Effects of Lifestyle Modification and Anti-diabetic Medicine on Prediabetes Progress: A Systematic Review and Meta-Analysis

Sheng, Zhi; Cao, Jiayu; Pang, Ying-Chang; Xu, Honghao; Chen, Jingwen; Yuan, Junhua; Wang, Rui; Zhang, Cai-Shun; Dong, Jun

doi:10.3389/fendo.2019.00455

Cited by 44 publications

(32 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Multivariable linear regression analyses showed that the intervention has high difference of differences in LDL, Triglycerides, T.Cholestrol and fasting blood sugar (FBS). A similar positive effect of life style modi cation was reported on lipid pro les (40)(41) and blood sugar level (42). It was also observed that the difference in differences was lower by 30.5 mg/dl for LDL among males compared to females.…”

Section: Discussionsupporting

confidence: 75%

Effect of Behaviour Change Communication on Metabolic Syndrome and Its Markers among Ethiopian Adults: Randomized Controlled Trial

Sinaga

Lindstrom

Teshome

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Metabolic syndrome (MetS) is a global public health problem with dire consequences on health, social and economic development. In Ethiopia although MetS has been increasing since the past few decades, there is no study that evaluated the effect of interventions. This study aimed to assess the effect of nutrition behaviour change communication on MetS and its markers.Methods: An individually randomized controlled trial was conducted using a parallel design among Ethiopian adults working in Jimma University from of September 1, 2015 to January 15, 2016 for the intervention group. A sample size of 230 was calculated using GPower 3.0 assuming an effect size of 0.4, margin of error of 0.05, power of 81%, with an intervention to control ratio of 1. The eligibility criteria include: not having any physical disability and having baseline data.. Study population was randomly selected from eligible population (n=704) and allocated into intervention (n=115) and controls (n=115) groups using simple randomization method. The intervention arm was given behaviour change communication using power point presentation, facilitated group discussion on MetS and effective dietary and life style behaviours every month for three months. An Amharic language brochure was also given after the first training and a text message reminder about key behaviours was sent to each individual every two weeks. Data on background characteristic, anthropometry, and clinical parameters and blood samples were collected by trained data collectors in the Nutrition and Dietetic Laboratory of Jimma University. The laboratory analyses were done in Mettu Karl Hospital for lipid profiles and in JUCAN project laboratory for fasting blood sugar. Primary outcomes of the study were metabolic syndrome and its components. Difference in the differences of metabolic syndrome components between baseline and endline (end of intervention) were compared by the intervention status. Multivariable linear regression models were fitted to isolate independent predictors of difference in differences of metabolic syndrome components. A multivariable logistic regression model was used to identify preditors of MetS at the end line.Results: Overall, there was a significant difference (P<0.001) in the prevalence of MetS between intervention (11.6%) and control groups (37.5%) on the end line survey. On multivariable logistic regression analyses, control groups were 8.5 times more likely to have MetS compared to intervention groups (AOR=8.53, 95%CI: 3.60, 20.21, P <0.001). There was a significant mean difference in differences in most components of metabolic syndrome and other lipid profiles except HDL (P=0.717) in the intervention group. The mean difference in differences in waist circumference was 6.3 cm (P<0.001), while that of systolic blood pressure (BP) and diastolic BP were 6.1 mmHg (P< 0.001) and 3.6 mmHg (P=0.001), respectively. Likewise the difference of differences between intervention and control groups was 30.7 mg/dl (P<0.001) for T.Cholestrol, 55.5 mg/dl (P<0.001) for triglycerides, 21.9 mg/dl (P=0.015) for LDL and 22.2 mg/dl (P<0.001) for fasting blood sugar. Further multivariable linear regression analyses showed that after adjusting for many variables, there was a significant difference in difference between intervention groups in the components of MetS. For the intervention group the mean difference in differences was 6.1cm (β=6.1, P<0.001) for waist circumference and 4.2 mm Hg (β=4.2, P<0.05) for diastolic blood pressure and 6.5 mmHg (β=6.5, P<0.001) for systolic blood pressure compared with controls. Similarly, the mean difference in differences was higher in the intervention group by 19.9 mg/dl (β=19.9, P<0.05) for FBS, 57.5 mg/dl for TG (β=57.5, P<0.05), 24.40 mg/dl for LDL (β=24.4, P<0.05) and 30.9mg/dl for T.Cholestrol (β=30.9, P<0.001). This trial is retrospectively registered on Pan African Clinical Trial Registration with unique identification number of PACTR202003465339638.Conclusion: The study demonstrated that nutrition and life style behaviour change communication has a significant positive effect in reducing metabolic syndrome and its components. Although the study was conducted in an institutional set up, the results imply that enhancing such an interevention have a great potential to curb the emerging burden of chronic non-communicable diseases in Ethiopia. Future research should examine how sustainable such behaviour changes are using a community based study.

show abstract

Section: Discussionsupporting

confidence: 75%

Effect of Behaviour Change Communication on Metabolic Syndrome and Its Markers among Ethiopian Adults: Randomized Controlled Trial

