An analysis of the associations between gender and metabolic syndrome components in Korean adults: a national cross-sectional study

Yang, Yeon-Mi; Shin, Byung‐Cheul; Son, Chihyoung; Ha, In‐Hyuk

doi:10.1186/s12902-019-0393-0

Cited by 15 publications

(12 citation statements)

References 40 publications

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“…Sex and age were other variables associated with metabolic syndrome. It was observed that males were 4.7 times more likely to have metabolic syndrome as compared to females, which is consistent with other reports (30). For one year increase in age, the likelihood of metabolic syndrome was higher by 6%, which is similar to a report from elsewhere (31).…”

Section: Resultssupporting

confidence: 91%

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

Sinaga

Lindstrom

Teshome

et al. 2020

Preprint

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Background: Metabolic syndrome is a global public health problem affecting both developing and developed countries with major consequences on human health, social and economic development. In Ethiopia although there is an increase in the prevalence of metabolic Syndrome due to epidemiologic transition, there is no study that evaluated the effect of interventions. This study aimed to assess the effect of nutrition behaviour change communication on metabolic syndrome and its markers. Method: A individually randomized controlled trial was conducted among Ethiopian adults working in Jimma University from mid of September 2015 to December 30, 2015. A total of 224 participants were randomly allocated into intervention (n=112) and controls (n=112) groups. The list of administrative and academic staff involved in the baseline survey was used as a sampling frame. Data on socio-demographic, anthropometric, biochemical and clinical parameters were collected using trained data collectors. Difference in the differences in metabolic syndrome and its components between baseline and end line were compared by the intervention status. Multivariable logistic and linear regression models were used to isolate independent predictors of metabolic syndrome and its components, respectively. Results: Overall, there was significant difference (P<0.001) in the prevalence of metabolic syndrome 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 metabolic syndrome 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.Cholesterol, 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 components of metabolic syndrome. 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: There was strong positive effect of behaviour change communication on metabolic syndrome and its components. The results imply the need for enhancing behaviour change interventions using various strategies at the community and health facility levels to curb the emerging burden of chronic non-communicable diseases in Ethiopia. Future research should examine the sustainability of such behaviour changes using a community based study.

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Section: Resultssupporting

confidence: 91%

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

Sinaga

Lindstrom

Teshome

et al. 2020

Preprint

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show abstract

“…Sex and age were other variables associated with metabolic syndrome. It was observed that males were 4.7 times more likely to have MetS as compared to females, which is consistent with other reports (30). For one year increase in age, the likelihood of MetS was higher by 6%, which is similar to a report from elsewhere (31).…”

Section: Discussionsupporting

confidence: 90%

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

Sinaga

Lindstrom

Teshome

et al. 2020

Preprint

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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.

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“…In addition, correlation of BMI with b-cell function and insulin and C-peptide responses were stronger in men, suggesting that there might be a need for different BMI cutoffs for risk evaluation based on sex. Epidemiologic studies have also reported a sex-related disparity in the prevalence of metabolic syndrome and type 2 diabetes (45). Women are diagnosed with type 2 diabetes at a higher BMI than men (46), suggesting that obesity could be defined differently according to sex, similar to the different cutoff values of waist circumference for men and women.…”

Section: Discussionmentioning

confidence: 99%

Association of Baseline Characteristics With Insulin Sensitivity and β-Cell Function in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness (GRADE) Study Cohort

et al. 2020

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OBJECTIVE We investigated sex and racial differences in insulin sensitivity, β-cell function, and glycated hemoglobin (HbA1c) and the associations with selected phenotypic characteristics. RESEARCH DESIGN AND METHODS This is a cross-sectional analysis of baseline data from 3,108 GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) participants. All had type 2 diabetes diagnosed <10 years earlier and were on metformin monotherapy. Insulin sensitivity and β-cell function were evaluated using the HOMA of insulin sensitivity and estimates from oral glucose tolerance tests, including the Matsuda Index, insulinogenic index, C-peptide index, and oral disposition index (DI). RESULTS The cohort was 56.6 ± 10 years of age (mean ± SD), 63.8% male, with BMI 34.2 ± 6.7 kg/m2, HbA1c 7.5 ± 0.5%, and type 2 diabetes duration 4.0 ± 2.8 years. Women had higher DI than men but similar insulin sensitivity. DI was the highest in Black/African Americans, followed by American Indians/Alaska Natives, Asians, and Whites in descending order. Compared with Whites, American Indians/Alaska Natives had significantly higher HbA1c, but Black/African Americans and Asians had lower HbA1c. However, when adjusted for glucose levels, Black/African Americans had higher HbA1c than Whites. Insulin sensitivity correlated inversely with BMI, waist-to-hip ratio, triglyceride-to-HDL-cholesterol ratio (TG/HDL-C), and the presence of metabolic syndrome, whereas DI was associated directly with age and inversely with BMI, HbA1c, and TG/HDL-C. CONCLUSIONS In the GRADE cohort, β-cell function differed by sex and race and was associated with the concurrent level of HbA1c. HbA1c also differed among the races, but not by sex. Age, BMI, and TG/HDL-C were associated with multiple measures of β-cell function and insulin sensitivity.

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An analysis of the associations between gender and metabolic syndrome components in Korean adults: a national cross-sectional study

Cited by 15 publications

References 40 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

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

Association of Baseline Characteristics With Insulin Sensitivity and β-Cell Function in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness (GRADE) Study Cohort

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