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Body mass index, waist circumference, waist–hip ratio, waist–height ratio and risk for type 2 diabetes in women: A case–control study
p u b l i c h e a l t h 1 2 7 ( 2 0 1 3 ) 2 4 1 e2 4 6
Available online at www.sciencedirect.com
Public Health journal homepage: www.elsevier.com/puhe
Original Research
Body mass index, waist circumference, waistehip ratio, waisteheight ratio and risk for type 2 diabetes in women: A caseecontrol study L. Radzeviciene_ *, R. Ostrauskas Institute of Endocrinology, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, 50009 Kaunas, Lithuania
article info
summary
Article history:
Objective: To assess the relationship between various anthropometric indexes and risk for
Received 27 September 2011
type 2 diabetes in women.
Received in revised form
Study design and methods: A caseecontrol study of 168 cases with newly diagnosed type 2
6 July 2012
diabetes and 336 controls who were free of the disease. Cases and controls (ratio 1:2) were
Accepted 3 December 2012
matched by age (5 years). A questionnaire was used to collect information on possible risk
Available online 2 January 2013
factors for type 2 diabetes. Odds ratios (OR) and 95% confidence intervals (CI) for type 2 diabetes were calculated by conditional logistic regression.
Keywords:
Results: After adjustment for possible confounders, increased risk for type 2 diabetes was
Anthropometric indexes
associated with body mass index (BMI) 30 kg/m2(OR 4.68, 95% CI 2.09e10.49), waist
General obesity
circumference (WC) >88 cm (OR 6.99, 95% CI 1.60e30.42)and waisteheight ratio (WHtR)
Central obesity
0.5 (OR 3.15, 95% CI 1.91e15.81).
Type 2 diabetes
Conclusions: Both general and central obesity are associated with type 2 diabetes. The
Caseecontrol study
results suggest that high BMI, WC and WHtR are significant risk factors for type 2 diabetes in women. Crown Copyright ª 2012 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. All rights reserved.
Introduction Diabetes is a major public health issue. In 2011, the estimated prevalence of diabetes was 366 million, representing 8.5% of the world’s adult population, and it has been predicted that the number of people with diabetes will have risen to 552 million by 2030.1 Type 2 diabetes is far more common than type 1 diabetes, and accounts for 85e95% of all people with diabetes.2 Lithuania, located on the south-east coast of the Baltic Sea, has an area of 65,200 km2 and an estimated population (2011) of 3,349,872.3 In Lithuania, the prevalence of type 2 diabetes
among adults aged 35e64 years increased from 2.30% in 19874 to 5.00% in 2004.5 The number of individuals with type 2 diabetes is increasing rapidly in both developed and developing countries worldwide. The combined effects of population ageing, urbanization, rising levels of obesity and physical inactivity are driving the emerging pandemic of type 2 diabetes.6 Excess body weight is the sixth most important risk factor contributing to the overall burden of disease worldwide. More than 1 billion adults and 10% of children are now classified as overweight or obese.7
* Corresponding author. Tel.: þ370 37 403962; fax: þ370 37 452075. iene). _ E-mail address: [email protected] (L. Radzevic 0033-3506/$ e see front matter Crown Copyright ª 2012 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. All rights reserved. http://dx.doi.org/10.1016/j.puhe.2012.12.001
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The prevalence of obesity has tripled in the last two decades and has now reached epidemic proportions.8 In European countries, the prevalence of overweight ranges between 28% and 78% in women.8 A random selected cohort study in Lithuania found that 33.7% of women aged 20e70 years were overweight and 14.2% were obese.9 Overweight and obesity are related to approximately 80% of cases of type 2 diabetes, 35% of cases of ischaemic heart disease and 55% of cases of hypertensive disease, and cause more than 1 million deaths and 12 million life-years of ill health each year among adults in the World Health Organization (WHO) European region.8 Type 2 diabetes appears to involve interplay between susceptible genetic backgrounds and environmental factors, including highly calorific westernized diets.10 Obesity provoke the epidemic of type 2 diabetes mellitus in developed and developing countries.6,11 Body mass index (BMI) is a common measure for general obesity, and is described as an independent predictor of type 2 diabetes in both genders.12 Waist circumference (WC), waistehip ratio (WHR) and waisteheight ratio (WHtR) are used as measures of central obesity, and also provide information on risk for type 2 diabetes.13e15 However, it is not known which anthropometric index is most suitable for assessment of the risk for type 2 diabetes in women. Therefore, the aim of this study was to assess the relationship between anthropometric indexes and risk for type 2 diabetes in women.
