RAPID REPORTS Population and social conditions. Pupils and students in the Community in 1990/91. 1993.9

<div><p>It is known that the macronutrient content of a meal has different impacts on the postprandial satiety and appetite hormonal responses. Whether obesity interacts with such nutrient-dependent responses is not well characterized. We examined the postprandial appetite and satiety hormonal responses after a high-protein (HP), high-carbohydrate (HC), or high-fat (HF) mixed meal. This was a randomized cross-over study of 9 lean insulin-sensitive (mean±SEM HOMA-IR 0.83±0.10) and 9 obese insulin-resistant (HOMA-IR 4.34±0.41) young (age 21–40 years), normoglycaemic Chinese men. We measured fasting and postprandial plasma concentration of glucose, insulin, active glucagon-like peptide-1 (GLP-1), total peptide-YY (PYY), and acyl-ghrelin in response to HP, HF, or HC meals. Overall postprandial plasma insulin response was more robust in the lean compared to obese subjects. The postprandial GLP-1 response after HF or HP meal was higher than HC meal in both lean and obese subjects. In obese subjects, HF meal induced higher response in postprandial PYY compared to HC meal. HP and HF meals also suppressed ghrelin greater compared to HC meal in the obese than lean subjects. In conclusion, a high-protein or high-fat meal induces a more favorable postprandial satiety and appetite hormonal response than a high-carbohydrate meal in obese insulin-resistant subjects.</p></div

The average and standard deviation of the blood pressure, glycemia and lipid profiles as well as renal function of the male and female subjects.

<p>The average and standard deviation of the blood pressure, glycemia and lipid profiles as well as renal function of the male and female subjects.</p

Age-Related Changes in the Cardiometabolic Profiles in Singapore Resident Adult Population: Findings from the National Health Survey 2010

<div><p>We describe the centile trends of the blood pressure, glycemia and lipid profiles as well as renal function of a representative population who participated in the Singapore National Health Survey in 2010. Representative survey population was sampled in two phases, first using geographical/ residential dwelling type stratification, followed up ethnicity. 2,407 survey participants without any self-reported medical or medication history for diabetes mellitus, hypertension and dyslipidemia were included in this analysis. All biochemistry analyses were performed on Roche platforms. After excluding outliers using Tukey's criteria, the results of the remaining participants were subjected to lambda-mu-sigma (LMS) analysis. In men, systolic blood pressure increased linearly with age. By contrast, an upward inflection around late 40s was seen in women. The diastolic blood pressure was highest in men in the late 30s-50s age group, and in women in the late 50s-60s age group. All glycemia-related parameters, i.e. fasting and 2-hour plasma glucose and HbA1c concentrations increased with age, although the rate of increase differed between the tests. Total cholesterol and LDL-cholesterol concentrations increased with age, which became attenuated between the early 30s and late 50s in men, and declined thereafter. In women, total cholesterol and LDL-cholesterol concentrations gradually increased with age until late 30s, when there is an upward inflection, plateauing after late 50s. Our findings indicate that diagnostic performance of laboratory tests for diabetes may be age-sensitive. Unfavourable age-related cardiovascular risk profiles suggest that the burden of cardiovascular disease in this population will increase with aging population.</p></div

Box plots showing the participants’ (A) ability to determine if the adjustment of treatment was required, (B) average time (in minutes) spent on each case, (C) perceived confidence before and after completing the survey using the mock CPSS2 interface, (D) perceived confidence before and after completing the survey using the mock CPSS2 interface, using either interface.

<p>The exact question asked in the survey is shown in the title of the graphs. ** denotes <i>p</i><0.05, **** denotes <i>p</i><0.0001.</p

A screenshot of the summary dashboard, alerts, table and interactive graphs in the Diabetes Dashboard.

<p>An example of the hover tool is shown, displaying the test result of the individual point in the HbA_1c graph when the mouse hovers over it (circled in red).</p

Treatment targets for each laboratory marker related to diabetes care, and their assigned color codes.

<p>Treatment targets for each laboratory marker related to diabetes care, and their assigned color codes.</p

An example of the lipid panel displayed in the mock CPSS2 interface.

<p>An example of the lipid panel displayed in the mock CPSS2 interface.</p