TY - JOUR. T1 - Patterns of childhood body mass index (BMI), overweight and obesity in South Asian and black participants in the English National child measurement programme. T2 - Effect of applying BMI adjustments standardising for ethnic differences in BMI-body fatness associations. AU - Hudda, M. T.. AU - Nightingale, C. M.. AU - Donin, A. S.. AU - Owen, C. G.. AU - Rudnicka, A. R.. AU - Wells, J. C.K.. AU - Rutter, H.. AU - Cook, D. G.. AU - Whincup, P. H.. PY - 2017/11/2. Y1 - 2017/11/2. N2 - Background:The National Child Measurement Programme (NCMP) records weight and height and assesses overweight-obesity patterns in English children using body mass index (BMI), which tends to underestimate body fatness in South Asian children and overestimate body fatness in Black children of presumed African ethnicity. Using BMI adjustments to ensure that adjusted BMI was similarly related to body fatness in South Asian, Black and White children, we reassessed population overweight and obesity patterns ...

TY - JOUR. T1 - Indirect effects of elevated body mass index on memory performance through altered cerebral metabolite concentrations. AU - Gonzales, Mitzi M.. AU - Tarumi, Takashi. AU - Eagan, Danielle E.. AU - Tanaka, Hirofumi. AU - Vaghasia, Miral. AU - Haley, Andreana P.. PY - 2012/9/1. Y1 - 2012/9/1. N2 - OBJECTIVE: Elevated body mass index (BMI) at midlife is associated with increased risk of cognitive decline in later life. The goal of the current study was to assess mechanisms of early brain vulnerability by examining if higher BMI at midlife affects current cognitive performance through alterations in cerebral neurochemistry. METHODS: Fifty-five participants, aged 40 to 60 years, underwent neuropsychological testing, health screen, and proton magnetic resonance spectroscopy examining N-acetylaspartate, creatine (Cr), myo-inositol (mI), choline, and glutamate concentrations in occipitoparietal gray matter. Concentrations of N-acetylaspartate, choline, mI, and glutamate were calculated as ...

The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values ,0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The ...

Body Mass Index May Predict Heart Disease Risk For Type-2 Diabetic Patients New Study Finds. By J. Brent Muhlestein, MD. April 25, 2014. Researchers from …. Body Mass Index, Fasting Plasma Glucose Levels, and C-peptide Levels as Predictors of the Future Insulin Use in Japanese Type 2 Diabetic Patients.. Dec 15, 2016 … A great BMI calculator with advanced features for Body Mass Index. … serious health problems such as heart disease and type 2 diabetes.. Body Mass Index (BMI) is a measure of body fat based on height and weight. How to calculate Body Mass Index. Body Mass Index is a simple calculation using …. Sep 9, 2014 … Effects of Body Mass Index, Abdominal Obesity, and Type 2 Diabetes on Mortality in Community-Dwelling Elderly in Sao Paulo, Brazil: Analysis …. aimed at investigating the effect of Body Mass Index on serum lipid profile in type II diabetic patients. The study was descriptive cross sectional in design.. Type 2 diabetes occurs when the hormone insulin is not used ...

Body Mass Index (BMI) or Quetelet index plays an important role in figure out your weight, health and lifestyle choices. Body mass index is developed by Adolphe Quetelet in the 1900s for evaluating body mass. Body mass index is not related to gender or age. BMI values are the same for men and women of all body types and ages.In BMI formulas simply put your weight and height and calculate your BMI value. There are three sets of values used to determine body mass.If your BMI weight status is below then 18.5 than youre in the category of underweight people. There are certain risks of being underweight such as slow wound healing, slow recovery from illness, high blood pressure and lack of period or fertility in females. If youve BMI score less than 18.5 or in between 18.5 - 20 then you required a more nutritional intake that helps you to gain weight and build strong immunity system in the body. You can try Accumass weight gain granules and Ayurvedic medicine to increase your BMI value.

Washington, DC, February 7, 2012 - The Trust for Americas Health (TFAH) has released a new report, Bending the Obesity Cost Curve, which finds that reducing the average body mass index by just five percent in the United States could lead to more than $29 billion in health care savings in just five years, due to reduced obesity-related costs. The analysis found that the country could save $158.1 billion in 10 years and $611.7 billion in 20 years.. Prevention is the key to halting the obesity epidemic, lowering health care costs and creating a long-term path to a healthier and economically sound America, said Jeff Levi, PhD, Executive Director of TFAH, who also serves as Chair of the Advisory Group on Prevention, Health Promotion, and Integrative and Public Health. The Prevention and Public Health Fund is now providing resources to support the kind of evidence-based strategies that can achieve this five percent reduction in average BMI, which makes the Fund a critical component of our efforts ...

