|
 
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| REVIEW ARTICLE |
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| Year : 2013 | Volume
: 1
| Issue : 2 | Page : 49-56 |
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Obesity and type 2 diabetes mellitus: A complex association
Abdulkareem Jassem Al-Quwaidhi1, Mark S Pearce2, Julia A Critchley3, Martin O'Flaherty4
1 Department of Public Health, General Directorate of Health Affairs at Al-Ahssa Region, Ministry of Health, United Kingdom
2 Sir James Spence Institute of Child Health Institute of Health and Society, Newcastle University, United Kingdom
3 Population Health Research Centre, St. George's University of London, United Kingdom
4 Division of Public Health Institute of Psychology, Health and Society, University of Liverpool, United Kingdom
| Date of Web Publication | 12-Mar-2014 |
Correspondence Address:
Abdulkareem Jassem Al-Quwaidhi
P.O. Box 35515, Al-Ahssa 31982
United Kingdom
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/2347-2618.128627
Obesity is a growing epidemic affecting all ages in both industrialized and developing countries. The most common suggested cause of this epidemic is the increasing levels of urbanization and lifestyle changes toward sedentary life and adopting "western" dietary patterns. The association between obesity and type 2 diabetes mellitus (T2DM) has been reproducibly observed in cross-sectional and prospective studies across various populations, even when using different fatness measures and diagnostic criteria for T2DM. However, there are some modifying factors that make such an association complex and multifactorial. These modifying factors include the duration of obesity, body fat distribution, physical activity, diet, and genetics/ethnicity. This review aims to summarize the evidence of this association and its potential modifying factors. Keywords: Association, obesity, type 2 diabetes mellitus
How to cite this article:
Al-Quwaidhi AJ, Pearce MS, Critchley JA, O'Flaherty M. Obesity and type 2 diabetes mellitus: A complex association. Saudi J Obesity 2013;1:49-56 |
| Introduction | |  |
Obesity is the "accumulation of adipose tissue to excess and to extent that impairs physical and psychosocial health and well-being". [1],[2] According to the World Health Organization (WHO), the world-wide obesity has more than doubled since 1980, and in 2008, there were around 1.5 billion overweight adults (aged ≥20 years). Of these, over 200 million men and 300 million women were obese, which means that more than one in ten of the world's adult population was obese in 2008. [3] In 2010, approximately 35 million overweight children were living in developing countries, compared to 8 million in industrialized countries. [3] The estimated economic burden of obesity in developed countries ranges between 2% and 7% of health care costs, and is higher in developing countries. [2] The region of Middle East and North Africa had the seventh (among the 21 regions of the Global Burden of Disease Study) highest prevalence of obesity in men, and the second highest in women between 1980 and 2008. [4]
The association between obesity and type 2 diabetes mellitus (T2DM) has been reproducibly observed in both cross-sectional [5],[6] and prospective studies, [7],[8] and has been consistent across various populations even when using different measures of fatness and T2DM diagnostic criteria. [9] It is often stated that obesity is the most important risk factor for T2DM, and the current epidemics of these two conditions seem to be related.
This review aims to summarize the evidence of the association between obesity and type 2 diabetes mellitus.
| Methodology | | |
To achieve the objective of this review, a comprehensive literature review was conducted using Google Scholar and Medline database (1980-January 2014). The review consisted of two stages. In the first stage, we used several terms of titles and keywords to search for relevant articles of different types (e.g., original research, reviews, systematic reviews and meta-analyses) in order to form a general picture of the recent evidence on the association between obesity and T2DM and the proposed pathophysiological pathways of such an association. Examples of terms used were 'obesity', 'fatness', 'body weight', 'weight', 'body mass index', 'BMI', 'waist circumference', 'diabetes', 'type 2 diabetes', 'association', etc. In the second stage, we used relevant search terms of titles and keywords for each of the five themes we used to explain the complexity of association. These themes include (1) duration of obesity; (2) body fat distribution; (3) physical activity; (4) diet; and (5) genetics/ethnicity. After combination of the search terms for each theme and reviewing titles and then abstracts, we included 10 articles for the first theme, 16 for the second theme, 23 for the third theme, 19 for the fourth theme, and 7 for the fifth theme, respectively. We included original research papers, reviews, and systematic reviews/ meta-analyses. We did not cite all articles obtained through the search strategy. Instead, whenever possible, we critically appraised articles and attempted to cite those with the most recently published data in each theme, in combination with having good sampling sizes/ techniques, and proper study designs and outcome ascertainment (determined by fulfilling at least 3 items from the 'guidelines and checklist for appraising a medical article' published by the BMJ). [10] To compare between different studies' findings, we included studies that reported either a positive or no association for each theme.