Subjects and methods A caseecontrol study was undertaken at an outpatient clinic in Kaunas, Lithuania. The study included 168 cases aged 34e85 years with newly diagnosed type 2 diabetes, according to WHO criteria,16 between 1 January 2001 and 31 December 2001. Three hundred and thirty-six controls, without impaired fasting glucose levels or type 2 diabetes, were individually matched to the diabetic patients by 5-year age group. The ratio of cases to controls was 1:2. Information on age, gender, family history of diabetes, education, occupational and marital status, nutrition habits, alcohol consumption, cigarette smoking, physical activity and stress level was assessed using a questionnaire designed by the research group. All subjects were invited to self-complete the questionnaire. If they were unable to do so (bad general condition, poor eyesight, pathology of upper extremities or personal wish for assistance to complete the questionnaire), they were interviewed by a trained interviewer. Interviewers were not aware of the study hypothesis. Participants were asked to fast for 12 h and to avoid smoking and heavy physical activity for at least 2 h before the examination. In accordance with WHO guidelines,17 a single investigator took all the anthropometric measurements. Height and weight were measured twice. Height without shoes was measured in centimetres (accuracy 0.1 cm). Weight in light clothing was measured in kilograms (0.5 kg accuracy). BMI was calculated as weight (kg)/height (m)2,18 WC was measured by holding a non-stretchable tape measure snugly around the waist, defined as the midpoint between the bottom rib and tip of the hipbones, and hip circumference was
measured at the level of the great femur trochanter in centimetres (0.1 cm accuracy). WHR was defined as WC (cm) divided by hip circumference (cm), and WHtR was defined as WC (cm) divided by height (cm).19,20 >Blood pressure was measured twice in the right arm with the subject in a sitting position. A mercurial sphygmomanometer was used with 2.0 mm mercurial column accuracy. Blood pressure was classified as normal or hypertensive (systolic blood pressure 140 mmHg and/or diastolic blood pressure 90 mmHg and/or receiving current medication for hypertension). Laboratory blood tests included fasting blood samples drawn from the subject’s elbow vein and venous plasma samples analysed for glucose and triglyceride (TG) levels. Venous plasma glucose was estimated by the Glucose oxidase phenol 4-aminoantipyrine (GOD-PAP) method (Eppendorf analyser, Hamburg, Germany). According to the 1999 WHO recommendations,19 75 g oral glucose tolerance tests were performed to assess carbohydrate disorders. TG was estimated by the Glycerol-3-phosphate oxidase phenolþaminophenazone (GPO-PAP) method (Randox analyser, London, United Kingdom). BMI was categorized as 18.5e24.9 kg/m2, 25e29.9 kg/m2 or 30 kg/m2 21; WC was categorized as<80 cm, 80e88 cm or >88 cm22; WHR was categorized as 0.85 or >0.85; and WHtR was categorized as <0.5 or 0.5. Family history of diabetes was categorized as first-degree relatives with history of diabetes or first-degree relatives without history of diabetes. Education was categorized as 10 years, 11e13 years or14 years. Marital status was categorized as married/living together, divorced/separated, single and widowed. Dietary habits were assessed according to eating speed (slower, the same or faster compared with others); food portion (smaller, the same or larger compared with others), and enjoyment of salty and fatty food (like very much, like or do not like). Morning exercise for at least 30 min during the last 12 months was categorized as no, sometimes or yes. Arterial hypertension was categorized as yes or no, and finally, plasma TG was categorized as <1.7 mmol/l or 1.7 mmol/l. A conditional logistic regression was used to calculate odds ratios (OR) and corresponding 95% confidence intervals (CI) for diabetes in relation to the exposures of interest. Variables were retained in models as confounders when their inclusion changed the value of the OR by more than 10% in any exposure category. All reported trend test significance levels (P-values) were two-sided.23 Chi-squared test was used to calculate the difference between proportions. The level of significance was set at 5%. All calculations were performed using STATA Version 7 (StataCorp LP, Texas, USA).
Results Table 1 shows the characteristics of the cases and controls. The cases had significantly lower levels of education and higher BMIs compared with controls. More controls reported no family history of diabetes compared with cases. General obesity was assessed using BMI, and central obesity was assessed using WC and WHR. Univariate regression showed that overweight and obesity were associated
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Table 1 e Characteristics of cases and controls. Variable
Age (years)
Education (years) Marital status
First-degree relatives with history of diabetes
Category
44 45e54 55e64 65 10 11e13 14 Married Divorced /separated Single Widowed No Yes
Cases
Controls
n
%
n
%
7 16 66 79 90 46 32 84 15
4.17 9.52 39.29 47.02 53.57 27.38 19.05 50.00 8.93
14 32 130 160 120 142 74 177 37
4.17 9.52 38.69 47.62 35.71 42.26 22.02 52.68 11.01
9 60 118 50
5.36 35.71 70.24 29.76
24 98 297 39
7.14 29.17 88.39 11.61
P-value for c2 Matched
<0.0001
NS
<0.0001
NS, not significant.
with higher risk for type 2 diabetes. Women with BMI of 25e29.99 kg/m2 had more than two-fold higher risk for type 2 diabetes (crude OR 2.32, 95% CI 1.14e4.87), and women with BMI 30 kg/m2 had about six times higher risk (crude OR 5.17, 95% CI 3.03e11.75) compared with those with BMI <25 kg/m2. A doseeresponse relationship was found between risk for diabetes and BMI, with P for trend <0.0001. Variables such as family history of diabetes, hypertension, plasma TG level and WHR were retained in the multivariate logistic regression model as confounders because their inclusion changed the OR value by more than 10% in any exposure category. Table 2
shows the results of the multivariate logistic regression of the relationship between type 2 diabetes and obesity. After adjustment for family history of diabetes, arterial hypertension and plasma TG level, the relationship between type 2 diabetes and BMI changed slightly but remained significant. After further adjustment for WHR, the risk for type 2 diabetes for women with BMI 30 kg/m2 (OR 4.68, 95% CI 2.09e10.49) was found to be four times higher compared with the risk for women with BMI <25 kg/m2. The relationship between type 2 diabetes and BMI 25e29.99 kg/m2 became non-significant. A significant doseeresponse relationship was found between BMI and the risk for type 2 diabetes ( p for trend <0.0001). WC, WHR and WHtR were also associated with the risk for type 2 diabetes. Univariate regression showed that women with WC > 88 cm had approximately four times higher risk for type 2 diabetes (crude OR 3.95, 95% CI 2.70e19.19). After adjustment for eating speed, enjoyment of salty and fatty food and morning exercise, the association between WC and risk for type 2 diabetes changed but remained significant. After controlling for eating speed, enjoyment of salty and fatty food, morning exercise, arterial hypertension, plasma TG level, education level and BMI, women with WC > 88 cm had about seven times higher risk for type 2 diabetes compared with women with WC < 80 cm (Table 2). Univariate regression showed that women with WHR >0.85 were at higher risk for type 2 diabetes (crude OR 2.68, 95% CI 1.17e2.79; P ¼ 0.007). After adjustment for hypertension, the relationship between WHR and type 2 diabetes became nonsignificant (Table 2). Univariate regression showed that women with WHtR 0.5 were at increased risk for type 2 diabetes (crude OR 3.81, 95% CI 2.67e21.26; P < 0.0001). After adjustment for family history of diabetes and education level, the relationship between WHtR and type 2 diabetes changed but remained significant.
