Obesity and Type 2 Diabetes Mellitus

International Textbook of Obesity. Edited by Per Bjorntorp. Copyright 2001 John Wiley & Sons Ltd Print ISBNs: 0-471-988707 (Hardback); 0-470-846739 (Electronic) 24 Obesity and Type 2 Diabetes Mellitus Allison M. Hodge, Maximilian P. de Courten and Paul Zimmet International Diabetes Institute, Caulfield, Victoria, Australia INTRODUCTION Obesity has reached epidemic proportions globally, and all evidence suggests that the situation is likely to get worse (1). In developed regions such as Europe (2), the USA (3), and Australia (4,5) the prevalence is high and increasing but in some developing countries even more extreme situations exist (6,7). Coincident with the high rates of obesity, the prevalence of type 2 (non-insulin-dependent) diabetes is also escalating, and this increase is expected to continue, so that by the year 2010 it is predicted that a total of 216 million people worldwide will have type 2 diabetes (8). Obesity and type 2 diabetes are lifestyle-related conditions and it seems likely that changes in diet and physical activity associated with increased affluence can influence diabetes risk both directly, and indirectly through obesity. The link between degree of obesity and diabetes that has been observed may be complicated by other factors such as duration of obesity, body fat distribution, physical activity, age, diet composition, ethnicity, genetic susceptibility to type 2 diabetes and obesity, weight loss associated with diabetes, and possibly fetal and early infant growth rate; many of which can be considered risk factors for obesity as well as contributing to type 2 diabetes risk independently of obesity. Thus at any level of obesity, the degree to which other risk factors for type 2 diabetes contribute will determine the overall risk of developing, and the age of onset of, diabetes. To estimate the effects of obesity on type 2 diabetes it is necessary that the influence of the above mentioned factors are understood, and that a standardized definition is used for obesity and diabetes. What is Obesity? Obesity may be simply defined as the degree of body fat storage associated with elevated health risks (1). Due to the difficulties of measuring body fat under field conditions the practical definition of obesity for adults is based on body mass index (BMI) (1). It should be noted that adult BMI cutpoints are not considered appropriate for children. Body mass index, also known as Quetelet s index, is calculated as an individual s weight (kg)/height (m ). Various cut-points and measures of obesity have been used in the past, but a World Health Organization (WHO) consultation on obesity proposed a system of classification based on BMI (1) (Table 24.1), which is similar to classifications used in a number of past studies. International Textbook of Obesity. Edited by Per Björntorp. 2001 John Wiley & Sons, Ltd.

352 INTERNATIONAL TEXTBOOK OF OBESITY Table 24.1 BMI classification in adults Classification BMI kg/m ) Risk of comorbities Underweight 18.5 Low (but increased risk of other clinical problems) Normal range 18.5 24.9 Average Overweight 25.0 Pre-obese 25.0 29.9 Increased Obese class I 30.0 34.9 Moderate Obese class II 25.0 39.9 Severe Obese class III 40.0 Very severe Measuring Body Fat Distribution Compared with subcutaneous adipose tissue, abdominal adipose tissue is more strongly linked to metabolic changes, including insulin resistance and glucose intolerance. The contribution of abdominal and subcutaneous adipose tissue to central obesity cannot be sufficiently determined using only anthropometric methods. Nonetheless, variations in anthropometrically evaluated body fat distribution contribute to the risk of cardiovascular disease (9 12) and type 2 diabetes (13 24) independent of overall obesity. A number of methods have been used to assess body fat distribution, including subscapular/triceps skinfold ratio, waist/hip circumference ratio, waist/ thigh circumference ratio, and more recently waist circumference alone. The preference for circumference measurements over skinfolds reflects the difficulty of reliably measuring skinfolds, especially in obese individuals. Waist-to-hip ratio (WHR) has now been accepted as a means of assessing abdominal fat distribution clinically and in epidemiological surveys. Cut-points indicating high risk vary between studies but commonly used criteria, at least for Caucasians, are WHR 1.0 in men and 0.85 in women (1). It is unlikely that universal cut-points for waist circumference will be developed due to variations between ethnic groups in the risk associated with a particular measurement (1). In a study of Dutch men and women the following waist measurements were found to be associated with a substantially increased risk of metabolic complications: 102 cm in men or 88 cm in women (1). Waist circumference can be used as a screening tool for identifying individuals at risk of obesity-related illness (1). It is also preferred to WHR for tracking changes in an individual over time, as WHR is less strongly correlated to weight change, and may in fact increase with weight loss in certain subgroups (smokers, black vs. white men, and anyone with WHR below the median at baseline) (25). It is important when using circumference measurements that standard anatomical locations are used. The WHO (26) recommends the following methods. Abdominal Circumference The subject stands with feet 25 30 cm apart, weight evenly distributed. Measurement is taken midway between the inferior margin of the last rib and the crest of the ilium in a horizontal plane. The measurer sits by the side of the subject and fits the tape snugly but not compressing soft tissues. Circumference is measured to nearest 0.1 cm. Hip (Buttocks) Circumference Wearing only non-restrictive briefs or underwear, or a light smock over underwear, the subject stands erect with arms at the sides and feet together. The measurer sits at the side of the subject so that the level of the maximum extension of the buttocks can be seen, and places the tape measure around the buttocks in a horizontal plane. The tape is held snugly but not compressing soft tissues. Circumference is measured to the nearest 0.1 cm. RISK FACTORS FOR TYPE 2 DIABETES Table 24.2 presents the known modifiable and nonmodifiable risk factors or aetiological determinants associated with type 2 diabetes (27). The overall risk of type 2 diabetes must be assessed on the basis of all of these. Because of the additive effect of different risk factors and determinants, individuals with high levels of non-obesity risk may develop type 2 diabetes without becoming obese, while in other cases obesity alone may be sufficient to lead to diabetes. Generalized and central obesity are just two of the interrelated risk factors associated with type 2 diabetes, and of the modifiable lifestyle factors are probably the most important in terms of size and consistency of effect.