Obesity is associated with breast white adipose tissue (WAT) inflammation, elevated levels of the estrogen biosynthetic enzyme, aromatase, and systemic changes that have been linked to the pathogenesis of breast cancer. Here, we determined whether metabolic obesity, including changes in breast biology and systemic effects, occurs in a subset of women with normal body mass index (BMI). Breast WAT and fasting blood were collected from 72 women with normal BMI (,25 kg/m2) undergoing mastectomy for breast cancer risk reduction or treatment. WAT inflammation was defined by the presence of crown-like structures of the breast (CLS-B) which are composed of dead or dying adipocytes surrounded by macrophages. Severity of inflammation was measured as CLS-B/cm2. The primary objective was to determine whether breast WAT inflammation is associated with aromatase expression and activity. Secondary objectives included assessment of circulating factors and breast adipocyte size. Breast WAT inflammation was ...

Many modifiable risk factors in early infancy have been shown to be associated with childhood overweight and obesity. These risk factors have not been studied within children of South Asian origin in the UK. The aims of this paper are to describe differences in the prevalence of modifiable risk factors for childhood obesity between children of White British and Pakistani origin and investigate the association between these risk factors and childhood BMI measured at age 3 years. We used data from a sub-study of the Born in Bradford birth cohort with detailed follow-up visits throughout early childhood. 987 participants with a BMI measurement at age 3 were included; 39% were White British, 48% were of Pakistani origin and 13% were of other ethnicities. Linear and Poisson regression models were used to assess the association between risk factors and two outcomes at age 3; BMI z-scores and child overweight. Compared to Pakistani mothers, White British mothers were more likely to smoke during pregnancy, have

TY - JOUR. T1 - A dose-response meta-analysis of the impact of body mass index on stroke and all-cause mortality in stroke patients. T2 - a paradox within a paradox. AU - Bagheri, M.. AU - Speakman, J. R.. AU - Shabbidar, S.. AU - Kazemi, F.. AU - Djafarian, K.. N1 - Acknowledgements We thank Dr. Nicola Orsini for helping us with the statistical analysis. This study was supported by Tehran University of Medical Sciences.. PY - 2015/5. Y1 - 2015/5. N2 - The obesity paradox is often attributed to fat acting as a buffer to protect individuals in fragile metabolic states. If this was the case, one would predict that the reverse epidemiology would be apparent across all causes of mortality including that of the particular disease state. We performed a dose-response meta-analysis to assess the impact of body mass index (BMI) on all-cause and stroke-specific mortality among stroke patients. Data from relevant studies were identified by systematically searching PubMed, OVID and Scopus databases and were ...

Introduction: There are conflicting reports on influence of ageing and gender on body mass index (BMI) and blood pressure (BP) in different population. This study evaluated the influence of ageing on these parameters in healthy subjects. Materials and Methods: BP, heart rate and BMI was measured in 140 apparently healthy subjects. They were divided into four groups. Group A: males ≤ 50 years of age; Group B: males above 50 years; Group C= females ≤ 50 years; Group D= females above 50 years. Data was analysed using unpaired t test and Mann-Whitney U test. Result: BMI of group B was significantly lower compared to group A (p = 0.004). Diastolic blood pressure was significantly higher in group D compared to group C (p = 0.016). Heart rate was significantly lower in group D compared to group C (p= 0.03) Conclusion: There is differential influence of ageing in males and females on body mass index and diastolic blood pressure.. ...

