The findings of DETECT underline the considerable burden for primary care doctors in managing a highly morbid patient population, with predominantly complex risk factor constellations, in routine care. Our data provide, in unprecedented detail, a basis for calculating age-, gender- and risk-group-adjusted risk-factor profiles in routine care.
BACKGROUND:In contrast to the well-documented high prevalence of overweight and obesity in the general population, the prevalence, recognition rates and management by primary care physiciansFas the core gatekeeper in the health care systemFremains poorly studied. PURPOSE OF THE STUDY: To examine (1) the point prevalence of overweight (BMI 25.0-29.9 kg/m 2 ) and obesity (BMIZ30 kg/ m 2 ) in primary care patients, (2) prevalence patterns in patients with high-risk constellations (diabetes, hypertension, cardiovascular disease, etc.), (3) doctors' recognition and interventions, as well as patients' use and perceived effectiveness of weight-loss interventions and (4) factors associated with non-treatment. METHODS: Cross-sectional point prevalence study of 45 125 unselected consecutive primary care attendees recruited from a representative nationwide sample of 1912 primary care practices. Measures: (1) standardized clinical appraisal of each patient by the physician (diagnostic status and recognition, severity, comorbidity, current and past interventions). (2) Patient self-report questionnaire: height and weight, illness history, past and current treatments and their perceived effectiveness, health attitudes and behaviors. RESULTS: (1) In all, 37.9% of all primary care attendees were overweight, 19.4% obese. (2) Rates for overweight and obesity were highest in patients with diabetes (43.6 and 36.7%) and hypertension (46.1 and 31.3%), followed by patients with cardiovascular disorders. Rates of overweight/obesity increased steadily by the number of comorbid conditions. (3) Doctors' recognition of overweight (20-30%) and obesity (50-65%) was low, patients' actual use of weight control interventions even lower (past 12 months: 8-11%, lifetime: 32-39%). Patient success rates were quite limited. (4) Co-and multimorbidity in particular as well as other patient and illness variables were identified as predictors for recognition, but prediction of patients' actual use of weight loss interventions was limited. CONCLUSIONS: Primary care management of overweight and obesity is largely deficient, predominantly due to four interrelated factors: doctors' poor recognition of patients' weight status, doctors' inefficient efforts at intervention, patients' poor acceptance of such interventions and dissatisfaction with existing life-style modification strategies.
Objective: We aimed at investigating the association of age-dependent IGF-I SDS with diabetes, dyslipidemia, hypertension, and heart diseases, in a large patient sample. Background: IGF-I has been suggested to be associated with several diseases and a prognostic marker for the development of cardiovascular diseases and risk factors. The findings, though, have been inconsistent possibly due to the methodological factors. Methods: We studied 6773 consecutive primary care patients, aged 18C years, in a cross-sectional, epidemiological study in primary care, Diabetes Cardiovascular Risk-Evaluation: Targets and Essential Data for Commitment of Treatment study. All patients underwent a standardized clinical diagnostic and laboratory assessment. IGF-I levels were measured with an automated chemiluminescence assay system. We calculated the odds ratios (OR) for diseases in quintiles of IGF-I, and additionally analyzed the association of age-dependent IGF-I SDS with these conditions. Results: After multiple adjustments for confounders, we found increased ORs for coronary artery disease in patients with high IGF-I. Women, but not men, with low IGF-I also showed increased ORs for coronary artery disease. Dyslipidemia was positively associated with IGF-I. Type 2 diabetes showed a curvilinear association with IGF-I SDS. Conclusions: The findings suggest the existence of multiple and complex interactions between IGF-I and several health conditions. The complex nature of disease-and subgroup-specific associations along with the methodological factors can be held responsible for divergent findings in previous studies.
European Journal of Endocrinology 158 153-161
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