1 Departments of Obstetrics and Gynaecology, 2 Geriatrics, 3 Internal Medicine, Akademiska Hospital, Uppsala University, Uppsala, Sweden and 4 Department of Obstetrics and Gynecology S. Anna Hospital, Torino University, Torino, Italy
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Abstract |
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Key words: euglycaemic hyperinsulinaemic clamp/insulin resistance/PCOS/screening
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Introduction |
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Since most women with PCOS come to clinical attention when their glucose tolerance is still normal and the cardiovascular damage is presumably at an early stage, screening for insulin resistance would be crucial in order to identify those cases at greater risk, allowing an appropriate medical intervention.
The hyperinsulinaemic euglycaemic clamp (De Fronzo et al., 1979) is considered to be the gold standard for evaluation of insulin sensitivity. In our department, we have been using this technique in recent years to investigate women with PCOS. However, the procedure is expensive, invasive, and time-consuming. In the present study, we aimed at defining prediction models for insulin resistance developed from clinical, anthropometric, hormonal and metabolic variables.
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Materials and methods |
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Eighty-one non-hirsute, normally menstruating women (mean age 30, range 1944 years) with normal ovaries according to ultrasound, covering a similarly wide range of body mass index (BMI kg/m2: range 17.340.9), formed the reference group for the calculation of the normal percentiles of insulin sensitivity.
All the women were in good physical condition, non-diabetic, with normal levels of prolactin, and did not suffer from any other metabolic disease. None of the subjects had been taking any drug known to affect carbohydrate metabolism, or any hormonal substance for at least 3 months prior to the metabolic and endocrine investigations. Seven women with PCOS were glucose intolerant, according to the results of a frequently sampling intra-venous glucose tolerance test (IVGTT) (k value <1) (Holte et al., 1994a).
A group of 20 elderly men, participating in a survey at the Department of Geriatrics of Uppsala University, were investigated twice 29 ± 7 days apart with the clamp technique in order to correct for within-subject variation in insulin sensitivity (see below).
Informed consent was obtained from all the women, and the study received the approval of the Human Ethics Committee of the Medical Faculty, Uppsala University.
Anthropometric variables
BMI was calculated as weight (kg) divided by squared height (m2). Measurements of the waist and hip circumferences and of the subscapularis, suprailiaca and umbilicalis skin folds were performed in duplicate as previously described in detail (Holte et al., 1994a).
Euglycaemic hyperinsulinaemic clamp and laboratory investigations
Insulin sensitivity was measured by the euglycaemic hyperinsulinaemic clamp as previously described (Pollare et al., 1990). Insulin (Actrapid Human®; Novo, Copenhagen, Denmark) was infused at a rate of 56 mU/(minxm2 body surface area). The amount of glucose infused to maintain the target plasma glucose concentration (5.1 mmol/l) during the second hour of the test was defined as glucose disposal (M: mg glucosexkg1xmin1). Adjusting M for the steady-state insulin concentration defined the insulin sensitivity index [M/I: mg glucosexkg1xmin1x (100 mU/l)1x100]. The within-subject variability of insulin sensitivity, calculated from the reproducibility study on 20 elderly men, was 0.61 units (13.9% of the mean).
The methods for the hormone and lipid analyses have been described previously (Holte et al., 1994a,b
).
The coefficients of variation for the variables chosen in the models (see below) were 15.7 and 14.8%, for plasma insulin and serum triglycerides respectively (Berglund and Lithell, 1996), and 8.5 and 2.9% for the subscapularis skin fold and the waist circumference respectively.
Statistics
All variables were examined for normality of distribution with KolmogorovSmirnov goodness-of-fit test and, where necessary, log transformation was performed. A forward stepwise-regression analysis was performed on a set of variables to find the best models for insulin sensitivity. The variables considered for the analyses were selected on the basis of a significant simple correlation coefficient with log M/I 0.5. Criteria for choosing the models were: ß coefficients significantly (P < 0.05) different from zero and high multiple correlation coefficients. The within-subject variation in insulin sensitivity will cause an under-estimation of the multiple correlations and an over-estimation of the prediction errors. In order to remove those biases, according to a published method (Rosner and Willett, 1988
), we used the data from the reproducibility study for insulin sensitivity.