Table 2 e Odds ratios (OR) and 95% confidence intervals (CI) for diabetes in relation to obesity in women. Variable
Category
2
Cases
Controls
n
%
n
%
Body mass index (kg/m )
<25 25e29.9 30
12 40 116
7.14 23.81 69.05
84 116 136
25.00 34.52 40.48
Waist circumference (cm)
<80 80e88 >88
5 10 153
2.98 5.95 91.07
49 69 218
14.58 20.54 64.88
Waistehip ratio
0.85 >0.85
36 132
21.43 78.57
110 226
32.74 67.26
Waisteheight ratio
<0.5 0.5
5 163
2.98 97.02
55 281
16.37 83.63
ORa(95% CI) P
ORb(95% CI) P
1.00 2.41 (1.16e5.03) 5.40 (2.73e10.67) P < 0.0001 1.00 1.23 (0.37e4.13) 6.48 (2.32e18.04) P < 0.0001 1.00 1.46 (0.93e2.29) P ¼ 0.104 1.00 3.44 (2.21e17.94) P ¼ 0.001
1.00 2.25 (0.99e5.14) 4.68 (2.09e10.49) P < 0.0001 1.00 1.57 (0.40e6.15) 6.99 (1.60e30.42) P ¼ 0.01
1.00 3.15 (1.91e15.81) P ¼ 0.002
Body mass index: ORa Adjusted for family history of diabetes, hypertension and plasma triglyceride level; ORb Adjusted for family history of diabetes, hypertension, plasma triglyceride level and waistehip ratio. Waistehip ratio: ORa adjusted for hypertension. Waist circumference: ORa adjusted for eating speed, enjoyment of salty and fatty food and morning exercise; ORb adjusted for eating speed, enjoyment of salty and fatty food, morning exercise, hypertension, plasma triglyceride level, education level and body mass index. Waisteheight ratio: ORa adjusted for family history of diabetes and education level; ORb adjusted for family history of diabetes, education level and morning exercise.
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After adjustment for family history of diabetes, education level and morning exercise, women with WHtR 0.5 had three times higher risk for type 2 diabetes compared with women with WHtR <0.5 (Table 2).
Discussion This study showed that both general and central obesity are associated with type 2 diabetes. Similar results have been obtained in numerous previous studies reporting the effects of anthropometric variables on risk for type 2 diabetes. However, most of these studies employed a prospective design,24 rather than the caseecontrol design employed in this study. Overweight and obesity represent a significant public health problem because of the link with numerous chronic health conditions.25 Over the last two decades, Lithuania has enjoyed an impressive change from a soviet economy to a market economy, and citizens have experienced many remarkable lifestyle changes. These changes are often associated with westernization of nutrition and increased obesity and chronic diseases. A survey of factual nutrition conducted by the National Nutrition Centre showed that most overweight and obese Lithuanian inhabitants were aged 50e64 years. Among females, 39.7% were overweight and 27.9% were obese.26 The present study found increased risk for type 2 diabetes related to both general and central obesity. Women with BMI 30 kg/m2 had 4.7 times higher risk for type 2 diabetes compared with women with BMI <25 kg/m2. Excess body weight, overweight and obesity are the result of an imbalance between energy intake and energy expenditure.27 A study of indigenous Canadians documented BMI as the strongest determinant of diabetes.28 BMI is an excellent predictor of the risk for type 2 diabetes in Pima Indians, and is not significantly improved by adding other measures of general adiposity or body fat distribution.29 The prospective Hoorn Study illustrated that WHR was a better predictor of diabetes than BMI.13 Use of the sagittal abdominal diameter has no advantages over simpler and more commonly used anthropometric measures such as WC in older men and women.30 Thigh circumference in women and hip circumference in both sexes were negatively associated with markers of glucose metabolism, independently of WC, BMI and age.31 Wang et al. observed that WHR was the best predictor for type 2 diabetes in Australian Aboriginal people and Torres Strait Islanders.32 Chan et al. reported that WC was a better indicator of the relationship between central adiposity and the risk for type 2 diabetes than WHR in males. This study also showed that BMI was the dominant risk factor for type 2 diabetes in males.33 In the San Antonio Heart Study, WC was a better independent predictor of type 2 diabetes than BMI, WHR and other measurements in Mexican Americans aged 25e64 years.34 Janssen et al., in an analysis of data from the third National Health and Nutrition Examination Survey, found that WC, but not BMI, better explained obesity-related health risks.35 Lorenzo et al. reported that WHtR is a better indicator than WC and BMI in women.36 Body fat distribution, especially intra-abdominal adipose tissue accumulation, is a key correlate of a cluster of diabetogenic, atherogenic, prothrombotic and inflammatory
