Objectives A mobile health intervention program was provided for employees with overweight and obesity for 12 weeks, and a process evaluation was completed at the end of the program. We investigated participant engagement based on app usage data, and whether engagement was associated with the degree of satisfaction with the program. Methods The program involved the use of a dietary coaching app and a wearable device for monitoring physical activity and body composition. A total of 235 employees participated in the program. App usage data were collected from a mobile platform, and a questionnaire survey on process evaluation and needs assessment was conducted during the post-test. Results The engagement level of the participants decreased over time. Participants in their 40s, high school graduates or lower education, and manufacturing workers showed higher engagement than other age groups, college graduates, and office workers, respectively. The overall satisfaction score was 3.6 out of 5. When participants were categorized into three groups according to their engagement level, the upper group was more satisfied than the lower group. A total of 71.5% of participants answered that they wanted to rejoin or recommend the program, and 71.9% answered that the program was helpful in improving their dietary habits. The most helpful components in the program were diet records and a 1:1 chat with the dietary coach from the dietary coaching app. The barriers to improving dietary habits included company dinners, special occasions, lack of time, and eating out. The workplace dietary management programs were recognized as necessary with a need score of 3.9 out of 5. Conclusions Participants were generally satisfied with the mobile health intervention program, particularly highly engaged participants. Feedback from a dietary coach was an important factor in increasing satisfaction.
Objectives This study aimed to determine whether a mobile health (mhealth) intervention is effective in reducing weight and changing dietary behavior among employees with overweight and obesity. The study also investigated whether engagement with the intervention affected its effectiveness. Methods The intervention involved the use of a dietary coaching app, a wearable device for monitoring physical activity and body composition, and a messenger app for communicating with participants and an intervention manager. A total of 235 employees were recruited for a 12-week intervention from eight workplaces in Korea. Questionnaire surveys, anthropometric measurements, and 24-h dietary recalls were conducted at baseline and after the intervention. Results After the intervention, significant decreases in the mean body weight, body mass index, body fat percentage, and waist circumference were observed. Furthermore, the consumption frequencies of multigrain rice and legumes significantly increased, whereas those of pork belly, instant noodles, processed meat, carbonated beverages, and fast food significantly decreased compared with those at baseline. The mean dietary intake of energy and most nutrients also decreased after the intervention. When the participants were categorized into three groups according to their engagement level, significant differences in anthropometric data, dietary behaviors, and energy intake were observed following the intervention, although there were no differences at baseline, indicating that higher engagement level led to greater improvements in weight loss and dietary behavior. Conclusions The intervention had positive effects on weight loss and dietary behavior changes, particularly among employees with higher engagement levels. These results indicate the importance of increasing the level of engagement in the intervention to enhance its effectiveness. The mhealth intervention is a promising model for health promotion for busy workers with limited time.
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Objectives Sarcopenia is one of the most representative factors of senescence, and nutritional status is known to affect sarcopenia. This study was performed to analyze the relationships between energy and protein intake and sarcopenia. Methods The study subjects were 3,236 individuals aged ≥ 65 that participated in the Korea National Health and Nutrition Examination Survey (KNHANES) 2008 ~ 2011. General characteristics and anthropometric and 24-hour dietary recall data were analyzed. Sarcopenia was diagnosed using a formula based on appendicular skeletal muscle mass (ASM) and body weight. Logistic regression was performed to determine relationships between sarcopenia risk and energy and protein intakes. Results For energy intake, the odds ratio (OR) of sarcopenia in women was significantly higher those with the lowest intake [OR = 1.680, 95% confidence interval (CI) = 1.213-2.326] than those with the highest intake (P for trend = 0.001). Regarding protein intake per kg of body weight, the odds ratio of sarcopenia was significantly higher for those that consumed < 0.8 g/kg of protein daily than those that consumed > 1.2g/kg for men (OR = 2.459, 95% CI = 1.481-4.085) and women (OR = 2.178, 95% CI = 1.423-3.334). Conclusions This study shows a link between sarcopenia and energy and protein intake levels and suggests that energy and protein consumption be promoted among older adults to prevent sarcopenia.
