QJM Advance Access originally published online on September 6, 2008
QJM 2008 101(11):875-879; doi:10.1093/qjmed/hcn109
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Type 2 diabetes mellitus: a high-risk condition for cardiovascular disease irrespective of the different degrees of obesity
From the 1Diabetes Centre, Northern General Hospital and 2Diabetes Centre, Royal Hallamshire Hospital, Sheffield, UK
Address correspondence to Dr Soon H. Song, Diabetes Centre, Northern General Hospital, Herries Road, Sheffield S5 7AU, UK. email: soon_song{at}hotmail.com
Received 16 May 2008 and in revised form 14 August 2008
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Summary |
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Background: Measurement of body weight with body mass index (BMI) is often utilized to stratify cardiovascular disease (CVD) risk.
Aim: To determine CVD risk profile and disease burden in subjects with type 2 diabetes mellitus (T2DM) across different categories of body weight as defined by BMI.
Design: Prospective observational study.
Methods: CVD risk including metabolic syndrome (MetS) and prevalence of macrovascular complications were determined for each category of body weight as defined by the World Health Organisation (WHO) classification.
Results: A total of 390 subjects were included in this study of which 35.9% were non-obese (BMI <30 kg/m2). Although increasing obesity as defined by BMI was associated with higher prevalence of central abdominal obesity, hypertension and MetS (P < 0.05), dyslipidaemia and macrovascular complications were not significantly different across the various body weight categories (P = NS). Similar observation was seen in non-obese (BMI <30 kg/m2) and obese subjects (BMI >30 kg/m2). Among non-obese (including normal weight) cohort, the majority of these subjects had adverse CVD risk profile including presence of at least two co-existing risk factors.
Conclusions: Subjects with T2DM possess adverse CVD risk factors with significant burden of macrovascular disease irrespective of their baseline body weight.
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Introduction |
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Since obesity is a major and potentially modifiable cardiovascular disease (CVD) risk factor in type 2 diabetes (T2DM),1 emphasis has been focused on the interaction between obesity, CVD risk and development of macrovascular complications.2,3 Much less attention has been paid to the significance of CVD risk among non-obese T2DM subjects. Contrary to conventional belief, the relationship between these parameters is conflicting. Although some studies showed obese T2DM subjects possessed more adverse CVD risk than their non-obese counterparts,2,3 others have demonstrated that non-obese T2DM (including normal weight) subjects have similar CVD risk profiles and obesity was not associated with an increased prevalence of CVD.4,5 Since most of these studies utilized body mass index (BMI) as a measurement for obesity, this could partly account for the discrepant observation. It is known that central abdominal obesity as determined by waist circumference (WC) or waist–hip ratio is a better discriminator of CVD risk than BMI.6
To our knowledge, the relationship between CVD risk and macrovascular complications among non-obese (including normal weight) T2DM subjects has not been assessed in a UK population. This is an important issue in clinical practice as a substantial proportion (
10–20%) of T2DM subjects are non-obese2,3,7 and CVD risk management strategy using lifestyle intervention programmes in clinical service often focus on weight loss and therefore, exclude non-obese subjects. With this background, we performed this study to determine the interaction between different levels of BMI-defined body weight, CVD risk and macrovascular complications among T2DM subjects in a large teaching hospital.
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Methods |
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Subjects with T2DM who attended hospital clinics were included in this observational prospective study over a 1-year period. None of these patients were excluded to reflect the true clinical picture of the CVD risk profile in this patient cohort. For each subject, the following demographic data were collected as part of their routine clinical care: age, sex, ethnicity, diabetes duration, weight, BMI, WC, blood pressure, HDL cholesterol, triglyceride, total cholesterol, HbA1c and history of CVD complications defined by presence of ischaemic heart disease (IHD), stroke and peripheral vascular disease (PVD). The lipid profiles were analysed on a fasting sample. Hypertension, dyslipidaemia (reduced HDL and/or raised triglyceride) and central abdominal obesity were defined using the International Diabetes Federation (IDF) criteria for metabolic syndrome (MetS). Normal weight, overweight and obesity were defined using the World Health Organisation (WHO) classification, namely, BMI 18.5–24.9 (normal), 25–29.9 (overweight), 30–34.9 (obese class 1), 35–39.9 (obese class 2) and >40 (obese class 3) kg/m2. The IDF definition for MetS is detailed below:
IDF definition
The diagnostic criteria are central abdominal obesity, defined as WC >94 cm and >80 cm for Caucasian male and female, respectively, or >90 cm and >80 cm for Asian male and female, respectively; together with two of the following: raised triglycerides >1.7 mmol/l or specific treatment for this lipid abnormality; reduced HDL-cholesterol (<1.03 mmol/l in males and <1.29 mmol/l in females) or specific treatment for this lipid abnormality; blood pressure >130/85 mm Hg; and fasting hyperglycaemia, defined as glucose >5.6 mmol/l or previous diagnosis of diabetes or impaired glucose tolerance. T2DM subjects with at least one other risk factor after fulfilling the waist circumference threshold are deemed to have MetS.
All statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) for Windows (SAS Institute, Cary, NC, USA). Data are expressed as mean ± standard deviation (SD) or percentage as appropriate. 
2- and unpaired t-tests were used to compare variables between two groups. The analysis of variance (ANOVA) and 2-value for the trend were used to determine the significance of trends of continuous variables and frequency, respectively, across the different BMI categories. Logistic regression analysis was used to determine the significance of association between BMI and CVD complications. P-values < 0.05 were considered significant.
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Results |
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Baseline patient characteristics and prevalence of different body weight categories
Demographic and clinical characteristics of the study population in the various BMI categories are shown in Table 1. A total of 390 subjects were included in this study of which 39 (10%), 101 (25.9%), 113 (29.0%), 83 (21.3%) and 54 (13.8%) had BMI of 18.5–24.9, 25–29.9, 30–34.9, 35–39.9 and >40 kg/m2, respectively. Mean age (
60 years), glycaemic control (HbA1c 8.3%) and diabetes duration (10 years) were similar across the different BMI categories (P = NS).
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Association between BMI and CVD risk factors and disease burden
Prevalence of CVD risk factors and complications including its individual components in the various BMI categories is shown in Table 2. Increasing BMI was significantly associated with higher body weight, WC and systolic blood pressure (P < 0.05) but not with total cholesterol, HDL, triglyceride and diastolic blood pressure (P = NS). Although the proportion of subjects with hypertension, central abdominal obesity, MetS and presence of at least two co-existing CVD risk factors increased with BMI (P < 0.05), the prevalence of dyslipidaemia and CVD complications were not significantly different (P = NS). Pairwise comparisons on macrovascular disease and its individual components did not show any significant difference between each of the five BMI categories. Consistent with this observation, the logistic regression analysis showed BMI to be a poor predictor of CVD [odds ratio, OR = 1.02 (95% CI 0.98–1.05), P = NS].
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Another interesting observation pertains to individuals with normal weight (BMI 18.5–24.9 kg/m2). A significant proportion of these subjects had MetS (
70%), central abdominal obesity (80%), dyslipidaemia (60%) and hypertension (45%). Approximately 65% had at least two co-existing risk factors (hypertension, dyslipidaemia or central abdominal obesity). To determine the CVD risk profile of non-obese (BMI <30 kg/m2) and obese (BMI >30 kg/m2) subjects, the prevalence of CVD complications including its individual components and risk factors was assessed in these two groups as shown in Table 3. There were no significant differences in the prevalence of dyslipidaemia and cardiovascular complications between non-obese and obese subjects. Although hypertension, central obesity, MetS and proportion of those with at least two co-existing risk factors were more prevalent in the obese subjects, majority of the non-obese subjects possessed adverse CVD risk factors.
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Discussion |
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This study demonstrated that T2DM is a high-risk condition for CVD irrespective of the different degrees of BMI-defined body weight including normal weight. Although increasing obesity was associated with higher prevalence of CVD risk factors, this relationship was not observed for macrovascular disease. Another important clinical observation was majority of the so-called ‘normal weight’ individuals possessed adverse CVD risk factors including central abdominal obesity albeit at a lower frequency compared to overweight and obese subjects.