Table 24.2 Aetiological determinants and risk factors of type 2 diabetes A. Genetic factors Genetic markers, family history, thrifty gene hypothesis etc. B. Demographic determinants Sex, age, ethnicity C. Behavioural and lifestyle-related risk factors Obesity (including distribution of obesity, duration) Physical inactivity Diet Stress Urban lifestyle D. Metabolic determinants and intermediate risk categories of type 2 diabetes Impaired glucose tolerance, impaired fasting glucose Insulin resistance Other components of the metabolic syndrome Pregnancy-related determinants (parity, gestational diabetes, diabetes in offspring of women with diabetes during pregnancy, intrauterine environment) Obesity and Type 2 Diabetes OBESITY AND TYPE 2 DIABETES MELLITUS 353 The association between obesity and type 2 diabetes has been observed in both cross-sectional (13 19, 28 33) and prospective studies (20 23, 31,34 38) across various populations. Obesity confers a minimum 3- to 10-fold risk of type 2 diabetes (39) and it is estimated that type 2 diabetes risk could be reduced by 50 75% by control of obesity (40). Weight loss associated with the onset of diabetes (36,41) means that the association of obesity with type 2 diabetes prevalence is generally weaker than its association with incidence. For example, in an Israeli study, the main determinant of the incidence of type 2 diabetes over a 10-year study period was the BMI at baseline, rather than the BMI at follow-up when glucose tolerance was measured (38). Incident impaired glucose tolerance was associated with both concurrent and prior BMI, as would be expected if weight loss only occurs after glucose tolerance has deteriorated to frank diabetes. In a study of Pima Indians baseline BMI was also strongly related to the incidence of type 2 diabetes but there was little association between diabetes prevalence and concurrent obesity (42). In a small subgroup of subjects of that study with BMI data from 4 years before diagnosis to 2 years after, there was a clear pattern of weight gain preceding diagnosis, followed by weight loss after diagnosis. Older participants developed diabetes at a lower BMI than younger individuals, suggesting that age-related deterioration in insulin sensitivity enables the development of diabetes at lower levels of adiposity than required for the development of diabetes in younger subjects. In contrast to the results in Pima Indians, Tai et al. (31) found that BMI was similarly associated with the prevalence or 4-year cumulative incidence of diabetes, with odds ratios of 1.12 and 1.14 respectively for a 1 unit increase in BMI in slim (mean BMI 23 kg/m ) Chinese. If diagnosis is made early in the natural history of diabetes before weight loss occurs it could be expected that a stronger positive association between BMI and prevalent type 2 diabetes would be observed. The Importance of Duration and Changes in Obesity for Risk of Type 2 Diabetes Although the duration of obesity is considered important in determining the risk of obesity associated conditions, including type 2 diabetes, there is little information available to quantify this relationship. Even in most prospective studies that actual onset of obesity is not measured and can only be estimated by recall. Moreover, if weight is changing it is difficult to differentiate between the effects of the degree and duration of obesity. In the above mentioned large study in Israel, Modan et al. (38) found that obesity lasting for less than 10 years was not associated with a major increase in diabetes incidence compared with that in subjects who had remained slim (BMI 23 kg/ m ). The risk of type 2 diabetes was increased in subjects who had lost weight to reach a specific BMI class relative to those who had remained stable within that class, while those with a stable BMI had in turn a greater risk of type 2 diabetes than those who had increased their BMI class, indicating that weight gain per se was not associated with increased risk of type 2 diabetes (38). Similar results were observed in the multiethnic population of Mauritius. For any level of BMI at 5 years of follow-up, the highest prevalence of type 2 diabetes was associated with weight loss since baseline, and the lowest with weight gain, while those whose weight had remained stable had an intermediate risk. Comparing the weight gainers with weight

354 INTERNATIONAL TEXTBOOK OF OBESITY maintainers in both studies suggests that the stable group were at greater risk due to their longer duration at the higher current BMI. In one of the few reports to actually examine the levels of glucose tolerance associated with different duration of self-reported obesity (based on percentage of standard weight ranging from 14 to 137% overweight), Ogilvie (43) observed that it took 5 to 18 years of obesity for glucose intolerance to develop, and 12 to 38 years for diabetes to occur. In contrast to other studies, the degree of obesity was not associated with glucose tolerance. In a more recent study, Felber et al. (44,45) examined fasting plasma glucose levels and glucose storage capacity in relation to obesity duration cross-sectionally in 67 moderately obese subjects (mean ideal body weight 150 3%). Participants with a duration of obesity less than 17 years generally had low fasting glucose concentrations and high rates of glucose uptake, while beyond this time fasting glucose began to increase and glucose storage capacity to fall. The time when fasting glucose began to rise and glucose uptake declined was considered the onset of type 2 diabetes; thus the results were interpreted as showing that at least 17 years of moderate obesity was required before type 2 diabetes developed. It seems likely that the actual level of obesity and other risk factors would affect the duration of obesity that had to be experienced before glucose tolerance deteriorated to diabetes. Evidence for a specific effect of weight gain on type 2 diabetes comes from two American studies, where self-reported weight gain throughout adulthood or immediately prior to the study period was associated with increased risk of diabetes independent of BMI in early adulthood (34,35); although weight gain was no longer significant if attained BMI was controlled for. However, if the effect of weight gain is modelled controlling for attained BMI, it is effectively modelling duration, as obese people who have not gained weight also have a longer duration of obesity (46). This emphasizes the difficulty in delineating the effects of current BMI, duration of BMI, and weight gain. Harris (47) also indicated that weight gain between 25 and 50 years of age was a risk factor for type 2 diabetes, and Di Pietro et al. (48) have shown a rapid weight gain between puberty and age 25 years in a cohort of Swedish adults who were overweight in childhood and went on to develop diabetes. Weight gain also preceded type 