TY - JOUR. T1 - Effect of body mass index on diabetogenesis factors at a fixed fasting plasma glucose level. AU - Lin, Jiunn Diann. AU - Hsu, Chun Hsien. AU - Wu, Chung Ze. AU - Hsieh, An-Tsz. AU - Hsieh, Chang Hsun. AU - Liang, Yao Jen. AU - Chen, Yen Lin. AU - Pei, Dee. AU - Chang, Jin Biou. PY - 2018/1/1. Y1 - 2018/1/1. N2 - Aim The present study evaluated the relative influence of body mass index (BMI) on insulin resistance (IR), first-phase insulin secretion (FPIS), second-phase insulin secretion (SPIS), and glucose effectiveness (GE) at a fixed fasting plasma glucose level in an older ethnic Chinese population. Methods In total, 265 individuals aged 60 years with a fasting plasma glucose level of 5.56 mmol/L were enrolled. Participants had BMIs of 20.0-34.2 kg/m2. IR, FPIS, SPIS, and GE were estimated using our previously developed equations. Pearson correlation analysis was conducted to assess the correlations between the four diabetogenesis factors and BMI. A general linear model was ...

What is body mass index and how is it measured? Body mass index is one important measurement to determine if someone is overweight, underweight, or at a healthy weight. If someones height and weight are known, then body mass index can be measured. There is a simple body mass index formula which is discussed in this article as well as many other body mass index facts.

Do you often worry about your childs weight? Do you think that your child is either too fat or too thin? If you do, you need to know your childs Body Mass Index or BMI, so you would determine whether your childs weight is right for his or her age and height.. The Body Mass Index for kids is also known as BMI-for-age because it is age and gender specific. This index is calculated from ages two to 20 years old. There is a separate chart for boys and girls because each gender has different body fat content, as they grow older.. There are many ways on how you can determine if your child is obese or overweight. But the fastest way of figuring whether your child is healthy or not is through the help of body mass index. In calculating your childs BMI, you need to determine your childs weight in kilograms and his or her height in meter Age calculator .. When you have this data, you may now start calculating using the BMI formula. First you need to multiply the height per meter by itself. Using this ...

can you tell me normal body mass index for women? Answered by Dr. Thomas Namey: BMI!: Good approximation for weight, but not as good as body composit...

TY - JOUR. T1 - Impact of pretransplant body mass index on the clinical outcome after allogeneic hematopoietic SCT. AU - Fuji, S.. AU - Takano, K.. AU - Mori, T.. AU - Eto, T.. AU - Taniguchi, S.. AU - Ohashi, K.. AU - Sakamaki, H.. AU - Morishima, Y.. AU - Kato, K.. AU - Miyamura, K.. AU - Suzuki, R.. AU - Fukuda, T.. PY - 2014/12/11. Y1 - 2014/12/11. N2 - To elucidate the impact of pretransplant body mass index (BMI) on the clinical outcome, we performed a retrospective study with registry data including a total of 12 050 patients (age ≥18 years) who received allogeneic hematopoietic SCT (HSCT) between 2000 and 2010. Patients were stratified as follows: BMI,18.5 kg/m 2, Underweight, n=1791; 18.5≤BMI,25, Normal, n=8444; 25≤BMI,30, Overweight, n=1591; BMI≥30, Obese, n=224. The median age was 45 years (range, 18-77). A multivariate analysis showed that the risk of relapse was significantly higher in the underweight group and lower in the overweight and obese groups compared with the ...

TY - JOUR. T1 - Joint effect of physical activity and body mass index on mortality for acute myocardial infarction in the elderly. T2 - Role of preinfarction angina as equivalent of ischemic preconditioning. AU - Abete, Pasquale. AU - Cacciatore, Francesco. AU - Della Morte, David. AU - Mazzella, Francesca. AU - Testa, Gianluca. AU - Galizia, Gianluigi. AU - De Santis, Domenico. AU - Longobardi, Giancarlo. AU - Ferrara, Nicola. AU - Rengo, Franco. PY - 2009/2/1. Y1 - 2009/2/1. N2 - BACKGROUND: Preinfarction angina (PrA), clinical equivalent of ischemic preconditioning, confers protection against in-hospital mortality for acute myocardial infarction (AMI) in adult but not in elderly patients. This study aims to examine the interaction between physical activity and body mass index (BMI) in preserving the cardioprotective effect of PrA in elderly patients with AMI. DESIGN: Elderly patients (≥65 years old) with AMI admitted to Coronary Care Unit. METHODS: Elderly patients with AMI were ...