| Obesity and T2DM | | |
Obesity measurements
The WHO recommends the body mass index (BMI) as a measure of obesity. [3] BMI is a simple index of weight-for-height and is defined as the weight in kilograms divided by the square of height in meters (kg/m 2 ). Overweight in adults is defined as a BMI of ≥25 kg/m 2 , and obesity as a BMI of ≥30 kg/m 2 . [3] BMI provides the most useful and widely accepted measure of overweight and obesity at the clinical and population level, as it is the same for both sexes and for all ages, and has been widely used in most studies world-wide. [3] However, BMI is prone to some limitations in persons with extremes of age, very muscular builds (overestimates obesity), and extreme height. [1],[3],[11] In addition, in some ethnic groups, particularly Asians, the above-mentioned cut-offs are not suitable to classify overweight and obesity. The mean or median BMI in Asians has been found to be lower than that observed in non-Asian populations; so the BMI distribution is shifted to the left. [12] This trend leads to the concern that application of the standard WHO's cut-offs will underestimate obesity-related risks in these populations, and therefore, new cut-offs of 23-27.5 kg/m 2 for overweight and ≥27.5 kg/m 2 for obesity have been recommended for Asians. [12]
BMI measures the "total" adiposity of the body and may miss many cases of "central/abdominal" obesity, in which the body fat accumulates mainly around the waist. The simple clinical measure of central obesity is the waist circumference (WC). The WHO recommends a cut-off of WC≥102 cm in men and ≥88 cm in women to define central obesity. [13] Again, Asian populations, particularly people of South Asian origin seem more prone to carrying excess fat centrally than the white populations and show raised obesity-related risk although they may not be considered obese by conventional BMI criteria. Hence, the WHO thresholds for central obesity in Asians are a WC≥90 cm in men and ≥80 cm in women. [13] In addition to WC, the waist-to-hip circumference ratio (WHR) is another measure of central obesity. A WHR>1.0 in men and WHR>0.85 in women are used as cut-offs for identifying individuals with central obesity. However, WC is the preferred and more commonly used measure of abdominal obesity compared with WHR. [13]
Pathophysiological pathways
The pathophysiological link between obesity and T2DM relates primarily to the adipose tissue, which has been recognized as an endocrine organ that secretes hormones and communicates with the central nervous system to regulate appetite and metabolism. [14] The main proposed pathways which link obesity and T2DM are briefly summarized in the following points:
- Elevated leptin levels. Leptin is a protein produced by adipocytes. The main role of leptin is to regulate food intake and energy expenditure by reducing food intake and increasing sympathetic nervous system outflow, therefore inducing weight loss. [15] Recent evidence showed that leptin levels fall during weight loss and increase brain activity in areas involved in emotional, cognitive, and sensory control of food intake. [15] Restoration of leptin levels maintain weight loss and reverse the changes in brain activity. Thus, leptin is a critical factor linking reduced energy stores to eating behavior. [15] In obese individuals, leptin levels are elevated, but this has been found to positively correlate with insulin resistance. Leptin can impair the production of insulin and reduce the effects of insulin on the liver. [14]
- Elevated levels of adipocyte-derived free fatty acids. In adipose tissues, glucose is involved in lipogenesis through its conversion to glycerol-3-phosphate, which is then combined with "non-esterified fatty acids (NEFAs)" to form triglycerides. An important role of insulin is also to prevent the breakdown of triglycerides (lipolysis), which liberates NEFAs. [14] In obese individuals, the levels of these fatty acids are raised, resulting in impairment of glucose metabolism by reducing insulin-stimulated glucose uptake in skeletal muscle, and increasing the hepatic glucose output. [14]
- Elevated levels of proteins secreted by adipose tissue. In addition to leptin, adipose tissue secretes many other proteins that modulate glucose metabolism and insulin action. Examples of these proteins include adiponectin, adipsin and resistin. Again, studies have generally suggested that circulating levels of these proteins are elevated in individuals with T2DM. [14]
