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indices</title> <meta name="description" content="Search results for: obesity indices"> <meta name="keywords" content="obesity indices"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="obesity indices"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1499</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: obesity indices</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1499</span> Correlations between Obesity Indices and Cardiometabolic Risk Factors in Obese Subgroups in Severely Obese Women</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seung%20Hun%20Lee">Seung Hun Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sang%20Yeoup%20Lee"> Sang Yeoup Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objectives: To investigate associations between degrees of obesity using correlations between obesity indices and cardiometabolic risk factors. Methods: BMI, waist circumference (WC), fasting insulin, fasting glucose, lipids, and visceral adipose tissue (VAT) area using computed tomographic images were measured in 113 obese female without cardiovascular disease (CVD). Correlations between obesity indices and cardiometabolic risk factors were analyzed in obese subgroups defined using sequential obesity indices. Results: Mean BMI and WC were 29.6 kg/m2 and 92.8 cm. BMI showed significant correlations with all five cardiometabolic risk factors until the BMI cut-off point reached 27 kg/m2, but when it exceeded 30 kg/m2, correlations no longer existed. WC was significantly correlated with all five cardiometabolic risk factors up to a value of 85 cm, but when WC exceeded 90 cm, correlations no longer existed. Conclusions: Our data suggest that moderate weight-loss goals may not be enough to ameliorate cardiometabolic markers in severely obese patients. Therefore, individualized weight-loss goals should be recommended to such patients to improve health benefits. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=correlation" title="correlation">correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=cardiovascular%20disease" title=" cardiovascular disease"> cardiovascular disease</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20factors" title=" risk factors"> risk factors</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a> </p> <a href="https://publications.waset.org/abstracts/23228/correlations-between-obesity-indices-and-cardiometabolic-risk-factors-in-obese-subgroups-in-severely-obese-women" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23228.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">357</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1498</span> Correlation between Neck Circumference and Other Anthropometric Indices as a Predictor of Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Madhur%20Verma">Madhur Verma</a>, <a href="https://publications.waset.org/abstracts/search?q=Meena%20Rajput"> Meena Rajput</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamal%20Kishore"> Kamal Kishore</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: The general view that obesity is a problem of prosperous Western countries has been repealed with substantial evidence showing that middle-income countries like India are now at the heart of a fat explosion. Neck circumference has evolved as a promising index to measure obesity, because of the convenience of its use, even in culture sensitive population. Objectives: To determine whether neck circumference (NC) was associated with overweight and obesity and contributed to the prediction like other classical anthropometric indices. Methodology: Cross-sectional study consisting of 1080 adults (> 19 years) selected through Multi-stage random sampling between August 2013 and September 2014 using the pretested semi-structured questionnaire. After recruitment, the demographic and anthropometric parameters [BMI, Waist & Hip Circumference (WC, HC), Waist to hip ratio (WHR), waist to height ratio (WHtR), body fat percentage (BF %), neck circumference (NC)] were recorded & calculated as per standard procedures. Analysis was done using appropriate statistical tests. (SPSS, version 21.) Results: Mean age of study participants was 44.55+15.65 years. Overall prevalence of overweight & obesity as per modified criteria for Asian Indians (BMI ≥ 23 kg/m2) was 49.62% (Females-51.48%; Males-47.77%). Also, number of participants having high WHR, WHtR, BF%, WC & NC was 827(76.57%), 530(49.07%), 513(47.5%), 537(49.72%) & 376(34.81%) respectively. Variation of NC, BMI & BF% with age was non- significant. In both the genders, as per the Pearson’s correlational analysis, neck circumference was positively correlated with BMI (men, r=0.670 {p < 0.05}; women, r=0.564 {p < 0.05}), BF% (men, r=0.407 {p < 0.05}; women, r= 0.283 {p < 0.05}), WC (men, r=0.598{p < 0.05}; women, r=0.615 {p < 0.05}), HC (men, r=0.512{p < 0.05}; women, r=0.523{p < 0.05}), WHR (men, r= 0.380{p > 0.05}; women, r=0.022{p > 0.05}) & WHtR (men, r=0.318 {p < 0.05}; women, r=0.396{p < 0.05}). On ROC analysis, NC showed good discriminatory power to identify obesity with AUC (AUC for males: 0.822 & females: 0.873; p- value < 0.001) with maximum sensitivity and specificity at a cut-off value of 36.55 cms for males & 34.05cms for females. Conclusion: NC has fair validity as a community-based screener for overweight and obese individuals in the study context and has also correlated well with other classical indices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=neck%20circumference" title="neck circumference">neck circumference</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=anthropometric%20indices" title=" anthropometric indices"> anthropometric indices</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20fat%20percentage" title=" body fat percentage"> body fat percentage</a> </p> <a href="https://publications.waset.org/abstracts/71299/correlation-between-neck-circumference-and-other-anthropometric-indices-as-a-predictor-of-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71299.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">248</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1497</span> Relationship of Sleep Duration with Obesity and Dietary Intake</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Ahmad%20Hosseini">Seyed Ahmad Hosseini</a>, <a href="https://publications.waset.org/abstracts/search?q=Makan%20Cheraghpour"> Makan Cheraghpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Shirali"> Saeed Shirali</a>, <a href="https://publications.waset.org/abstracts/search?q=Roya%20Rafie"> Roya Rafie</a>, <a href="https://publications.waset.org/abstracts/search?q=Matin%20Ghanavati"> Matin Ghanavati</a>, <a href="https://publications.waset.org/abstracts/search?q=Arezoo%20Amjadi"> Arezoo Amjadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Meysam%20Alipour"> Meysam Alipour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: There is a mutual relationship between sleep duration and obesity. We studied the relationship between sleep duration with obesity and dietary Intake. Methods: This cross-sectional study was conducted on 444 male students in Ahvaz Jundishapur University of Medical Science. Dietary intake was analyzed by food frequency questionnaire (FFQ). Anthropometric indices were analyzed. Participants were being asked about their sleep duration and they were categorized into three groups according to their responses (less than six hours, between six and eight hours, and more than eight hours). Results: Macronutrient, micronutrient, and antioxidant intake did not show significant difference between three groups. Moreover, we did not observe any significant difference between anthropometric indices (weight, body mass index, waist circumference, and percentage body fat). Conclusions: Our study results show no significant relationship between sleep duration, nutrition pattern, and obesity. Further study is recommended. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sleep%20duration" title="sleep duration">sleep duration</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=dietary%20intake" title=" dietary intake"> dietary intake</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-sectional" title=" cross-sectional"> cross-sectional</a> </p> <a href="https://publications.waset.org/abstracts/58463/relationship-of-sleep-duration-with-obesity-and-dietary-intake" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58463.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">342</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1496</span> Evaluation of the Weight-Based and Fat-Based Indices in Relation to Basal Metabolic Rate-to-Weight Ratio</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma">Orkide Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma"> Mustafa M. Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Basal metabolic rate is questioned as a risk factor for weight gain. The relations between basal metabolic rate and body composition have not been cleared yet. The impact of fat mass on basal metabolic rate is also uncertain. Within this context, indices based upon total body mass as well as total body fat mass are available. In this study, the aim is to investigate the potential clinical utility of these indices in the adult population. 287 individuals, aged from 18 to 79 years, were included into the scope of the study. Based upon body mass index values, 10 underweight, 88 normal, 88 overweight, 81 obese, and 20 morbid obese individuals participated. Anthropometric measurements including height (m), and weight (kg) were performed. Body mass index, diagnostic obesity notation model assessment index I, diagnostic obesity notation model assessment index II, basal metabolic rate-to-weight ratio were calculated. Total body fat mass (kg), fat percent (%), basal metabolic rate, metabolic age, visceral adiposity, fat mass of upper as well as lower extremities and trunk, obesity degree were measured by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical evaluations were performed by statistical package (SPSS) for Windows Version 16.0. Scatterplots of individual measurements for the parameters concerning correlations were drawn. Linear regression lines were displayed. The statistical significance degree was accepted as p < 0.05. The strong correlations between body mass index and diagnostic obesity notation model assessment index I as well as diagnostic obesity notation model assessment index II were obtained (p < 0.001). A much stronger correlation was detected between basal metabolic rate and diagnostic obesity notation model assessment index I in comparison with that calculated for basal metabolic rate and body mass index (p < 0.001). Upon consideration of the associations between basal metabolic rate-to-weight ratio and these three indices, the best association was observed between basal metabolic rate-to-weight and diagnostic obesity notation model assessment index II. In a similar manner, this index was highly correlated with fat percent (p < 0.001). Being independent of the indices, a strong correlation was found between fat percent and basal metabolic rate-to-weight ratio (p < 0.001). Visceral adiposity was much strongly correlated with metabolic age when compared to that with chronological age (p < 0.001). In conclusion, all three indices were associated with metabolic age, but not with chronological age. Diagnostic obesity notation model assessment index II values were highly correlated with body mass index values throughout all ranges starting with underweight going towards morbid obesity. This index is the best in terms of its association with basal metabolic rate-to-weight ratio, which can be interpreted as basal metabolic rate unit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=basal%20metabolic%20rate" title="basal metabolic rate">basal metabolic rate</a>, <a href="https://publications.waset.org/abstracts/search?q=body%20mass%20index" title=" body mass index"> body mass index</a>, <a href="https://publications.waset.org/abstracts/search?q=children" title=" children"> children</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnostic%20obesity%20notation%20model%20assessment%20index" title=" diagnostic obesity notation model assessment index"> diagnostic obesity notation model assessment index</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a> </p> <a href="https://publications.waset.org/abstracts/101857/evaluation-of-the-weight-based-and-fat-based-indices-in-relation-to-basal-metabolic-rate-to-weight-ratio" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101857.