Cardiovascular and metabolic risk profiles in young and old patients with type 2 diabetes

ObjectiveInvestigating the association between total physical activity, physical activity in different domains and sedentary time with clustered metabolic risk in patients with type 2 diabetes from Jiangsu province, China.DesignInterview-based cross-sectional study conducted between December 2013 and January 2014.Setting44 selected townships across two cities, Changshu and Huai’an, in Jiangsu province.Participants20 340 participants selected using stratified cluster-randomised sampling and an interviewer-managed questionnaire.MethodsWe constructed clustered metabolic risk by summing sex-specific standardised values of waist circumference, fasting triacylglycerol, fasting plasma glucose, systolic blood pressure and the inverse of blood high-density lipoprotein cholesterol (HDL-cholesterol). Self-reported total physical activity included occupation, commuting and leisure-time physical activity. The un-standardised regression coefficient [B] and its 95% CI were calculated using multivariate linear regression analyses.ResultsThis study included 17 750 type 2 diabetes patients (aged 21–94 years, 60.3% female). The total (B=−0.080; 95% CI: −0.114 to −0.046), occupational (B=−0.066; 95% CI: −0.101 to− 0.031) and leisure-time physical activity (B=−0.041; 95% CI: −0.075 to −0.007), and sedentary time (B=0.117; 95% CI: 0.083 to 0.151) were associated with clustered metabolic risk. Total physical activity, occupational physical activity and sedentary time were associated with waist circumference, triacylglycerol and HDL-cholesterol, but not with systolic blood pressure. Commuting physical activity and sedentary time were significantly associated with triacylglycerol (B=−0.012; 95% CI: −0.019 to −0.005) and fasting plasma glucose (B=0.008; 95% CI: 0.003 to 0.01), respectively. Leisure-time physical activity was only significantly associated with systolic blood pressure (B=−0.239; 95% CI: −0.542 to− 0.045).ConclusionsTotal, occupational and leisure-time physical activity were inversely associated with clustered metabolic risk, whereas sedentary time increased metabolic risk. Commuting physical activity was inversely associated with triacylglycerol. These findings suggest that increased physical activity in different domains and decreased sedentary time may have protective effects against metabolic risk in type 2 diabetes patients.

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Vitamin D Deficiency and Cardio-Metabolic Risk in a North Indian Community with Highly Prevalent Type 2 Diabetes

Journal of Diabetes & Metabolism ◽

10.4172/2155-6156.1000213 ◽

2012 ◽

Vol 03 (07) ◽

Cited By ~ 7

Author(s):

Timothy R Braun

Keyword(s):

Type 2 Diabetes ◽

Vitamin D ◽

Vitamin D Deficiency ◽

Metabolic Risk ◽

Indian Community

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Metabolic Syndrome and Ethnic Groups Second edition

10.26415/978-9931-9446-4-5 ◽

2021 ◽

Author(s):

Mohammadhosain Afrand ◽

Mohammad Afkhami-Ardekani ◽

Ahmad Shojaoddiny-Ardekani ◽

Azita Ariaeinejad

Keyword(s):

Physical Activity ◽

Risk Factors ◽

Type 2 Diabetes ◽

Metabolic Syndrome ◽

Preventive Measures ◽

Lifestyle Modification ◽

Treatment Strategies ◽

Subsequent Development ◽

Metabolic Risk

Metabolic syndrome is defined as the co-occurrence of metabolic risk factors for both type 2 diabetes and cardiovascular disease (i.e. abdominal obesity, hyperglycemia, dyslipidemia, and hypertension). Indeed, metabolic syndrome is an important risk factor for subsequent development of type 2 diabetes and/or CVD. Thus, the key clinical implication of a diagnosis of metabolic syndrome is the identification of a patient who needs aggressive lifestyle modification focused on weight reduction and increased physical activity. Multiple different phenotypes and ethnic-specific values for waist circumference are included within metabolic syndrome, with indications for differing treatment strategies. This book covers several aspects of metabolic syndrome, including its definition, diagnostic criteria, preventive measures, and treatment, as well as the possible association between ethnicity and the occurrence of metabolic syndrome.