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OBJECTIVE: This study investigated how a wide spectrum of body mass index (BMI) values at ages 7 to 13 years are associated with type 2 diabetes throughout adulthood, including potential modifying effects of sex and birth weight.. METHODS: From the Copenhagen School Health Records Register, 292,827 individuals, born between 1930 and 1989, were followed in national registers for type 2 diabetes (women, n = 7,472; men, n = 11,548). Heights and weights were measured at ages 7 to 13 years.. RESULTS: Below-average BMIs, with few exceptions, were not associated with type 2 diabetes. Above-average BMIs had positive associations that were stronger in women than men, stronger in younger birth cohorts, and weaker with older age at diagnosis. Women born 1930-1947, 1948-1965, and 1966-1983 with above-average BMIs at 13 years (≥18.2 kg/m(2) ) had hazard ratios (95% confidence intervals) ranging from 2.12 (1.91-2.36) to 2.84 (2.31-3.49) per z score when diagnosed at 30 to 47 years. Birth weight did not ...

TY - JOUR. T1 - Does Low Body Mass Index Predict the Hospital Mortality of Adult Western or Asian Patients?. AU - Compher, Charlene. AU - Higashiguchi, Takashi. AU - Yu, Jianchun. AU - Jensen, Gordon L.. PY - 2018/2/1. Y1 - 2018/2/1. N2 - Background: Some strategies for screening and assessment of malnutrition include a low but variable body mass index (BMI) cutoff, while others do not. The purpose of this systematic review was to investigate published data for Western and Asian hospital samples to determine how the prevalence of low BMI is associated with increased hospital mortality. Method: A PubMed search of the past 10 years (2006-2016) was conducted with the terms BMI, malnutrition, adult, outcome, and hospital or ICU for articles published in English. Studies that examined BMI levels among Western or Asian populations were included. Forest plots were constructed to determine the odds of hospital mortality in low versus normal BMI groups. Results: Twenty studies met inclusion ...

The body mass index otherwise known as BMI, is a simple calculation using a persons height and weight. The result typically in the range of 15 to 60 is known as the BMI or body mass index score. Most health organizations put a healthy BMI score between 18.5 and 25.0. Some people refer to this as a normal BMI.. Because it measures excess weight and not actually excess fat, BMI is considered a surrogate measure of body fat. However, studies show strong correlations between BMI measurements and the results of more direct body fat measures. If you are concerned about your weight or body size, calculating your body mass index is a good place to start before heading to the doctors office. BMI can predict future weight-related issues including disease and even death, so it is a very helpful tool in screening for health risks and obesity.. Individuals with a body mass index under 18.5 are considered underweight. A BMI this low can indicate an undernourished individual. Your body needs meat on your ...

Definition of body mass index in the Fine Dictionary. Meaning of body mass index with illustrations and photos. Pronunciation of body mass index and its etymology. Related words - body mass index synonyms, antonyms, hypernyms and hyponyms. Example sentences containing body mass index

Definition of body mass index in the Financial Dictionary - by Free online English dictionary and encyclopedia. What is body mass index? Meaning of body mass index as a finance term. What does body mass index mean in finance?

The high prevalence of disease and associated weight loss at older ages limits the validity of prospective cohort studies examining the association between body mass index (BMI) and mortality. I examined mortality associated with excess weight using maximum BMI-a measure that is robust to confounding by illness-induced weight loss. Analyses were carried out on US never-smoking adults ages 50-84 using data from the National Health and Nutrition Examination Surveys (1988-1994 and 1999-2004) linked to the National Death Index through 2006. Cox models were used to estimate hazard ratios for mortality according to BMI at time of survey and at maximum. Using maximum BMI, hazard ratios for overweight (BMI, 25.0-29.9 kg/m2), obese class 1 (BMI, 30.0-34.9 kg/m2) and obese class 2 (BMI, 35.0 kg/m2 and above) relative to normal weight (BMI, 18.5-24.9 kg/m2) were 1.28 (95% confidence interval [CI], 0.89-1.84), 1.67 (95% CI, 1.15-2.40), and 2.15 (95% CI, 1.47-3.14), respectively. The corresponding hazard ratios

Subjects The parents of the subjects selected for the sample of the second growth and development study (Berdasco et al., 1991) were the subjects of this survey. After cleaning the data, the total number of adults was 31 662, of whom 11912 were males and 19 750 were females. This difference in the numbers was probably due to the better attendance of mothers for their appointments. Field work The adults attended the measuring centres where they were weighed, and had their height, upper arm circumference, triceps and subscapular fat-folds measured. The survey was undertaken by eight measuring teams (two anthropometrists each) working simultaneously from May to December 1982. Individuals living in the countrys 14 provinces were measured. In order to assure the best possible quality in the primary data, anthropometrists were trained in the same measuring procedures utilized in the first national growth and development study (Jordan, 1979), namely, those recommended by UN International Biological ...