metabolic abnormalities increasing the risk for type 2 diabetes and cardiovascular disease.14 Abdominal obesity is associated with an increased risk for coronary heart disease and type 2 diabetes independently of overall adiposity.37 The mechanisms leading from obesity to type 2 diabetes are complicated and not fully elucidated. It seems that free fatty acids and adipokines produced by the abdominal adipose tissue decrease insulin sensitivity and increase insulin demands.38 The classical perception of adipose tissue as a storage place of fatty acids has been replaced by the notion that adipose tissue has a central role in lipid and glucose metabolism, and produces a large number of hormones and cytokines (e.g. tumour necrosis factor-alpha, interleukin-6, adiponectin, leptin and plasminogen activator inhibitor-1).39 Therefore, the increased prevalence of excessive visceral obesity and obesity-related cardiovascular risk factors is closely associated with the rising incidence of type 2 diabetes.39 Genes concerned with carbohydrate, lipid and amino acid metabolic pathways, neuronal function and inflammation play a significant role in the pathobiology of obesity and type 2 diabetes.40 Increased oxidative stress together with decreased antioxidative defence seem to contribute to decreased insulin sensitivity and impaired insulin secretion response in obese diabetics, and may be hypothesized to favour the development of diabetes in obese individuals.41 Central (visceral) obesity is more closely associated with insulin resistance, type 2 diabetes and cardiovascular disease than peripheral (subcutaneous) obesity. However, the underlying differences in morphology and pathophysiology between subcutaneous and visceral adipose are largely unknown.42 Visceral fat is more metabolically active than subcutaneous fat, and therefore more deleterious to health.43 Accumulation of intra-abdominal fat correlates with insulin resistance, whereas subcutaneous fat deposition correlates with circulating leptin levels.39 Consequently, WC has several advantages as a risk marker for diabetes prevention in health promotion activities.44 The above-mentioned data suggest that visceral fat is the risk for type 2 diabetes. However, general obesity may not be a separate risk factor for diabetes, because it is debated that an increased hip circumference reduces the risk for diabetes.45 The close relationship between an increased quantity of visceral fat, metabolic disturbances, including low-grade inflammation, cardiovascular diseases and the unique anatomical relationship with the hepatic portal circulation has led to an intense endeavour to unravel the specific endocrine functions of this visceral fat depot.39
What this study adds To the authors’ knowledge, this study differs from other case reports by case selection. All cases were individuals with newonset type 2 diabetes at a urban outpatient clinic over 1 year. The anthropometric parameters of the patients were not influenced by special diets and treatment. In most other cohort studies, the cases were selected at random and not related by time of onset. Controls in the present study were selected at random as in another caseecontrol studies. Furthermore, the information reported in this study may serve as evidence for the prevention and early development of type 2 diabetes among females who are visiting outpatient clinics.
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Limitations of this study The present study has some limitations that need to be acknowledged. Firstly, data were not collected about the duration of overweight. It was considered that the presence of overweight and the region of fat distribution were more important than the duration of enlarged body mass. Also, the data were not corrected for age because there was no age difference between the case and control groups. However, the degree of overweight and obesity may increase with age, and age may be considered a predominant risk factor for diabetes. Finally, the relevance and precision of data on physical activity in the questionnaire could be insufficient, because diabetes manifestation is strongly related to physical activity.46
Conclusions In this study, the relationship between WHR and risk for type 2 diabetes in women was not statistically significant. However, women with WC > 88 cm had approximately seven times higher risk for type 2 diabetes compared with those with WC < 80 cm. Women with WHtR 0.5 had three times higher risk for type 2 diabetes compared with those with WHtR <0.5 cm. The data suggest that high BMI, WC and WHtR may be considered as significant risk factors for type 2 diabetes in women. Furthermore, the data suggest that it is not necessary to exclude general obesity from the risk factors because it is usually accompanied by increased visceral fat. Overweight and large WC increases the risk for type 2 diabetes, and decreasing body fat deposits may reduce the risk for type 2 diabetes.
Acknowledgements Ethical approval Bioethics Committee of Kaunas University of Medicine.
Funding None declared.
Competing interests None declared.
