Effect of a continuous diabetes lifestyle intervention program on male workers in Korea

Kang, Ji Yeon; Cho, Sang Woon; Sung, Sook Hee; Park, Yoo Kyoung; Paek, Yun Mi; Choi, Tae In

doi:10.1016/j.diabres.2010.06.006

Cited by 22 publications

(37 citation statements)

References 39 publications

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“…The guidelines were derived from evidence accumulated from RCTs, meta-analyses, and observational studies that were evaluated for quality. 164,202,228,[236][237][238][239] Of these, only 3 studies were of sufficient quality to include here. Because of the limited number of studies using mHealth as part of the intervention to target improved lipids, we included studies reporting lipid as a secondary outcome in Table 7.…”

Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

Burke¹,

Ma²,

Azar³

et al. 2015

Circulation

477

389

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A lthough mortality for cardiovascular disease (CVD) has declined for several decades, heart disease and stroke continue to be the leading causes of death, disability, and high healthcare costs. Unhealthy behaviors related to CVD risk (eg, smoking, sedentary lifestyle, and unhealthful eating habits) remain highly prevalent. The high rates of overweight, obesity, and type 2 diabetes mellitus (T2DM); the persistent presence of uncontrolled hypertension; lipid levels not at target; and the ≈18% of adults who continue to smoke cigarettes pose formidable challenges for achieving improved cardiovascular health.1,2 It is apparent that the performance of healthful behaviors related to the management of CVD risk factors has become an increasingly important facet of the prevention and management of CVD. 3In 2010, the American Heart Association (AHA) made a transformative shift in its strategic plan and added the concept of cardiovascular health.2 To operationalize this concept, the AHA targeted 4 health behaviors in the 2020 Strategic Impact Goals: reduction in smoking and weight, healthful eating, and promotion of regular physical activity. Three health indicators also were included: glucose, blood pressure (BP), and cholesterol. On the basis of the AHA Life's Simple 7 metrics for improved cardiovascular health, <1% of adults in the United States follow a healthful eating plan, only 32% have a normal body mass index, and > 30% have not reached the target levels for lipids or BP. National Health and Nutrition Examination Survey (NHANES) data revealed that people who met ≥6 of the cardiovascular health metrics had a significantly better risk profile (hazard ratio for all-cause mortality, 0.49) compared with individuals who had achieved only 1 metric or none.2 The studies reviewed in this statement targeted these behaviors (ie, smoking, physical activity, healthful eating, and maintaining a healthful weight) and cardiovascular health indicators (ie, blood glucose, lipids, BP, body mass index) as the primary outcomes in the clinical trials testing mobile health (mHealth) interventions.eHealth, or digital health, is the use of emerging communication and information technologies, especially the Internet, to improve health and health care 4 (Table 1). mHealth, a subsegment of eHealth, is the use of mobile computing and communication technologies (eg, mobile phones, wearable sensors) for health services and information.4,5 mHealth technology uses techniques and advanced concepts from an array of disciplines, for example, computer science, electrical and

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Section: Use Of Mhealth In Management Of Dyslipidemiamentioning

confidence: 99%

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

Burke¹,

Ma²,

Azar³

et al. 2015

Circulation

477

389

View full text Add to dashboard Cite

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“…Multi-component studies appeared to be more effective, as all 4 studies (2 trials and 2 pre-post studies) found significant associations between their intervention and outcomes[29]–[32].…”

Section: Resultsmentioning

confidence: 99%

“…Among the randomized studies, 16 were largely internet-based[13]–[28], while the other 2 were multi-component studies[29], [30]. Similarly, 2 of the 10 interventions (11 studies) in the pre-post group had multiple components[31], [32], while the others were largely internet-based [12], [33]–[40].…”

Section: Resultsmentioning

confidence: 99%

“…In all, twenty studies reported on weight, BMI/obesity, waist circumference, skin fold thickness, and body fat changes of which 15 were high quality studies and 5 were of low-quality. Among the high quality studies, less than half (7) reported significant improvement in any weight related outcome[12], [14], [16], [22], [23], [26], [29]. The same number of high quality studies reported no significant change in the outcomes[15], [17], [20], [21], [24], [25], [27] while the last high quality study reported worsening of the outcome, in this case an increase in body fat[28].…”