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1495</span> The Relationship between Anthropometric Obesity Indices and Insulin in Children with Metabolic Syndrome</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The number of indices developed for the evaluation of obesity both in adults and pediatric population is ever increasing. These indices are also used in cases with metabolic syndrome (MetS), mostly the ultimate form of morbid obesity. Aside from anthropometric measurements, formulas constituted using these parameters also find clinical use. These formulas can be listed as two groups; being weight-dependent and –independent. Some are extremely sophisticated equations and their clinical utility is questionable in routine clinical practice. The aim of this study is to compare presently available obesity indices and find the most practical one. Their associations with MetS components were also investigated to determine their capacities in differential diagnosis of morbid obesity with and without MetS. Children with normal body mass index (N-BMI) and morbid obesity were recruited for this study. Three groups were constituted. Age- and sex- dependent BMI percentiles for morbid obese (MO) children were above 99 according to World Health Organization tables. Of them, those with MetS findings were evaluated as MetS group. Children, whose values were between 85 and 15 were included in N-BMI group. The study protocol was approved by the Ethics Committee of the Institution. Parents filled out informed consent forms to participate in the study. Anthropometric measurements and blood pressure values were recorded. Body mass index, hip index (HI), conicity index (CI), triponderal mass index (TPMI), body adiposity index (BAI), body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), waist-to-hip ratio (WHR) and waist circumference+hip circumference/2 ((WC+HC)/2) were the formulas examined within the scope of this study. Routine biochemical tests including fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein-cholesterol (HDL-C) were performed. Statistical package program SPSS was used for the evaluation of study data. p<0.05 was accepted as the statistical significance degree. Hip index did not differ among the groups. A statistically significant difference was noted between N-BMI and MetS groups in terms of ABSI. All the other indices were capable of making discrimination between N-BMI-MO, N-BMI- MetS and MO-MetS groups. No correlation was found between FBG and any obesity indices in any groups. The same was true for INS in N-BMI group. Insulin was correlated with BAI, TPMI, CI, BRI, AVI and (WC+HC)/2 in MO group without MetS findings. In MetS group, the only index, which was correlated with INS was (WC+HC)/2. These findings have pointed out that complicated formulas may not be required for the evaluation of the alterations among N-BMI and various obesity groups including MetS. The simple easily computable weight-independent index, (WC+HC)/2, was unique, because it was the only index, which exhibits a valuable association with INS in MetS group. It did not exhibit any correlation with other obesity indices showing associations with INS in MO group. It was concluded that (WC+HC)/2 was pretty valuable practicable index for the discrimination of MO children with and without MetS findings. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=insulin" title=" insulin"> insulin</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20syndrome" title=" metabolic syndrome"> metabolic syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity%20indices" title=" obesity indices"> obesity indices</a> </p> <a href="https://publications.waset.org/abstracts/158884/the-relationship-between-anthropometric-obesity-indices-and-insulin-in-children-with-metabolic-syndrome" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158884.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">77</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1494</span> A New Obesity Index Derived from Waist Circumference and Hip Circumference Well-Matched with Other Indices in Children with Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Anthropometric obesity indices such as waist circumference (WC), indices derived from anthropometric measurements such as waist-to-hip ratio (WHR), and indices created from body fat mass composition such as trunk-to-leg fat ratio (TLFR) are commonly used for the evaluation of mild or severe forms of obesity. Their clinical utilities are being compared using body mass index (BMI) percentiles to classify obesity groups. The best of them is still being investigated to make a clear-cut discrimination between healthy normal individuals (N-BMI) and overweight or obese (OB) or morbid obese patients. The aim of this study is to derive a new index, which best suits the purpose for the discrimination of children with N-BMI from OB children. A total of eighty-three children participated in the study. Two groups were constituted. The first group comprised 42 children with N-BMI, and the second group was composed of 41 OB children, whose age- and sex- adjusted BMI percentile values vary between 95 and 99. The corresponding values for the first group were between 15 and 85. This classification was based upon the tables created by World Health Organization. The institutional ethics committee approved the study protocol. Informed consent forms were filled by the parents of the participants. Anthropometric measurements were taken and recorded following a detailed physical examination. Within this context, weight, height (Ht), WC, hip C (HC), neck C (NC) values were taken. Body mass index, WHR, (WC+HC)/2, WC/Ht, (WC/HC)/Ht, WC*NC were calculated. Bioelectrical impedance analysis was performed to obtain body’s fat compartments in terms of total fat, trunk fat, leg fat, arm fat masses. Trunk-to-leg fat ratio, trunk-to-appendicular fat ratio (TAFR), (trunk fat+leg fat)/2 ((TF+LF)/2) were calculated. Fat mass index (FMI) and diagnostic obesity notation model assessment-II (D2I) index values were calculated. Statistical analysis of the data was performed. Significantly increased values of (WC+HC)/2, (TF+LF)/2, D2I, and FMI were observed in OB group in comparison with those of N-BMI group. Significant correlations were calculated between BMI and WC, (WC+HC)/2, (TF+LF)/2, TLFR, TAFR, D2I as well as FMI both in N-BMI and OB groups. The same correlations were obtained for WC. (WC+HC)/2 was correlated with TLFR, TAFR, (TF+LF)/2, D2I, and FMI in N-BMI group. In OB group, the correlations were the same except those with TLFR and TAFR. These correlations were not present with WHR. Correlations were observed between TLFR and BMI, WC, (WC+HC)/2, (TF+LF)/2, D2I as well as FMI in N-BMI group. Same correlations were observed also with TAFR. In OB group, correlations between TLFR or TAFR and BMI, WC as well as (WC+HC)/2 were missing. None was noted with WHR. From these findings, it was concluded that (WC+HC)/2, but not WHR, was much more suitable as an anthropometric obesity index. The only correlation valid in both groups was that exists between (WC+HC)/2 and (TF+LF)/2. This index was suggested as a link between anthropometric and fat-based indices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=hip%20circumference" title=" hip circumference"> hip circumference</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=waist%20circumference" title=" waist circumference"> waist circumference</a> </p> <a href="https://publications.waset.org/abstracts/144461/a-new-obesity-index-derived-from-waist-circumference-and-hip-circumference-well-matched-with-other-indices-in-children-with-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144461.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">168</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1493</span> Comparison of the Anthropometric Obesity Indices in Prediction of Cardiovascular Disease Risk: Systematic Review and Meta-analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Pourhassan">Saeed Pourhassan</a>, <a href="https://publications.waset.org/abstracts/search?q=Nastaran%20Maghbouli"> Nastaran Maghbouli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Statement of the problem: The relationship between obesity and cardiovascular diseases has been studied widely(1). The distribution of fat tissue gained attention in relation to cardiovascular risk factors during lang-time research (2). American College of Cardiology/American Heart Association (ACC/AHA) is widely and the most reliable tool to be used as a cardiovascular risk (CVR) assessment tool(3). This study aimed to determine which anthropometric index is better in discrimination of high CVR patients from low risks using ACC/AHA score in addition to finding the best index as a CVR predictor among both genders in different races and countries. Methodology & theoretical orientation: The literature in PubMed, Scopus, Embase, Web of Science, and Google Scholar were searched by two independent investigators using the keywords "anthropometric indices," "cardiovascular risk," and "obesity." The search strategy was limited to studies published prior to Jan 2022 as full-texts in the English language. Studies using ACC/AHA risk assessment tool as CVR and those consisted at least 2 anthropometric indices (ancient ones and novel ones) are included. Study characteristics and data were extracted. The relative risks were pooled with the use of the random-effect model. Analysis was repeated in subgroups. Findings: Pooled relative risk for 7 studies with 16,348 participants were 1.56 (1.35-1.72) for BMI, 1.67(1.36-1.83) for WC [waist circumference], 1.72 (1.54-1.89) for WHR [waist-to-hip ratio], 1.60 (1.44-1.78) for WHtR [waist-to-height ratio], 1.61 (1.37-1.82) for ABSI [A body shape index] and 1.63 (1.32-1.89) for CI [Conicity index]. Considering gender, WC among females and WHR among men gained the highest RR. The heterogeneity of studies was moderate (α²: 56%), which was not decreased by subgroup analysis. Some indices such as VAI and LAP were evaluated just in one study. Conclusion & significance: This meta-analysis showed WHR could predict CVR better in comparison to BMI or WHtR. Some new indices like CI and ABSI are less accurate than WHR and WC. Among women, WC seems to be a better choice to predict cardiovascular disease risk. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=obesity" title="obesity">obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=cardiovascular%20disease" title=" cardiovascular disease"> cardiovascular disease</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20assessment" title=" risk assessment"> risk assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=anthropometric%20indices" title=" anthropometric indices"> anthropometric indices</a> </p> <a href="https://publications.waset.org/abstracts/149972/comparison-of-the-anthropometric-obesity-indices-in-prediction-of-cardiovascular-disease-risk-systematic-review-and-meta-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149972.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">102</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1492</span> The Link between Anthropometry and Fat-Based Obesity Indices in Pediatric Morbid Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Anthropometric measurements are essential for obesity studies. Waist circumference (WC) is the most frequently used measure, and along with hip circumference (HC), it is used in most equations derived for the evaluation of obese individuals. Morbid obesity is the most severe clinical form of obesity, and such individuals may also exhibit some clinical findings leading to metabolic syndrome (MetS). Then, it becomes a requirement to discriminate morbid obese children with (MOMetS+) and without (MOMetS-) MetS. Almost all obesity indices can differentiate obese (OB) children from children with normal body mass index (N-BMI). However, not all of them are capable of making this distinction. A recently introduced anthropometric obesity index, waist circumference + hip circumference/2 ((WC+HC)/2), was confirmed to differ OB children from those with N-BMI, however it has not been tested whether it will find clinical usage for the differential diagnosis of MOMetS+ and MOMetS-. This study was designed to find out the availability of (WC+HC)/2 for the purpose and to compare the possible preponderance of it over some other anthropometric or fat-based obesity indices. Forty-five MOMetS+ and forty-five MOMetS- children were included in the study. Participants have submitted informed consent forms. The study protocol was approved by the Non-interventional Ethics Committee of Tekirdag Namik Kemal University. Anthropometric measurements were performed. Body mass index (BMI), waist-to-hip circumference (W/H), (WC+HC)/2, trunk-to-leg fat ratio (TLFR), trunk-to-appendicular fat ratio (TAFR), trunk fat+leg fat/2 ((trunk+leg fat)/2), diagnostic obesity notation model assessment index-2 (D2I) and fat mass index (FMI) were calculated for both groups. Study data was analyzed statistically, and 0.05 for p value was accepted as the statistical significance degree. Statistically higher BMI, WC, (WC+HC)/2, (trunk+leg fat)/2 values were found in MOMetS+ children than MOMetS- children. No statistically significant difference was detected for W/H, TLFR, TAFR, D2I, and FMI between two groups. The lack of difference between the groups in terms of FMI and D2I pointed out the fact that the recently developed fat-based index; (trunk+leg fat)/2 gives much more valuable information during the evaluation of MOMetS+ and MOMetS- children. Upon evaluation of the correlations, (WC+HC)/2 was strongly correlated with D2I and FMI in both MOMetS+ and MOMetS- groups. Neither D2I nor FMI was correlated with W/H. Strong correlations were calculated between (WC+HC)/2 and (trunk+leg fat)/2 in both MOMetS- (r=0.961; p<0.001) and MOMetS+ (r=0.936; p<0.001) groups. Partial correlations between (WC+HC)/2 and (trunk+leg fat)/2 after controlling the effect of basal metabolic rate were r=0.726; p<0.001 in MOMetS- group and r=0.932; p<0.001 in MOMetS+ group. The correlation in the latter group was higher than the first group. In conclusion, recently developed anthropometric obesity index (WC+HC)/2 and fat-based obesity index (trunk+leg fat)/2 were of preponderance over the previously introduced classical obesity indices such as W/H, D2I and FMI during the differential diagnosis of MOMetS+ and MOMetS- children. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=hip%20circumference" title=" hip circumference"> hip circumference</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20syndrome" title=" metabolic syndrome"> metabolic syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=morbid%20obesity" title=" morbid obesity"> morbid obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=waist%20circumference" title=" waist circumference"> waist circumference</a> </p> <a href="https://publications.waset.org/abstracts/158891/the-link-between-anthropometry-and-fat-based-obesity-indices-in-pediatric-morbid-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158891.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">289</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1491</span> The Association of Vitamin B12 with Body Weight-and Fat-Based Indices in Childhood Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20Metin%20Donma">Mustafa Metin Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Vitamin deficiencies are common in obese individuals. Particularly, the status of vitamin B12 and its association with vitamin B9 (folate) and vitamin D is under investigation in recent time. Vitamin B12 is closely related to many vital processes in the body. In clinical studies, its involvement in fat metabolism draws attention from the obesity point of view. Obesity, in its advanced stages and in combination with metabolic syndrome (MetS) findings, may be a life-threatening health problem. Pediatric obesity is particularly important because it may be a predictor of severe chronic diseases during the adulthood period of the child. Due to its role in fat metabolism, vitamin B12 deficiency may disrupt metabolic pathways of the lipid and energy metabolisms in the body. The association of low B12 levels with obesity degree may be an interesting topic to be investigated. Obesity indices may be helpful at this point. Weight- and fat-based indices are available. Of them, body mass index (BMI) is in the first group. Fat mass index (FMI), fat-free mass index (FFMI) and diagnostic obesity notation model assessment-II (D2I) index lie in the latter group. The aim of this study is to clarify possible associations between vitamin B12 status and obesity indices in the pediatric population. The study comprises a total of one hundred and twenty-two children. Thirty-two children were included in the normal body mass index (N-BMI) group. Forty-six and forty-four children constitute groups with morbid obese children without MetS and with MetS, respectively. Informed consent forms and the approval of the institutional ethics committee were obtained. Tables prepared for obesity classification by World Health Organization were used. Metabolic syndrome criteria were defined. Anthropometric and blood pressure measurements were taken. Body mass index, FMI, FFMI, D2I were calculated. Routine laboratory tests were performed. Vitamin B9, B12, D concentrations were determined. Statistical evaluation of the study data was performed. Vitamin B9 and vitamin D levels were reduced in MetS group compared to children with N-BMI (p>0.05). Significantly lower values were observed in vitamin B12 concentrations of MetS group (p<0.01). Upon evaluation of blood pressure as well as triglyceride levels, there exist significant increases in morbid obese children. Significantly decreased concentrations of high density lipoprotein cholesterol were observed. All of the obesity indices and insulin resistance index exhibit increasing tendency with the severity of obesity. Inverse correlations were calculated between vitamin D and insulin resistance index as well as vitamin B12 and D2I in morbid obese groups. In conclusion, a fat-based index, D2I, was the most prominent body index, which shows a strong correlation with vitamin B12 concentrations in the late stage of obesity in children. A negative correlation between these two parameters was a confirmative finding related to the association between vitamin B12 and obesity degree. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=body%20mass%20index" title="body mass index">body mass index</a>, <a href="https://publications.waset.org/abstracts/search?q=children" title=" children"> children</a>, <a href="https://publications.waset.org/abstracts/search?q=D2I%20index" title=" D2I index"> D2I index</a>, <a href="https://publications.waset.org/abstracts/search?q=fat%20mass%20index" title=" fat mass index"> fat mass index</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a> </p> <a href="https://publications.waset.org/abstracts/138313/the-association-of-vitamin-b12-with-body-weight-and-fat-based-indices-in-childhood-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138313.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">206</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1490</span> Correlation between Overweightness and the Extent of Coronary Atherosclerosis among the South Caspian Population</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maryam%20Nabati">Maryam Nabati</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmood%20Moosazadeh"> Mahmood Moosazadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ehsan%20Soroosh"> Ehsan Soroosh</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanieh%20Shiraj"> Hanieh Shiraj</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahnaneh%20Gholami"> Mahnaneh Gholami</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Ghaemian"> Ali Ghaemian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Reported effects of obesity on the extent of angiographic coronary artery disease(CAD) have beeninconsistent. The present study aimed to investigate the relationships between the indices of obesity and otheranthropometric markers with the extent of CAD. Methods: This study was conducted on 1008 consecutive patients who underwent coronary angiography. Bodymass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) wereseparately calculated for each patient. Extent, severity, and complexity of CAD were determined by the Gensini andSYNTAX scores. Results: According to the results, there was a significant inverse correlation between the SYNTAX score with BMI(r = − 0.110; P < 0.001), WC (r = − 0.074; P = 0.018), and WHtR (r = − 0.089; P = 0.005). Furthermore, a significant inversecorrelation was observed between the Gensini score with BMI (r = − 0.090; P = 0.004) and WHtR (r = − 0.065; P =0.041). However, the results of multivariate linear regression analysis did not show any association between theSYNTAX and Gensini scores with the indices of obesity and overweight. On the other hand, the patients with anunhealthy WC had a higher prevalence of diabetes mellitus (DM) (P = 0.004) and hypertension (HTN) (P < 0.001) compared to the patients with healthy values. Coexistence of HTN and DM was more prevalent in subjects with anunhealthy WC and WHR compared to that in those with healthy values (P = 0.002 and P = 0.032, respectively). Conclusion: It seems that the anthropometric indices of obesity are not the predictors of the angiographic severityof CAD. However, they are associated with an increased risk of cardiovascular risk factors and higher risk profile. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=body%20mass%20index" title="body mass index">body mass index</a>, <a href="https://publications.waset.org/abstracts/search?q=BMI" title=" BMI"> BMI</a>, <a href="https://publications.waset.org/abstracts/search?q=coronary%20artery%20disease" title=" coronary artery disease"> coronary artery disease</a>, <a href="https://publications.waset.org/abstracts/search?q=waist%20circumference" title=" waist circumference"> waist circumference</a> </p> <a href="https://publications.waset.org/abstracts/150561/correlation-between-overweightness-and-the-extent-of-coronary-atherosclerosis-among-the-south-caspian-population" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150561.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">140</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1489</span> The Valuable Triad of Adipokine Indices to Differentiate Pediatric Obesity from Metabolic Syndrome: Chemerin, Progranulin, Vaspin</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obesity is associated with cardiovascular disease risk factors and metabolic syndrome (MetS). In this study, associations between adipokines and adipokine as well as obesity indices were evaluated. Plasma adipokine levels may exhibit variations according to body adipose tissue mass. Besides, upon consideration of obesity as an inflammatory disease, adipokines may play some roles in this process. The ratios of proinflammatory adipokines to adiponectin may act as highly sensitive indicators of body adipokine status. The aim of the study is to present some adipokine indices, which are thought to be helpful for the evaluation of childhood obesity and also to determine the best discriminators in the diagnosis of MetS. 80 prepubertal children (aged between 6-9.5 years) included in the study were divided into three groups; 30 children with normal weight (NW), 25 morbid obese (MO) children and 25 MO children with MetS. Physical examinations were performed. Written informed consent forms were obtained from the parents. The study protocol was approved by Ethics Committee of Namik Kemal University Medical Faculty. Anthropometric measurements, such as weight, height, waist circumference (C), hip C, head C, neck C were recorded. Values for body mass index (BMI), diagnostic obesity notation model assessment Index-II (D2 index) as well as waist-to-hip, head-to-neck ratios were calculated. Adiponectin, resistin, leptin, chemerin, vaspin, progranulin assays were performed by ELISA. Adipokine-to-adiponectin ratios were obtained. SPSS Version 20 was used for the evaluation of data. p values ≤ 0.05 were accepted as statistically significant. Values of BMI and D2 index, waist-to-hip, head-to-neck ratios did not differ between MO and MetS groups (p ≥ 0.05). Except progranulin (p ≤ 0.01), similar patterns were observed for plasma levels of each adipokine. There was not any difference in vaspin as well as resistin levels between NW and MO groups. Significantly increased leptin-to-adiponectin, chemerin-to-adiponectin and vaspin-to-adiponectin values were noted in MO in comparison with those of NW. The most valuable adipokine index was progranulin-to-adiponectin (p ≤ 0.01). This index was strongly correlated with vaspin-to-adiponectin ratio in all groups (p ≤ 0.05). There was no correlation between vaspin-to-adiponectin and chemerin-to--adiponectin in NW group. However, a correlation existed in MO group (r = 0.486; p ≤ 0.05). Much stronger correlation (r = 0.609; p ≤ 0.01) was observed in MetS group between these two adipokine indices. No correlations were detected between vaspin and progranulin as well as vaspin and chemerin levels. Correlation analyses showed a unique profile confined to MetS children. Adiponectin was found to be correlated with waist-to-hip (r = -0.435; p ≤ 0.05) as well as head-to-neck (r = 0.541; p ≤ 0.05) ratios only in MetS children. In this study, it has been investigated if adipokine indices have priority over adipokine levels. In conclusion, vaspin-to-adiponectin, progranulin-to-adiponectin, chemerin-to-adiponectin along with waist-to-hip and head-to-neck ratios were the optimal combinations. Adiponectin, waist-to-hip, head-to-neck, vaspin-to-adiponectin, chemerin-to-adiponectin ratios had appropriate discriminatory capability for MetS children. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adipokine%20indices" title="adipokine indices">adipokine indices</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20syndrome" title=" metabolic syndrome"> metabolic syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity%20indices" title=" obesity indices"> obesity indices</a>, <a href="https://publications.waset.org/abstracts/search?q=pediatric%20obesity" title=" pediatric obesity"> pediatric obesity</a> </p> <a href="https://publications.waset.org/abstracts/77350/the-valuable-triad-of-adipokine-indices-to-differentiate-pediatric-obesity-from-metabolic-syndrome-chemerin-progranulin-vaspin" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77350.