Objective: Insulin-like growth factor-I (IGF-I) has been suggested to be a prognostic marker for the development of cancer and, more recently, cardiovascular disease. These diseases are closely linked to obesity, but reports of the association of IGF-I with measures of obesity are divergent. In this study, we assessed the association of age-dependent IGF-I standard deviation scores with body mass index (BMI) and intra-abdominal fat accumulation in a large population. Design: A cross-sectional, epidemiological study. Methods: IGF-I levels were measured with an automated chemiluminescence assay system in 6282 patients from the DETECT study. Weight, height, and waist and hip circumference were measured according to the written instructions. Standard deviation scores (SDS), correcting IGF-I levels for age, were calculated and were used for further analyses. Results: An inverse U-shaped association of IGF-I SDS with BMI, waist circumference, and the ratio of waist circumference to height was found. BMI was positively associated with IGF-I SDS in normal weight subjects, and negatively associated in obese subjects. The highest mean IGF-I SDS were seen at a BMI of 22.5–25 kg/m2 in men (+0.08), and at a BMI of 27.5–30 kg/m2 in women (+0.21). Multiple linear regression models, controlling for different diseases, medications and risk conditions, revealed a significant negative association of BMI with IGF-I SDS. BMI contributed most to the additional explained variance to the other health conditions. Conclusions: IGF-I standard deviation scores are decreased in obesity and underweight subjects. These interactions should be taken into account when analyzing the association of IGF-I with diseases and risk conditions.

Objective: IGF1 is associated with metabolic parameters and involved in glucose metabolism. Low-IGF1 has been implicated in the etiology of glucose intolerance and subjects with pathological causes of either low- or high-IGF1 are at risk of diabetes. We hypothesized that both low- and high-IGF1 levels increase the risk of diabetes and aimed to assess the role of IGF1 in the risk of developing diabetes in a large prospective study. Design: An analysis of two prospective cohort studies, the DETECT study and SHIP. Methods: We measured IGF1 levels in 7777 nondiabetic subjects and assessed incident diabetes mellitus during follow-up. Results: There were 464 cases of incident diabetes during 32 229 person-years (time of follow-up in the DETECT study and SHIP: 4.5 and 5 years respectively). There was no heterogeneity between both studies (P>0.4). The hazard ratios (HRs) of incident diabetes in subjects with IGF1 levels below the 10th or above the 90th age- and sex-specific percentile, compared to subjects with intermediate IGF1 levels, were 1.44 (95% confidence interval (CI) 1.07–1.94) and 1.55 (95% CI 1.06–2.06) respectively, after multiple adjustment. After further adjustment for metabolic parameters, the HR for low-IGF1 became insignificant. Analysis of IGF1 quintiles revealed a U-shaped association of IGF1 with risk of diabetes. Results remained similar after exclusion of patients with onset of new diabetes within 1 year or with borderline glucose or HbA1c levels at baseline. Conclusions: Subjects with low- or high-IGF1 level are at increased risk of developing diabetes.

Background: There is a lack of the generic data comparing the influence of different diseases on health-related quality of life (HrQoL) in a representative sample of primary care patients. Methods: Patient data were collected in the DETECT (Diabetes Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) study including 55,000 patients. Results: 3,109 patients (33.3% female) with myocardial infarction (MI), stroke or both were compared to patients with a wide range of other diagnoses. Stroke and MI patients revealed a lower HrQoL as compared to patients with other diagnoses. Stroke was associated with strongest quality of life reduction. Multivariate analysis revealed several different determining factors. Conclusions: The reduction of HrQoL of patients with MI and stroke is primarily determined by the CNS insult. These data provide further evidence that early diagnosis and treatment of cardiovascular risk factors is essential to reduce subsequent stroke.

Objective: Insulin-like growth factor-I (IGF-I) has been suggested to be a prognostic marker for the development of cancer and, more recently, cardiovascular disease. These diseases are closely linked to obesity, but reports of the association of IGF-I with measures of obesity are divergent. In this study, we assessed the association of age-dependent IGF-I standard deviation scores with body mass index (BMI) and intra-abdominal fat accumulation in a large population. Design: A cross-sectional, epidemiological study. Methods: IGF-I levels were measured with an automated chemiluminescence assay system in 6282 patients from the DETECT study. Weight, height, and waist and hip circumference were measured according to the written instructions. Standard deviation scores (SDS), correcting IGF-I levels for age, were calculated and were used for further analyses. Results: An inverse U-shaped association of IGF-I SDS with BMI, waist circumference, and the ratio of waist circumference to height was found. BMI was positively associated with IGF-I SDS in normal weight subjects, and negatively associated in obese subjects. The highest mean IGF-I SDS were seen at a BMI of 22.5–25 kg/m2 in men (+0.08), and at a BMI of 27.5–30 kg/m2 in women (+0.21). Multiple linear regression models, controlling for different diseases, medications and risk conditions, revealed a significant negative association of BMI with IGF-I SDS. BMI contributed most to the additional explained variance to the other health conditions. Conclusions: IGF-I standard deviation scores are decreased in obesity and underweight subjects. These interactions should be taken into account when analyzing the association of IGF-I with diseases and risk conditions.

Objective: IGF1 is associated with metabolic parameters and involved in glucose metabolism. Low-IGF1 has been implicated in the etiology of glucose intolerance and subjects with pathological causes of either low- or high-IGF1 are at risk of diabetes. We hypothesized that both low- and high-IGF1 levels increase the risk of diabetes and aimed to assess the role of IGF1 in the risk of developing diabetes in a large prospective study. Design: An analysis of two prospective cohort studies, the DETECT study and SHIP. Methods: We measured IGF1 levels in 7777 nondiabetic subjects and assessed incident diabetes mellitus during follow-up. Results: There were 464 cases of incident diabetes during 32 229 person-years (time of follow-up in the DETECT study and SHIP: 4.5 and 5 years respectively). There was no heterogeneity between both studies (P>0.4). The hazard ratios (HRs) of incident diabetes in subjects with IGF1 levels below the 10th or above the 90th age- and sex-specific percentile, compared to subjects with intermediate IGF1 levels, were 1.44 (95% confidence interval (CI) 1.07–1.94) and 1.55 (95% CI 1.06–2.06) respectively, after multiple adjustment. After further adjustment for metabolic parameters, the HR for low-IGF1 became insignificant. Analysis of IGF1 quintiles revealed a U-shaped association of IGF1 with risk of diabetes. Results remained similar after exclusion of patients with onset of new diabetes within 1 year or with borderline glucose or HbA1c levels at baseline. Conclusions: Subjects with low- or high-IGF1 level are at increased risk of developing diabetes.

Background: There is a lack of the generic data comparing the influence of different diseases on health-related quality of life (HrQoL) in a representative sample of primary care patients. Methods: Patient data were collected in the DETECT (Diabetes Cardiovascular Risk Evaluation: Targets and Essential Data for Commitment of Treatment) study including 55,000 patients. Results: 3,109 patients (33.3% female) with myocardial infarction (MI), stroke or both were compared to patients with a wide range of other diagnoses. Stroke and MI patients revealed a lower HrQoL as compared to patients with other diagnoses. Stroke was associated with strongest quality of life reduction. Multivariate analysis revealed several different determining factors. Conclusions: The reduction of HrQoL of patients with MI and stroke is primarily determined by the CNS insult. These data provide further evidence that early diagnosis and treatment of cardiovascular risk factors is essential to reduce subsequent stroke.