds ratio (95% CI)P value
Prevalent PAD   
    Age (for an increase of 10 years) 1.95 (1.56–2.45) <0.001 
    Taking insulin (with or without OHAs) 2.05 (1.27–3.33) 0.004 
    Systolic blood pressure (for an increase of 10 mmHg) 1.11 (1.03–1.20) 0.009 
    Taking blood pressure–lowering medication 1.74 (1.17–2.58) 0.006 
    Total serum cholesterol (for an increase of 1 mmol/l) 1.24 (1.05–1.45) 0.010 
    Taking aspirin 1.55 (1.05–2.30) 0.028 
    Other European ethnicity* 1.91 (1.11–3.31) 0.020 
    Smoking status   
        Never  
        Ex-smoker 1.92 (1.29–2.87) 0.001 
        Current smoker 2.78 (1.59–4.88) <0.001 
Incident PAD (n = 474)   
    Age (for an increase of 10 years) 2.72 (1.80–4.09) <0.001 
    Diet-treated (fourth review) 0.36 (0.16–0.83) 0.016 
    Systolic blood pressure (fourth review; for an increase of 10 mmHg) 1.23 (1.09–1.38) 0.001 
    Baseline total serum cholesterol (for an increase of 1 mmol/l) 1.39 (1.09–1.76) 0.008 
    Taking aspirin (fourth review) 1.95 (1.10–3.43) 0.021 
    Baseline smoking status   
        Never  
Ex-smoker 1.16 (0.62–2.15) 0.65 
Current smoker 4.45 (2.04–9.71) <0.001 
Odds ratio (95% CI)P value
Prevalent PAD   
    Age (for an increase of 10 years) 1.95 (1.56–2.45) <0.001 
    Taking insulin (with or without OHAs) 2.05 (1.27–3.33) 0.004 
    Systolic blood pressure (for an increase of 10 mmHg) 1.11 (1.03–1.20) 0.009 
    Taking blood pressure–lowering medication 1.74 (1.17–2.58) 0.006 
    Total serum cholesterol (for an increase of 1 mmol/l) 1.24 (1.05–1.45) 0.010 
    Taking aspirin 1.55 (1.05–2.30) 0.028 
    Other European ethnicity* 1.91 (1.11–3.31) 0.020 
    Smoking status   
        Never  
        Ex-smoker 1.92 (1.29–2.87) 0.001 
        Current smoker 2.78 (1.59–4.88) <0.001 
Incident PAD (n = 474)   
    Age (for an increase of 10 years) 2.72 (1.80–4.09) <0.001 
    Diet-treated (fourth review) 0.36 (0.16–0.83) 0.016 
    Systolic blood pressure (fourth review; for an increase of 10 mmHg) 1.23 (1.09–1.38) 0.001 
    Baseline total serum cholesterol (for an increase of 1 mmol/l) 1.39 (1.09–1.76) 0.008 
    Taking aspirin (fourth review) 1.95 (1.10–3.43) 0.021 
    Baseline smoking status   
        Never  
Ex-smoker 1.16 (0.62–2.15) 0.65 
Current smoker 4.45 (2.04–9.71) <0.001 
*

An overrepresentation of European ethnic background other than Anglo-Celt or Southern European.

Table 2—

Cox proportional hazards model of baseline predictors of time to cardiac death

Hazard ratio (95% CI)P value
Age (for an increase of 10 years) 2.49 (1.92–3.22) <0.001 
A1C (for an increase of 1%) 1.12 (1.01–1.24) 0.039 
Systolic blood pressure (for an increase of 10 mmHg) 0.91 (0.83–0.99) 0.036 
ln(ACR) (mg/mmol)* 1.15 (1.01–1.31) 0.040 
Neuropathy 2.09 (1.42–3.06) <0.001 
Retinopathy 1.89 (1.23–2.90) 0.004 
CHD 3.33 (2.27–4.90) <0.001 
CVD 2.25 (1.42–3.56) 0.001 
Current smoker 1.75 (1.05–2.92) 0.033 
Indigenous Australian 3.03 (0.99–8.67) 0.050 
ABI   
    0.91–1.40  
    ≤0.90 1.67 (1.13–2.47) 0.010 
    >1.40 2.19 (0.75–6.38) 0.15 
Hazard ratio (95% CI)P value
Age (for an increase of 10 years) 2.49 (1.92–3.22) <0.001 
A1C (for an increase of 1%) 1.12 (1.01–1.24) 0.039 
Systolic blood pressure (for an increase of 10 mmHg) 0.91 (0.83–0.99) 0.036 
ln(ACR) (mg/mmol)* 1.15 (1.01–1.31) 0.040 
Neuropathy 2.09 (1.42–3.06) <0.001 
Retinopathy 1.89 (1.23–2.90) 0.004 
CHD 3.33 (2.27–4.90) <0.001 
CVD 2.25 (1.42–3.56) 0.001 
Current smoker 1.75 (1.05–2.92) 0.033 
Indigenous Australian 3.03 (0.99–8.67) 0.050 
ABI   
    0.91–1.40  
    ≤0.90 1.67 (1.13–2.47) 0.010 
    >1.40 2.19 (0.75–6.38) 0.15 
*

ln, natural logarithm; a 2.72-fold increase in ACR corresponds to an increase of 1 in ln(ACR).

The Raine Foundation, University of Western Australia funded the FDS.

We thank the FDS patients for their participation, FDS staff for help with data collection, the Biochemistry Department at Fremantle Hospital and Health Service for performing laboratory tests, and Fremantle Hospital staff for assistance with patient recruitment.

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A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

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