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">205</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1488</span> Association of Overweight and Obesity with Breast Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amir%20Ghasemlouei">Amir Ghasemlouei</a>, <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Khalaj"> Alireza Khalaj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In women, cancer of the breast is one of the most common incident cancer and cause of death from cancer .we reviewed the prevalence of obesity and its association with breast cancer. In this study, a total of 25 articles regarding the subject matter of the article have been presented in which 640 patients were examined that 320 patients with breast cancer and 320 were controls. The distribution of breast cancer patients and controls with respect to their anthropometric indices in patients with higher weight, which was statistically significant (60.2 ± 10.2 kg) compared with control group (56.1 ± 11.3 kg). The body mass index of patients was (26.06+/-3.42) and significantly higher than the control group (24.1+/-1.7). Obesity leads to increased levels of adipose tissue in the body that can be stored toxins and carcinogens to produce a continuous supply. Due to the high level of fat and the role of estrogen in a woman is endogenous estrogen of the tumor and regulate the activities of growth steroids, obesity is a risk factor for breast cancer is confirmed. Our study and other studies show that obesity is a risk factor for breast cancer. And with a weight loss intervention for breast cancer can be prevented in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title="breast cancer">breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=review%20study" title=" review study"> review study</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=overweight" title=" overweight"> overweight</a> </p> <a href="https://publications.waset.org/abstracts/16945/association-of-overweight-and-obesity-with-breast-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16945.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">453</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1487</span> Laboratory Indices in Late Childhood Obesity: The Importance of DONMA Indices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma">Orkide Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma"> Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammet%20Demirkol"> Muhammet Demirkol</a>, <a href="https://publications.waset.org/abstracts/search?q=Murat%20Aydin"> Murat Aydin</a>, <a href="https://publications.waset.org/abstracts/search?q=Tuba%20Gokkus"> Tuba Gokkus</a>, <a href="https://publications.waset.org/abstracts/search?q=Burcin%20Nalbantoglu"> Burcin Nalbantoglu</a>, <a href="https://publications.waset.org/abstracts/search?q=Aysin%20Nalbantoglu"> Aysin Nalbantoglu</a>, <a href="https://publications.waset.org/abstracts/search?q=Birol%20Topcu"> Birol Topcu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obesity in childhood establishes a ground for adulthood obesity. Especially morbid obesity is an important problem for the children because of the associated diseases such as diabetes mellitus, cancer and cardiovascular diseases. In this study, body mass index (BMI), body fat ratios, anthropometric measurements and ratios were evaluated together with different laboratory indices upon evaluation of obesity in morbidly obese (MO) children. Children with nutritional problems participated in the study. Written informed consent was obtained from the parents. Study protocol was approved by the Ethics Committee. Sixty-two MO girls aged 129.5±35.8 months and 75 MO boys aged 120.1±26.6 months were included into the scope of the study. WHO-BMI percentiles for age-and-sex were used to assess the children with those higher than 99<sup>th</sup> as morbid obesity. Anthropometric measurements of the children were recorded after their physical examination. Bio-electrical impedance analysis was performed to measure fat distribution. Anthropometric ratios, body fat ratios, Index-I and Index-II as well as insulin sensitivity indices (ISIs) were calculated. Girls as well as boys were binary grouped according to homeostasis model assessment-insulin resistance (HOMA-IR) index of <2.5 and >2.5, fasting glucose to insulin ratio (FGIR) of <6 and >6 and quantitative insulin sensitivity check index (QUICKI) of <0.33 and >0.33 as the frequently used cut-off points. They were evaluated based upon their BMIs, arms, legs, trunk, whole body fat percentages, body fat ratios such as fat mass index (FMI), trunk-to-appendicular fat ratio (TAFR), whole body fat ratio (WBFR), anthropometric measures and ratios [waist-to-hip, head-to-neck, thigh-to-arm, thigh-to-ankle, height/2-to-waist, height/2-to-hip circumference (C)]. SPSS/PASW 18 program was used for statistical analyses. p≤0.05 was accepted as statistically significance level. All of the fat percentages showed differences between below and above the specified cut-off points in girls when evaluated with HOMA-IR and QUICKI. Differences were observed only in arms fat percent for HOMA-IR and legs fat percent for QUICKI in boys (p≤ 0.05). FGIR was unable to detect any differences for the fat percentages of boys. Head-to-neck C was the only anthropometric ratio recommended to be used for all ISIs (p≤0.001 for both girls and boys in HOMA-IR, p≤0.001 for girls and p≤0.05 for boys in FGIR and QUICKI). Indices which are recommended for use in both genders were Index-I, Index-II, HOMA/BMI and log HOMA (p≤0.001). FMI was also a valuable index when evaluated with HOMA-IR and QUICKI (p≤0.001). The important point was the detection of the severe significance for HOMA/BMI and log HOMA while they were evaluated also with the other indices, FGIR and QUICKI (p≤0.001). These parameters along with Index-I were unique at this level of significance for all children. In conclusion, well-accepted ratios or indices may not be valid for the evaluation of both genders. This study has emphasized the limiting properties for boys. This is particularly important for the selection process of some ratios and/or indices during the clinical studies. Gender difference should be taken into consideration for the evaluation of the ratios or indices, which will be recommended to be used particularly within the scope of obesity studies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anthropometry" title="anthropometry">anthropometry</a>, <a href="https://publications.waset.org/abstracts/search?q=childhood%20obesity" title=" childhood obesity"> childhood obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=gender" title=" gender"> gender</a>, <a href="https://publications.waset.org/abstracts/search?q=insulin%20sensitivity%20index" title=" insulin sensitivity index"> insulin sensitivity index</a> </p> <a href="https://publications.waset.org/abstracts/42290/laboratory-indices-in-late-childhood-obesity-the-importance-of-donma-indices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42290.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">356</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1486</span> Anthropometric Indices of Obesity and Coronary Artery Atherosclerosis: An Autopsy Study in South Indian population</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Francis%20Nanda%20Prakash%20Monteiro">Francis Nanda Prakash Monteiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Shyna%20Quadras"> Shyna Quadras</a>, <a href="https://publications.waset.org/abstracts/search?q=Tanush%20Shetty"> Tanush Shetty</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The association between human physique and morbidity and mortality resulting from coronary artery disease has been studied extensively over several decades. Multiple studies have also been done on the correlation between grade of atherosclerosis, coronary artery diseases and anthropometrical measurements. However, the number of autopsy-based studies drastically reduces this number. It has been suggested that while in living subjects, it would be expensive, difficult, and even harmful to subject them to imaging modalities like CT scans and procedures involving contrast media to study mild atherosclerosis, no such harm is encountered in study of autopsy cases. This autopsy-based study was aimed to correlate the anthropometric measurements and indices of obesity, such as waist circumference (WC), hip circumference (HC), body mass index (BMI) and waist hip ratio (WHR) with the degree of atherosclerosis in the right coronary artery (RCA), main branch of the left coronary artery (LCA) and the left anterior descending artery (LADA) in 95 South Indian origin victims of both the genders between the age of 18 years and 75 years. The grading of atherosclerosis was done according to criteria suggested by the American Heart Association. The study also analysed the correlation of the anthropometric measurements and indices of obesity with the number of coronaries affected with atherosclerosis in an individual. All the anthropometric measurements and the derived indices were found to be significantly correlated to each other in both the genders except for the age, which is found to have a significant correlation only with the WHR. In both the genders severe degree of atherosclerosis was commonly observed in LADA, followed by LCA and RCA. Grade of atherosclerosis in RCA is significantly related to the WHR in males. Grade of atherosclerosis in LCA and LADA is significantly related to the WHR in females. Significant relation was observed between grade of atherosclerosis in RCA and WC, and WHR, and between grade of atherosclerosis in LADA and HC in males. Significant relation was observed between grade of atherosclerosis in RCA and WC, and WHR, and between grade of atherosclerosis in LADA and HC in females. Anthropometric measurements/indices of obesity can be an effective means to identify high risk cases of atherosclerosis at an early stage that can be effective in reducing the associated cardiac morbidity and mortality. A person with anthropometric measurements suggestive of mild atherosclerosis can be advised to modify his lifestyle, along with decreasing his exposure to the other risk factors. Those with measurements suggestive of higher degree of atherosclerosis can be subjected to confirmatory procedures to start effective treatment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=atherosclerosis" title="atherosclerosis">atherosclerosis</a>, <a href="https://publications.waset.org/abstracts/search?q=coronary%20artery%20disease" title=" coronary artery disease"> coronary artery disease</a>, <a href="https://publications.waset.org/abstracts/search?q=indices" title=" indices"> indices</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a> </p> <a href="https://publications.waset.org/abstracts/168871/anthropometric-indices-of-obesity-and-coronary-artery-atherosclerosis-an-autopsy-study-in-south-indian-population" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168871.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">66</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1485</span> The Potential Involvement of Platelet Indices in Insulin Resistance in Morbid Obese Children </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma">Orkide Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma"> Mustafa M. Donma </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Association between insulin resistance (IR) and hematological parameters has long been a matter of interest. Within this context, body mass index (BMI), red blood cells, white blood cells and platelets were involved in this discussion. Parameters related to platelets associated with IR may be useful indicators for the identification of IR. Platelet indices such as mean platelet volume (MPV), platelet distribution width (PDW) and plateletcrit (PCT) are being questioned for their possible association with IR. The aim of this study was to investigate the association between platelet (PLT) count as well as PLT indices and the surrogate indices used to determine IR in morbid obese (MO) children. A total of 167 children participated in the study. Three groups were constituted. The number of cases was 34, 97 and 36 children in the normal BMI, MO and metabolic syndrome (MetS) groups, respectively. Sex- and age-dependent BMI-based percentile tables prepared by World Health Organization were used for the definition of morbid obesity. MetS criteria were determined. BMI values, homeostatic model assessment for IR (HOMA-IR), alanine transaminase-to-aspartate transaminase ratio (ALT/AST) and diagnostic obesity notation model assessment laboratory (DONMA-lab) index values were computed. PLT count and indices were analyzed using automated hematology analyzer. Data were collected for statistical analysis using SPSS for Windows. Arithmetic mean and standard deviation were calculated. Mean values of PLT-related parameters in both control and study groups were compared by one-way ANOVA followed by Tukey post hoc tests to determine whether a significant difference exists among the groups. The correlation analyses between PLT as well as IR indices were performed. Statistically significant difference was accepted as p-value < 0.05. Increased values were detected for PLT (p < 0.01) and PCT (p > 0.05) in MO group compared to those observed in children with N-BMI. Significant increases for PLT (p < 0.01) and PCT (p < 0.05) were observed in MetS group in comparison with the values obtained in children with N-BMI (p < 0.01). Significantly lower MPV and PDW values were obtained in MO group compared to the control group (p < 0.01). HOMA-IR (p < 0.05), DONMA-lab index (p < 0.001) and ALT/AST (p < 0.001) values in MO and MetS groups were significantly increased compared to the N-BMI group. On the other hand, DONMA-lab index values also differed between MO and MetS groups (p < 0.001). In the MO group, PLT was negatively correlated with MPV and PDW values. These correlations were not observed in the N-BMI group. None of the IR indices exhibited a correlation with PLT and PLT indices in the N-BMI group. HOMA-IR showed significant correlations both with PLT and PCT in the MO group. All of the three IR indices were well-correlated with each other in all groups. These findings point out the missing link between IR and PLT activation. In conclusion, PLT and PCT may be related to IR in addition to their identities as hemostasis markers during morbid obesity. Our findings have suggested that DONMA-lab index appears as the best surrogate marker for IR due to its discriminative feature between morbid obesity and MetS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=insulin%20resistance" title=" insulin resistance"> insulin resistance</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20syndrome" title=" metabolic syndrome"> metabolic syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=plateletcrit" title=" plateletcrit"> plateletcrit</a>, <a href="https://publications.waset.org/abstracts/search?q=platelet%20indices" title=" platelet indices"> platelet indices</a> </p> <a href="https://publications.waset.org/abstracts/117529/the-potential-involvement-of-platelet-indices-in-insulin-resistance-in-morbid-obese-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/117529.