- Elevated levels of adipocyte-nonspecific proteins. There are some proteins which are secreted by adipocytes and other cells and tissues. For instance, cytokines, such as tumor necrosis factor-α and interleukin-6 are produced by macrophages and also by adipocytes. [14] These proteins are involved in innate immunity and contribute to the process of inflammation, either directly through acting on inflammatory cells or indirectly by acting on the liver to produce acute phase proteins. [14] Cytokines have been found to induce "suppressor of cytokine signaling-3 (SOCS-3)," which is an intracellular signaling molecule that impairs the signaling of both leptin and insulin. In obesity, SOCS-3 levels are elevated and thus may result in obesity-associated resistance to the actions of both leptin and insulin. [14]
| Modifying Factors of The Association Between Obesity and T2DM | | |
Not every obese individual develops diabetes and therefore, obesity alone is not sufficient to cause T2DM. [9] The relationship between obesity and T2DM is complicated by the effects of several modifying factors. These factors include duration of obesity, [7] distribution of body fat, [16] physical activity (PA), [17] diet, [18] and genetics/ethnicity. [19] The following subsections concisely discuss these factors and their possible modifying effects. [Table 1] summarizes the primary research studies included in this review for each of the modifying factors. | Table 1: Summary of the primary studies included in the review (for each of the modifying factors studied)
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Duration of obesity
The evidence quantifying the relationship between obesity duration and risk of T2DM is complicated by the difficulty to measure the actual onset of obesity and to differentiate between the effects of degree and duration of obesity in case the weight is changing. [9]
Examples of recent studies that reported an association include the study of Reis et al., [7] who followed a cohort of 5,115 white and black adults aged 18-30 years in 1985-1986. Years spent abdominally obese were calculated for participants without abdominal obesity (WC>102 cm in men and>88 cm in women) or diabetes at baseline (n = 4,092) and was based upon repeat measurements conducted 2, 5, 7, 10, 15, 20, and 25 years later. After 25 years of follow-up, 392 participants developed incident diabetes. Following adjustment for socio-demographic variables (age, sex), family history of diabetes, time varying WC, energy intake, PA, smoking, and alcohol, each additional year of abdominal obesity was associated with a 4% higher risk of developing diabetes [hazard ratio (HR) 1.04 (95% confidence interval [CI]: 1.02-1.07)]. [7]
In another prospective study, [20] a total of 1256 participants who were free from T2DM at baseline, but were obese on at least two consecutive of the study's twenty-four biennial examinations, were included. T2DM status was collected throughout the 48 years of follow-up of the study. The unadjusted HR for the risk of T2DM for men was 1.13 (95% CI: 1.09, 1.17) and for women was 1.12 (95% CI: 1.08, 1.16) per additional 2-year increase in the duration of obesity (BMI≥30 kg/m 2 ). There was no significant difference to these HRs after adjustment for several covariates (socio-demographic variables, family history of T2DM, health behavior and PA). [20]
Body fat distribution
There is considerable evidence suggesting that both overall adiposity and fat distribution are independent risk factors for T2DM in both men and women. Some studies, such as that of Meisinger et al., [8] have shown that there was an 'additive' effect of overall and abdominal obesity on the prediction of the risk of T2DM. They followed a cohort of 3055 men and 2957 women, aged 35-74 years and free of T2DM at baseline, for a mean period of 9.2 years. A total of 243 cases of incident T2DM occurred in men and 158 in women. Multivariable-adjusted HRs across quartiles of BMI were 1.0, 1.37, 2.08, and 4.15 in men and 1.0, 3.77, 4.95, and 10.58 in women; while those of WC were 1.0, 1.15, 1.57, and 3.40 in men and 1.0, 3.21, 3.98, and 10.70 in women; and those of WHR were 1.0, 1.14, 1.80, and 2.84 in men and 1.0, 0.82, 2.06, and 3.51 in women. In joint analyses, the highest risk was observed in men and women with a high BMI in combination with a high WC and a high WHR. Therefore, the authors concluded that WC should be measured in addition to BMI to assess the risk of T2DM in both sexes. [8] These findings are supported by a meta-analysis [16] conducted based on 32 studies from 1966 to 2004, and demonstrated that the three major obesity indicators (BMI, WC, and WHR) have similar associations with incident diabetes. The pooled relative risks (RRs) for incident diabetes were 1.87 (95% CI: 1.67-2.10), 1.87 (95% CI: 1.58-2.20), and 1.88 (95% CI: 1.61-2.19) per standard deviation of BMI, WC, and WHR respectively.