2 diabetes in Pima Indians (36,42). However, as mentioned earlier weight change had little effect on risk of type 2 diabetes in the Israeli study, and most of the incident cases of type 2 diabetes had not changed weight over 10 years of follow-up, and BMI had been at 27 kg/m or greater for at least the period of the study (38). The effect of weight gain on diabetes incidence was quantified in a follow-up study of the baseline NHANES (National Health and Nutrition Examination Survey) cohort in the USA (49). The 9-year diabetes incidence, as determined from death certificates, hospitalization and nursing home records, increased by 4.5% for every kilogram of weight gained. This was after controlling for a number of factors including baseline BMI, but not BMI at diagnosis. From this result it was estimated that the average weight gain of 3.6 kg recorded between NHANES II and NHANES III could theoretically give rise to a 16% increase in diabetes incidence between 1990 and 2000. Mechanisms Linking Obesity and Glucose Intolerance Numerous mechanisms have been proposed linking obesity and glucose intolerance. Most obese individuals with type 2 diabetes are also insulin resistant, while lean subjects with type 2 diabetes are likely to have a defect in insulin secretion. A continuum between obese glucose tolerant, obese glucose intolerant, obese diabetic with hyperinsulinaemia, and obese diabetes with hypoinsulinaemia has been proposed by Golay et al. (45) and is supported by the work of others (50,51). Deficiency in glucose storage as glycogen is evident in each of these groups of obese subjects. The first step in both glucose storage and oxidation is through glucose 6-phosphate. Glucose storage proceeds under the action of glycogen synthase and mobilization is controlled by glycogen phosphorylase. Glucose oxidation proceeds via glycolysis to the citric acid cycle. In obesity there are increased circulating levels of free fatty acids (FFAs) and elevated lipid oxidation. This results in metabolic products (acetyl-coa and citrate) which inhibit glucose mobilization. Intracellular glycogen therefore accumulates, inhibiting glycogen synthase and glucose storage (45). This occurs independent of the positive effect of hyperglycaemia and hyperinsulinaemia on glucose storage. As long as glucose tolerance is normal in obesity,

the negative effect of increased intracellular glycogen on glucose uptake is smaller than the positive effect of hyperinsulinaemia and hyperglycaemia. Glucose intolerance occurs when the stimulating effects of increased glucose and insulin can no longer overcome the resistance to glucose storage hence resulting in continuous hyperglycaemia. A vicious cycle develops with higher fasting glycaemia inhibiting glucose storage and inhibition of glucose storage causing hyperglycaemia (45). Initially hyperglycaemia is accompanied by an increased insulin response to a glucose load, but eventually β-cell response becomes insufficient, and although basal insulin levels may still be elevated in comparison to lean subjects, insulin response to a glucose load or meal is diminished and hyperglycaemia persists (45,50,51). This simplified account provides a framework within which the association between obesity and type 2 diabetes can be understood. The lowering of fat stores with weight loss enables mobilization of glycogen and therefore increased uptake of glucose for storage. In the short term, an energy-deficient diet or exercise will also improve glucose uptake by facilitating glycogen mobilization without any change in body fat content. Weight gain, as well as current weight, has been considered a risk factor for type 2 diabetes. At any level and duration of BMI, extra body fat could tip the balance to impaired glucose uptake. Behavioural factors resulting in weight gain, such as dietary changes or reduced physical activity, may also promote the development of type 2 diabetes. Fat Distribution and Type 2 Diabetes Abdominal fat, especially the visceral rather than subcutaneous depots, is strongly associated with the metabolic complications of obesity (52). Kissebah has recently reviewed the current understanding of the relationship between abdominal adiposity and metabolic changes leading to insulin resistance and glucose intolerance, elevated blood pressure and dyslipidaemia (52). Microcirculatory changes in blood flow may contribute to insulin resistance, along with a primary neurohumoral dysregulation, enhanced by genetically or environmentally overactive arousal systems. The increased lipolysis associated with visceral adipose OBESITY AND TYPE 2 DIABETES MELLITUS 355 tissue, and the resultant increase in FFA flux to the liver, may impair hepatic insulin extraction, while increased androgenic hormones in centrally obese women could also contribute to insulin resistance (52). There are several issues pertinent to the relationship between fat distribution and diabetes. Independent Effects of Overall and Central Obesity Anthropometric measures of body fat distribution (e.g. waist-to-hip ratio (WHR), subscapular-totriceps skinfold ratio (STR), waist-to-thigh ratio) or computed tomography (CT) scan measures are associated with risk of diabetes, in both longitudinal (20 23) and cross-sectional (13 19,24,32,53) studies. The effects of fat distribution are generally independent of measures of overall fatness (13 23) and may be even more important. Using a variety of markers of fat distribution, prevalence studies in Asian Indians (17,18), English Caucasians (18), Pima Indians (36), American Caucasians (24) and American Hispanics (24) have demonstrated that overall body fat is less closely associated with type 2 diabetes than is body fat distribution. In addition, some studies indicated that the effect of fat distribution is greater in more obese individuals (16,21,53). Exceptions occurred in Mauritius, where there was no apparent effect of BMI on the prevalence of type 2 diabetes across tertiles of WHR (14), and in American men (16), where the effect of WHR was higher in the leaner individuals. In both these studies the general level of BMI was not extreme. In the Pima Indians, an extremely obese population, the effect of fat distribution was diminished with increased BMI or age (36). It may be that a threshold amount of body fat is required before the effects of fat distribution become apparent, and that after a certain level of obesity, the deposition of fat in peripheral depots diminishes the importance of central fat. Longitudinal studies are less consistent. Among men of the Normative Aging Study who were followed over 18 years, fat distribution as measured by the ratio of abdominal circumference/hip breadth was a stronger predictor of both type 2 diabetes and impaired glucose tolerance than was BMI (23), but in prospective studies of Swedish men (20), and women (21), BMI and WHR were of similar importance.

