Health Risks Associated with High Waist Circumference: A Systematic Review

Darsini, Darsini; Hamidah, Hamidah; Notobroto, Hari Basuki; Cahyono, Eko Agus

doi:10.4081/jphr.2020.1811

Cited by 75 publications

(66 citation statements)

References 23 publications

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“…This explains why Asians have a higher fat percentage than Europeans despite having the same BMI. Furthermore, high waist circumference increased the risks of developing hypertension, type 2 diabetes mellitus, hypercholesterolemia, joint pain, low back pain, and hyperuricemia as mentioned in the paper by Darsini et al [37].…”

Section: Literature Reviewsmentioning

confidence: 88%

Simulation of 3D Body Shapes for Pregnant and Postpartum Women

Sinthanayothin

Xuto

Bholsithi

et al. 2022

Sensors

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Several studies have reported that pre-pregnant women's body mass index (BMI) affects women’s weight gain with complications during pregnancy and the postpartum weight retention. It is important to control the BMI before, during and after pregnancy. Our objectives are to develop a technique that can compute and visualize 3D body shapes of women during pregnancy and postpartum in various gestational ages, BMI, and postpartum durations. Body changes data from 98 pregnant and 83 postpartum women were collected, tracked for six months, and analyzed to create 3D model shapes. This study allows users to simulate their 3D body shapes in real-time and online, based on weight, height, and gestational age, using multiple linear regression and morphing techniques. To evaluate the results, precision tests were performed on simulated 3D pregnant and postpartum women’s shapes. Additionally, a satisfaction test on the application was conducted on new 149 mothers. The accuracy of the simulation was tested on 75 pregnant and 74 postpartum volunteers in terms of relationships between statistical calculation, simulated 3D models and actual tape measurement of chest, waist, hip, and inseam. Our results can predict accurately the body proportions of pregnant and postpartum women.

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Section: Literature Reviewsmentioning

confidence: 88%

Simulation of 3D Body Shapes for Pregnant and Postpartum Women

Sinthanayothin

Xuto

Bholsithi

et al. 2022

Sensors

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show abstract

“…Increased body weight and BMI are the yardsticks for generalised obesity and is signi cantly correlated to different NCDs like asthma, hypertension, dyslipidemia, metabolic syndrome and others as studied in women (46-49). For Indian women WC > 80 cm and WHR > 0.85 is considered as abdominal obesity and signi cantly associated with cardiovascular problems, diabetes, metabolic syndrome, pulmonary disorders, osteo-arthritis, reproductive problems and so on (50,51).Midha et al…”

Section: Discussionmentioning

confidence: 99%

Comparative assessment of two behavioural risk factors (physical inactivity and unhealthy diet) among obese Bengalee women in rural and urban areas of West Bengal, India

Bose¹,

Sultana²,

Banerjee

et al. 2022

Preprint

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Background:Unhealthy diet and physical inactivity are the behavioural risks, closely associated with obesity which is a metabolic risk leading to the development of Non Communicable Diseases (NCDs). Dietary transition and sedentary living is also significant even in rural India which might be accountable to uprising NCDs there. So the aim of our study was to assess dietary pattern and unhealthy dietary factors, to determine the prevalence of physical inactivity among obese bengalee women in rural and urban areas of West BengalMethods:This study was conducted in Hooghly district of West Bengal, India and 150 female subjects (75 from rural area and 75 from urban area) of 20-40 years age group were recruited for the study considering inclusion and exclusion criteria. Different physical and socio-demographic variables were measured and dietary information was collected using questionnaire. Global Physical Activity Questionnaire (GPAQ) was used to collect information about physical activities of the study participants. Different anthropometric parameters (body weight, height, Body Mass Index [BMI], waist circumference [WC], hip circumference [HC], waist to hip ratio [WHR] and waist to height ratio [WHtR]) were measures as the strong prediction tools for assessing their risks related to NCDs.Results:We found that most of the daily energy comes from carbohydrate in the diet of both groups, consumption of food groups like animal protein and dairy products, fruits, visible fat and sugar were significantly higher in urban group whereas dietary fibre, green leafy and other vegetables, pulses and nuts intake was significantly high in rural group. Physical inactivity prevalence was 64% in rural and 78.7% in urban and there was significant difference between rural and urban group regard to all the anthropometric indices.Conclusions:In summary, the behavioural risk factors those were assessed are undoubtedly apprehensive and anthropometric indices are pointing out towards associated possible metabolic risks which were poorer in urban group than rural, so further clinical investigation along with proper intervention measure is indispensible.

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“…Con el análisis de las curvas ROC, la medida del perímetro abdominal presentó mayor poder discriminativo para predecir la diabetes (AUC=0,747; p<0,001; IC: 0,624-0,870). Esto concuerda con diversos estudios Roos (16) , Yoon (17) , Darsini (18) en los cuales este indicador resultó eficaz en la predicción de riesgo. En un estudio de cohorte, con diferentes puntos de corte se evaluó el peligro de adquirir diabetes (19) y se determinó que el perímetro abdominal fue la más importante.…”

Section: Discussionunclassified

Evaluation Of The Discriminative Capacity Of Anthropometric Indicators And Their Predictive Relationship Of Diabetes In Health Workers Of The University Hospital Of Guayaquil - Ecuador

Gordillo-Cortaza¹,

Encalada-Calero²,

Feraud-Ibarra³

et al. 2021

RFMH

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Ojetivos: Evaluar la capacidad discriminativa de predicción de diabetes con indicadores antropométricos, bioquímicos y antecedentes. Métodos: El muestreo realizado fue censal y la muestra estuvo conformada por 104 trabajadores. Se realizó un estudio longitudinal para evaluar la capacidad discriminativa de predicción de diabetes con los indicadores antropométricos, bioquímicos y antecedentes, mediante dos modelos, el análisis de las curvas ROC y regresión logística binaria. Resultados: Mediante el análisis de las curvas ROC, el perímetro abdominal obtuvo mayor poder discriminativo de predicción (AUC=0,747; p<0,001; IC: 0,624-0,870), en comparación a la glicemia (AUC=0,749; p<0,001; IC: 0,645-0,852) y el índice de cintura-talla (AUC=0,737; p=0,001; IC: 0,638-0,836). Los antecedentes patológicos personales se incluyen en la ecuación de regresión logística P(Y=1) = (1+e0,693+1,897APP)-1 para predecir el riesgo de tener diabetes en el futuro. Conclusión: El perímetro abdominal obtuvo mayor poder discriminativo, seguido de los antecedentes patológicos personales.

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Health Risks Associated with High Waist Circumference: A Systematic Review

Cited by 75 publications

References 23 publications

Simulation of 3D Body Shapes for Pregnant and Postpartum Women

Simulation of 3D Body Shapes for Pregnant and Postpartum Women

Comparative assessment of two behavioural risk factors (physical inactivity and unhealthy diet) among obese Bengalee women in rural and urban areas of West Bengal, India

Evaluation Of The Discriminative Capacity Of Anthropometric Indicators And Their Predictive Relationship Of Diabetes In Health Workers Of The University Hospital Of Guayaquil - Ecuador

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