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Results |
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Discussion |
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Waist circumference was an independent predictor of insulin resistance in all three models. This simple measure has proven to be a reliable predictor of visceral fat and related cardiovascular risk in both sexes (Hartz et al., 1984; Pouliot et al., 1994
; Han et al., 1995
), and it is correlated with indices of insulin resistance, especially in women (Bjorntorp, 1990
; Pouliot et al., 1994
). The presence of such a measure of visceral fat in all models is in line with the well-documented relationship between abdominal fat and insulin resistance in women with PCOS (Holte et al., 1994a
, 1995
; Bouchard, 1997
).
In the most efficient model, fasting insulin was an independent predictor of insulin sensitivity. Indeed, fasting insulin showed the highest degree of simple correlation (inverse) to the insulin sensitivity index (Table I). This was expected and it is in line with results obtained in different non-diabetic populations (Bergman et al., 1985
; Matthews et al., 1985
; Ferranini et al., 1997
). However, the fact that fasting insulin and waist girth had similar and independent statistical impacts in model I suggests that fasting insulin provides only a partial measurement of peripheral insulin resistance.
A recent study reported that the glucose to insulin ratio measured in the fasting state may provide a useful prediction measure of insulin resistance in women with PCOS (Legro et al., 1998). In that study measurements of body fat distribution were not included. In spite of a significant simple correlation with the insulin sensitivity index in our population (Table I
), the glucose to insulin ratio was not better than fasting insulin alone, and the index was not selected in any of the best models, suggesting that a measurement of truncal fat increases the power of the model. In the above cited study, insulin sensitivity was measured with the frequently sampled i.v. glucose tolerance test (`FSIGT'; Legro et al., 1998). Although the two techniques of investigating insulin sensitivity usually give similar results, the clamp technique is regarded as the gold standard. A recent thorough study on subjects with varying degrees of glucose tolerance failed to find any close correlation between the glucose to insulin ratio and the insulin sensitivity index obtained with the euglycaemic clamp (Matsuda and DeFronzo, 1999
).
In model II, fasting serum concentration of triglycerides was chosen as the second variable. Increased triglyceride concentrations are found in states of insulin resistance, most probably as a result of lower activation of the lipoprotein lipase and impaired triglyceride clearance (Frayn, 1993). In analogy with the findings for body fat distribution, the association between triglycerides and insulin resistance is common in states of insulin resistance (Laakso et al., 1990
; Berglund and Lithell, 1996
), suggesting that the metabolic derangements encountered in PCOS are not unique, but generally conform with the well established insulin resistance syndrome (De Fronzo and Ferranini, 1991
; Reaven, 1995
; Holte, 1996
).
The subscapularis skin fold formed the basis for prediction model III, along with the waist girth. Interestingly, the two anthropometric measures predicted independently the degree of insulin resistance. Most probably, the waist girth and the subscapularis skin fold measure two different types of fat, the predominantly visceral and the subcutaneous truncal fat respectively (Bouchard et al., 1993), both types being independently associated with insulin resistance (Ross et al., 1996
). Recent studies show that in healthy individuals subcutaneous truncalabdominal fat is highly correlated with the level of insulin resistance even more so than is intraperitoneal fat (Abate et al., 1995
), even when the insulin resistance is measured by DXA (dual X-ray absorptiometry) (Marcus et al., 1999
). In addition, it has been suggested that the thickness of subscapularis skin fold could help to identify women at risk of non-insulin dependent diabetes mellitus (NIDDM; Peiris et al., 1989). The coefficient of variation for waist girth was 2.9%, whereas it was somehow higher for the subscapularis skin fold (8.5%). The latter value is not far from that of previous investigations on different populations (Durnin and Womersley, 1974
; Peiris et al., 1989
). It should be stressed that despite the obvious variability in anthropometric measurements, the predictive power of model III was strong, making it suitable for clinical use.
Interestingly, no measures of androgen excess qualified in the prediction models, in spite of fairly high simple correlation coefficients. These findings suggest that such associations are mainly indirect, and the results are in line with previous reports of similar degrees of metabolic derangements in women with normal androgen concentrations as in those with increased concentrations (Norman et al., 1995).
In total, the results support the strong relationship between decreased insulin sensitivity, truncalabdominal fatness, and dyslipidaemia in women with PCOS, whereas measures of androgen excess are lost when tested in multiple regression analyses. In conclusion, the present study allowed the construction of three simple and inexpensive models with high predictive power, which thus would be potentially useful in clinical practice on an outpatient basis.
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Notes |
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References |
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Submitted on April 26, 2000; accepted on July 3, 2000.