To determine rates and predictors of postpartum diabetes screening among Aboriginal and/or Torres Strait Islander and non-Indigenous women with gestational diabetes mellitus (GDM).
Abstract Epidemiological studies often rely on self‐reported cardiovascular disease (CVD) information, but this may be inaccurate. We investigated the accuracy of self‐reported CVD (myocardial infarction, stroke, coronary artery bypass surgery and coronary artery angioplasty) during the follow up of the Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Self‐reported CVD events, including the date of the event and hospital admission details, were collected with an interviewer‐administered questionnaire. Of the 276 self‐reported CVD events, 188 (68.1%) were verified by adjudication of medical records. Furthermore, linkage to the statewide Western Australian Hospital Morbidity Database (WAHMD) showed that CVD events were unlikely to be missed, with only 0.2% of those denying any CVD event being recorded as having had an event on the WAHMD. The adjudication of medical records was as accurate as record linkage to the WAHMD for validation of self‐reported CVD, but combining the results from both methods of ascertainment improved CVD event identification.
The prevalence of cardiometabolic multimorbidity is increasing.
Objective
To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.
Design, Setting, and Participants
Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689 300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128 843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499 808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates.
Exposures
A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).
Main Outcomes and Measures
All-cause mortality and estimated reductions in life expectancy.
Results
In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.
Conclusions and Relevance
Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.
Genetically encoded biosensors can be used to track signaling events in living cells by measuring changes in fluorescence emitted by one or more fluorescent proteins. Here, we describe the use of genetically encoded biosensors based on Förster resonance energy transfer (FRET), combined with high-content microscopy, to image dynamic signaling events simultaneously in thousands of neurons in response to drug treatments. We first applied this approach to examine intercellular variation in signaling responses among cultured striatal neurons stimulated with multiple drugs. Using high-content FRET imaging and immunofluorescence, we identified neuronal subpopulations with unique responses to pharmacological manipulation and used nuclear morphology to identify medium spiny neurons within these heterogeneous striatal cultures. Focusing on protein kinase A (PKA) and extracellular signal-regulated kinase 1/2 (ERK1/2) signaling in the cytoplasm and nucleus, we noted pronounced intercellular differences among putative medium spiny neurons, in both the magnitude and kinetics of signaling responses to drug application. Importantly, a conventional “bulk” analysis that pooled all cells in culture yielded a different rank order of drug potency than that revealed by single-cell analysis. Using a single-cell analytical approach, we dissected the relative contributions of PKA and ERK1/2 signaling in striatal neurons and unexpectedly identified a novel role for ERK1/2 in promoting nuclear activation of PKA in striatal neurons. This finding adds a new dimension of signaling crosstalk between PKA and ERK1/2 with relevance to dopamine D1 receptor signaling in striatal neurons. In conclusion, high-content single-cell imaging can complement and extend traditional population-level analyses and provides a novel vantage point from which to study cellular signaling.
SIGNIFICANCE STATEMENT
High-content imaging revealed substantial intercellular variation in the magnitude and pattern of intracellular signaling events driven by receptor stimulation. Since individual neurons within the same population can respond differently to a given agonist, interpreting measures of intracellular signaling derived from the averaged response of entire neuronal populations may not always reflect what happened at the single-cell level. This study uses this approach to identify a new form of cross-talk between PKA and ERK1/2 signaling in the nucleus of striatal neurons.
To investigate pedometer-measured physical activity (PA) in 2000 and change in PA over 5 years with subsequent risk of dysglycemia by 2005.This prospective cohort study in Tasmania, Australia, analyzed 458 adults with normal glucose tolerance and a mean (SD) age of 49.7 (12.1) years in 2000. Variables assessed in 2000 and 2005 included PA, by pedometer and questionnaire, nutrient intake, and other lifestyle factors. Incident dysglycemia was defined as the development of impaired fasting glucose or impaired glucose tolerance revealed by oral glucose tolerance testing in 2005, without type 2 diabetes.Incident dysglycemia developed in 26 participants during the 5-year period. Higher daily steps in 2000 were independently associated with a lower 5-year risk of incident dysglycemia (adjusted odds ratio [AOR] 0.87 [95% CI 0.77-0.97] per 1,000-step increment). Higher daily steps in 2005, after controlling for baseline steps in 2000 (thus reflecting change in steps over 5 years), were not associated with incident dysglycemia (AOR 1.02 [0.92-1.14]). Higher daily steps in 2000 were also associated with lower fasting blood glucose, but not 2-h plasma glucose by 2005. Further adjustment for BMI or waist circumference did not remove these associations.Among community-dwelling adults, a higher rate of daily steps is associated with a reduced risk of incident dysglycemia. This effect appears to be not fully mediated through reduced adiposity.
Achieving a healthier balance of more time spent in physical activity (PA) and less time in sedentary behavior is now widely advocated for achieving multiple health benefits. This study introduces a Physical Activity and Sitting Time Balance Index (PASTBI), a potential risk identification tool addressing the interplay between PA and sedentary behavior; and aims to explore its association with the risk of all-cause mortality in Australian adults.
PURPOSE: Television (TV) viewing time is associated with increased risk of all cause, cardiovascular disease (CVD) and cancer mortality. However, a large proportion of deaths are due to non-cancer or CVD causes. Prolonged sitting time is associated with high C-reactive protein levels, suggesting that sitting may be associated with chronic inflammation. We examined the associations of TV viewing time with non-cancer or CVD, inflammatory-related mortality in Australian adults. METHODS: Baseline (1999/2000) TV viewing time in relation to inflammatory-related mortality (with an inflammatory, oxidative or infectious component as the predominant underlying pathophysiology1) was examined among 9290 adults from the Australian Diabetes, Obesity and Lifestyle Study, who at baseline were ≥25 years of age and did not report previous myocardial infarction or stroke. Baseline data was used to categorise participant smoking status. RESULTS: Over a median of 7.5 years, 99 of 705 deaths were classified as non-cancer or CVD, inflammatory-related. In the fully adjusted model (age, sex, education, fasting lipids, angina, hypertension, lipid medication, diabetes status, diet quality, waist circumference, energy intake, alcohol, smoking status and physical activity) the inflammatory-related mortality hazard ratios (HRs) compared to TV viewing of <2 h/d were: 1.25 (95% CI 0.78 to 2.01) for ≥2 to <4 h/d, and 2.07 (1.18 to 3.61) for ≥4 h/d. A sensitivity analysis was performed, removing ex-smokers and smokers. A significant effect of high TV viewing time on inflammatory-related mortality remained for non-smokers (n=5016; 51 deaths): compared to <2 h/d of TV viewing time, the fully adjusted HRs for inflammatory-related mortality were 1.65 (95% CI 0.85 to 3.19) for ≥2 to <4 h/d and 3.10 (1.36 to 7.03) for ≥4 h/d. CONCLUSION: TV viewing time was significantly associated with increased risk of non-cancer or CVD, inflammatory-related mortality in the overall study population, and in non-smokers. This is consistent with the hypothesis that high TV viewing is associated with a chronic inflammatory state, and provides further observational evidence that, in addition to promoting physical activity, chronic disease prevention strategies should focus on reducing prolonged sitting time. 1 Andersen et al., 2006. Am J Clin Nutr, 83:1039-46
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