Number of individuals and prevalence of being at increased cardiometabolic risk in individuals whose %BF is above and below the sex-specific threshold, stratified by BMI and sex.

<p>%BF = percentage body fat; BMI = body mass index.</p><p>Number of individuals and prevalence of being at increased cardiometabolic risk in individuals whose %BF is above and below the sex-specific threshold, stratified by BMI and sex.</p

Crude and adjusted odds ratios (OR), with 95% confidence intervals, of being at increased cardiometabolic risk with %BF above and below sex-specific thresholds (25.9% for men, 37.1% for women) and BMI <25 kg/m², 25−<30 kg/m² and ≥30 kg/m² compared with %BF<25.9/37.1% and BMI <25 kg/m².

<p>%BF  =  percentage body fat; BMI  =  body mass index.</p><p>*adjusted for age and smoking status.</p><p>Crude and adjusted odds ratios (OR), with 95% confidence intervals, of being at increased cardiometabolic risk with %BF above and below sex-specific thresholds (25.9% for men, 37.1% for women) and BMI <25 kg/m², 25−<30 kg/m² and ≥30 kg/m² compared with %BF<25.9/37.1% and BMI <25 kg/m².</p

Bland-Altman plots showing the limits of agreement between percentage body fat measured by bioimpedance analysis (%BF_BIA) and percentage body fat measured by dual-energy X-ray absorptiometry (%BF_DXA) in men (a, n = 363) and women (b, n = 596).

<p>Mean difference is calculated by %BF_BIA-%BF_DXA and the limits of agreement are calculated by mean difference ± two standard deviations. The solid line represents the mean difference and the dashed lines represent the limits of agreement.</p

Characteristics of study population, stratified by sex.

<p>Values are reported as mean ± standard deviation, except BMI, glucose and triglycerides which are reported as median (interquartile range). Increased cardiometabolic risk is defined as having diabetes and/or the metabolic syndrome. Proportions are reported for hypertension medication, increased metabolic risk, type 2 diabetes, metabolic syndrome and smoking status as n (%). %BF = percentage body fat; BMI = body mass index; DBP = diastolic blood pressure; HDL = high density lipoprotein; SBP = systolic blood pressure; WC = waist circumference.</p><p>Characteristics of study population, stratified by sex.</p

Glucose measurement on admission by patient characteristics.

a<p>All figures are counts (%) except for hospital, for which the proportion with glucose measures across hospitals was summarised using the median (interquartile range) and [range].</p

3-year risk of type 2 diabetes by admission glucose.

<p>The solid line represents the estimate and the ribbon represents the 95% CI obtained from a logistic regression model of incident type 2 diabetes on glucose, glucose-squared, and glucose-cubed. Points represent the risk of diabetes for patients categorised according to admission glucose, with the x-axis indicating the mean glucose level and the point size indicating the number of patients for each category.</p

Baseline characteristics by admission glucose.

<p>All data are <i>n</i> (%) except age, which is reported as mean (standard deviation).</p><p>Elevated WCC, white cell count ≥11×10⁹/l.</p

Predicted 3-year risk of type 2 diabetes in patients admitted to ICU compared to patients not admitted to ICU.

<p>Estimates and 95% CIs were obtained from logistic regression models with ICU as an interaction term. The reference category for each risk ratio and risk difference was the risk for patients with admission glucose equal to 5 mmol/l.</p

3-year risk of type 2 diabetes by glucose, age, sex, and Scottish Index of Multiple Deprivation (SIMD) score: coefficients and odds ratios from logistic regression models.

<p>There were no statistically significant interactions (on the scale of the linear predictor) for any of these variables. The natural logarithm of glucose in mmol/l was used for all models. Glucose provided in mg/dl should be converted to mmol/l by dividing by 18. The 3-year risk of type 2 diabetes is the inverse logit of the linear predictor (sum of the relevant coefficients). For example, for a male patient aged 60 with a glucose of 5 mmol/l the risk of type 2 diabetes is calculated as follows:</p><p></p><p></p><p></p><p></p><p>Fitted values with standard errors and the model variance/covariance matrix are shown in Tables S8 and S9. We have also provided an online tool to carry out this calculation, which is available at <a href="http://www.cphs.mvm.ed.ac.uk/diabetes-risk/" target="_blank">www.cphs.mvm.ed.ac.uk/diabetes-risk/</a>.</p

Diabetes according to age, sex, and admission glucose from time to event analyses.

<p>csHR (95% CI) derived from Cox regression model. sdHR (95% CI) derived from Fine and Gray regression model. Estimates are presented for all variables included in the models.</p