Predicting diabetes-related conditions in need of intervention: Lolland-Falster Health Study, Denmark

In the Danish population, about one-in-ten adults have prediabetes, undiagnosed, poorly or potentially sub-regulated diabetes, for short DMRC. It is important to offer these citizens relevant healthcare intervention. We therefore built a model for prediction of prevalent DMRC.Data were derived from the Lolland-Falster Health Study undertaken in a rural-provincial area of Denmark with disadvantaged health. We included variables from public registers (age, sex, age, citizenship, marital status, socioeconomic status, residency status); from self-administered questionnaires (smoking status, alcohol use, education, self-rated health, dietary habits, physical activity); and from clinical examinations (body mass index (BMI), pulse rate, blood pressure, waist-to-hip ratio). Data were divided into training/testing datasets for development and testing of the prediction model.The study included 15,801 adults; of whom 1,575 with DMRC. Statistically significant variables in the final model included age, self-rated health, smoking status, BMI, waist-to-hip ratio, and pulse rate. In the testing dataset this model had an area under the curve (AUC) = 0.77 and a sensitivity of 50% corresponding to a specificity of 84%.In a health disadvantaged Danish population, presence of prediabetes, undiagnosed, or poorly or potentially sub-regulated diabetes could be predicted from age, self-rated health, smoking status, BMI, waist-to-hip ratio, and pulse rate. Age is known from the Danish personal identification number, self-rated health and smoking status can be obtained from simple questions, and BMI, waist-to-hip ratio, and pulse rate can be measured by any person in health care and potentially by the person him/her-self. Our model might therefore be useful as a screening tool

Correlation between allostatic load index and cumulative mortality: a register-based study of Danish municipalities

Objectives The aim of this study was to examine population-based allostatic load (AL) indices as an indicator of community health across 14 municipalities in Denmark.Design Register-based study.Setting Data derived from: the Lolland-Falster Health Study, the Copenhagen General Population Study and the Danish General Suburban Population Study. Nine biomarkers (systolic blood pressure, diastolic blood pressure, pulse rate, total serum cholesterol, high-density lipoprotein cholesterol, waist-to-hip ratio, triglycerides, C-reactive protein and serum albumin) were divided into high-risk and low-risk values based on clinically accepted criteria, and the AL index was defined as the average between the nine values. All-cause mortality data were obtained from Statistics Denmark.Participants We examined a total of 106 808 individuals aged 40–79 years.Primary outcome measure Linear regression models were performed to investigate the association between mean AL index and cumulative mortality risk.Results Mean AL index was higher in men (range 2.3–3.3) than in women (range 1.7–2.6). We found AL index to be strongly correlated with the cumulative mortality rate, correlation coefficient of 0.82. A unit increase in mean AL index corresponded to an increase in the cumulative mortality rate of 19% (95% CI 13% to 25%) for men, and 16% (95% CI 8% to 23%) for women but this difference was not statistically significant. The overall mean increase in cumulative mortality rate for both men and women was 17% (95% CI 14% to 20%).Conclusions Our findings indicate the population-based AL index to be a strong indicator of community health, and suggest identification of targets for reducing AL