Balkau et al. [5] have conducted the International Day for the Evaluation of Abdominal obesity study, which evaluates whether WC in addition to BMI is a useful clinical marker of physician-reported cardiovascular disease and diabetes. It covered a total of 168,000 primary care patients (aged 18-80 years) in 63 countries from different regions of the world, including Saudi Arabia and other Middle East and North African countries. The standardized odds ratios (ORs) for diabetes mellitus were higher for WC than for BMI in almost all regions, with overall ORs (95% CI) of 1.59 (1.56-1.63) versus 1.52 (1.49-1.56) in men and 1.83 (1.79-1.87) versus 1.67 (1.64-1.71) in women. The exceptions were the Middle East and Australia, where the ORs for diabetes mellitus were consistently higher for BMI than for WC in both genders. In North Africa, men with diabetes have equivalent ORs for WC and BMI. [5] In contrast, Abolfotouh et al. [21] have conducted a large home-based survey among 1800 participants (aged ≥18 years) in 4 Egyptian governorates, and reported a significant association between WC and the risk of diabetes (P = 0.02). However, BMI was not significantly associated with diabetes (P = 0.11). [21]
As indicated earlier, Asian populations are generally more prone to abdominal obesity and low muscle mass with increased insulin resistance compared with white western individuals. [22],[23] The risk of T2DM was found to start at a lower BMI for Asians than their European counterparts. [22],[23]
Lear et al. [6] compared the relation between abdominal adipose tissue and total body fat between persons living in Canada of Aboriginal, Chinese, and South Asian origin with persons of European origin. They matched healthy Aboriginal, Chinese, European, and South Asian participants (n = 822) aged 30-65 years by sex, ethnicity, and BMI. Total abdominal adipose tissue (TAT), subcutaneous abdominal adipose tissue (SAT), visceral adipose tissue (VAT), total body fat mass, lifestyle, and demographics were assessed. They investigated the relations between BMI and total body fat, TAT, SAT, and VAT and between total body fat and TAT, SAT, and VAT. [6] It has been found that BMI significantly underestimated VAT in all non-European groups. Throughout a range of total body fat mass, VAT was not significantly different between the Aboriginals and the Europeans. With total body fat >9.1 kg, Chinese participants had increasingly greater amounts of VAT than did the Europeans (P value for interaction =0.008). South Asians had less VAT with total body fat >37.4 kg but more VAT below that amount than did Europeans (P value for interaction < 0.001). [6]
Physical activity and diet
Obesity generally results from an imbalance between energy intake (diet) and energy expenditure (PA). [24] There is good evidence supporting that PA is an important component on long-term weight control. [17],[25],[26],[27] PA generally affects body composition and weight favorably by promoting fat loss. It has been observed by numerous studies that a minimum of 150 min/week of moderate-intensity PA (e.g., 30 min of brisk walking daily) is associated with health-related benefits. [26],[27] However, higher levels of PA (200-300 min/week) may be necessary to improve long-term weight loss outcomes. [26],[27] Moreover, studies have demonstrated that exercise alone can have a significant impact on body weight when maintained for ≥12 months, and that individuals who reduce their level of leisure-time PA can have weight regain after a specific period of time. Another important observation is that the combination of increased PA and dieting appears to be more effective for long-term weight regulation than is dieting alone. [25]
The progress in understanding the role of diet in the etiology of obesity has been seriously confounded by the profound under-reporting, which is now widely recognized as a feature of obesity. Several studies have reported that obese individuals might under-report their intake by an average of 30% due to many reasons, such as forgetfulness, underestimation of portion size, inadequate knowledge of food composition, or even self-deception. [28] The evidence is inconsistent regarding the relation between intake of individual macronutrients (fat, carbohydrate and protein) and obesity, with fat overconsumption being the most commonly suggested dietary factor to have a role in the etiology. It has been suggested that fat appears to have a weaker satiating capacity than that of carbohydrates and proteins, so that individuals readily overeat in response to high fat foods. As fat has twice as much energy per gram as protein or carbohydrate, this may eventually result in energy density. [29] Nevertheless, some studies have shown a positive linear relationship between energy density and fat consumption, but a modest negative correlation with carbohydrate intake. [30],[31] On the other hand, some studies have found that a dry high-carbohydrate food such as pretzels can have similar energy density as high-fat foods such as cheese. [32] Moreover, some researchers now suggest that it is the "total" energy intake which has a more obvious association than fat intake only. [30]