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">106</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1484</span> Blood Pressure and Anthropometric Measurements: A Correlational Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdul-Monim%20Batiha">Abdul-Monim Batiha</a>, <a href="https://publications.waset.org/abstracts/search?q=Manar%20AlAzzam"> Manar AlAzzam</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20ALBashtawy"> Mohammed ALBashtawy</a>, <a href="https://publications.waset.org/abstracts/search?q=Loai%20Tawalbeh"> Loai Tawalbeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20%20Tubaishat"> Ahmad Tubaishat</a>, <a href="https://publications.waset.org/abstracts/search?q=Fadwa%20N.%20Alhalaiqa"> Fadwa N. Alhalaiqa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Obesity is the major modifiable risk factor for many chronic illnesses especially high blood pressure. Objectives: To evaluate the relationship between anthropometric indices and high blood pressure, and which one was most strongly correlated with high blood pressure in Jordanian population. Methods: A cross-sectional study was conducted with a total 622 students and workers from three Jordanian universities. Results: Nearly half of the participant are overweight (34.7%) and obese (15.4%) and hypertension was detected among 138 (22.2%) of the participants. Linear correlation was significant (p<0.01) between both systolic blood pressure and diastolic blood pressure for all anthropometric indices, except for A body shape index and diastolic blood pressure was significant at p< 0.05. Stepwise multiple linear regression analysis was used to assess the influence of age and anthropometric measurements. Conclusions: The waist circumference was the only independent predictor of hypertension, showing that this simple measurement may be an importance marker of high blood pressure in Jordanian population. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anthropometric%20indices" title="anthropometric indices">anthropometric indices</a>, <a href="https://publications.waset.org/abstracts/search?q=Jordan" title=" Jordan"> Jordan</a>, <a href="https://publications.waset.org/abstracts/search?q=blood%20pressure" title=" blood pressure"> blood pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-sectional%20study" title=" cross-sectional study"> cross-sectional study</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=hypertension" title=" hypertension"> hypertension</a>, <a href="https://publications.waset.org/abstracts/search?q=waist%20circumference" title=" waist circumference"> waist circumference</a> </p> <a href="https://publications.waset.org/abstracts/54804/blood-pressure-and-anthropometric-measurements-a-correlational-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54804.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">288</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1483</span> Low Density Lipoprotein: The Culprit in the Development of Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ojiegbe%20Ikenna%20Nathan">Ojiegbe Ikenna Nathan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obesity is a medical condition in which excess body fat has accumulated to the extent that it leads to reduced life expectancy and or increased health problems. Obesity as a worldwide problem is seen clustered in the families and it moves from generation to generation. It causes some disabilities, mortality and morbidity if left unattended to. The predisposing factors to obesity are either genetic or environment in origin. Nevertheless, the main predisposing factor to obesity is the excessive consumption of food rich in low-density lipoprotein (LDL) such as organ meats, saturated fats etc. This low-density lipoprotein causes an increase in adipose tissue and complicates to obesity. There are varieties of obesity which one needs to take appropriate measures to avoid; such as android, gynoid and morbid obesity. Nonetheless, studies have shown that there is hope for the obese individuals, despite the cause, type and degree of their obesity. This is through the use of the different available treatment measures which increase in physical activities, caloric restrictions, drug therapy and surgical intervention. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=low-density" title="low-density">low-density</a>, <a href="https://publications.waset.org/abstracts/search?q=lipoprotein" title=" lipoprotein"> lipoprotein</a>, <a href="https://publications.waset.org/abstracts/search?q=culprit" title=" culprit"> culprit</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity "> obesity </a> </p> <a href="https://publications.waset.org/abstracts/23090/low-density-lipoprotein-the-culprit-in-the-development-of-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23090.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">400</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1482</span> The Importance of Erythrocyte Parameters in Obese Children</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma">Orkide Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Metin%20Donma"> M. Metin Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Burcin%20Nalbantoglu"> Burcin Nalbantoglu</a>, <a href="https://publications.waset.org/abstracts/search?q=Birol%20Topcu"> Birol Topcu</a>, <a href="https://publications.waset.org/abstracts/search?q=Feti%20Tulubas"> Feti Tulubas</a>, <a href="https://publications.waset.org/abstracts/search?q=Murat%20Aydin"> Murat Aydin</a>, <a href="https://publications.waset.org/abstracts/search?q=Tuba%20Gokkus"> Tuba Gokkus</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmet%20Gurel"> Ahmet Gurel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Increasing prevalence of childhood obesity has increased the interest in early and late indicators of gaining weight. Cell blood counts may be indicators of proinflammatory states. The aim was to evaluate associations of hematological parameters, including Hematocrit (HTC), hemoglobin, blood cell counts, and their indices with the degree of obesity in pediatric population. A total of 249; -139 morbidly obese (MO), 82 healthy Normal Weight (NW) and 28 Overweight (OW) children were included into the scope of the study. WHO BMI-for age percentiles were used to form age- and sex-matched groups. Informed consent forms and the Ethics Committee approval were obtained. Anthropometric measurements were performed. Hematological parameters were determined. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. Significant differences (p=0.000) between waist-to-hip ratios and head-to-neck ratios (hnrs) of MO and NW children were detected. A significant difference between hnrs of OW and MO children (p=0.000) was observed. Red cell Distribution Width (RDW) was higher in OW children than NW group (p=0.030). Such finding couldn’t be detected between MO and NW groups. Increased RDW was prominent in OW children. The decrease in Mean Corpuscular Hemoglobin Concentration (MCHC) values in MO children was sharper than the values in OW children (p=0.006 vs p=0.042) compared to those in NW group. Statistically higher HTC levels were observed between MO-NW (p=0.014), but none between OW-NW. Though the cause-effect relationship between obesity and erythrocyte indices still needs further investigation, alterations in RDW, HTC, MCHC during obesity may be of significance in the early life. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anthropometry" title="anthropometry">anthropometry</a>, <a href="https://publications.waset.org/abstracts/search?q=children" title=" children"> children</a>, <a href="https://publications.waset.org/abstracts/search?q=erythrocytes" title=" erythrocytes"> erythrocytes</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a> </p> <a href="https://publications.waset.org/abstracts/30528/the-importance-of-erythrocyte-parameters-in-obese-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30528.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">352</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1481</span> An Indispensable Parameter in Lipid Ratios to Discriminate between Morbid Obesity and Metabolic Syndrome in Children: High Density Lipoprotein Cholesterol</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma">Orkide Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma"> Mustafa M. Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obesity is a low-grade inflammatory disease and may lead to health problems such as hypertension, dyslipidemia, diabetes. It is also associated with important risk factors for cardiovascular diseases. This requires the detailed evaluation of obesity, particularly in children. The aim of this study is to enlighten the potential associations between lipid ratios and obesity indices and to introduce those with discriminating features among children with obesity and metabolic syndrome (MetS). A total of 408 children (aged between six and eighteen years) participated in the scope of the study. Informed consent forms were taken from the participants and their parents. Ethical Committee approval was obtained. Anthropometric measurements such as weight, height as well as waist, hip, head, neck circumferences and body fat mass were taken. Systolic and diastolic blood pressure values were recorded. Body mass index (BMI), diagnostic obesity notation model assessment index-II (D2 index), waist-to-hip, head-to-neck ratios were calculated. Total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDLChol), low-density lipoprotein cholesterol (LDLChol) analyses were performed in blood samples drawn from 110 children with normal body weight, 164 morbid obese (MO) children and 134 children with MetS. Age- and sex-adjusted BMI percentiles tabulated by World Health Organization were used to classify groups; normal body weight, MO and MetS. 15<sup>th</sup>-to-85<sup>th</sup> percentiles were used to define normal body weight children. Children, whose values were above the 99th percentile, were described as MO. MetS criteria were defined. Data were evaluated statistically by SPSS Version 20. The degree of statistical significance was accepted as p≤0.05. Mean±standard deviation values of BMI for normal body weight children, MO children and those with MetS were 15.7±1.1, 27.1±3.8 and 29.1±5.3 kg/m<sup>2</sup>, respectively. Corresponding values for the D2 index were calculated as 3.4±0.9, 14.3±4.9 and 16.4±6.7. Both BMI and D2 index were capable of discriminating the groups from one another (p≤0.01). As far as other obesity indices were considered, waist-to hip and head-to-neck ratios did not exhibit any statistically significant difference between MO and MetS groups (p≥0.05). Diagnostic obesity notation model assessment index-II was correlated with the triglycerides-to-HDL-C ratio in normal body weight and MO (r=0.413, p≤0.01 and r=0.261, (p≤0.05, respectively). Total cholesterol-to-HDL-C and LDL-C-to-HDL-C showed statistically significant differences between normal body weight and MO as well as MO and MetS (p≤0.05). The only group in which these two ratios were significantly correlated with waist-to-hip ratio was MetS group (r=0.332 and r=0.334, p≤0.01, respectively). Lack of correlation between the D2 index and the triglycerides-to-HDL-C ratio was another important finding in MetS group. In this study, parameters and ratios, whose associations were defined previously with increased cardiovascular risk or cardiac death have been evaluated along with obesity indices in children with morbid obesity and MetS. Their profiles during childhood have been investigated. Aside from the nature of the correlation between the D2 index and triglycerides-to-HDL-C ratio, total cholesterol-to-HDL-C as well as LDL-C-to- HDL-C ratios along with their correlations with waist-to-hip ratio showed that the combination of obesity-related parameters predicts better than one parameter and appears to be helpful for discriminating MO children from MetS group. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=lipid%20ratios" title=" lipid ratios"> lipid ratios</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20syndrome" title=" metabolic syndrome"> metabolic syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity%20indices" title=" obesity indices"> obesity indices</a> </p> <a href="https://publications.waset.org/abstracts/77349/an-indispensable-parameter-in-lipid-ratios-to-discriminate-between-morbid-obesity-and-metabolic-syndrome-in-children-high-density-lipoprotein-cholesterol" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77349.