Background: The elderly is an age group that is susceptible to nutritional problems, especially protein intake which tends to be less intake, so it affects the body mass index. Both of these problems directly or indirectly will also affect the quality of life of the elderly. This study aimed to determine the correlation between body mass index, protein intake and quality of life in the elderly.Methods: In a cross-sectional design, a sample of 165 elderlies aged≥60 years were enrolled and randomized from three community health centers of Karanganyar Regency. The body mass index (BMI), height, weight, protein intake data were obtained through interviews using 24-hour recall form. The quality of life data was prepared through interviews using the WQOOL-BREF questionnaire.Results: There was a significant correlation between protein intake and quality of life; however, there was no correlation between body mass index and the quality of life.Conclusion: Protein intake was shown to have a significant

BMI Calculator Body mass index Posted by bmt in Health & Fitness , July 7, 2014 , 0 Comments. Apk file size: 0 bytes. What is BMI? how to calculator BMI ? - Body mass index - commonly known under the acronym BMI Body Mass Index English name - was used to assess the level of a skinny or fat. - Body mass index calculated by a persons weight (kg) divided by height (measured in meters or centimeters). It can be calculated by the formula given in the definition or standard tables - This indicator can help determine a person is obese or malnourished patients through data on the shape, height and body weight. ** Application is based on the evaluation boards standard World Health Organization (WHO) and dedicated to Asian (IDI & WPRO) App ** BMI helps you quickly and accurately help you determine the condition of which you can adjust the diet and moderate exercise routine to get a healthy body Please vote 5 * and leave your comments for us to improve the content better and will have more exciting ...

A total of 19 760 (80.0%) children attended childcare before age 6. Childcare prior to age 6 was associated with BMI z-score at 7 years (0.004 units per each additional 6 months of care; 95% CI: 0.001, 0.008; p = 0.01). Childcare in a kindergarten was the only type of care associated with BMI (0.009 units; 95% CI: 0.003, 0.02; p = 0.01). For children of higher socio-occupational status mothers, childcare was associated with a 0.008 unit increase in BMI (95% CI: 0.004, 0.01; p , 0.001). ...

TY - CONF. T1 - Body mass index and waist-to-height ratio as a predictors of metabolic syndrome. AU - Rumpe, Sabīne. AU - Daniļenko, Jeļena. PY - 2021/3/24. Y1 - 2021/3/24. N2 - The purpose of this study was to evaluate and compare usefulness of the body mass index (BMI) and waist-to-height ratio (WHtR) in screening for metabolic syndrome (MS). A cross-sectional study was conducted in MFD Outpatient hospital Ilguciems from October 2017 to March 2018 and continued from October 2020 to December 2020. The patients were asked to complete a questionnaire about their socio-demographic characteristics and lifestyle factors. Patients systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood sugar (FBS), serum triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C) levels were measured. Disease history were studied. Anthropometric measurements (height, weight and WC) were taken. BMI and WHtR were calculated. All statistical analysis was performed in IBM SPSS 23.0. The ...

Genome-wide association studies have implicated the transcription factor 7-like 2 (TCF7L2) gene in type 2 diabetes risk, and more recently, in decreased body mass index. Given the contrary direction of genetic effects on these two traits, it has been suggested that the observed association with body mass index may reflect either selection bias or a complex underlying biology at TCF7L2. Using 9031 Hispanic/Latino adults (21-76 years) with complete weight history and genetic data from the community-based Hispanic Community Health Study/Study of Latinos (HCHS/SOL, Baseline 2008-2011), we estimated the multivariable association between the additive number of type 2 diabetes increasing-alleles at TCF7L2 (rs7903146-T) and body mass index. We then used structural equation models to simultaneously model the genetic association on changes in body mass index across the life course and estimate the odds of type 2 diabetes per TCF7L2 risk allele. We observed both significant increases in type 2 diabetes prevalence