356 INTERNATIONAL TEXTBOOK OF OBESITY The tendency for markers of fat distribution to be more strongly associated with prevalence of type 2 diabetes than is BMI in cross-sectional studies could be explained by decreases in BMI, but not WHR, associated with the onset of diabetes. Unpublished analyses from a prospective study in Mauritius show a fall in BMI but not WHR, over 5 years in people with diabetes. Gender, Fat Distribution and Diabetes Overall the literature suggests that both general adiposity and distribution of fat deposits are independently important risk factors for type 2 diabetes, in both men and women. However, some studies suggest that there are gender differences in the relative importance of overall fatness and fat distribution. In general, fat distribution appeared to be less important in men than women in comparison with overall fat measure (14 16,54), This observation led Haffner et al. (54) to propose a plateau effect of centrality, in this case measured STR, whereby above a certain level of STR, i.e. that achieved in most men, there was no further increase in rates of type 2 diabetes. Fat deposition in men is generally abdominal; thus waist circumference or WHR will correlate more strongly with overall obesity, and the range of fat distribution may be limited, compared to women. These factors may explain statistically the lack of an independent association of prevalence of type 2 diabetes with fat distribution in men, rather than their higher degree of abdominal obesity as suggested above. In summary, both overall obesity and fat distribution contribute to the risk of type 2 diabetes, but their relative importance may vary in relation to whether incidence or prevalence is considered, the gender of the individuals examined or their degree of obesity. However, strategies to reduce type 2 diabetes risk via diet and physical activity can reduce both overall and abdominal obesity and improvements in both should be sought. For management of obesity, waist circumference rather than WHR is probably a better measure of benefit, as weight loss and decrease in abdominal adipose tissue, can occur without changes in WHR. Ethinicity and Body Fat Distribution There is evidence to suggest that in some ethnic groups the risk associated with a central distribution of body fat is relatively low. Among non-hispanics in Colorado the diabetes risks associated with BMI, triceps and subscapular skinfold thicknesses, family history and income were similar to those found in Hispanics. However, a 1 unit increase in either WHR or STR was associated with a greater increase in risk of type 2 diabetes among non-hispanic whites than among Hispanics (28). Similarly, upper body obesity was more closely associated with higher levels of plasma insulin and glucose, and reduced insulin sensitivity, in obese Caucasian compared to African-American women (55). This metabolic study, along with the study of Marshall et al. (28), suggest that Caucasians may be more susceptible to the effects of fat distribution than some other ethnic groups. Genetic Factors and Type 2 Diabetes There is clearly a genetic component to type 2 diabetes as indicated by twin studies, familial clustering of cases, and at the population level, by apparent ethnic differences in diabetes susceptibility with several genes assumed to contribute. Individual Level At the individual level, family history of type 2 diabetes can be used as an index of genetic predisposition to diabetes. A number of studies, examining different populations, have suggested that lean individuals with type 2 diabetes have a greater load of susceptibility genes. Thus individuals with a strong family history of type 2 diabetes do not need to accumulate large fat depots to achieve the same level of risk as those with less genetic susceptibility but a higher degree of obesity. In Japanese men with a family history of type 2 diabetes it appeared that elevated prior or current obesity was not as strongly associated with type 2 diabetes as in men with no family history (56). Lemieux et al. (57) showed that among normal glucose tolerant men with relatively high levels of insulin or glucose or both following an oral glucose tolerance test (OGTT), that is those at high risk of progression to diabetes, those with no family history of diabetes had a mean BMI at age 20 which was 2.6 kg/m higher than those with a family his-

tory of type 2 diabetes. Using a different approach, Kuzuya and Matsuda found that patients with type 2 diabetes who had a definite history of obesity had a significantly (P 0.01) lower prevalence of family history of diabetes (32%) than those who had not been obese (50%) (58). Similarly, the siblings of lean diabetics tended to have a higher prevalence of type 2 diabetes than the siblings of obese diabetics in the study of Lee et al. (59), while Hanson et al. (60) observed that the odds ratio for type 2 diabetes in the offspring of obese diabetic parents was 0.6 compared with offspring of lean diabetic parents. Among elderly diabetic men in the Zutphen (Netherlands) study, there was no difference in the degree or duration of obesity in those with a family history of type 2 diabetes or those with no family history (61). This lack of interaction could be related to the older age of these men, 69 90 years. If, as reported by Kuzuya (58) and Lee (59), family history of diabetes is associated with earlier onset of diabetes, it is possible that men with a strong family history and young onset of type 2 diabetes will have already died, which could bias the results. Ohlson et al. (21) also did not find any statistically significant interaction between obesity and family history of diabetes in Swedish men. Population Level Comparisons between different ethnic groups indicate residual differences in the prevalence of type 2 diabetes even after adjusting for BMI and other risk factors (28,62). Such differences may be attributed to a variety of factors, including increased genetic susceptibility, increased levels of other risk factors that were not considered, or the inability of anthropometric methods to accurately assess overall fat mass and distribution. Asian Indians, for example, appear to have an elevated risk of type 2 diabetes compared with members of other ethnic groups, even when BMI is at a similar or lower level (63 65). This is explained to some extent by differences in body fat distribution (66) which mean that Indian BMIs are not equivalent, regarding risk for diabetes, to BMIs of other ethnic groups. Fijian Indians had lower BMI than Melanesians, but their triceps skinfold thicknesses were greater, suggesting a higher