Combine body mass index and body fat percentage measures to improve the accuracy of obesity screening in young adults

Hung, Shang-Ping; Chen, Ching-Yu; Guo, Fei-Ran; Chang, Ching-I; Jan, Chyi-Feng

doi:10.1016/j.orcp.2016.02.005

Cited by 47 publications

(38 citation statements)

References 33 publications

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“…However, the recommended BMI cut-off values for overweight and obesity have been criticised due to their inconsistent relationship with body fat percentage (BF%) [2][3][4]. Moreover, it is also limited to discriminate between fat and lean mass [5]. Given these findings, there may be a variation in BF% for the same BMI range among people in a population or between individuals [6].…”

Section: Body Mass Index (Bmi) and Body Fat % (Bf%)mentioning

confidence: 99%

High body fat percentage among adult women in Malaysia: the role of lifestyle

Johari

Nordin

Sahar

et al. 2018

J. Fundam and Appl Sci.

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Body fat percentage is regarded as an important measurement for diagnosis of obesity. The aim of this study is to determine the association of high body fat percentage (BF%) and lifestyle among adult women. The study was conducted on 327 women, aged 40-59 years, recruited during a health screening program. Data on socio-demography, dietary intake and physical activity were collected through validated questionnaires. BF% was measured using InBody 270 Body Impedance analyzer machine. Association between lifestyle factors and body fat percentage were investigated using multiple linear regression, adjusted for age and body mass index (BMI). Intake of protein, calcium and physical activity on household intensity were the predictors of high BF%.

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Section: Body Mass Index (Bmi) and Body Fat % (Bf%)mentioning

confidence: 99%

High body fat percentage among adult women in Malaysia: the role of lifestyle

Johari

Nordin

Sahar

et al. 2018

J. Fundam and Appl Sci.

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“…Obesity is defined as increased adipose tissue to a degree in which health is impaired and is mainly characterized by systemic low‐grade inflammation . Individuals with a body mass index (BMI) of 27.5–34.9 kg/m 2 , 35–39.9 kg/m 2 , and ≥40 kg/m 2 are categorized as class I, II, and III obese, respectively .…”

Section: Introductionmentioning

confidence: 99%

Peri‐implant parameters and C‐reactive protein levels among patients with different obesity levels

Vohra

Alkhudhairy

Al‐Kheraif

et al. 2017

Clin Implant Dent Rel Res

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“…To succeed in dealing with limitation of BMI for categorization, this paper has combined the value of BMI and body fat percentage to classify the subject in overweight or no overweight group and further precisely estimate the likelihood of overweight [10].…”

Section: Introductionmentioning

confidence: 99%

“…The related health care cost is also a significant factor. The urban lifestyle, overreliance on technology, and less focus on physical activities bring health related problems such as overweight or obesity among the young students [10][11]. This raises the question about prevalence and contributing factors about overweight using simple and cost effective screening method in young students.…”

Section: Introductionmentioning

confidence: 99%

Application of Binary Logistic Regression Model to Assess the Likelihood of Overweight

Shrestha¹

2019

AJTAS

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This study attempts to assess the likelihood of overweight and associated factors among the young students by analyzing their physical measurements and physical activity index. This paper has classified four hundred and fifteen subjects and precisely estimated the likelihood of outcome overweight by combining body mass index and CUN-BAE calculated. Multicollinearity is tested with multiple regression analysis. Box-Tidwell Test is used to check the linearity of the continuous independent variables and their logit (log odds). The binary regression analysis was executed to determine the influences of gender, physical activity index, and physical measurements on the likelihood that the subjects fall in overweight category. The sensitivity and specificity described by the model are 55.9% and 96.9% respectively. The increase in the value of waist to height ratio and neck circumference and drop in physical activity index are associated with the increased likelihood of subjects falling to overweight group. The prevalence of overweight is higher (27.8%) in female than in male (14.7%) subjects. The odds ratio for gender reveals that the likelihood of subjects falling to overweight category is 2.6 times higher in female compared to male subjects.

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Combine body mass index and body fat percentage measures to improve the accuracy of obesity screening in young adults

Cited by 47 publications

References 33 publications

High body fat percentage among adult women in Malaysia: the role of lifestyle

High body fat percentage among adult women in Malaysia: the role of lifestyle

Peri‐implant parameters and C‐reactive protein levels among patients with different obesity levels

Application of Binary Logistic Regression Model to Assess the Likelihood of Overweight

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