references
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23. Woodward M. Epidemiology: study design and data analysis. 2nd ed. Boca Raton, FL: Chapman and Hall/CRC Press; 2005. 24. Ross R, Berentzen T, Bradshaw AJ, Janssen I, Kahn HS, Katzmarzyk PT, et al. Does the relationship between waist circumference, morbidity and mortality depend on measurement protocol for waist circumference? Obes Rev 2008;9:312e25. 25. Shepherd A. Obesity: prevalence, causes and clinical consequences. Nurs Stand 2009;23:51e8. 26. Brimas G. Surgical treatment of obesity. Vilnius: Ciklonas; 2005 [in Lithuanian]. 27. Jakicic JM, Otto AD. Physical activity considerations for the treatment and prevention of obesity. Am J Clin Nutr 2005;82(Suppl. 1):226Se9. 28. Young TK, Harris SB. Risk of clinical diabetes in a northern Native Canadian cohort. Arctic Med Res 1994;53:64e70. 29. Tulloch-Reid MK, Williams DE, Looker HC, Hanson RL, Knowler WC. Do measures of body fat distribution provide information on the risk of type 2 diabetes in addition to measures of general obesity? Comparison of anthropometric predictors of type 2 diabetes in Pima Indians. Diabetes Care 2003;26:2556e61. 30. Mukuddem-Petersen J, Snijder MB, van Dam RM, Dekker JM, Bouter LM, Stehouwer CD, et al. Sagittal abdominal diameter: no advantage compared with other anthropometric measures as a correlate of components of the metabolic syndrome in elderly from the Hoorn study. Am J Clin Nutr 2006;84:995e1002. 31. Snijder MB, Dekker JM, Visser M, Yudkin JS, Stehouwer CD, Bouter LM, et al. Larger thigh and hip circumferences are associated with better glucose tolerance: the Hoorn study. Obes Res 2003;11:104e11. 32. Wang Z, Rowley K, Wang Z, Piers L, O’Dea K. Anthropometric indices and their relationship with diabetes, hypertension and dyslipidemia in Australian aboriginal people and torres strait islanders. Eur J Cardiovasc Prev Rehabil 2007;14:172e8. 33. Chan JM, Rimm EB, Colditz GA, Stampfer MJ, Willett WC. Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men. Diabetes Care 1994;17:961e9. 34. Wei M, Gaskill SP, Haffner SM, Stern MP. Waist circumference as the best predictor of noninsulin dependent diabetes mellitus (NIDDM) compared to body mass index, waist/hip ratio and other anthropometric measurements in Mexican
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Available online at www.sciencedirect.com
Public Health journal homepage: www.elsevier.com/puhe
Original Research
Body mass index, waist circumference, waistehip ratio, waisteheight ratio and risk for type 2 diabetes in women: A caseecontrol study L. Radzeviciene_ *, R. Ostrauskas Institute of Endocrinology, Medical Academy, Lithuanian University of Health Sciences, Eiveniu 2, 50009 Kaunas, Lithuania
article info
summary
Article history:
Objective: To assess the relationship between various anthropometric indexes and risk for
Received 27 September 2011
type 2 diabetes in women.
Received in revised form
Study design and methods: A caseecontrol study of 168 cases with newly diagnosed type 2
6 July 2012
diabetes and 336 controls who were free of the disease. Cases and controls (ratio 1:2) were
Accepted 3 December 2012
matched by age (5 years). A questionnaire was used to collect information on possible risk
Available online 2 January 2013
factors for type 2 diabetes. Odds ratios (OR) and 95% confidence intervals (CI) for type 2 diabetes were calculated by conditional logistic regression.
Keywords:
Results: After adjustment for possible confounders, increased risk for type 2 diabetes was
Anthropometric indexes
associated with body mass index (BMI) 30 kg/m2(OR 4.68, 95% CI 2.09e10.49), waist
General obesity
circumference (WC) >88 cm (OR 6.99, 95% CI 1.60e30.42)and waisteheight ratio (WHtR)
Central obesity
0.5 (OR 3.15, 95% CI 1.91e15.81).
Type 2 diabetes
Conclusions: Both general and central obesity are associated with type 2 diabetes. The
Caseecontrol study
results suggest that high BMI, WC and WHtR are significant risk factors for type 2 diabetes in women. Crown Copyright ª 2012 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. All rights reserved.
Introduction Diabetes is a major public health issue. In 2011, the estimated prevalence of diabetes was 366 million, representing 8.5% of the world’s adult population, and it has been predicted that the number of people with diabetes will have risen to 552 million by 2030.1 Type 2 diabetes is far more common than type 1 diabetes, and accounts for 85e95% of all people with diabetes.2 Lithuania, located on the south-east coast of the Baltic Sea, has an area of 65,200 km2 and an estimated population (2011) of 3,349,872.3 In Lithuania, the prevalence of type 2 diabetes
among adults aged 35e64 years increased from 2.30% in 19874 to 5.00% in 2004.5 The number of individuals with type 2 diabetes is increasing rapidly in both developed and developing countries worldwide. The combined effects of population ageing, urbanization, rising levels of obesity and physical inactivity are driving the emerging pandemic of type 2 diabetes.6 Excess body weight is the sixth most important risk factor contributing to the overall burden of disease worldwide. More than 1 billion adults and 10% of children are now classified as overweight or obese.7
* Corresponding author. Tel.: þ370 37 403962; fax: þ370 37 452075. iene). _ E-mail address: [email protected] (L. Radzevic 0033-3506/$ e see front matter Crown Copyright ª 2012 Published by Elsevier Ltd on behalf of The Royal Society for Public Health. All rights reserved. http://dx.doi.org/10.1016/j.puhe.2012.12.001
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The prevalence of obesity has tripled in the last two decades and has now reached epidemic proportions.8 In European countries, the prevalence of overweight ranges between 28% and 78% in women.8 A random selected cohort study in Lithuania found that 33.7% of women aged 20e70 years were overweight and 14.2% were obese.9 Overweight and obesity are related to approximately 80% of cases of type 2 diabetes, 35% of cases of ischaemic heart disease and 55% of cases of hypertensive disease, and cause more than 1 million deaths and 12 million life-years of ill health each year among adults in the World Health Organization (WHO) European region.8 Type 2 diabetes appears to involve interplay between susceptible genetic backgrounds and environmental factors, including highly calorific westernized diets.10 Obesity provoke the epidemic of type 2 diabetes mellitus in developed and developing countries.6,11 Body mass index (BMI) is a common measure for general obesity, and is described as an independent predictor of type 2 diabetes in both genders.12 Waist circumference (WC), waistehip ratio (WHR) and waisteheight ratio (WHtR) are used as measures of central obesity, and also provide information on risk for type 2 diabetes.13e15 However, it is not known which anthropometric index is most suitable for assessment of the risk for type 2 diabetes in women. Therefore, the aim of this study was to assess the relationship between anthropometric indexes and risk for type 2 diabetes in women.
