Background: Obstructive sleep apnea (OSA) is a common yet underdiagnosed condition. The aim of our study is to test whether prediabetes and type 2 diabetes are associated with obstructive sleep apnea (OSA) in extremely obese (BMI ≥ 40 kg/m²) subjects.
Methods: One hundred and thirty seven consecutive extremely obese patients (99 females) from a controlled clinical trial [MOBIL-study (Morbid Obesity treatment, Bariatric surgery versus Intensive Lifestyle intervention Study) (ClinicalTrials.gov number NCT00273104)] underwent somnography with Embletta® and a 2-hour oral glucose tolerance test (OGTT). OSA was defined by an apnea-hypopnea index (AHI) ≥ 5 events/hour. Patients were categorized into three groups according to criteria from the American Diabetes Association: normal glucose tolerance, pre-diabetes and type 2 diabetes. Multiple logistic regression analysis was used to identify possible determinants of OSA.
Results: The patients had a mean (SD) age of 43 (11) years and a body mass index (BMI) of 46.9 (5.7) kg/m². Males had significantly higher AHI than females, 29 (25) vs 12 (17) events/hour, p < 0.001. OSA was observed in 81% of men and in 55% of women, p = 0.008. Twenty-nine percent of subjects had normal glucose tolerance, 42% had pre-diabetes and 29% had type 2 diabetes. Among the patients with normal glucose tolerance 33% had OSA, while 67% of the pre-diabetic patients and 78% of the type 2 diabetic patients had OSA, p < 0.001. After adjusting for age, gender, BMI, high sensitive CRP and HOMA-IR, both pre-diabetes and type 2 diabetes were still associated with OSA, odds ratios 3.18 (95% CI 1.00, 10.07), p = 0.049 and 4.17 (1.09, 15.88), p = 0.036, respectively. Mean serum leptin was significantly lower in the OSA than in the non-OSA group, while other measures of inflammation did not differ significantly between groups.
Conclusions: Type 2 diabetes and pre-diabetes are associated with OSA in extremely obese subjects.
Trial Registration: MOBIL-study (Morbid Obesity treatment, Bariatric surgery versus Intensive Lifestyle intervention Study) (ClinicalTrials.gov number NCT00273104).
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http://dx.doi.org/10.1186/1475-2840-10-84 | DOI Listing |
Health Place
January 2025
Department of Forest Resources Management, Faculty of Forestry, University of British Columbia, Vancouver, V6T 1Z4, Canada. Electronic address:
The engagement of senior citizens with urban nature has been shown to provide multiple health benefits and mitigate health issues associated with demographic aging. This review utilized the PRISMA methodology to systematically analyze the relationship between monitoring tools, seniors' behaviors in urban nature, and influencing factors. The main findings are as follows: (1) 4 main types, including self-reports, on-site observations, sensors, and third-party data, and 24 sub-types of measurement tools: ranging from questionnaires to crowdsourced imagery services.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Diabetes Management Research, Steno Diabetes Center Copenhagen, Herlev, Denmark.
Background: Although commercially developed automated insulin delivery (AID) systems have recently been approved and become available in a limited number of countries, they are not universally available, accessible, or affordable. Therefore, open-source AID systems, cocreated by an online community of people with diabetes and their families behind the hashtag #WeAreNotWaiting, have become increasingly popular.
Objective: This study focused on examining the lived experiences, physical and emotional health implications of people with diabetes following the initiation of open-source AID systems, their perceived challenges, and their sources of support, which have not been explored in the existing literature.
Diabetes Care
January 2025
Department of Medicine, University of California San Diego, La Jolla, CA.
Objective: Plasma metabolite profiling has uncovered several nonglycemic markers of incident type 2 diabetes (T2D). We investigated whether such biomarkers provide information about specific aspects of T2D etiology, such as impaired fasting glucose and impaired glucose tolerance, and whether their association with T2D risk varies by race.
Research Design And Methods: Untargeted plasma metabolite profiling was performed of participants in the FINRISK 2002 cohort (n = 7,564).
Diabetes
January 2025
Adelaide Medical School and Centre of Research Excellence (CRE) in Translating Nutritional Science to Good Health, The University of Adelaide, Adelaide, Australia.
Individuals with type 2 diabetes are at high risk of postprandial falls in blood pressure (BP) (i.e., a reduction in systolic BP of ≥20mmHg, termed postprandial hypotension (PPH)), which increases the risk of falls and mortality.
View Article and Find Full Text PDFDiabetes
January 2025
Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Circulating proteins may be promising biomarkers or drug targets. Leveraging genome-wide association studies of type 1 diabetes (18,942 cases and 501,638 controls of European ancestry) and circulating protein abundances (10,708 European ancestry individuals), Mendelian randomization analyses were conducted to assess the associations between circulating abundances of 1,560 candidate proteins and the risk of type 1 diabetes, followed by multiple sensitivity and colocalization analyses, horizontal pleiotropy examinations, and replications. Bulk tissue and single-cell gene expression enrichment analyses were performed to explore candidate tissues and cell types for prioritized proteins.
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