body fat content in Indians (65). Indians also had a greater mean WHR than Europeans for the same level of BMI (18). In a comparison of young European and Polynesian women in New OBESITY AND TYPE 2 DIABETES MELLITUS Zealand it was found that a BMI of 30 kg/m for a European was equivalent, in terms of body fat content, to a BMI of about 34 kg/m for a Polynesian (67); therefore the effect of similar BMI on risk of type 2 diabetes may differ between these ethnic groups. Swinburn et al. (68) previously reported that resistance measured by a bioelectrical impedance device was lower in Polynesians than Caucasians at any level of weight (adjusted for height and age), also implying a lower body fat content. On the other hand, a recent study of Chinese and Dutch adults found similar relationships between BMI and body fat in both populations (69), suggesting that differences between ethnic groups are not universal. Diet, Obesity and Type 2 Diabetes 357 Diet is associated with risk of type 2 diabetes through its effect on obesity, and more specifically, dietary components such as fat, sugar and fibre have long been implicated in the development of type 2 diabetes (70). The importance of diet, independent of obesity, in at least some studies, indicates that among subjects with similar BMIs, the risk of type 2 diabetes could be modified by their usual diet. In the San Luis Valley Diabetes Study, total fat intake was predictive of type 2 diabetes over 1 3 years of follow-up in 123 individuals with impaired glucose tolerance, independent of BMI (71). After adjusting for a number of dietary, anthropometric and metabolic risk factors the odds ratio for type 2 diabetes associated with a 40 g increment in total fat intake was around 7; however, saturated fat intake was not a predictor. In a cross-sectional analysis of baseline data from the same study the evidence was also in support of total fat being associated with type 2 diabetes (72). Tsunehara et al. have published cross-sectional (73) and prospective (74) data on diet and type 2 diabetes in Japanese American men indicating an association with animal fat, which is consistent with the results of a study on Seventh Day Adventists showing relationships between meat consumption and diabetes (75), although these studies did not control for obesity. In the Finnish and Dutch cohorts of the Seven Countries Study, total fat, saturated fat, monounsaturated fat and cholesterol

358 INTERNATIONAL TEXTBOOK OF OBESITY were higher 20 years before diagnosis in men with diabetes compared with men who were normal or had impaired glucose tolerance (76). After adjustment for past BMI and other factors, total fat was still significantly associated with 2-h post-load glucose level. Beneficial effects of fish on glucose tolerance have also been noted and it is believed that ω-3 fatty acids may be protective (77), although in one study this was only if accompanied by moderate physical activity (78). Thus the evidence for fat quantity and type being involved in the development of type 2 diabetes is expanding and is supported by studies on the effects of lipid composition of cell membranes on insulin sensitivity (79). Two reports published in 1997, based on the long-running Health Professionals Follow-Up Study (80) and Nurses Health Study (81), concluded that diets with a high glycaemic load and low content of cereal fibre increased the risk of type 2 diabetes independently of BMI, in men and women respectively; the authors recommended that grains be consumed in a minimally refined form to reduce the risk of diabetes. The risk of developing type 2 diabetes for men and women in the top tertile of glycaemic load and the lowest for cereal fibre intake was twice that of those with low glycaemic load and high cereal fibre intake. Nevertheless, a number of other studies have been unable to show any associations between diet and type 2 diabetes (82 85). However, it is clearly important to get some idea of dietary composition in order to evaluate the type 2 diabetes risk in individuals. The magnitude of the effect of diet on risk of type 2 diabetes is estimated as being of similar order as that of BMI; thus it should not be ignored. Physical Activity, Obesity and Type 2 Diabetes Obesity and physical activity have been found to be independently associated with both prevalence (14,86) and incidence (87 91) of type 2 diabetes in men and women. Physical activity may lower the risk of type 2 diabetes via reduced total body fat (86,87,89 93) and less abdominally distributed fat (86,89,92,93), and/or through its action in improving insulin sensitivity (92,93). These mechanisms are closely linked, but the independent effects of activity and obesity suggest that physical activity can modify the risk of type 2 diabetes at any given level of obesity. In prospective studies where the effect of physical activity on type 2 diabetes risk has been shown to be independent of obesity, the benefits of physical activity were similar for lean and obese subjects among men and women in Malta (91), and women in the Nurses Health Study (87). In two studies of Caucasian American men, the effect of physical activity was strongest for more obese men and nonexistent in the leanest men (88,90), in contrast to the findings of the Honolulu Heart Study, where only the leaner men were protected by physical activity (89). These conflicting results cannot be explained by very different BMI levels in the different populations, but levels of other risk factors may be important. Gender may also modify the interaction between obesity and physical activity. The relative risk of type 2 diabetes in less active individuals depends also on the levels of activity being compared, as well as many other factors. In the studies discussed above the relative risks ranged from 1.1 for the Pennsylvania Alumni (88), to 2.6 in Malta (91), of similar magnitude to the risks associated with obesity. Fetal and Early Infant Nutrition, Obesity and Type 2 Diabetes Hales and colleagues have proposed that poor intrauterine nutrition, and perhaps poor nutrition in early infancy, reflected in low birthweights and decreased rates of postnatal growth, can increase the risk of type 2 diabetes and cardiovascular diseases in later life, through either reducing pancreatic β- cell capacity, or increasing insulin resistance (94,95). The effects of low birthweight on insulin resistance (96) or the insulin resistance syndrome (97) appear to be enhanced by adult obesity. Thus for adults with a ponderal index at birth of 20.6 kg/m, the degree of insulin resistance (t min) ranged from 18 to 31 at adult BMI increased, compared with a range of 14 to 19 for those with a ponderal index at birth of 25 kg/m (96). Data in support of the so-called thrifty phenotype hypothesis have been reported in Europeans (96 101), Indians (102), Mexican Americans (97), Australian Aborigines