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SUN-LB113 A Continuous Remote Care Intervention Utilizing Carbohydrate Restriction Including Nutritional Ketosis Improves Markers of Metabolic Risk and Reduces Diabetes Medication Use in Patients With Type 2 Diabetes Over 3.5 Years

Journal of the Endocrine Society ◽

10.1210/jendso/bvaa046.2302 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

Author(s):

Amy McKenzie ◽

Shaminie Athinarayanan ◽

Rebecca Adams ◽

Jeff Volek ◽

Stephen Phinney ◽

...

Keyword(s):

Type 2 Diabetes ◽

Nutrition Therapy ◽

Diabetes Remission ◽

Metabolic Risk ◽

Carbohydrate Restriction ◽

Diabetes Medication ◽

Care Intervention ◽

Remote Care

Abstract Novel lifestyle, pharmaceutical, and/or surgical therapies for type 2 diabetes (T2D) are under study to assess lasting impact on metabolic risk. Among them, carbohydrate restriction including nutritional ketosis (CR) has emerged as a safe and effective nutrition therapy for reducing hyperglycemia in patients with T2D1, yet longer term effects are unknown. At the conclusion of a 2-year study assessing a continuous remote care intervention utilizing CR (CCI) among patients who selected this therapy, intervention participants were offered the opportunity to consent to participate in a 3-year extension assessing outcomes at 3.5- and 5-y following initial enrollment. 143 of 169 extension-consented participants provided data at 3.5-y follow up. Among 3.5-y completers, linear mixed effects models were used to assess change over time in diabetes-related outcomes and McNemar’s tests were used to assess for a difference in the proportion of participants meeting certain criteria at baseline compared to follow-up. At enrollment, 3.5-y completers were (mean±SE) 55±1 y of age, 40.8±0.7 kg/m2, and 8±1 y since diagnosis. Following treatment with the CCI for 3.5 y, significant improvements compared to baseline were observed in HbA1c (-0.6±0.1 from 7.4±0.1%; P = 1.9x10-5), weight (-10.9±1.1 from 117.4 kg; P = 6.9x10-17), nonHDL-C (-10±4 from 139±3 mg/dL; P = 0.005), triglycerides (-41±11 from 189±10 mg/dl; P = 2.1x10-4), and HDL-C (+9±1 from 43±1 mg/dl; P = 3.0x10-11); total cholesterol and LDL-C were statistically unchanged. The percentage of participants prescribed diabetes medication decreased from 84.6 to 67.1% (P = 5.0x10-6), while 50.2% of diabetes medications and 71.4% of diabetes medications other than metformin were discontinued. The percentage of participants treated with no pharmaceuticals or monotherapy increased from 52.5 to 81.9% (P = 1.3x10-8). 45.5% (65/143) of participants achieved HbA1c <6.5% with either no medication (34/65, 52%) or only metformin (31/65, 48%) at 3.5 y; 37.8% of participants maintained this status from 1 through 3.5 y of treatment. 22% of participants achieved diabetes remission at 3.5 y, and 17.5% of participants maintained remission status from 2 through 3.5 y of treatment. This demonstrates that clinically meaningful improvements across multiple markers of metabolic risk can be sustained in patients with T2D who selected treatment with this CCI for 3.5 y. Improvements in metabolic risk markers reduced the need for diabetes medication, allowing some patients to achieve and sustain diabetes remission. This ongoing trial will assess 5-y effects. 1. American Diabetes Association. Standards of Medical Care in Diabetes. Diabetes Care. 2020; 43(Supplement 1): S48-S65. 2. Athinarayanan SJ, et al. Front Endocrinol. 2019; 10:348.

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