Several intervention studies have reported that reductions in energy intake (e.g., diet) alone, or increasing energy expenditure (e.g., exercise) alone have a positive impact on body weight, [24] although the combination of diet plus exercise has the greatest impact on weight loss. [33] For example, an intervention study reported reductions in body weight by 4.9% and 5.7% in participants with 18 months of diet alone, and diet plus exercise, respectively (P < 0.05). [33]
Genetics and ethnicity
There is a continuing search for the genetic basis of predisposition to obesity. Several single gene mutations in rodents and humans were suggested to cause the development of obesity. [34],[35],[36] However, these are extremely rare and an increase in genetic defects is insufficient to explain the substantial increase in the prevalence of obesity over the recent decades. [37]
Some research studies suggest an association between family history and obesity. For instance, Gibson et al. [38] carried out a population-based prospective study on 329 children aged 6-13 years (192 healthy weight, 97 overweight and 40 obese) and their mothers (n = 265) recruited from a pediatric hospital and primary schools in Perth, Australia. Height, weight and BMI of children and mothers were among the main outcome measures in the study. It has been found that having an overweight mother increases the likelihood of a child being overweight or obese. Maternal BMI and family structure (single-parent versus two-parent families) were the only significant predictors of child BMI. [38] Similar findings were obtained from a cross-sectional study in Riyadh, Saudi Arabia. [39] A total of 894 Saudi male adolescents (age 12-20 years) were selected from intermediate and secondary schools in Riyadh. Adolescents with a BMI age-specific percentile of ≥95 th were considered obese. It has been found that family history of obesity was associated with adolescent obesity (OR 2.49; 95% CI: 1.72-3.61). [39]
A large number of studies have revealed that some ethnic groups have an elevated risk of T2DM compared to other ethnicities. [19],[40],[41] In all these studies, which have not adjusted for some confounding variables (e.g., BMI), obesity might be a modifying factor for increased levels of the disease. However, some other studies have adjusted their results for BMI and still found variations by ethnicity. For example, Shai et al. [42] prospectively followed 78,419 apparently healthy women (75,584 whites, 801 Asians, 613 Hispanics, and 1,421 blacks) for 20 years, with detailed dietary and lifestyle information for each participant repeatedly collected every 4 years. It has been found that compared with whites, the age-adjusted relative risks RRs (with 95% CIs) were 1.43 (1.08-1.90) for Asians, 1.76 (1.32-2.34) for Hispanics, and 2.18 (1.82-2.61) for blacks. After adjustment for BMI, the RRs changed to 2.26 (1.70-2.99) for Asians, 1.86 (1.40-2.47) for Hispanics, and 1.34 (1.12-1.61) for blacks. [42] They concluded that the risk of diabetes is significantly higher among Asians, Hispanics, and blacks than among whites before and after taking into account differences in BMI. In addition, the association between increasing BMI and greater weight gain and risk of diabetes was most pronounced among Asians, suggesting that lower cut-off BMI values are needed to identify Asians at a higher risk of diabetes. [42]
| Conclusion | | |
The association between obesity and T2DM is well-established across numerous studies in different populations. However, such an association does not appear to be simple, but is modified by several factors, including duration of obesity, body fat distribution, PA, diet, and genetics/ethnicity. These factors significantly influence the occurrence/risk of T2DM among obese individuals. There are some regional and ethnic variations as whether central or total obesity would be a better predictor of T2DM. Healthy lifestyle, with combination of PA and a balanced diet, has a positive impact on body weight control, and hence should be strongly promoted, particularly among populations that experience socio-economic transitions.
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[Table 1]
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| FadwaE Alhayali, AysegülA Yücel, ZainabF Ashoor | | Mustansiriya Medical Journal. 2021; 20(2): 76 | | [Pubmed] | [DOI] | | | 3 |
Dietary pattern of patients with type 2 diabetes mellitus including date consumption |
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| Muneera Q. Al-Mssallem,Ali Ahmed Al-Qarni,Mohammed Al-Jamaan | | Journal of Public Health. 2020; | | [Pubmed] | [DOI] | | | 4 |
Prevalence, awareness, and determinants of type 2 diabetes mellitus among commercial taxi drivers in buffalo city metropolitan municipality South Africa |
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| Aanuoluwa Odunayo Adedokun,Daniel Ter Goon,Eyitayo Omolara Owolabi,Oladele Vincent Adeniyi,Anthony Idowu Ajayi | | Medicine. 2019; 98(9): e14652 | | [Pubmed] | [DOI] | |
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