(103) and Native Americans (104), although at least two studies in Europeans have failed to show the expected associations (105,106). A recent review of studies into associations between fetal and/or infant growth and adult chronic disease concludes that the reported associations may be biased rather than causal, with possible selection bias due to loss to follow-up and confounding by socioeconomic factors (107). New evidence for a genetic explanation of the link between fetal growth and adult diabetes comes from Dunger et al. (108), with the observation that variation in the expression of the insulin gene is associated with size at birth. Whatever the mechanism for the association of low birthweight with adult disease, and McCance et al. have suggested that the observations can be explained by more conventional genetic hypotheses (104), the association is strong in a number of ethnically varied populations and hence its effects may contribute to differences in risk of type 2 diabetes seen in people with similar levels of adult obesity. Leptin, Obesity and Type 2 Diabetes OBESITY AND TYPE 2 DIABETES MELLITUS 359 While it is now accepted that human obesity is generally associated with elevated circulating leptin levels (109), and in many studies leptin is correlated with insulin levels (110 114) or insulin resistance (115,116), it is not clear whether leptin has a role in glucose intolerance in humans. In the leptin deficient ob/ob mouse treatment with leptin lowered glucose and insulin concentrations in the blood independently of weight loss (117,118). The leptin treated animals also increased physical activity and metabolic rate to normal levels (117) and this may have enhanced insulin sensitivity and glucose uptake via increased glycogen mobilization as discussed above, or increased glucose uptake by some insulin-independent mechanism which would result in reduced insulin levels (118). Leptin may also influence insulin secretion in ob/ob mice via neuropeptide Y (NPY) (119) or by direct action on β-cells (120,121). In humans, in contrast to rats and mice, insulin does not have an acute effect on leptin levels (111,113,122), although chronic hyperinsulinaemia appears to be associated with elevated leptin levels (111,123,124), perhaps due to adipocyte hypertrophy (111). On the other hand, there is some evidence for leptin influencing insulin sensitivity. In isolated human liver cells leptin antagonizes insulin signalling (125), and in the Israeli sand rat (Psammomys obesus), a polygenic animal model of type 2 diabetes, leptin has been reported to inhibit insulin binding to adipocyte insulin receptors (126). A number of studies have reported on leptin levels in diabetic versus non-diabetic individuals; after adjusting for obesity there is no consistent picture with no difference being found in Polynesians in Western Samoa (110), Mexican Americans (127), Finnish men (123), American men and women (128) and German men and women (129) who mostly appear to have type 2 diabetes. Clément et al. (130) have found lower leptin levels in morbidly obese, poorly controlled diabetes compared with controlled diabetes or non-diabetics with similar levels of obesity. The low leptin levels in poorly controlled subjects may have been associated with lower insulin levels in this group. Although the development of obesity in humans is unlikely to be linked to a defect in the OB gene as in the ob/ob mouse, in two related cases OB mutations in the homozygous form were reported to result in severe leptin deficiency and obesity (131). Recently, a rare mutation in exon 16 of OB-R was identified in humans. This alteration was found to result in morbid obesity and endocrine abnormalities in individuals homozygous for the mutation (132). Leptin resistance, as observed in the db/db mouse and fa/fa rat which have a single mutation in the leptin receptor gene, has not been demonstrated yet in humans (133) and it may be that leptin resistance is due to a defect in body mass regulation downstream of leptin. It may also be that leptin is not important in preventing obesity in humans as it is in ob/ob mice, and merely reflects fat stores. In a small study of Pima Indians, low leptin levels predicted weight gain (134), but in a population-based study of Mauritians we were unable to find any association between high (leptin resistance) or low (leptin deficiency) leptin levels and weight gain over 5 years (135). Consistent with human evolutionary pressure, it has been suggested that leptin may have a more important role in protecting against the effects of undernutrition (136 138), especially in relation to reproduction (139 141), rather than preventing overnutrition. In this case it may have little relevance to type 2 diabetes, but more research is

360 INTERNATIONAL TEXTBOOK OF OBESITY Figure 24.1 The complex relationship between obesity and type 2 diabetes mellitus, illustrating the roles of other risk factors. IGT, impaired glucose tolerance needed to determine whether leptin has a role in the development of diabetes. CONCLUSION Obesity, and central obesity in particular, are known to be important risk factors for development of type 2 diabetes. As discussed in this review, the association between obesity and type 2 diabetes may be modified by diet, physical activity, duration of obesity and other factors (Figure 24.1). Obesity and diabetes are interlinked through several mechanisms, and some of the relations are complicated by methodological issues surrounding assessment of obesity and study design. In a multifactonal setting comprising environmental (including behavioural) and genetic factors, where risk factors and outcome can both influence each other, data derived from epidemiological studies describing average effects can only provide a rough estimate of an individual s risk of developing type 2 diabetes. On the other hand, reducing an individual s risk from obesity should reflect the complexity of the relationship between obesity and type 2 diabetes, and other risk factors for type 2 diabetes must also be considered. Thus all individuals at a similar level of obesity should not necessarily be treated in the same way. REFERENCES 1. World Health Organization. Obesity: Preventing and Managing the Global Epidemic. Geneva: World Health Organization, 1998. 2. Bjo rntorp P. Obesity. Lancet 1997; 350: 423 426. 3. Kuczmarski R, Flegal K, Campbell S, Johnson C. Increasing prevalence of overweight among US adults: the National Health and Nutrition Examination Surveys. JAMA 1994; 272: 205 211. 4. Risk Factor Prevalence Study Management Committee. Risk Factor Prevalence Study: Survey No 2 1983. Canberra: National Heart Foundation of Australia and Australian Institute of Health, 1984. 5. Risk Factor Prevalence Study Management Committee. Risk Factor Prevalence Study: Survey No 3 1989. Canberra: National Heart Foundation of Australia and Australian Institute of Health, 1990. 6. Hodge AM, Dowse GK, Zimmet PZ, Collins VR. Preva-