Sinaga

Lindstrom

Teshome

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…It is known that IFG is pre-diabetes [19] , and the prevalence of IFG in this study was 11.95%, which is slightly lower than diabetes mellitus. If they are not taken seriously, it is easy for them to further develop into diabetes, which in turn increases the prevalence of diabetes.…”

Section: Discussionmentioning

confidence: 57%

Prevalence and Risk Factors of Diabetes Mellitus in People over 40 Years Old in Rural Areas of Central Hunan Province

Liao

Xiao

et al. 2020

Preprint

View full text Add to dashboard Cite

Objective To explore the prevalence of diabetes mellitus in rural areas of central Hunan province, and to analyze the risk factors related to diabetes mellitus (DM). Methods A cross-sectional study was conducted by using questionnaires (gender, age, occupation, degree of education, exercise habits, smoke status, alcohol consumption, hypertension, cardiovascular disease, family history of diabetes), anthropometric measurements (height, weight, waist circumference, blood pressure) and biochemical indexes test (fasting blood-glucose, glycosylated hemoglobin, blood lipids). Villagers over 40 years old from a community in rural areas of central Hunan Province were investigated. Results A total of 410 clinical data were collected. The prevalence of diabetes mellitus in 410 (177 in male and 233 in female) villagers was 13.41%, including 13 males with a prevalence rate of 7.34% and 42 females with a prevalence rate of 15.16%. The prevalence of impaired fasting glucose (IFG) was 11.95%, 21 males (11.86% of males) and 28 females (10.11% of females). And the results of glycosylated hemoglobin test showed that 64% villagers with diabetes mellitus had hemoglobin A1c(HbA1c) above 6.5%. Univariate analysis suggested that gender, smoke status, alcohol consumption, family history of diabetes mellitus, hypercholesterolemia and hypertension were involved in diabetes mellitus (P<0.05). Multivariate logistic regression analysis showed that family history of diabetes (OR: 1.759; 95% CI: 1.010-3.065), hypercholesterolemia (OR: 3.819; 95% CI: 1.27-11.486) and hypertension (OR: 2.074; 95% CI: 1.130-3.809) were independent risk factors for diabetes mellitus, and the differences were statistically significant (P < 0.05). Conclusion The prevalence of diabetes mellitus in rural areas of central Hunan Province is higher. Family history of diabetes, hypercholesterolemia and hypertension are major risk factors for diabetes mellitus. The knowledge of diabetes should be strengthened. Related interventions should be given based on the diabetes epidemic status of local.

show abstract

“…73 Also Sheng et al found that long-term modifications in lifestyle including nutrition, exercise and weight loss contribute to health by reducing fasting, and 2-h postprandial blood glucose, total cholesterol and by increasing HDL. 74 Our study had some strengths, to the best of our knowledge, this is the first study to investigate the association between healthy lifestyle score including four factors together (diet, physical activity, smoking status and BMI) with both CRF and muscle strength and in order to reduce bias risk we used the standard protocols for assessment of CRF, hand grip strength, dietary intake and physical activity. In addition, we adjusted for several known factors which may influence CRF and muscle strength also the sample covered a wide age range.…”

Section: Discussionmentioning

confidence: 99%

“…However, Chitra et al investigated that diet and physical activity significantly affect the serum lipid profile 73 . Also Sheng et al found that long‐term modifications in lifestyle including nutrition, exercise and weight loss contribute to health by reducing fasting, and 2‐h postprandial blood glucose, total cholesterol and by increasing HDL 74 …”

Section: Discussionmentioning

confidence: 99%

The association between healthy lifestyle score with cardiorespiratory fitness and muscle strength

et al. 2020

View full text Add to dashboard Cite

Physical fitness can be defined as an comprehensive indicator of most body functions 1 and applies to a good health state, that is, the capacity to carry out active everyday tasks, as well as capabilities correlated with a reduced probability of cardiovascular illness and early death. 2 The primary components of physical fitness include cardiorespiratory strength, musculoskeletal activity and motor fitness and recognised as an important factor in health-related outcomes in childhood and adulthood. 3,4 Low levels of fitness during childhood and adolescence are associated with the risk of obesity, cardiovascular disease, 5 loss of quality of life and mental health. Physical fitness includes cardiorespiratory fitness (CRF) and muscle strength. CRF is a good predictor of health outcomes, such as mortality in obese people, high blood pressure or diabetics. 6 Muscle strength, other than other physical fitness, is also used as an important indicator of mortality in diseases that are associated with weakness and sarcopenia. 7,8 Studies have shown that improvement in CRF with muscle strength together has more beneficial effects than when each one is alone. 9 Of the factors that may influence CRF

show abstract

Effects of Lifestyle Modification and Anti-diabetic Medicine on Prediabetes Progress: A Systematic Review and Meta-Analysis

Cited by 44 publications

References 53 publications

Effect of Behaviour Change Communication on Metabolic Syndrome and Its Markers among Ethiopian Adults: Randomized Controlled Trial

Effect of Behaviour Change Communication on Metabolic Syndrome and Its Markers among Ethiopian Adults: Randomized Controlled Trial

Prevalence and Risk Factors of Diabetes Mellitus in People over 40 Years Old in Rural Areas of Central Hunan Province

The association between healthy lifestyle score with cardiorespiratory fitness and muscle strength

Contact Info

Product

Resources

About