Subjects and methods A caseecontrol study was undertaken at an outpatient clinic in Kaunas, Lithuania. The study included 168 cases aged 34e85 years with newly diagnosed type 2 diabetes, according to WHO criteria,16 between 1 January 2001 and 31 December 2001. Three hundred and thirty-six controls, without impaired fasting glucose levels or type 2 diabetes, were individually matched to the diabetic patients by 5-year age group. The ratio of cases to controls was 1:2. Information on age, gender, family history of diabetes, education, occupational and marital status, nutrition habits, alcohol consumption, cigarette smoking, physical activity and stress level was assessed using a questionnaire designed by the research group. All subjects were invited to self-complete the questionnaire. If they were unable to do so (bad general condition, poor eyesight, pathology of upper extremities or personal wish for assistance to complete the questionnaire), they were interviewed by a trained interviewer. Interviewers were not aware of the study hypothesis. Participants were asked to fast for 12 h and to avoid smoking and heavy physical activity for at least 2 h before the examination. In accordance with WHO guidelines,17 a single investigator took all the anthropometric measurements. Height and weight were measured twice. Height without shoes was measured in centimetres (accuracy 0.1 cm). Weight in light clothing was measured in kilograms (0.5 kg accuracy). BMI was calculated as weight (kg)/height (m)2,18 WC was measured by holding a non-stretchable tape measure snugly around the waist, defined as the midpoint between the bottom rib and tip of the hipbones, and hip circumference was
measured at the level of the great femur trochanter in centimetres (0.1 cm accuracy). WHR was defined as WC (cm) divided by hip circumference (cm), and WHtR was defined as WC (cm) divided by height (cm).19,20 >Blood pressure was measured twice in the right arm with the subject in a sitting position. A mercurial sphygmomanometer was used with 2.0 mm mercurial column accuracy. Blood pressure was classified as normal or hypertensive (systolic blood pressure 140 mmHg and/or diastolic blood pressure 90 mmHg and/or receiving current medication for hypertension). Laboratory blood tests included fasting blood samples drawn from the subject’s elbow vein and venous plasma samples analysed for glucose and triglyceride (TG) levels. Venous plasma glucose was estimated by the Glucose oxidase phenol 4-aminoantipyrine (GOD-PAP) method (Eppendorf analyser, Hamburg, Germany). According to the 1999 WHO recommendations,19 75 g oral glucose tolerance tests were performed to assess carbohydrate disorders. TG was estimated by the Glycerol-3-phosphate oxidase phenolþaminophenazone (GPO-PAP) method (Randox analyser, London, United Kingdom). BMI was categorized as 18.5e24.9 kg/m2, 25e29.9 kg/m2 or 30 kg/m2 21; WC was categorized as<80 cm, 80e88 cm or >88 cm22; WHR was categorized as 0.85 or >0.85; and WHtR was categorized as <0.5 or 0.5. Family history of diabetes was categorized as first-degree relatives with history of diabetes or first-degree relatives without history of diabetes. Education was categorized as 10 years, 11e13 years or14 years. Marital status was categorized as married/living together, divorced/separated, single and widowed. Dietary habits were assessed according to eating speed (slower, the same or faster compared with others); food portion (smaller, the same or larger compared with others), and enjoyment of salty and fatty food (like very much, like or do not like). Morning exercise for at least 30 min during the last 12 months was categorized as no, sometimes or yes. Arterial hypertension was categorized as yes or no, and finally, plasma TG was categorized as <1.7 mmol/l or 1.7 mmol/l. A conditional logistic regression was used to calculate odds ratios (OR) and corresponding 95% confidence intervals (CI) for diabetes in relation to the exposures of interest. Variables were retained in models as confounders when their inclusion changed the value of the OR by more than 10% in any exposure category. All reported trend test significance levels (P-values) were two-sided.23 Chi-squared test was used to calculate the difference between proportions. The level of significance was set at 5%. All calculations were performed using STATA Version 7 (StataCorp LP, Texas, USA).
Results Table 1 shows the characteristics of the cases and controls. The cases had significantly lower levels of education and higher BMIs compared with controls. More controls reported no family history of diabetes compared with cases. General obesity was assessed using BMI, and central obesity was assessed using WC and WHR. Univariate regression showed that overweight and obesity were associated
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Table 1 e Characteristics of cases and controls. Variable
Age (years)
Education (years) Marital status
First-degree relatives with history of diabetes
Category
44 45e54 55e64 65 10 11e13 14 Married Divorced /separated Single Widowed No Yes
Cases
Controls
n
%
n
%
7 16 66 79 90 46 32 84 15
4.17 9.52 39.29 47.02 53.57 27.38 19.05 50.00 8.93
14 32 130 160 120 142 74 177 37
4.17 9.52 38.69 47.62 35.71 42.26 22.02 52.68 11.01
9 60 118 50
5.36 35.71 70.24 29.76
24 98 297 39
7.14 29.17 88.39 11.61
P-value for c2 Matched
<0.0001
NS
<0.0001
NS, not significant.