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">159</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1480</span> Evaluation of Vitamin D Levels in Obese and Morbid Obese Children </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma">Orkide Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma"> Mustafa M. Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obesity may lead to growing serious health problems throughout the world. Vitamin D appears to play a role in cardiovascular and metabolic health. Vitamin D deficiency may add to derangements in human metabolic systems, particularly those of children. Childhood obesity is associated with an increased risk of chronic and sophisticated diseases. The aim of this study is to investigate associations as well as possible differences related to parameters affected by obesity and their relations with vitamin D status in obese (OB) and morbid obese (MO) children. This study included a total of 78 children. Of them, 41 and 37 were OB and MO, respectively. WHO BMI-for age percentiles were used for the classification of obesity. The values above 99 percentile were defined as MO. Those between 95 and 99 percentiles were included into OB group. Anthropometric measurements were recorded. Basal metabolic rates (BMRs) were measured. Vitamin D status is determined by the measurement of 25-hydroxy cholecalciferol [25- hydroxyvitamin D3, 25(OH)D] using high-performance liquid chromatography. Vitamin D status was evaluated as deficient, insufficient and sufficient. Values < 20.0 ng/ml, values between 20-30 ng/ml and values > 30.0 ng/ml were defined as vitamin D deficient, insufficient and sufficient, respectively. Optimal 25(OH)D level was defined as ≥ 30 ng/ml. SPSSx statistical package program was used for the evaluation of the data. The statistical significance degree was accepted as p < 0.05. Mean ages did not differ between the groups. Significantly increased body mass index (BMI), waist circumference (C) and neck C as well as significantly decreased fasting blood glucose (FBG) and vitamin D values were observed in MO group (p < 0.05). In OB group, 37.5% of the children were vitamin D deficient, and in MO group the corresponding value was 53.6%. No difference between the groups in terms of lipid profile, systolic blood pressure (SBP), diastolic blood pressure (DBP) and insulin values was noted. There was a severe statistical significance between FBG values of the groups (p < 0.001). Important correlations between BMI, waist C, hip C, neck C and both SBP as well as DBP were found in OB group. In MO group, correlations only with SBP were obtained. In a similar manner, in OB group, correlations were detected between SBP-BMR and DBP-BMR. However, in MO children, BMR correlated only with SBP. The associations of vitamin D with anthropometric indices as well as some lipid parameters were defined. In OB group BMI, waist C, hip C and triglycerides (TRG) were negatively correlated with vitamin D concentrations whereas none of them were detected in MO group. Vitamin D deficiency may contribute to the complications associated with childhood obesity. Loss of correlations between obesity indices-DBP, vitamin D-TRG, as well as relatively lower FBG values, observed in MO group point out that the emergence of MetS components starts during obesity state just before the transition to morbid obesity. Aside from its deficiency state, associations of vitamin D with anthropometric measurements, blood pressures and TRG should also be evaluated before the development of morbid obesity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=morbid%20obesity" title=" morbid obesity"> morbid obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=vitamin%20D" title=" vitamin D"> vitamin D</a> </p> <a href="https://publications.waset.org/abstracts/90584/evaluation-of-vitamin-d-levels-in-obese-and-morbid-obese-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90584.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">141</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1479</span> Associations between Surrogate Insulin Resistance Indices and the Risk of Metabolic Syndrome in Children </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma </a> </p> <p class="card-text"><strong>Abstract:</strong></p> A well-defined insulin resistance (IR) is one of the requirements for the good understanding and evaluation of metabolic syndrome (MetS). However, underlying causes for the development of IR are not clear. Endothelial dysfunction also participates in the pathogenesis of this disease. IR indices are being determined in various obesity groups and also in diagnosing MetS. Components of MetS have been well established and used in adult studies. However, there are some ambiguities particularly in the field of pediatrics. The aims of this study were to compare the performance of fasting blood glucose (FBG), one of MetS components, with some other IR indices and check whether FBG may be replaced by some other parameter or ratio for a better evaluation of pediatric MetS. Five-hundred and forty-nine children were involved in the study. Five groups were constituted. Groups 109, 40, 100, 166, 110, 24 children were included in normal-body mass index (N-BMI), overweight (OW), obese (OB), morbid obese (MO), MetS with two components (MetS2) and MetS with three components (MetS3) groups, respectively. Age and sex-adjusted BMI percentiles tabulated by World Health Organization were used for the classification of obesity groups. MetS components were determined. Aside from one of the MetS components-FBG, eight measures of IR [homeostatic model assessment of IR (HOMA-IR), homeostatic model assessment of beta cell function (HOMA-%β), alanine transaminase-to-aspartate transaminase ratio (ALT/AST), alanine transaminase (ALT), insulin (INS), insulin-to-FBG ratio (INS/FBG), the product of fasting triglyceride and glucose (TyG) index, McAuley index] were evaluated. Statistical analyses were performed. A p value less than 0.05 was accepted as the statistically significance degree. Mean values for BMI of the groups were 15.7 kg/m<sup>2</sup>, 21.0 kg/m<sup>2</sup>, 24.7 kg/m<sup>2</sup>, 27.1 kg/m<sup>2</sup>, 28.7 kg/m<sup>2</sup>, 30.4 kg/m<sup>2</sup> for N-BMI, OW, OB, MO, MetS2, MetS3, respectively. Differences between the groups were significant (p < 0.001). The only exception was MetS2-MetS3 couple, in spite of an increase detected in MetS3 group. Waist-to-hip circumference ratios significantly differed only for N-BMI vs, OB, MO, MetS2; OW <em>vs</em> MO; OB <em>vs</em> MO, MetS2 couples. ALT and ALT/AST did not differ significantly among MO-MetS2-MetS3. HOMA-%β differed only between MO and MetS2. INS/FBG, McAuley index and TyG were not significant between MetS2 and MetS3. HOMA-IR and FBG were not significant between MO and MetS2. INS was the only parameter, which showed statistically significant differences between MO-MetS2, MO-MetS3, and MetS2-MetS3. In conclusion, these findings have suggested that FBG presently considered as one of the five MetS components, may be replaced by INS during the evaluation of pediatric morbid obesity and MetS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=insulin%20resistance%20indices" title=" insulin resistance indices"> insulin resistance indices</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20syndrome" title=" metabolic syndrome"> metabolic syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a> </p> <a href="https://publications.waset.org/abstracts/115468/associations-between-surrogate-insulin-resistance-indices-and-the-risk-of-metabolic-syndrome-in-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115468.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">122</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1478</span> Association of Phosphorus and Magnesium with Fat Indices in Children with Metabolic Syndrome</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Metabolic syndrome (MetS) is a disease associated with obesity. It is a complicated clinical problem possibly affecting body composition as well as macrominerals. These parameters gain further attention, particularly in the pediatric population. The aim of this study is to investigate the amount of discrete body composition fractions in groups that differ in the severity of obesity. Also, the possible associations with calcium (Ca), phosphorus (P), magnesium (Mg) will be examined. The study population was divided into four groups. Twenty-eight, 29, 34, and 34 children were involved in Group 1 (healthy), 2 (obese), 3 (morbid obese), and 4 (MetS), respectively. Institutional Ethical Committee approved the study protocol. Informed consent forms were obtained from the participants. The classification of obese groups was performed based upon the recommendations of the World Health Organization. Metabolic syndrome components were defined. Serum Ca, P, Mg concentrations were measured. Within the scope of body composition, fat mass, fat-free mass, protein mass, mineral mass were determined by a body composition monitor using bioelectrical impedance analysis technology. Weight, height, waist circumference, hip circumference, head circumference, and neck circumference values were recorded. Body mass index, diagnostic obesity notation model assessment index, fat mass index, and fat-free mass index values were calculated. Data were statistically evaluated and interpreted. There was no statistically significant difference among the groups in terms of Ca and P concentrations. Magnesium concentrations differed between Group 1 and Group 4. Strong negative correlations were detected between P as well as Mg and fat mass index as well as diagnostic obesity notation model assessment index in Group 4, the group, which comprised morbid obese children with MetS. This study emphasized unique associations of P and Mg minerals with diagnostic obesity notation model assessment index and fat mass index during the evaluation of morbid obese children with MetS. It was also concluded that diagnostic obesity notation model assessment index and fat mass index were more proper indices in comparison with body mass index and fat-free mass index for the purpose of defining body composition in children. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=children" title="children">children</a>, <a href="https://publications.waset.org/abstracts/search?q=fat%20mass" title=" fat mass"> fat mass</a>, <a href="https://publications.waset.org/abstracts/search?q=fat-free%20mass" title=" fat-free mass"> fat-free mass</a>, <a href="https://publications.waset.org/abstracts/search?q=macrominerals" title=" macrominerals"> macrominerals</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a> </p> <a href="https://publications.waset.org/abstracts/143556/association-of-phosphorus-and-magnesium-with-fat-indices-in-children-with-metabolic-syndrome" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143556.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">153</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1477</span> Blood Microbiome in Different Metabolic Types of Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Irina%20M.%20Kolesnikova">Irina M. Kolesnikova</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrey%20M.%20Gaponov"> Andrey M. Gaponov</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergey%20A.%20Roumiantsev"> Sergey A. Roumiantsev</a>, <a href="https://publications.waset.org/abstracts/search?q=Tatiana%20V.%20Grigoryeva"> Tatiana V. Grigoryeva</a>, <a href="https://publications.waset.org/abstracts/search?q=Dilyara%20R.%20Khusnutdinova"> Dilyara R. Khusnutdinova</a>, <a href="https://publications.waset.org/abstracts/search?q=Dilyara%20R.%20Kamaldinova"> Dilyara R. Kamaldinova</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20V.%20Shestopalov"> Alexander V. Shestopalov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background. Obese patients have unequal risks of metabolic disorders. It is accepted to distinguish between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO). MUHO patients have a high risk of metabolic disorders, insulin resistance, and diabetes mellitus. Among the other things, the gut microbiota also contributes to the development of metabolic disorders in obesity. Obesity is accompanied by significant changes in the gut microbial community. In turn, bacterial translocation from the intestine is the basis for the blood microbiome formation. The aim was to study the features of the blood microbiome in patients with various metabolic types of obesity. Patients, materials, methods. The study included 116 healthy donors and 101 obese patients. Depending on the metabolic type of obesity, the obese patients were divided into subgroups with MHO (n=36) and MUHO (n=53). Quantitative and qualitative assessment of the blood microbiome was based on metagenomic analysis. Blood samples were used to isolate DNA and perform sequencing of the variable v3-v4 region of the 16S rRNA gene. Alpha diversity indices (Simpson index, Shannon index, Chao1 index, phylogenetic diversity, the number of observed operational taxonomic units) were calculated. Moreover, we compared taxa (phyla, classes, orders, and families) in terms of isolation frequency and the taxon share in the total bacterial DNA pool between different patient groups. Results. In patients with MHO, the characteristics of the alpha-diversity of the blood microbiome were like those of healthy donors. However, MUHO was associated with an increase in all diversity indices. The main phyla of the blood microbiome were Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. Cyanobacteria, TM7, Thermi, Verrucomicrobia, Chloroflexi, Acidobacteria, Planctomycetes, Gemmatimonadetes, and Tenericutes were found to be less significant phyla of the blood microbiome. Phyla Acidobacteria, TM7, and Verrucomicrobia were more often isolated in blood samples of patients with MUHO compared with healthy donors. Obese patients had a decrease in some taxonomic ranks (Bacilli, Caulobacteraceae, Barnesiellaceae, Rikenellaceae, Williamsiaceae). These changes appear to be related to the increased diversity of the blood microbiome observed in obesity. An increase of Lachnospiraceae, Succinivibrionaceae, Prevotellaceae, and S24-7 was noted for MUHO patients, which, apparently, is explained by a magnification in intestinal permeability. Conclusion. Blood microbiome differs in obese patients and healthy donors at class, order, and family levels. Moreover, the nature of the changes is determined by the metabolic type of obesity. MUHO linked to increased diversity of the blood microbiome. This appears to be due to increased microbial translocation from the intestine and non-intestinal sources. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blood%20microbiome" title="blood microbiome">blood microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=blood%20bacterial%20DNA" title=" blood bacterial DNA"> blood bacterial DNA</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolically%20healthy%20obesity" title=" metabolically healthy obesity"> metabolically healthy obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolically%20unhealthy%20obesity" title=" metabolically unhealthy obesity"> metabolically unhealthy obesity</a> </p> <a href="https://publications.waset.org/abstracts/145332/blood-microbiome-in-different-metabolic-types-of-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145332.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">164</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1476</span> Relationship between Hepatokines and Insulin Resistance in Childhood Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20Metin%20Donma">Mustafa Metin Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Childhood obesity is an important clinical problem because it may lead to chronic diseases during the adulthood period of the individual. Obesity is a metabolic disease associated with low-grade inflammation. The liver occurs at the center of metabolic pathways. Adropin, fibroblast growth factor-21 (FGF-21), and fetuin-A are hepatokines. Due to the immense participation of the liver in glucose metabolism, these liver-derived factors may be associated with insulin resistance (IR), which is a phenomenon discussed within the scope of obesity problems. The aim of this study is to determine the concentrations of adropin, FGF-21, and fetuin-A in childhood obesity, to point out possible differences between the obesity groups, and to investigate possible associations among these three hepatokines in obese and morbidly obese children. A total of one hundred and thirty-two children were included in the study. Two obese groups were constituted. The groups were matched in terms of mean ± SD values of ages. Body mass index values of obese and morbidly obese groups were 25.0 ± 3.5 kg/m² and 29.8 ± 5.7 kg/m², respectively. Anthropometric measurements including waist circumference, hip circumference, head circumference, and neck circumference were recorded. Informed consent forms were taken from the parents of the participants. The ethics committee of the institution approved the study protocol. Blood samples were obtained after overnight fasting. Routine biochemical tests, including glucose- and lipid-related parameters, were performed. Concentrations of the hepatokines (adropin, FGF-21, fetuin A) were determined by enzyme-linked immunosorbent assay. Insulin resistance indices such as homeostasis model assessment for IR (HOMA-IR), alanine transaminase-to aspartate transaminase ratio (ALT/AST), diagnostic obesity notation model assessment laboratory index, diagnostic obesity notation model assessment metabolic syndrome index as well as obesity indices such as diagnostic obesity notation model assessment-II index, and fat mass index were calculated using the previously derived formulas. Statistical evaluation of the study data as well as findings of the study was performed by SPSS for Windows. Statistical difference was accepted significant when p is smaller than 0.05. Statistically significant differences were found for insulin, triglyceride, high-density lipoprotein cholesterol levels of the groups. A significant increase was observed for FGF-21 concentrations in the morbidly obese group. Higher adropin and fetuin-A concentrations were observed in the same group in comparison with the values detected in the obese group (p > 0.05). There was no statistically significant difference between the ALT/AST values of the groups. In all of the remaining IR and obesity indices, significantly increased values were calculated for morbidly obese children. Significant correlations were detected between HOMA-IR and each of the hepatokines. The highest one was the association with fetuin-A (r=0.373, p=0.001). In conclusion, increased levels observed in adropin, FGF-21, and fetuin-A have shown that these hepatokines possess increasing potential going from obese to morbid obese state. Out of the correlations found with the IR index, the most affected hepatokine was fetuin-A, the parameter possibly used as the indicator of the advanced obesity stage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adropin" title="adropin">adropin</a>, <a href="https://publications.waset.org/abstracts/search?q=fetuin%20A" title=" fetuin A"> fetuin A</a>, <a href="https://publications.waset.org/abstracts/search?q=fibroblast%20growth%20factor-21" title=" fibroblast growth factor-21"> fibroblast growth factor-21</a>, <a href="https://publications.waset.org/abstracts/search?q=insulin%20resistance" title=" insulin resistance"> insulin resistance</a>, <a href="https://publications.waset.org/abstracts/search?q=pediatric%20obesity" title=" pediatric obesity"> pediatric obesity</a> </p> <a href="https://publications.waset.org/abstracts/138265/relationship-between-hepatokines-and-insulin-resistance-in-childhood-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138265.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">176</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1475</span> Gender Differences in Morbid Obese Children: Clinical Significance of Two Diagnostic Obesity Notation Model Assessment Indices </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Murat%20Aydin"> Murat Aydin</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammet%20Demirkol"> Muhammet Demirkol</a>, <a href="https://publications.waset.org/abstracts/search?q=Burcin%20Nalbantoglu"> Burcin Nalbantoglu</a>, <a href="https://publications.waset.org/abstracts/search?q=Aysin%20Nalbantoglu"> Aysin Nalbantoglu</a>, <a href="https://publications.waset.org/abstracts/search?q=Birol%20Topcu"> Birol Topcu </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Childhood obesity is an ever increasing global health problem, affecting both developed and developing countries. Accurate evaluation of obesity in children requires difficult and detailed investigation. In our study, obesity in children was evaluated using new body fat ratios and indices. Assessment of anthropometric measurements, as well as some ratios, is important because of the evaluation of gender differences particularly during the late periods of obesity. A total of 239 children; 168 morbid obese (MO) (81 girls and 87 boys) and 71 normal weight (NW) (40 girls and 31 boys) children, participated in the study. Informed consent forms signed by the parents were obtained. Ethics Committee approved the study protocol. Mean ages (years)±SD calculated for MO group were 10.8±2.9 years in girls and 10.1±2.4 years in boys. The corresponding values for NW group were 9.0±2.0 years in girls and 9.2±2.1 years in boys. Mean body mass index (BMI)±SD values for MO group were 29.1±5.4 kg/m<sup>2</sup> and 27.2±3.9 kg/m<sup>2 </sup>in girls and boys, respectively. These values for NW group were calculated as 15.5±1.0 kg/m<sup>2</sup> in girls and 15.9±1.1 kg/m<sup>2 </sup>in boys. Groups were constituted based upon BMI percentiles for age-and-sex values recommended by WHO. Children with percentiles >99 were grouped as MO and children with percentiles between 85 and 15 were considered NW. The anthropometric measurements were recorded and evaluated along with the new ratios such as trunk-to-appendicular fat ratio, as well as indices such as Index-I and Index-II. The body fat percent values were obtained by bio-electrical impedance analysis. Data were entered into a database for analysis using SPSS/PASW 18 Statistics for Windows statistical software. Increased waist-to-hip circumference (C) ratios, decreased head-to-neck C, height ‘to’ ‘two’-‘to’-waist C and height ‘to’ ‘two’-‘to’-hip C ratios were observed in parallel with the development of obesity (p≤0.001). Reference value for height ‘to’ ‘two’-‘to’-hip ratio was detected as approximately 1.0. Index-II, based upon total body fat mass, showed much more significant differences between the groups than Index-I based upon weight. There was not any difference between trunk-to-appendicular fat ratios of NW girls and NW boys (p≥0.05). However, significantly increased values for MO girls in comparison with MO boys were observed (p≤0.05). This parameter showed no difference between NW and MO states in boys (p≥0.05). However, statistically significant increase was noted in MO girls compared to their NW states (p≤0.001). Trunk-to-appendicular fat ratio was the only fat-based parameter, which showed gender difference between NW and MO groups. This study has revealed that body ratios and formula based upon body fat tissue are more valuable parameters than those based on weight and height values for the evaluation of morbid obesity in children. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anthropometry" title="anthropometry">anthropometry</a>, <a href="https://publications.waset.org/abstracts/search?q=childhood%20obesity" title=" childhood obesity"> childhood obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=gender" title=" gender"> gender</a>, <a href="https://publications.waset.org/abstracts/search?q=morbid%20obesity" title=" morbid obesity"> morbid obesity</a> </p> <a href="https://publications.waset.org/abstracts/42289/gender-differences-in-morbid-obese-children-clinical-significance-of-two-diagnostic-obesity-notation-model-assessment-indices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42289.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">325</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1474</span> Indicators for Success of Obesity Reduction Programs in Adolescents; Body Composition and Body Mass Index: Evaluating a School-Based Health Promotion Project in Iran after 12 Weeks of Intervention</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeid%20Doaei">Saeid Doaei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Obesity in adolescence is a primary risk factor for obesity in adulthood. The objective of this study was the assessment of the effect of a comprehensive lifestyle intervention on different anthropometric indices in 12 to 16 years old boy adolescents. Methods: 96 adolescent boys of two schools of District 5 of Tehran have participated in this study. The schools were randomly assigned as intervention school (n=53) and control school (n=43). The height and weight of students were measured with a calibrated tape line and digital scale respectively and their BMI were calculated. The amounts of body fat percent (BF) and body muscle (BM) percent were determined by Bio Impedance Analyzer (BIA) considering the age, gender and height of students at baseline and after intervention. The intervention was implemented in the intervention school, according to the Ottawa charter principles. Results: 12 weeks of intervention decreased body fat percent in the intervention group in comparison with the control group (decreased by 1.81 % in the intervention group and increased by .39 % in the control group, P < .01). However, weight, BMI and BM did not change significantly. Conclusion: The result of this study showed that the implementation of comprehensive intervention in obese adolescents may improve the body composition, although these changes may not be reflected in BMI. It is possible that BMI is not a good indicator in assessment of the success of obesity management intervention. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=obesity" title="obesity">obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=childhood" title=" childhood"> childhood</a>, <a href="https://publications.waset.org/abstracts/search?q=BMI" title=" BMI"> BMI</a>, <a href="https://publications.waset.org/abstracts/search?q=nutrition" title=" nutrition"> nutrition</a> </p> <a href="https://publications.waset.org/abstracts/71017/indicators-for-success-of-obesity-reduction-programs-in-adolescents-body-composition-and-body-mass-index-evaluating-a-school-based-health-promotion-project-in-iran-after-12-weeks-of-intervention" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71017.