Section: Resultsmentioning

confidence: 99%

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A Systematic Review of Internet-Based Worksite Wellness Approaches for Cardiovascular Disease Risk Management: Outcomes, Challenges & Opportunities

et al. 2014

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ContextThe internet is gaining popularity as a means of delivering employee-based cardiovascular (CV) wellness interventions though little is known about the cardiovascular health outcomes of these programs. In this review, we examined the effectiveness of internet-based employee cardiovascular wellness and prevention programs.Evidence AcquisitionWe conducted a systematic review by searching PubMed, Web of Science and Cochrane library for all published studies on internet-based programs aimed at improving CV health among employees up to November 2012. We grouped the outcomes according to the American Heart Association (AHA) indicators of cardiovascular wellbeing – weight, BP, lipids, smoking, physical activity, diet, and blood glucose.Evidence SynthesisA total of 18 randomized trials and 11 follow-up studies met our inclusion/exclusion criteria. Follow-up duration ranged from 6 – 24 months. There were significant differences in intervention types and number of components in each intervention. Modest improvements were observed in more than half of the studies with weight related outcomes while no improvement was seen in virtually all the studies with physical activity outcome. In general, internet-based programs were more successful if the interventions also included some physical contact and environmental modification, and if they were targeted at specific disease entities such as hypertension. Only a few of the studies were conducted in persons at-risk for CVD, none in blue-collar workers or low-income earners.ConclusionInternet based programs hold promise for improving the cardiovascular wellness among employees however much work is required to fully understand its utility and long term impact especially in special/at-risk populations.

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“…The web-based lifestyle intervention was developed based on a previous study (16) and guidelines (17, 18). It is detailed in Fig.…”

Section: Methodsmentioning

confidence: 99%

Impact of ENPP1 K121Q on Change of Insulin Resistance after Web-Based Intervention in Korean Men with Diabetes and Impaired Fasting Glucose

Kang¹,

Sung²,

Lee³

et al. 2014

J Korean Med Sci

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Ectoenzyme nucleotide pyrophosphate phosphodiesterase 1 (ENPP1) gene has been studied in relation to type 2 diabetes mellitus (T2DM) and insulin resistance (IR). We hypothesized that the difference in genotype may be one of the factors that affect the outcome of intervention. We genotyped 448 men with fasting glucose≥5.6 mM/L, including 371 in subjects with K allele (KK) (69 control group [CG]; and 302 intervention group [IG]) and 77 in subjects with Q allele (KQ+QQ) (13 CG and 64 IG). The web-based intervention based on a lifestyle modification was delivered by e-mail once a month for 10 months. In the KK, IG demonstrated significantly decreased levels of fasting serum insulin (FSI) as compared to CG and homeostasis model of assessment of insulin resistance (HOMA-IR). In the KQ+QQ IG group, hemoglobin A1c (HbA1c), FSI and HOMA-IR were significantly decreased, and showed further reduction in the HOMA-IR than KQ+QQ CG. After analysis of covariance, K121Q did significantly influence the change of HbA1c in CG after appropriate adjustment. In a multivariate model, BMI change predicted HOMA-IR change (adjusted β=0.801; P=0.022) in KK IG subjects with T2DM. ENPP1 K121Q did not influence the change in IR. However, individuals with T2DM carrying the K121 variant are very responsive to the effect of BMI reduction on HOMA-IR.Graphical Abstract

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Effect of a continuous diabetes lifestyle intervention program on male workers in Korea

Cited by 22 publications

References 39 publications

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention

A Systematic Review of Internet-Based Worksite Wellness Approaches for Cardiovascular Disease Risk Management: Outcomes, Challenges & Opportunities

Impact of ENPP1 K121Q on Change of Insulin Resistance after Web-Based Intervention in Korean Men with Diabetes and Impaired Fasting Glucose

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