Anthropometric indices and metabolic co-morbidities

Arisaka, Osamu; Ichikawa, Go; Koyama, Satomi; Shimura, Naoto

doi:10.1016/j.jpeds.2015.02.005

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…Among various anthropometric indices of obesity ( 99 ), the waist-to-height ratio is thought to be the best predictor to identify adolescence with a cardiometabolic risk associated with excess visceral fat ( 100 ). However, this risk can be reversed if individuals attain a low level of adiposity by adolescence or avoid becoming obese.…”

Section: Early Prediction Of Future Cardiometabolic Riskmentioning

confidence: 99%

Childhood obesity: rapid weight gain in early childhood and subsequent cardiometabolic risk

Arisaka

Ichikawa

Koyama

et al. 2020

Clin Pediatr Endocrinol

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. Dynamic changes in body weight have long been recognized as important indicators of risk for human health. Many population-based observational studies have shown that rapid weight gain during infancy, including a catch-up growth phenomenon or adiposity rebound in early childhood, predisposes a person to the development of obesity, type 2 diabetes, and cardiovascular diseases later in life. However, a consensus has not been established regarding which period of weight gain contributes to future risks. This review evaluates recent evidence on the relationship between early rapid growth and future obesity and cardiometabolic risk, with a focus on the differential significance of rapid weight gain in infancy and early childhood. Although there is a need for attention to childhood growth during early infancy before 1 yr of age as it may be related to future obesity, emerging evidence strongly suggests that toddlers showing an increase in body mass index (BMI) before 3 yr of age, a period normally characterized by decreased BMI, are prone to developing later cardiometabolic risk.

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Section: Early Prediction Of Future Cardiometabolic Riskmentioning

confidence: 99%

Childhood obesity: rapid weight gain in early childhood and subsequent cardiometabolic risk

Arisaka

Ichikawa

Koyama

et al. 2020

Clin Pediatr Endocrinol

Self Cite

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“…By providing information on duration of excess adiposity and rate of change in anthropometric measures over time, it is possible that serial measurements collected throughout childhood and adolescence would improve prediction. For example, data from Arisaka et al have shown that those who had an earlier adiposity rebound had a more atherogenic lipid profile at age 12 years compared with those who had a later adiposity rebound 32 , and those with increasing BMI during the typically 12 stable BMI period from age 1.5-3 years had increased insulin resistance at 12 years of age 33 , independent of current BMI status. Moreover, data from the Cardiovascular Risk in Young Finns…”

Section: Discussion 10mentioning

confidence: 99%

Predictive utility of childhood anthropometric measures on adult glucose homeostasis measures: a 20-year cohort study

Fraser

et al. 2018

Int J Obes

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“…36 Namun demikian, beberapa studi melaporkan bahwa IMT, LP, RLPP, dan parameter antropometri lainnya memiliki keterbatasan untuk memprediksi sindrom metabolik pada remaja obesitas. 37,38 Salah satu faktornya yaitu mayoritas subjek overweight dan obesitas memiliki LP dan RLPP yang lebih tinggi. 39 Studi kami juga menemukan bahwa kolesterol total dan LDL tidak dapat diprediksi oleh 5 parameter antropometri yang diteliti (IMT, lemak viseral, LP, lingkar panggul, dan RLPP) pada subjek dengan IMT normal, overweight, maupun obesitas.…”

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Hubungan Antara Parameter Antropometri Dan Profil Lipid Pada Wanita Sehat Di Semarang

Purwanti

Syauqy

2022

Gizindo

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Obesity is associated with dyslipidemia and cardiovascular disease (CVD). The objective of the study was to determine the association between anthropometric parameters with lipid profiles among healthy women in Semarang. This study used a cross-sectional design with consecutive sampling. Anthropometric parameters in this research were body mass index (BMI), visceral fat, waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR). While, lipid profiles were total cholesterol, high-density lipoprotein (HDL), triglyceride (TG), low-density lipoprotein (LDL), and triglyceride and high-density lipoprotein ratio (TG/HDL). The association of anthropometric parameters with the lipid profiles was analyzed by Spearman correlation. Among subjects with nutritional status normal, BMI has significantly correlated with TG, HDL, and TG/HDL ratio. Moreover, WHR was significantly correlated with HDL and TG. While, among subjects overweight and obese, BMI, visceral fat, and WC were significantly correlated with TG, HDL, and TG/HDL ratio. Anthropometric parameters such as BMI, visceral fat, WC, and WHR were associated with lipid profiles among healthy women in Semarang. BMI and WHR can be used in individuals with normal nutritional status to predict lipid profiles. While, BMI, visceral fat, and WC can be used in overweight and obese individuals to predict lipid profiles

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Anthropometric indices and metabolic co-morbidities

Cited by 3 publications

References 9 publications

Childhood obesity: rapid weight gain in early childhood and subsequent cardiometabolic risk

Childhood obesity: rapid weight gain in early childhood and subsequent cardiometabolic risk

Predictive utility of childhood anthropometric measures on adult glucose homeostasis measures: a 20-year cohort study

Hubungan Antara Parameter Antropometri Dan Profil Lipid Pada Wanita Sehat Di Semarang

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