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">271</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1473</span> Family History of Obesity and Risk of Childhood Overweight and Obesity: A Meta-Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Martina%20Kanciruk">Martina Kanciruk</a>, <a href="https://publications.waset.org/abstracts/search?q=Jac%20J.%20W.%20Andrews"> Jac J. W. Andrews</a>, <a href="https://publications.waset.org/abstracts/search?q=Tyrone%20Donnon"> Tyrone Donnon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this study was to determine the significance of history of obesity for the development of childhood overweight and/or obesity. Accordingly, a systematic literature review of English-language studies published from 1980 to 2012 using the following data bases: MEDLINE, PsychINFO, Cochrane Database of Systematic Reviews, and Dissertation Abstracts International was conducted. The following terms were used in the search: pregnancy, overweight, obesity, family history, parents, childhood, risk factors. Eleven studies of family history and obesity conducted in Europe, Asia, North America, and South America met the inclusion criteria. A meta-analysis of these studies indicated that family history of obesity is a significant risk factor of overweight and /or obesity in offspring; risk for offspring overweight and/or obesity associated with family history varies depending of the family members included in the analysis; and when family history of obesity is present, the offspring are at greater risk for developing obesity or overweight. In addition, the results from moderator analyses suggest that part of the heterogeneity discovered between the studies can be explained by the region of world that the study occurred in and the age of the child at the time of weight assessment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=childhood%20obesity" title="childhood obesity">childhood obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=overweight" title=" overweight"> overweight</a>, <a href="https://publications.waset.org/abstracts/search?q=family%20history" title=" family history"> family history</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20factors" title=" risk factors"> risk factors</a>, <a href="https://publications.waset.org/abstracts/search?q=meta-analysis" title=" meta-analysis"> meta-analysis</a> </p> <a href="https://publications.waset.org/abstracts/4316/family-history-of-obesity-and-risk-of-childhood-overweight-and-obesity-a-meta-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4316.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">521</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1472</span> Interpretation of Two Indices for the Prediction of Cardiovascular Risk in Pediatric Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20M.%20Donma">Mustafa M. Donma</a>, <a href="https://publications.waset.org/abstracts/search?q=Orkide%20Donma"> Orkide Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obesity and weight gain are associated with increased risk of developing cardiovascular diseases and the progression of liver fibrosis. Aspartate transaminase–to-platelet count ratio index (AST-to-PLT, APRI) and fibrosis-4 (FIB-4) were primarily considered as the formulas capable of differentiating hepatitis from cirrhosis. Recently, they have found clinical use as measures of liver fibrosis and cardiovascular risk. However, their status in children has not been evaluated in detail yet. The aim of this study is to determine APRI and FIB-4 status in obese (OB) children and compare them with values found in children with normal body mass index (N-BMI). A total of sixty-eight children examined in the outpatient clinics of the Pediatrics Department in Tekirdag Namik Kemal University Medical Faculty were included in the study. Two groups were constituted. In the first group, thirty-five children with N-BMI, whose age- and sex-dependent BMI indices vary between 15 and 85 percentiles, were evaluated. The second group comprised thirty-three OB children whose BMI percentile values were between 95 and 99. Anthropometric measurements and routine biochemical tests were performed. Using these parameters, values for the related indices, BMI, APRI, and FIB-4, were calculated. Appropriate statistical tests were used for the evaluation of the study data. The statistical significance degree was accepted as p<0.05. In the OB group, values found for APRI and FIB-4 were higher than those calculated for the N-BMI group. However, there was no statistically significant difference between the N-BMI and OB groups in terms of APRI and FIB-4. A similar pattern was detected for triglyceride (TRG) values. The correlation coefficient and degree of significance between APRI and FIB-4 were r=0.336 and p=0.065 in the N-BMI group. On the other hand, they were r=0.707 and p=0.001 in the OB group. Associations of these two indices with TRG have shown that this parameter was strongly correlated (p<0.001) both with APRI and FIB-4 in the OB group, whereas no correlation was calculated in children with N-BMI. Triglycerides are associated with an increased risk of fatty liver, which can progress to severe clinical problems such as steatohepatitis, which can lead to liver fibrosis. Triglycerides are also independent risk factors for cardiovascular disease. In conclusion, the lack of correlation between TRG and APRI as well as FIB-4 in children with N-BMI, along with the detection of strong correlations of TRG with these indices in OB children, was the indicator of the possible onset of the tendency towards the development of fatty liver in OB children. This finding also pointed out the potential risk for cardiovascular pathologies in OB children. The nature of the difference between APRI vs FIB-4 correlations in N-BMI and OB groups (no correlation versus high correlation), respectively, may be the indicator of the importance of involving age and alanine transaminase parameters in addition to AST and PLT in the formula designed for FIB-4. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=APRI" title="APRI">APRI</a>, <a href="https://publications.waset.org/abstracts/search?q=children" title=" children"> children</a>, <a href="https://publications.waset.org/abstracts/search?q=FIB-4" title=" FIB-4"> FIB-4</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=triglycerides" title=" triglycerides"> triglycerides</a> </p> <a href="https://publications.waset.org/abstracts/158882/interpretation-of-two-indices-for-the-prediction-of-cardiovascular-risk-in-pediatric-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158882.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">348</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1471</span> Behavior and Obesity: The Perception of Healthcare Professionals Concerning the Role of Behavior on Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Wahass">Saeed Wahass</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: Obesity is epidemic, affecting all societies and cultures. Most serious medical illnesses are attributed to obesity. For this reason, all healthcare systems worldwide have focused on obesity for both intervention and prevention. However, there is scientific evidence supporting that obesity is treatable through implementing different modalities of interventions. They include biological interventions like medications and bariatric surgeries and behavioral interventions. It seems healthcare professionals may suggest the quick and the easiest interventions for obesity like surgery, ignoring other modesties that might require efforts from their sides and patients as well. Searching on the onset, progression and prevention, behavior plays a major role. As a result, psychological interventions have become increasingly core for intervention and prevention of obesity. They are effective and cost effective in dealing with obesity. Methods: A questionnaire describing the role of behavior on obesity and the way it can be prevented and treated was distributed to a group of health professionals who are dealing with obesity e.g. bariatric surgeons, bariatric physicians, psychologists, health educators, nurses and social workers. Results: 88% of healthcare professionals believed that behavior plays a major role on the onset and progression of obesity, 95% of them recognized that obesity can be prevented with consideration for behavior factors. A major proportion (87%) of the respondents see that psychological interventions are effective and cost effective in treating obesity. Conclusions: It optimistically appears that the majority of healthcare professionals believe that behavior is a key component in understanding, preventing and treating obesity. This outcome may help in developing specific training courses for healthcare professionals, who are dealing with obesity concerning the way they can treat patients behaviorally and, moreover, educating the community. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=behavior" title="behavior">behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=healthcare%20provider" title=" healthcare provider"> healthcare provider</a>, <a href="https://publications.waset.org/abstracts/search?q=psychological%20interventions" title=" psychological interventions"> psychological interventions</a> </p> <a href="https://publications.waset.org/abstracts/24440/behavior-and-obesity-the-perception-of-healthcare-professionals-concerning-the-role-of-behavior-on-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24440.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">496</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1470</span> Waist Circumference-Related Performance of Tense Indices during Varying Pediatric Obesity States and Metabolic Syndrome</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustafa%20Metin%20Donma">Mustafa Metin Donma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Obesity increases the risk of elevated blood pressure, which is a metabolic syndrome (MetS) component. Waist circumference (WC) is accepted as an indispensable parameter for the evaluation of these health problems. The close relationship of height with blood pressure values revealed the necessity of including height in tense indices. The association of tense indices with WC has also become an increasingly important topic. The purpose of this study was to develop a tense index that could contribute to differential diagnosis of MetS more than the indices previously introduced. One hundred and ninety-four children, aged 06-11 years, were considered to constitute four groups. The study was performed on normal weight (Group 1), overweight+obese (Group 2), morbid obese [without (Group 3) and with (Group 4) MetS findings] children. Children were included in the groups according to the recommendations of World Health Organization based on age- and gender dependent body mass index percentiles. For MetS group, MetS components well-established before were considered. Anthropometric measurements, as well as blood pressure values were taken. Tense indices were computed. The formula for the first tense index was (SP+DP)/2. The second index was Advanced Donma Tense Index (ADTI). The formula for this index was [(SP+DP)/2] * Height. Statistical calculations were performed. 0.05 was accepted as the p value indicating statistical significance. There were no statistically significant differences between the groups for pulse pressure, systolic-to-diastolic pressure ratio and tense index. Increasing values were observed from Group 1 to Group 4 in terms of mean arterial blood pressure and advanced Donma tense index (ADTI), which was highly correlated with WC in all groups except Group 1. Both tense index and ADTI exhibited significant correlations with WC in Group 3. However, in Group 4, ADTI, which includes height parameter in the equation, was unique in establishing a strong correlation with WC. In conclusion, ADTI was suggested as a tense index while investigating children with MetS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blood%20pressure" title="blood pressure">blood pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=child" title=" child"> child</a>, <a href="https://publications.waset.org/abstracts/search?q=height" title=" height"> height</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20syndrome" title=" metabolic syndrome"> metabolic syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=waist%20circumference" title=" waist circumference"> waist circumference</a> </p> <a href="https://publications.waset.org/abstracts/175738/waist-circumference-related-performance-of-tense-indices-during-varying-pediatric-obesity-states-and-metabolic-syndrome" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175738.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">59</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=obesity%20indices&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=obesity%20indices&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=obesity%20indices&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=obesity%20indices&page=5">5</a></li> <li class="page-item"><a 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