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OBJECTIVES This study was conducted to investigate the association between sarcopenia and sarcopenic obesity and cardiovascular disease risk in Korean postmenopausal women. METHODS We analyzed data of 2,019 postmenopausal women aged 50-64 years who participated in the Korea National Health and Nutrition Examination Survey in 2008-2011 and were free of cardiovascular disease history. Blood pressure, height, and weight were measured. We analyzed the serum concentrations of glucose, total cholesterol, high density lipoprotein cholesterol, low density lipoprotein cholesterol and triglyceride levels. Waist circumference was used to measure obesity. Appendicular skeletal muscle mass was measured by dual-energy X-ray absorptiometry. Sarcopenia was defined as the appendicular skeletal muscle mass/body weight<1 standard deviation below the gender-specific means for healthy young adults. The estimated 10-year risk of cardiovascular disease risk was calculated by Pooled Cohort Equation. Subjects were classified as non-sarcopenia, sarcopenia, or sarcopenic obesity based on status of waist circumference and appendicular skeletal muscle mass. RESULTS The prevalence of sarcopenia and sarcopenic obesity was 16.3% (n=317) and 18.3% (n=369), respectively. The 10-year risk of cardiovascular disease risk in the sarcopenic obesity group was higher (3.82 ± 0.22%) than the normal group (2.73 ± 0.09%) and sarcopenia group (3.17 ± 0.22%) (p < 0.000). The odd ratios (ORs) for the ≥7.5% 10-year risk of cardiovascular disease risk were significantly higher in the sarcopenic obesity group (OR 3.609, 95% CI: 2.030-6.417) compared to the sarcopenia group (OR 2.799, 95% CI: 1.463-5.352) (p for trend < 0.000) after adjusting for independent variables (i.e., exercise, period of menopausal, alcohol use disorders identification test (AUDIT) score, income, education level, calorie intake, %fat intake and hormonal replacement therapy). CONCLUSIONS Sarcopenia and sarcopenic obesity appear to be associated with higher risk factors predicting the 10-year risks of cardiovascular disease risk in postmenopausal women. These findings imply that maintaining normal weight and muscle mass may be important for cardiovascular disease risk prevention in postmenopausal women.
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OBJECTIVES This study compared the differences of postmenopausal women's bone mineral density in relation to the degree of obesity, metabolism index and dietary factors that affect bone mineral density. METHODS The subjects included in the study are 39 postmenopausal women of normal weight with body mass index less than 25 kg/m2 and 32 postmenopausal who are obese. Anthropometry and biochemical analysis were performed and nutrient intakes and DQI-I were assessed. RESULTS Normal weight women were 56.03 ± 3.76 years old and obese women were 58.09 ± 5.13 years old and there was no significant difference in age between the two groups. The T-score of bone mineral density was 0.03 ± 1.06 in normal weight women and -0.60 ± 1.47 in obese women and this was significantly different between the two groups (p<0.05). Blood Leptin concentration was significantly lower in normal weight women (6.09 ± 3.37 ng/mL) compared to obese women in (9.01 ± 4.99 ng/mL) (p<0.05). The total score of diet quality index-international was 70.41±9.34 in normal weight women and 64.93 ± 7.82 in obese women (p<0.05). T-score of bone mineral density showed negative correlations with percentage of body fat (r = -0.233, p=0.05), BMI (r = -0.197, p=0.017), triglyceride (r = -0.281, p=0.020) and leptin (r = -0.308, p=0.011). The results of multiple regression analysis performed as the method of entry showed that with 22.0% of explanation power, percentage of body fat (β=-0.048, p<0.05), triglyceride (β=-0.005, p<0.05) and HDL-cholesterol (β=0.034, p<0.01), moderation of DQI-I (β=-0.231, p<0.05) affected T-score significantly. CONCLUSIONS The results of the study showed that obese women have less bone density than those with normal weight women. In addition, the factor analysis result that affect bone mineral density showed that intake of fat is a very important factor. Therefore, postmenopausal women need to maintain normal weight and manage blood lipid levels within normal range. They also need to take various sources of protein and reduce consumption of empty calorie foods that have high calories, fat, cholesterol and sodium.