Very few studies have focused on the CVD risk profile and outcome in non-obese T2DM subjects. There is evidence suggesting that these individuals are at risk of macrovascular complications exemplified by similar incidence of CVD and mortality in both non-obese and obese subjects.8,9 Although obesity is considered a risk factor for CVD and T2DM, it appears that once diabetes develops other factors may become more important in the development of CVD. This argument is supported by the findings of United Kingdom Prospective Diabetes Study (UKPDS) where obesity was not considered a significant factor in the development of CVD in T2DM.10
The discordant relationship between obesity and CVD raises the question on how obesity should be defined in T2DM. In our study, T2DM subjects classified as being normal weight by virtue of the BMI values have high prevalence of central abdominal obesity and other CVD risk factors. Our clinical observation emphasizes the importance of the concept ‘metabolically obese normal weight’ in T2DM in which, individuals who despite having normal body weight BMI demonstrated metabolic disturbances typical of obese individuals11 and highlights the failure of BMI obesity measurement to reliably detect the extent of central abdominal obesity, a risk factor intimately linked with clustering of metabolic disturbances and CVD.6,12 Our observation of the high degree of central abdominal obesity across the different body weight categories may also provide the explanation for the lack of relationship between BMI-defined obesity and macrovascular disease in T2DM observed in other studies.5,8,13
As more data emerge, it has become increasing clear that T2DM is the same disease in non-obese and obese subjects in reference to insulin resistance and CVD risk. The long-held clinical view that obese subjects have greater insulin resistance was accentuated by UKPDS findings of the effectiveness of metformin not only in improving glycaemic control but also in reducing CVD events in obese T2DM subjects mediated perhaps through its insulin-sensitising properties.14 However, this view has been challenged by recent studies demonstrating equivalence in glycaemic response and CVD outcome in metformin-treated non-obese and obese T2DM subjects.9,15 Since the hypoglycaemic effect of metformin occurs by counteracting the elevated basal hepatic glucose production, one of the physiological consequences of insulin resistance, it can be implied from the findings of these studies that insulin resistance also plays an important role in non-obese subjects. This concept is supported by a recent study that showed central abdominal adiposity as quantified by CT scan was increased and significantly correlated with HOMA-IR, an index of insulin resistance, in non-obese T2DM.16 Interestingly, similar proportion of non-obese and obese subjects in our study had atherogenic dyslipidaemic profile, a metabolic manifestation of insulin resistance.
The primary therapeutic strategy of current obesity reduction guidelines is achieving weight loss through diet- and/or exercise-based interventions.17 However, the assumption that weight loss is the primary antecedent to lifestyle-induced benefits precludes the possibility that exercise could induce a reduction in central abdominal obesity, a strong predictor of CVD morbidity and mortality, without a corresponding reduction in body weight (i.e. BMI). In our clinical experience, most non-obese (including normal weight) T2DM subjects are not offered lifestyle intervention. Recent evidence has suggested that moderate-intensity aerobic exercise without weight loss can lead to significant preferential reduction in central abdominal obesity and improvement in cardio-respiratory fitness in T2DM.18,19 Combined with the observation that this exercise regime is associated with increased insulin sensitivity,20,21 an alternative lifestyle intervention strategy to reduce central abdominal obesity and its associated health risk should be considered for non-obese (including normal weight) T2DM subjects.
There are limitations to our study. Firstly, there is no data on the cumulative incidence of CVD events in the different BMI categories and the impact of the different degrees of obesity on subsequent CVD events could not be determined. Secondly, our study population is not large particularly for normal weight subjects. However, the proportion of this patient cohort and the observed CVD risk profile across the different body weight categories in our study population is in agreement with the findings of other studies with much larger population and therefore, is likely to be reflective of the underlying CVD risk of T2DM subjects as a whole. Thirdly, as this is a hospital clinic rather than population based, it is plausible that higher-risk subjects are preferentially referred to hospital clinics.
To conclude, our study on subjects routinely seen in general diabetes clinics hopes to raise awareness among clinicians that non-obese (including normal weight) T2DM subjects are not without the detrimental risk for macrovascular disease. It challenges the widely held perception that body weight in the so-called acceptable range indicates benign CVD risk profile. More importantly, the focus and outcome objective of lifestyle intervention currently offered in clinical practice has to be critically reviewed and hopefully stimulate more research in this clinically challenging area.
Conflict of interest: None declared.
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References |
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|---|
1. The Look AHEAD Research Group. Reduction in weight and cardiovascular disease risk factors in individuals with type 2 diabetes; one-year results of the Look AHEAD trial. Diabetes Care (2007) 30:1374–83.
2. Ridderstrale M, Gudbjorndottir S, Eliason B, Nilsson PM, Cederholm J. Obesity and cardiovascular risk factors in type 2 diabetes: results from the Swedish National Diabetes Register. J Intern Med (2006) 259:314–22.[CrossRef][Web of Science][Medline]
3. Daousi C, Casson IF, Gill GV, MacFarlane IA, Wilding JPH, Pinkney JH. Prevalence of obesity in type 2 diabetes in secondary care: association with cardiovascular risk factors. Postgrad Med J (2006) 82:280–4.
