The combination of body mass index and fasting plasma glucose is associated with type 2 diabetes mellitus in Japan: a secondary retrospective analysis

This review addresses the interplay between obesity, type 2 diabetes mellitus, and cardiovascular diseases. It is proposed that obesity, generally defined by an excess of body fat causing prejudice to health, can no longer be evaluated solely by the body mass index (expressed in kg/m 2 ) because it represents a heterogeneous entity. For instance, several cardiometabolic imaging studies have shown that some individuals who have a normal weight or who are overweight are at high risk if they have an excess of visceral adipose tissue—a condition often accompanied by accumulation of fat in normally lean tissues (ectopic fat deposition in liver, heart, skeletal muscle, etc). On the other hand, individuals who are overweight or obese can nevertheless be at much lower risk than expected when faced with excess energy intake if they have the ability to expand their subcutaneous adipose tissue mass, particularly in the gluteal-femoral area. Hence, excessive amounts of visceral adipose tissue and of ectopic fat largely define the cardiovascular disease risk of overweight and moderate obesity. There is also a rapidly expanding subgroup of patients characterized by a high accumulation of body fat (severe obesity). Severe obesity is characterized by specific additional cardiovascular health issues that should receive attention. Because of the difficulties of normalizing body fat content in patients with severe obesity, more aggressive treatments have been studied in this subgroup of individuals such as obesity surgery, also referred to as metabolic surgery. On the basis of the above, we propose that we should refer to obesities rather than obesity.

Obesity leads to chronic, systemic inflammation and can lead to insulin resistance (IR), β-cell dysfunction, and ultimately type 2 diabetes (T2D). This chronic inflammatory state contributes to long-term complications of diabetes, including non-alcoholic fatty liver disease (NAFLD), retinopathy, cardiovascular disease, and nephropathy, and may underlie the association of type 2 diabetes with other conditions such as Alzheimer's disease, polycystic ovarian syndrome, gout, and rheumatoid arthritis. Here, we review the current understanding of the mechanisms underlying inflammation in obesity, T2D, and related disorders. We discuss how chronic tissue inflammation results in IR, impaired insulin secretion, glucose intolerance, and T2D and review the effect of inflammation on diabetic complications and on the relationship between T2D and other pathologies. In this context, we discuss current therapeutic options for the treatment of metabolic disease, advances in the clinic and the potential of immune-modulatory approaches.

Interventions to prevent type 2 diabetes should be directed toward individuals at increased risk for the disease. To identify such individuals without laboratory tests, we developed the Diabetes Risk Score. A random population sample of 35- to 64-year-old men and women with no antidiabetic drug treatment at baseline were followed for 10 years. New cases of drug-treated type 2 diabetes were ascertained from the National Drug Registry. Multivariate logistic regression model coefficients were used to assign each variable category a score. The Diabetes Risk Score was composed as the sum of these individual scores. The validity of the score was tested in an independent population survey performed in 1992 with prospective follow-up for 5 years. Age, BMI, waist circumference, history of antihypertensive drug treatment and high blood glucose, physical activity, and daily consumption of fruits, berries, or vegetables were selected as categorical variables. Complete baseline risk data were found in 4435 subjects with 182 incident cases of diabetes. The Diabetes Risk Score value varied from 0 to 20. To predict drug-treated diabetes, the score value >or=9 had sensitivity of 0.78 and 0.81, specificity of 0.77 and 0.76, and positive predictive value of 0.13 and 0.05 in the 1987 and 1992 cohorts, respectively. The Diabetes Risk Score is a simple, fast, inexpensive, noninvasive, and reliable tool to identify individuals at high risk for type 2 diabetes.