Osteoprotegerin (OPG) plays a core role in bone reformation by antagonizing the effect of receptor activator of nuclear factor kappa-B ligand (RANKL), and mediates vascular calcification in cardiovascular disease patients. Thus, we aimed to examine the relationship between serum OPG levels and cardiovascular factors and inflammatory markers in metabolic syndrome patients (MS). This cross-sectional study included 96 men who visited the diet clinic between May and July 2011. Patients were classified into 2 groups based on NCEP-ATP guidelines: normal and with MS (n = 50 and 46, respectively). Physical measurements, biochemical assay were measured. Serum OPG and IL-6, diponectin and hs-CRP were assessed. MS were aged 50.02 +/- 10.85 years, and normal patients 52.07 +/- 9.56 years, with no significant differences. Significant differences were not observed in BMI between the 2 groups. Moreover, significant differences were not observed in serum OPG, however, the serum OPG level (4.41 +/- 1.86 pmol/L) differed significantly between an overweight MS (BMI > 25) and normal patients. OPG was correlated to age (r = 0.410, p = 0.000), HDL-cholesterol (r = 0.209, p = 0.015), and log adiponectin (r = 0.175, p = 0.042). Multiple regression analyses using the enter method showed that age (beta = 0.412, p = 0.000) and BMI (beta = 0.265, p = 0.000) considerably affected OPG. In conclusion, out study showed that serum OPG levels are correlated with cardiovascular risk factors, such as BMI, HDL-cholesterol and adiponectin in MS and adiponectin, suggesting that serum OPG has potential as a cardiovascular disease indicator and predictor.
Elevated serum concentration of inflammation markers is known as an independent risk factor of metabolic syndrome (MS) and dietary intake is an important factor to control MS. The purpose of this study was to investigated the hypothesis that inflammatory indices are associated with dietary intake and diet quality index-international (DQI-I) in subjects with MS. A cross-sectional study was conducted on 156 men and 73 postmenopausal women with MS, defined by three or more risk factors of the modified Adult Treatment Panel III criteria. Serum levels of high sensitive C-reactive protein (hs-CRP), adiponectin were examined and nutrients intake and DQI-I were assessed using a semi-quantitative food frequency questionnaire. The total DQI-I score was significantly higher in female subjects (65.87 +/- 9.86) than in male subjects (62.60 +/- 8.95). There was a positive association between hs-CRP and polyunsaturated fatty acid intake (p < 0.05) and a negative association between adiponectin and lipid (p < 0.05), total sugar (p < 0.01), and total fatty acids (p < 0.05). When the subjects were divided into 5 groups by quintile according to serum adiponectin and hs-CRP level, there was no association between DQI-I score and hs-CRP levels. Moderation score of DQI-I was significantly higher in highest quintile group than the lower quintile groups. Therefore, our results provide some evidence that dietary intake and diet quality are associated with inflammation markers and dietary modification might be a predictor to decrease risk for metabolic syndrome complications. However further research is needed to develop the dietary quality index reflecting the inflammatory change by considering the dietary habit and pattern of Koreans.
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The purpose of this study was performed to evaluate the prevalence of overweight and to compare the dietary behaviors, nutrient intake and physical activities of specialized game high school students. Total of 163 subjects participated and their weight, height, waist circumference, hip circumference and bone status by a quantitative ultrasound method were measured. The subjects were surveyed by a self-administered questionnaire about general characteristics, dietary behaviors and physical activities. Nutrient intakes of the subjects were assessed by semi-quantitative food frequency questionnaire. The subjects were divided into four groups on their obesity level by BMI. The prevalence of underweight, normal, overweight and obese group was 6%, 58%, 16%, and 20% respectively. BMI was negatively correlated with bone mineral density (p < 0.01) and positively correlated with WHR (p < 0.01). The dietary guideline compliance score for "Enjoy Korean rice food style" was 2.63, followed by "Prepare food sanitarily" 2.48, "Do not skip breakfast" 2.29, "Eat a variety of vegetables, fruits, dairy products daily" 2.25, "Drink water instead of beverage" 2.10, "Choose less fried foods" 2.09 and "Maintain healthy weight" 1.91. The exercise frequency of walking was not significantly different between groups; however, heavy exercise frequency was significantly lower in underweight group than the other groups (p < 0.05). The energy intake was 2153 kcal, which was 81.2% of the Estimate Energy Requirement, and the intake of calcium and vitamin B2 was 66.7% and 77.8% of KDRIs. Particularly, the intake of iron, vitamin A and vitamin C was about 59.4%, 52.2% and 55.4% of KDRIs and INQ was 0.71, 0.63 and 0.65 respectively, and intake of folic acid fell behind 39.1% of KDRIs and INQ was 0.46. Our study suggests that the systematic and continuous nutrition education will have to be provided at schools to improve dietary and health behaviors and prevent chronic metabolic disease for students of specialized game high school.