with higher risk for type 2 diabetes. Women with BMI of 25e29.99 kg/m2 had more than two-fold higher risk for type 2 diabetes (crude OR 2.32, 95% CI 1.14e4.87), and women with BMI 30 kg/m2 had about six times higher risk (crude OR 5.17, 95% CI 3.03e11.75) compared with those with BMI <25 kg/m2. A doseeresponse relationship was found between risk for diabetes and BMI, with P for trend <0.0001. Variables such as family history of diabetes, hypertension, plasma TG level and WHR were retained in the multivariate logistic regression model as confounders because their inclusion changed the OR value by more than 10% in any exposure category. Table 2
shows the results of the multivariate logistic regression of the relationship between type 2 diabetes and obesity. After adjustment for family history of diabetes, arterial hypertension and plasma TG level, the relationship between type 2 diabetes and BMI changed slightly but remained significant. After further adjustment for WHR, the risk for type 2 diabetes for women with BMI 30 kg/m2 (OR 4.68, 95% CI 2.09e10.49) was found to be four times higher compared with the risk for women with BMI <25 kg/m2. The relationship between type 2 diabetes and BMI 25e29.99 kg/m2 became non-significant. A significant doseeresponse relationship was found between BMI and the risk for type 2 diabetes ( p for trend <0.0001). WC, WHR and WHtR were also associated with the risk for type 2 diabetes. Univariate regression showed that women with WC > 88 cm had approximately four times higher risk for type 2 diabetes (crude OR 3.95, 95% CI 2.70e19.19). After adjustment for eating speed, enjoyment of salty and fatty food and morning exercise, the association between WC and risk for type 2 diabetes changed but remained significant. After controlling for eating speed, enjoyment of salty and fatty food, morning exercise, arterial hypertension, plasma TG level, education level and BMI, women with WC > 88 cm had about seven times higher risk for type 2 diabetes compared with women with WC < 80 cm (Table 2). Univariate regression showed that women with WHR >0.85 were at higher risk for type 2 diabetes (crude OR 2.68, 95% CI 1.17e2.79; P ¼ 0.007). After adjustment for hypertension, the relationship between WHR and type 2 diabetes became nonsignificant (Table 2). Univariate regression showed that women with WHtR 0.5 were at increased risk for type 2 diabetes (crude OR 3.81, 95% CI 2.67e21.26; P < 0.0001). After adjustment for family history of diabetes and education level, the relationship between WHtR and type 2 diabetes changed but remained significant.
Table 2 e Odds ratios (OR) and 95% confidence intervals (CI) for diabetes in relation to obesity in women. Variable
Category
2
Cases
Controls
n
%
n
%
Body mass index (kg/m )
<25 25e29.9 30
12 40 116
7.14 23.81 69.05
84 116 136
25.00 34.52 40.48
Waist circumference (cm)
<80 80e88 >88
5 10 153
2.98 5.95 91.07
49 69 218
14.58 20.54 64.88
Waistehip ratio
0.85 >0.85
36 132
21.43 78.57
110 226
32.74 67.26
Waisteheight ratio
<0.5 0.5
5 163
2.98 97.02
55 281
16.37 83.63
ORa(95% CI) P
ORb(95% CI) P
1.00 2.41 (1.16e5.03) 5.40 (2.73e10.67) P < 0.0001 1.00 1.23 (0.37e4.13) 6.48 (2.32e18.04) P < 0.0001 1.00 1.46 (0.93e2.29) P ¼ 0.104 1.00 3.44 (2.21e17.94) P ¼ 0.001
1.00 2.25 (0.99e5.14) 4.68 (2.09e10.49) P < 0.0001 1.00 1.57 (0.40e6.15) 6.99 (1.60e30.42) P ¼ 0.01
1.00 3.15 (1.91e15.81) P ¼ 0.002
Body mass index: ORa Adjusted for family history of diabetes, hypertension and plasma triglyceride level; ORb Adjusted for family history of diabetes, hypertension, plasma triglyceride level and waistehip ratio. Waistehip ratio: ORa adjusted for hypertension. Waist circumference: ORa adjusted for eating speed, enjoyment of salty and fatty food and morning exercise; ORb adjusted for eating speed, enjoyment of salty and fatty food, morning exercise, hypertension, plasma triglyceride level, education level and body mass index. Waisteheight ratio: ORa adjusted for family history of diabetes and education level; ORb adjusted for family history of diabetes, education level and morning exercise.
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After adjustment for family history of diabetes, education level and morning exercise, women with WHtR 0.5 had three times higher risk for type 2 diabetes compared with women with WHtR <0.5 (Table 2).