Methods and Results-We determined the frequency and results of lipid testing in 301 080 children and adolescents aged 3 to 19 enrolled in 3 large US health systems in 2007 to 2010 before the 2011 guidelines were issued. Overall, 9.8% of the study population was tested for lipids. The proportion tested varied by body mass index percentile (5.9% of normal weight, 10.8% of overweight, and 26.9% of obese children) and age (8.9% of 9- to 11-year olds and 24.3% of 17- to 19-year olds). In normal weight individuals, 2.8% of 9- to 11-year olds and 22.0% of 17- to 19-year olds were tested. In multivariable models, age and body mass index category remained strongly associated with lipid testing. Sex, race, ethnicity, and blood pressure were weakly associated with testing. Abnormal lipid levels were found in 8.6% for total cholesterol, 22.5% for high-density lipoprotein-cholesterol, 12.0% for non-high-density lipoprotein-cholesterol, 8.0% for low-density lipoprotein-cholesterol, and 21% for triglycerides ...

As the use of self-reported data to classify obesity continues, the temporal change in the accuracy of self-report measurement when compared to clinical measurement remains unclear. The objective of this study was to examine temporal trends in misclassification patterns, as well as sensitivity and specificity, of clinically measured versus self-report based body mass index (BMI) from three national lifestyle surveys over a 10-year period. The Surveys of Lifestyle Attitudes and Nutrition (SLÁN) were interview based cross-sectional survey/measurements involving nationally representative samples in 1998, 2002 and 2007. Data from a subsample of both self-reported and measured height and weight were available from 66 men and 142 women in 1998, 147 men and 184 women in 2002 and 909 men and 1128 women in 2007. Respondents were classified into the BMI categories normal (| 25 kg m-2), overweight (25- | 30 kg m-2) and obese (≥ 30 kg m-2). Underreporting of BMI increased across the three surveys (14%→21%→24

The purpose of this study was to determine the influence of physical activity and dietary fat intake on Body Mass Index (BMI) of lecturers within a higher learning institutionalized setting. The study adopted a Cross-sectional Correlational Design and included 120 lecturers selected proportionately by simple random sampling techniques from a population of 600 lecturers. Data was collected using questionnaires, which had sections including physical activity checklist adopted from the international physical activity questionnaire (IPAQ), 24-hour food recall, anthropometric measurements mainly weight and height. Analysis involved the use of bivariate correlations and linear regression. A significant inverse association was registered between BMI and duration (in minutes) spent doing moderate intense physical activity per day (r=-0.322,p,0.01). Physical activity also predicted BMI (r 2=0.096, F=13.616, ß=-3.22, t=-3.69, n=120, P,0.01). However, the association between Body Mass Index and dietary ...

TY - JOUR. T1 - Tri-ponderal mass index vs body mass index in estimating body fat during adolescence. AU - Peterson, Courtney M.. AU - Su, Haiyan. AU - Thomas, Diana M.. AU - Heo, Moonseong. AU - Golnabi, Amir H.. AU - Pietrobelli, Angelo. AU - Heymsfield, Steven B.. PY - 2017/7. Y1 - 2017/7. N2 - IMPORTANCE Body mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents. OBJECTIVE To compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016. MAIN OUTCOMES AND MEASURES ...

Our aim was to examine the degree to which changes in BMI percentile reflect changes in body fat and lean body mass during childhood and how age and gender affe

We examined the lipid values of obese and normal-weight children, to look if there is an association between Body Mass Index (BMI) and lipid profiles. Our study group included 100 volunteers (50 children with normal BMI and 50 with high BMI) who were admitted to Kagithane State Hospital Pediatrics Clinic for various reasons between July 2010 and May 2011. The inclusion criteria were as follows: age between 2 and 14 years, no chronic disease and no developmental defects. The high BMI group had significantly higher Low Density Lipoprotein (LDL) levels in comparison to the normal BMI group (p < 0.05). We also found that the high BMI group had higher cholesterol levels close to upper limit than the normal BMI group. We found high triglyceride levels not only in the high BMI group but also in the normal BMI group with a rate of 26% and 24% respectively. The difference of 2% was not significant. We advise that identification and treatment of elevated LDL cholesterol levels is of tremendous significance for

Background:Weight and weight gain throughout infancy are related to later obesity, but whether the strength of the associations varies during the infancy period is uncertain.Aims:Our aims were to identify the period of infancy when change in body weight has the strongest association with adult body mass index (BMI) and also the extent to which these associations during infancy are mediated through childhood BMI.Methods:The Copenhagen Perinatal Cohort, in which participants were followed from birth through 42 years of age, provided information on weight at 12 months and BMI at 42 years for 1633 individuals. Information on weight at birth, 2 weeks, 1, 2, 3, 4 and 6 months was retrieved from health visitors records and information on BMI at ages 7 and 13 years from school health records. The associations of infant weight and weight gain standard deviation scores (SDS) with adult BMI-SDS were analyzed using multiple linear regression and path analysis.Results:Higher-weight-SDS at all ages from ...