Several studies about hospital malnutrition have been reported that about more than 40% of hospitalized patients are having nutritional risk factors and hospital malnutrition presents a high prevalence. People in a more severe nutritional status ended up with a longer length of hospital stay and higher hospital cost. Nutrition screening tools identify individuals who are malnourished or at risk of becoming malnourished and who may benefit from nutritional support. For the early detection and treatment of malnourished hospital patients, few valid screening instruments for Koreans exist. Therefore, the aim of this study was to develop a simple, reliable and valid malnutrition screening tool that could be used at hospital admission to identify adult patients at risk of malnutrition using medical electrical record data. Two hundred and one patients of the university affiliated medical center were assessed on nutritional status and classified as well nourished, moderately or severely malnourished by a Patient-Generated subjective global assessment (PG-SGA) being chosen as the 'gold standard' for defining malnutrition. The combination of nutrition screening questions with the highest sensitivity and specificity at prediction PG-SGA was termed the nutrition screening index (NSI). Odd ratio, and binary logistic regression were used to predict the best nutritional status predictors. Based on regression coefficient score, albumin less than 3.5 g/dl, body mass index (BMI) less than 18.5 kg/m2, total lymphocyte count less than 900 and age over 65 were determined as the best set of NSI. By using best nutritional predictors receiver operating characteristic curve with the area under the curve, sensitivity and 1-specificity were analyzed to determine the best optimal cut-off point to decide normal or abnormal in nutritional status. Therefore simple and beneficial NSI was developed for identifying patients with severe malnutrition. Using NSI, nutritional information of the severe malnutrition patient should be shared with physicians and they should be cared for by clinical dietitians to improve their nutritional status.
Protein-calorie malnutrition is common in maintenance dialysis patients. Indeed, diabetic patients with chronic renal failure are considered to be at increased risk of malnutrition. The aim of this study was to compare the nutritional status and markers of inflammation of hemodialysis patients with and without type 2 diabetes. We compared nutritional parameters and C-reactive protein (CRP) as a marker of inflammation in 30 type 2 diabetic patients and age-matched 30 non-diabetic patients with hemodialysis. Serum albumin was significantly lower in patients with type 2 diabetes (3.45 +/- 0.43 g/dL) than in non-diabetic patients (3.64 +/- 0.36 g/dL) (p < 0.05). In contrast, the concentration of serum CRP was significantly higher in type 2 diabetes (1.42 +/- 1.8 mg/dL) (p < 0.05). There were significant negative-relationships between serum albumin and CRP level in both diabetic (r = -0.553, p < 0.01) and non-diabetic (r = -0.579, p < 0.01) patients. In diabetic patients, serum albumin level was significantly correlated with hemoglobin (r = 0.488, p < 0.01) and hematocrit (r = 0.386, p < 0.01). Diabetic patients as compared to non-diabetic patients showed a significant (p < 0.01) increased serum triglyceride (TG) (153.1 +/- 80.1 mg/dL vs 101.6 +/- 62.4 mg/dL) and decreased serum HDL cholesterol (36.89 +/- 13.48mg/dL vs 47.00 +/- 14.02 mg/dL, P < 0.05). There were significant correlations in the intake of calorie and serum albumin levels in both diabetic (r = 0.438, p < 0.05) and non-diabetic (r = 0.527, p < 0.05) patients. Serum CRP level was negatively correlated with calorie (r = -0.468, p < 0.05), protein (r = -0.520, p < 0.01) and fat intakes (r = -0.403, p < 0.05) in diabetic patients and calorie (r = -0.534, p < 0.05) and protein intakes (r = -0.559, p < 0.05) in non-diabetic patients. The prevalence of protein malnutrition and the risk factors of cardiovascular disease were significantly higher in type 2 diabetic patients than in non-diabetic hemodialysis patients. Thus, we can suggest that the higher comorbidity and mortality rate in diabetic hemodialysis patients are partially explained by malnutrition and inflammation.