lence and secular trends in obesity in Pacific and Indian Ocean island populations. Obes Res 1995; 3(Suppl. 2): 77s 87s. 7. Hodge AM, Dowse GK, Zimmet PZ. Obesity in Pacific populations. Pacific Health Dialog 1996; 3(1): 77 86. 8. Amos A, McCarty D, Zimmet P. The rising global burden of diabetes and its complications: Estimates and projections to the year 2010. Diebet Med 1997; 14(Suppl 5): S1 S85. 9. Lapidus L, Bengtsson C, Larsson B, Pennert K, Rybo E, Sjöström L. Distribution of adipose tissue and risk of cardiovascular disease and death: a 12 year follow up of participants in the population study of women in Gothenburg, Sweden. BMJ 1984; 289: 1257 1261. 10. Larsson B, Svardsudd K, Welin L, Welhelmsen L, Bjo rntorp P, Tibblin G. Abdominal adipose tissue distribution, obesity, and risk of cardiovascular disease and death: 13 year follow up of participants in the study of men born in 1913. BMJ 1984; 288: 1401 1404. 11. Filipovský J, Ducimetière P, Darné B, Richard J. Abdominal body mass distribution and elevated blood pressure are associated with increased risk of death from cardiovascular diseases and cancer in middle-aged men. The results of a 15-to 20-year follow-up in the Paris prospective study. Int J Obes 1993; 17: 197 203. 12. Prineas R, Folsom A, Kaye S. Central adiposity and increased risk of coronary artery disease mortality in older women. Ann Epidemiol 1993; 3: 34 41. 13. Haffner S, Stern M, Hazuda H, Pugh J, Paterson J. Do upper-body and centralized adiposity measure different aspects of regional body-fat distribution? Relationship to non-insulin dependent diabetes mellitus, lipids, and lipoproteins. Diabetes 1987; 36:43 51. 14. Dowse G, Zimmet P, Gareeboo H, et al. Abdominal obesity and physical inactivity as risk factors for NIDDM and impaired glucose tolerance in Indian, Creole and Chinese Mauritians. Diabetes Care 1991; 14: 271 282. 15. Chou P, Liao M-J, Shih-Tzer T. Associated risk factors of diabetes in Kin-Hu, Kinmen. Diabetes Res Clin Pract 1994; 26: 229 235. 16. Schmidt M, Duncan B, Canani L, Karohl C, Chambless L. Associations of waist-hip ratio with diabetes mellitus. Strength and possible modifiers. Diabetes Care 1992; 15: 912 914. 17. Shelgikar K, Hockaday T, Yajnik C. Central rather than generalized obesity is related to hyperglycaemia in Asian Indian subjects. Diabet Med 1991; 8: 712 717. 18. McKeigue P, Pierpoint T, Ferrie J, Marmot M. Relationship of glucose intolerance and hyperinsulinaemia to body fat pattern in South Asians and Europeans. Diabetologia 1992; 35: 785 791. 19. Collins V, Dowse G, Toelupe P, et al. Increasing prevalence of NIDDM in the Pacific island population of Western Samoa over a 13-year period. Diabetes Care 1994; 17: 288 296. 20. Lundgren H, Bengtsson C, Blohme G, Lapidus L, Sjo ström L. Adiposity and adipose tissue distribution in relation to incidence of diabetes in women: results from a prospective population study in Gothenburg, Sweden. Int J Obes 1989; 13: 413 423. 21. Ohlson L-O, Larsson B, Svardsudd K, et al. The influence OBESITY AND TYPE 2 DIABETES MELLITUS 361 of body fat distribution on the incidence of diabetes mellitus. 13.5 years of follow-up of the participants in the study of men born in 1913. Diabetes 1985; 35: 1055 1058. 22. Haffner SM, Stern MP, Mitchell BD, Hazuda HP, Patterson JK. Incidence of type II diabetes in Mexican Americans predicted by fasting insulin and glucose levels, obesity and body-fat distribution. Diabetes 1990; 39: 283 288. 23. Cassano P, Rosner B, Vokonas P, Weiss S. Obesity and body fat distribution in relation to the incidence of noninsulin-dependent diabetes mellitus. Am J Epidemiol 1992; 136: 1474 1486. 24. Sosenko J, Kato M, Soto R, Goldberg R. A comparison of adiposity measures for screening of non-insulin dependent diabetes mellitus. Int J Obes 1993; 17: 441 444. 25. Caan B, Armstrong M, Selby J, et al. Changes in measurements of body fat distribution accompanying weight change. Int J Obes 1994; 18: 397 404. 26. WHO Expert Committee. Physical Status: the Use and Interpretation of Anthropometry. Geneva: World Health Organization, 1995. 27. de Courten M, Bennett P, Tuomilehto J, Zimmet P. Epidemiology of NIDDM in non-europids. In: Alberti KGMM, Zimmet P, DeFronzo RA (eds) International Textbook of Diabetes Mellitus, 2nd edn. Chichester: John Wiley, 1997. 28. Marshall J, Hamman R, Baxter J, et al. Ethnic differences in risk factors associated with the prevalence of non-insulindependent diabetes mellitus. Am J Epidemiol 1993; 137: 706 718. 29. Skarfors E, Selinus K, Lithell H. Risk factors for developing non-insulin dependent diabetes: a 10 year follow-up of men in Uppsala. BMJ 1991; 303: 755 760. 30. Shaten B, Smith G, Kuller L, Neaton J. Risk factors for the development of Type II diabetes among men enrolled in the Usual Care group of the Multiple Risk Factor Intervention Trial. Diabetes Care 1993; 16: 1331 1339. 31. Tai T-Y, Chuang L-M, Wu H-P, Chen C-J. Association of body build with non-insulin-dependent diabetes mellitus and hypertension among Chinese adults: A 4-year followup study. Int J Epidemiol 1992; 21(3): 511 517. 32. Van Noord P, Seidell J, Den Tonkelaar I, Baanders-Van Halewijn E, Ouwehand I. The relationship between fat distribution and some chronic diseases in 11825 women participating in the DOM-Project. Int J Epidemiol 1990; 19: 564 570. 33. Hartz A, Rupley D, Rimm A. The association of girth measurements with disease in 32,856 women. Am J Epidemiol 1984; 119:71 80. 34. Colditz GA, Willett WC, Stampfer MJ, et al. Weight as a risk factor for clinical diabetes in women. Am J Epidemiol 1990; 132(3): 501 513. 35. Chan J, Rimm E, Colditz G, Stampfer M, Willett W. Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care 1994; 17: 961 966. 36. Knowler W, Pettitt D, Saad M, Charles M, Nelson R, Howard B. Obesity in the Pima Indians: its magnitude and relationship with diabetes. Am J Clin Nutr 1991; 53: 1543S 1551S. 37. Charles M, Fontbonne A, Thibult N, Warnet J-M, Rosselin G, Eschwege E. Risk factors for NIDDM in white population. Paris Prospective Study. Diabetes 1991; 40: 796 799.