The online calculator calculates the body mass index - BMI body mass index (BMI) - a value that allows you to assess the degree of correspondence of a persons mass and his height. The calculation of body weight is made in accordance with the so-called body mass index (BMI). How to determine normal body weight? This can be done according to the formula of Adolf Quetelet, used in many countries, which allows you to calculate bodyweight depending on the height of the person.

Body Mass Index Calculator. Body Mass Index (BMI) is one of the most accurate ways to determine when extra pounds translate into health risks. BMI is a measure which takes into account a persons weight and height to gauge total body fat in adults. Someone with a BMI of 26 to 27 is about 20 percent overweight, which is generally believed to carry moderate health risks. A BMI of 30 and higher is considered obese. The higher the BMI, the greater the risk of developing additional health problems.. Heart disease, diabetes and high blood pressure are all linked to being overweight. A BMI of 30 and over increases the risk of death from any cause by 50 to 150 percent, according to some estimates. Be sure to consult your doctor or other health professional before beginning any exercise or weight-loss program.. In June 1998, the federal government announced guidelines which create a new definition of a healthy weight -- a BMI of 24 or less. So now a BMI of 25 to 29.9 is considered overweight. Individuals ...

The purpose of this study was to develop and cross-validate an equation for estimating percentage body fat (%BF) from body mass index and other potential independent variables among young persons with intellectual disability. Participants were 128 persons with intellectual disability (62 women; age 16-24 years) split between development (n = 98) and cross-validation (n = 30) samples. Dual-energy X-ray absorptiometry served as the reference method for %BF. An equation including 1/body mass index and sex (0 = male; 1 = female) was highly accurate in estimating %BF (p , .001; R2 = .82; standard error of estimate = 5.22%). Mean absolute and root mean square errors were small (3.1% and 3.9%, respectively). A Bland-Altman plot indicated nearly zero mean difference between actual and predicted %BF with modest 95% confidence intervals. The prediction equation was %BF = 56.708 − (729.200 × [1/body mass index]) + (12.134 × sex). Health care professionals may use the prediction equation for monitoring ...

Article: The impact of body mass index on the associations of lipids with the risk of coronary heart disease in the Asia Pacific ...

Bhattacharya , S , Campbell , D M , Liston , W A & Bhattacharya , S 2007 , Effect of Body Mass Index on pregnancy outcomes in nulliparous women delivering singleton babies BMC Public Health , vol. 7 , 168 . DOI: 10.1186/1471-2458-7- ...

INSTRUCTIONS: Determination of Nutritional Status of Children Within the Ages of Four (4) to Ten (10) Years Using their Body Mass Index (Bmi) project material.. Please, sit back and study the researched project material carefully after a successful download. DO NOT copy word for word.. Our aim of providing this project research material is to reduce the stress of moving from one school library to another all in the name of searching for Determination of Nutritional Status of Children Within the Ages of Four (4) to Ten (10) Years Using their Body Mass Index (Bmi) research materials.. We are not encouraging any form of plagiarism. This service is legal because, all institutions permit their students to read previous projects, books, articles or papers while developing their own works. According to Austin Kleon, All creative work builds on what came before. You are about to download: Determination of Nutritional Status of Children Within the Ages of Four (4) to Ten (10) Years Using their Body ...

The Body Mass Index Percentiles for Girls calculation allows you to evaluate if a patient is at an appropriate weight based on their age, height and weight.

The value of school screening for scoliosis has largely been an appreciation of the high prevalence of small degrees of surface deformity and curvature and the opportunity to study the natural history of these curvatures [1, 2]. Not adequately recognised is the potential, through epidemiological studies of screened subjects, to understand better some factors involved in the pathogenesis of adolescent idiopathic scoliosis (AIS) [3-13]. In this connection, body mass index (BMI) has been evaluated in relation to both AIS [14-23] and the trunk asymmetry (TA) of normal subjects [7, 16, 23-25]. But no attempts have been made to evaluate how BMI may relate to the pathogenesis of the trunk shape distortion of TA as it has recently for girls with AIS [23].. Employing a new approach of comparing skeletal data between subsets of higher and lower body mass index (BMI) in adolescent girls - preoperative with AIS, screened for AIS and normals, BMI was found to be related to skeletal maturation of the trunk, ...