4. Ezenwaka CE, Offiah NV. Cardiovascular risk in obese and nonobese patients with type 2 diabetes in the West Indies. J Biomed Sci (2001) 8:314–20.[CrossRef][Web of Science][Medline]
5. Bo S, Gentile L, Cavallo-Perin P, Vineis P, Ghia V. Sex and BMI-related differences in risk factors for coronary artery disease in patients with type 2 diabetes mellitus. Acta Diabetol (1999) 36:147–53.[CrossRef][Web of Science][Medline]
6. Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, et al. Obesity and risk of myocardial infarction in 27,000 participants from 52 countries. A case control study. Lancet (2005) 366:1640–9.[CrossRef][Web of Science][Medline]
7. Saydah SH, Fradkin J, Cowle CC. Poor control of risk factors for vascular disease among adults with previously diagnosed diabetes. JAMA (2004) 291:335–42.
8. Klein R, Klein BEK, Moss SE. Is obesity related to microvascular and macrovascular complications in diabetes? The Wisconsin Epidemiological Study of Diabetic Retinopathy. Arch Intern Med (1997) 157:650–6.
9. Ong CR, Molyneaux LM, Constantino MI, Twigg SM, Yue DK. Long-term efficacy of metformin therapy in nonobese individuals with type 2 diabetes. Diabetes Care (2006) 29:2361–4.
10. Turner RC, Millns H, Holman RR. Coronary heart disease and risk factors in NIDDM – experience from the United Kingdom Prospective Diabetes Study. Diabetologia (1997) 40:S121–2.[CrossRef][Web of Science][Medline]
11. Ruderman NB, Chisholm D, Pi-Sunyer X, Schneider S. The metabolically obese, normal-weight individual revisited. Diabetes (1998) 47:699–713.[Abstract]
12. Despres JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature (2006) 444:881–7.[CrossRef][Web of Science][Medline]
13. Nelson RG, Sievers ML, Knowler WC, Swinburn BA, Pettitt DJ, Saad MF, et al. Low incidence of fatal coronary heart disease in Pima Indians despite high prevalence of non-insulin-dependent diabetes mellitus. Circulation (1990) 81:987–95.
14. UK Prospective Diabetes Study (UKPDS) Group. Effect of intensive blood glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). Lancet (1998) 352:854–65.[CrossRef][Web of Science][Medline]
15. Donnelly LA, Doney ASF, Hattersley AT, Morris AD, Pearson ER. The effect of obesity on glycaemic response to metformin or sulphonylurea in type 2 diabetes. Diabet Med (2006) 23:128–33.[CrossRef][Web of Science][Medline]
16. Basat O, Ucak S, Ozkurt H, Basak M, Seber S, Altuntas Y. Visceral adipose tissue as an indicator of insulin resistance in nonobese patients with new onset type 2 diabetes mellitus. Exp Clin Endocrinol Diabetes (2006) 114:58–62.[CrossRef][Web of Science][Medline]
17. National Institute for Clinical Excellence. Obesity: Guidance on the Prevention, Identification, Assessment and Management of Overweight and Obesity in Adults and Children. (2006) London: National Institute for Clinical Excellence.
18. Lee S, Kuk JL, Davidson LE, Hudson R, Kilpatrick K, Graham TE, et al. Exercise without weight loss is an effective strategy for obesity reduction in obese individuals with and without type 2 diabetes. J Appl Physiol (2005) 99:1220–5.
19. Janiszewski PM, Ross R. Physical activity in the treatment of obesity: beyond body weight reduction. Appl Physiol Nutr Metab (2007) 32:512–22.[CrossRef][Web of Science][Medline]
20. Boule NG, Weisnagel SJ, Lakka TA, Tremblay A, Bergman RN, Rankinen T, et al. Effects of exercise training on glucose homeostasis: the HERITAGE Family Study. Diabetes Care (2005) 28:108–14.
21. Duncan GE, Perri MG, Theriaque DW, Hutson AD, Eckel RH, Stacpoole PW. Exercise training, without weight loss, increases insulin sensitivity and postheparin plasma lipase activity in previously sedentary adults. Diabetes Care (2003) 26:557–62.
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