Discussion This study showed that both general and central obesity are associated with type 2 diabetes. Similar results have been obtained in numerous previous studies reporting the effects of anthropometric variables on risk for type 2 diabetes. However, most of these studies employed a prospective design,24 rather than the caseecontrol design employed in this study. Overweight and obesity represent a significant public health problem because of the link with numerous chronic health conditions.25 Over the last two decades, Lithuania has enjoyed an impressive change from a soviet economy to a market economy, and citizens have experienced many remarkable lifestyle changes. These changes are often associated with westernization of nutrition and increased obesity and chronic diseases. A survey of factual nutrition conducted by the National Nutrition Centre showed that most overweight and obese Lithuanian inhabitants were aged 50e64 years. Among females, 39.7% were overweight and 27.9% were obese.26 The present study found increased risk for type 2 diabetes related to both general and central obesity. Women with BMI 30 kg/m2 had 4.7 times higher risk for type 2 diabetes compared with women with BMI <25 kg/m2. Excess body weight, overweight and obesity are the result of an imbalance between energy intake and energy expenditure.27 A study of indigenous Canadians documented BMI as the strongest determinant of diabetes.28 BMI is an excellent predictor of the risk for type 2 diabetes in Pima Indians, and is not significantly improved by adding other measures of general adiposity or body fat distribution.29 The prospective Hoorn Study illustrated that WHR was a better predictor of diabetes than BMI.13 Use of the sagittal abdominal diameter has no advantages over simpler and more commonly used anthropometric measures such as WC in older men and women.30 Thigh circumference in women and hip circumference in both sexes were negatively associated with markers of glucose metabolism, independently of WC, BMI and age.31 Wang et al. observed that WHR was the best predictor for type 2 diabetes in Australian Aboriginal people and Torres Strait Islanders.32 Chan et al. reported that WC was a better indicator of the relationship between central adiposity and the risk for type 2 diabetes than WHR in males. This study also showed that BMI was the dominant risk factor for type 2 diabetes in males.33 In the San Antonio Heart Study, WC was a better independent predictor of type 2 diabetes than BMI, WHR and other measurements in Mexican Americans aged 25e64 years.34 Janssen et al., in an analysis of data from the third National Health and Nutrition Examination Survey, found that WC, but not BMI, better explained obesity-related health risks.35 Lorenzo et al. reported that WHtR is a better indicator than WC and BMI in women.36 Body fat distribution, especially intra-abdominal adipose tissue accumulation, is a key correlate of a cluster of diabetogenic, atherogenic, prothrombotic and inflammatory
metabolic abnormalities increasing the risk for type 2 diabetes and cardiovascular disease.14 Abdominal obesity is associated with an increased risk for coronary heart disease and type 2 diabetes independently of overall adiposity.37 The mechanisms leading from obesity to type 2 diabetes are complicated and not fully elucidated. It seems that free fatty acids and adipokines produced by the abdominal adipose tissue decrease insulin sensitivity and increase insulin demands.38 The classical perception of adipose tissue as a storage place of fatty acids has been replaced by the notion that adipose tissue has a central role in lipid and glucose metabolism, and produces a large number of hormones and cytokines (e.g. tumour necrosis factor-alpha, interleukin-6, adiponectin, leptin and plasminogen activator inhibitor-1).39 Therefore, the increased prevalence of excessive visceral obesity and obesity-related cardiovascular risk factors is closely associated with the rising incidence of type 2 diabetes.39 Genes concerned with carbohydrate, lipid and amino acid metabolic pathways, neuronal function and inflammation play a significant role in the pathobiology of obesity and type 2 diabetes.40 Increased oxidative stress together with decreased antioxidative defence seem to contribute to decreased insulin sensitivity and impaired insulin secretion response in obese diabetics, and may be hypothesized to favour the development of diabetes in obese individuals.41 Central (visceral) obesity is more closely associated with insulin resistance, type 2 diabetes and cardiovascular disease than peripheral (subcutaneous) obesity. However, the underlying differences in morphology and pathophysiology between subcutaneous and visceral adipose are largely unknown.42 Visceral fat is more metabolically active than subcutaneous fat, and therefore more deleterious to health.43 Accumulation of intra-abdominal fat correlates with insulin resistance, whereas subcutaneous fat deposition correlates with circulating leptin levels.39 Consequently, WC has several advantages as a risk marker for diabetes prevention in health promotion activities.44 The above-mentioned data suggest that visceral fat is the risk for type 2 diabetes. However, general obesity may not be a separate risk factor for diabetes, because it is debated that an increased hip circumference reduces the risk for diabetes.45 The close relationship between an increased quantity of visceral fat, metabolic disturbances, including low-grade inflammation, cardiovascular diseases and the unique anatomical relationship with the hepatic portal circulation has led to an intense endeavour to unravel the specific endocrine functions of this visceral fat depot.39
What this study adds To the authors’ knowledge, this study differs from other case reports by case selection. All cases were individuals with newonset type 2 diabetes at a urban outpatient clinic over 1 year. The anthropometric parameters of the patients were not influenced by special diets and treatment. In most other cohort studies, the cases were selected at random and not related by time of onset. Controls in the present study were selected at random as in another caseecontrol studies. Furthermore, the information reported in this study may serve as evidence for the prevention and early development of type 2 diabetes among females who are visiting outpatient clinics.
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Limitations of this study The present study has some limitations that need to be acknowledged. Firstly, data were not collected about the duration of overweight. It was considered that the presence of overweight and the region of fat distribution were more important than the duration of enlarged body mass. Also, the data were not corrected for age because there was no age difference between the case and control groups. However, the degree of overweight and obesity may increase with age, and age may be considered a predominant risk factor for diabetes. Finally, the relevance and precision of data on physical activity in the questionnaire could be insufficient, because diabetes manifestation is strongly related to physical activity.46
Conclusions In this study, the relationship between WHR and risk for type 2 diabetes in women was not statistically significant. However, women with WC > 88 cm had approximately seven times higher risk for type 2 diabetes compared with those with WC < 80 cm. Women with WHtR 0.5 had three times higher risk for type 2 diabetes compared with those with WHtR <0.5 cm. The data suggest that high BMI, WC and WHtR may be considered as significant risk factors for type 2 diabetes in women. Furthermore, the data suggest that it is not necessary to exclude general obesity from the risk factors because it is usually accompanied by increased visceral fat. Overweight and large WC increases the risk for type 2 diabetes, and decreasing body fat deposits may reduce the risk for type 2 diabetes.
Acknowledgements Ethical approval Bioethics Committee of Kaunas University of Medicine.
Funding None declared.
Competing interests None declared.
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