Body Mass Index (BMI) Calculator (add to your website or run on ours). Calculate body mass index (BMI), BMI classification and weight range in US or Metric.

Simple body Mass IndexbrThe body mass index BMI or Quetelet index is a heuristic proxy for human body fat based on an individuals weight and height brRequirements Windows Phone 81 Windows Phone 8 Windows Phone 75

Objective: To evaluate whether the duration of the active phase of labor is associated with maternal body mass index (BMI), in nulliparous women with spontaneous onset of labor. Study design: Historical prospective cohort study including 63,829 nulliparous women with a singleton pregnancy and a spontaneous onset of labor, who delivered between January 1, 1995 and December 31, 2009. Data were collected from the Perinatal Revision South registry, a regional perinatal database in Southern Sweden. Women were categorized into six classes of BMI. Overweight and obese women were compared to normal weight women regarding duration of active labor. Adjustments were made for year of delivery, maternal age and infant birth weight. Results: The median duration of labor was significantly longer in obese women (class I obesity (BMI 30-34.9) = 9.1 h, class II obesity (BMI 35-39.9) = 9.2 h and class III obesity (BMI , 40) = 9.8 h) compared to normal-weight women (BMI 18.5-24.9) = 8.8 h (p , 0.001). The risk of ...

Did You Know? The average Americans BMI is 27.8?! Low exercise and poor eating habits are the primary reason BMI numbers in the U.S. are rising. If you fall into the 25 and higher range, do your best to make a change! Go ahead, use this Body Mass Calculator to see your exact BMI and other interesting facts! BMI Calculator provided by calculators.tech BMI or Body Mass Index is not an exact measure of your health but can be used as a guideline for managing a healthy weight according to your height. Body mass index determines whether you are underweight, ideal weight, overweight or obese. A BMI score between 18.5 to 25 is considered as healthy. A BMI score of 18.5 or less means that the person is underweight while that above 25 is an indication of being overweight. People with a BMI score above 30 are considered obese, and should consult a physician as soon as possible ...

TY - JOUR. T1 - Glycaemic control and body mass index in late-adolescents and young adults with type 1 diabetes mellitus. T2 - a population-based study. AU - Acharya, S H. AU - Philip, S. AU - Viswanath, A K. AU - Boroujerdi, M. AU - Waugh, N R. AU - Pearson, D W M. PY - 2008/3. Y1 - 2008/3. N2 - Aims Studies of children with diabetes up to the age of 15 years report deteriorating glycaemic control in the early teenage years. The aim was to investigate glycaemia and body mass index in older teenagers and young adults. Method A Scottish, regional, population-based, cross-sectional study of 255 young people (117 female, 138 male) with Type 1 diabetes, aged 15-25 years (mean ±sd 19.8 ± 2.8 years, diabetes duration: 8.8 ± 5.4 years) registered on a diabetes database. Glycaemic control, body mass index (BMI) and insulin regimens were assessed in three age groups [group 1 (n = 96) 15-18 years; group 2 (n = 74) 18.1-22 years; and group 3 (n = 85) 22.1-25 years]. Results Subjects in the oldest age ...

TY - JOUR. T1 - Secular trends in the association between nativity/length of US residence with body mass index and waist circumference among Mexican-Americans, 1988-2008. AU - Albrecht, Sandra S.. AU - Diez Roux, Ana V.. AU - Aiello, Allison E.. AU - Schulz, Amy J.. AU - Abraido-Lanza, Ana. PY - 2013/1/1. Y1 - 2013/1/1. N2 - Objectives: We investigated whether associations between nativity/length of US residence and body mass index (BMI) and waist circumference (WC) varied over the past two decades. Methods: Mexican-Americans aged 20-64 years from the National Health and Nutrition Survey (NHANES) III (1988-1994), and NHANES (1999-2008). Sex-stratified multivariable linear regression models further adjusted for age, education, and NHANES period. Results: We found no evidence of secular variation in the nativity/length of US residence gradient for men or women. Foreign-born Mexican-Americans, irrespective of residence length, had lower mean BMI and WC than their US-born counterparts. However among ...