362 INTERNATIONAL TEXTBOOK OF OBESITY 38. Modan M, Karasik A, Halkin H, et al. Effect of past and concurrent body mass index on prevalence of glucose intolerance and type 2 (non-insulin dependent) diabetes and on insulin response. The Israeli study of glucose intolerance, obesity and hypertension. Diabetologia 1986; 29: 82 89. 39. Zimmet P, Alberti K. Leptin: Is it important in diabetes? Diabet Med 1996; 13: 501 503. 40. Manson J, Spelsberg A. Primary prevention of non-insulindependent diabetes mellitus. Am J Prev Med 1994; 10: 172 184. 41. Sicree R, Zimmet P, King H, Coventry J. Weight change amongst Nauruans over 6.5 years extent, and association with glucose intolerance. Diabetes Res Clin Pract 1987; 3: 327 336. 42. Knowler W, Pettitt D, Savage P, Bennett P. Diabetes incidence in Pima Indians: contributions of obesity and parental diabetes. Am J Epidemiol 1981; 113: 144 156. 43. Ogilvie R. Sugar tolerance in obese subjects. A review of sixty-five cases. Q J Med 1935; Series 2, 4: 345 358. 44. Felber J, Golay A, Jéquier E, et al. The metabolic consequences of long-term human obesity. Int J Obes 1988; 12: 377 389. 45. Golay A, Munger R, Felber J-P. Obesity and NIDDM: the retrograde regulation concept. Diabetes Rev 1997; 5: 69 82. 46. Colditz G, Willett W, Rotnitzky A, Manson J. Weight gain as a risk factor for clinical diabetes mellitus in women. Ann Intern Med 1995; 122: 481 486. 47. Harris MI. Impaired glucose tolerance in the US population. Diabetes Care 1989; 12: 464 474. 48. DiPietro L, Mossberg H-O, Stunkard A. A 40-year history of overweight children in Stockholm: life-time overweight, morbidity, and mortality. Int J Obes 1994; 18: 585 590. 49. Ford E, Williamson D, Liu S. Weight change and diabetes incidence: Findings from a national cohort of US adults. Am J Epidemiol 1997; 146: 214 222. 50. Hansen B, Bodkin H. Heterogeneity of insulin responses: phases leading to Type 2 (non-insulin-dependent) diabetes mellitus in the rhesus monkey. Diabetologia 1986; 29: 713 719. 51. Dowse G, Zimmet P, Collins V. Insulin levels and the natural history of glucose intolerance in Nauruans. Diabetes 1996; 45: 1367 1372. 52. Kissebah A. Central obesity: measurement and metabolic effects. Diabetes Rev 1997; 5: 8 20. 53. Hartz A, Rupley D, Kalkhoff R, Rimm A. Relationship of obesity to diabetes: influence of obesity level and body fat distribution. Prev Med 1983; 12: 351 357. 54. Haffner S, Stern M, Hazuda H, Rosenthal M, Knapp J, Malina R. Role of obesity and fat distribution in noninsulin-dependent diabetes mellitus in Mexican Americans and Non-Hispanic whites. Diabetes Care 1986; 9: 153 561. 55. Dowling H, Pi-Sunyer F. Race-dependent health risks of upper body obesity. Diabetes 1993; 42: 537 543. 56. Fujimoto W, Leonetti D, Newell-Morris L, Shuman W, Wahl P. Relationship of absence or presence of a family history of diabetes to body weight and body fat distribution in type 2 diabetes. Int J Obes 1991; 15: 111 120. 57. Lemieux S, Després J-P, Nadeau A, Prud homme D, Tremblay A, Bouchard C. Heterogeneous glycaemic and insulinaemic responses to oral glucose in non-diabetic men: Interactions between duration of obesity, body fat distribution and family history of diabetes mellitus. Diabetologia 1992; 35: 653 659. 58. Kuzuya T, Matsuda A. Family history of diabetes among Japanese patients with type 1 (insulin-dependent) and type 2 (non-insulin-dependent) diabetes. Diabetologia 1982; 22: 372 374. 59. Lee E, Anderson P, Jr, Bryan J, Bahr C, Coniglione T, Cleves M. Diabetes, parental diabetes, and obesity in Oklahoma Indians. Diabetes Care 1985; 8: 107 113. 60. Hanson R, Pettit D, Bennett P, et al. Familial relationships between obesity and NIDDM. Diabetes 1995; 44: 418 422. 61. Boer J, Feskens E, Kromhout D. Characteristics of noninsulin-dependent diabetes mellitus in elderly men: Effect modification by family history. Int J Epidemiol 1996; 25: 394 302. 62. Stern M, Gaskill S, Hazuda H, Gardner L, Haffner S. Does obesity explain excess prevalence of diabetes among Mexican Americans? Results of the San Antonio Heart Study. Diabetologia 1983; 14: 272 277. 63. Mather H, Keen H. The Southall diabetes survey: prevalence of known diabetes in Asians and Europeans. BMJ 1985; 291: 1081 1084. 64. Simmons D, Williams DR, Powell MJ. Prevalence of diabetes in a predominantly Asian community: preliminary findings of the Coventry diabetes study. BMJ 1989; 298: 18 21. 65. Zimmet P, Taylor R, Ram P, et al. The prevalence of diabetes and impaired glucose tolerance in the biracial (Melanesian and Indian) population of Fiji: a rural urban comparison. Am J Epidemiol 1983; 118: 673 688. 66. Hodge AM, Dowse GK, Collins VR, et al. Abdominal fat distribution and insulin levels only partially explain adverse cardiovascular risk profile in Asian Indians. J Cardiovasc Risk 1996; 3: 263 270. 67. Rush E, Plank L, Laulu M, Robinson S. Prediction of percentage body fat from anthropometric measurements: comparison of New Zealand European and Polynesian young women. Am J Clin Nutr 1997; 66:2 7. 68. Swinburn B, Craig P, Daniel R, Dent D, Strauss B. Body composition differences between Polynesians and Caucasians assessed by bioelectrical impedance. Int J Obes 1996; 20: 889 894. 69. Deurenberg P, Keyou G, Hautvast J, Jingzhong W. Body mass index as predictor for body fat: comparison between Chinese and Dutch adult subjects. Asia Pacific J Clin Nutr 1997; 6: 102 105. 70. West K. Epidemiology of Diabetes and its Vascular Lesions. New York: Elsevier, 1978. 71. Marshall JA, Hoag S, Shetterly S, Hamman RF. Dietary fat predicts conversion from impaired glucose tolerance to NIDDM. Diabetes Care 1994; 17(1): 50 56. 72. Marshall JA, Hamman RF, Baxter H. High-fat, low-carbohydrate diet and the etiology of non-insulin-dependent diabetes mellitus: The San Luis Valley Diabetes Study. Am J Epidemiol 1991; 134: 590 603. 73. Tsunehara CH, Leonetti DL, Fujimoto WY. Diet of second-generation Japanese-American men with and without non-insulin-dependent diabetes. Am J Clin Nutr 1990; 52: 731 738. 74. Tsunehara CH, Leonetti DL, Fujimoto WY. Animal fat and cholesterol intake is high in men with IGT progressing