Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity
Body mass index (BMI), usually used as a body fatness marker, does not accurately discriminate between amounts of lean and fat mass, crucial factors in determining metabolic syndrome (MS) risk. We assessed the predictive ability of the estimate of FM (eFM) calculated using the following formula: FM...
Guardado en:
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/54beddbe163e4c17aa5c2327e297af67 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:54beddbe163e4c17aa5c2327e297af67 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:54beddbe163e4c17aa5c2327e297af672021-11-25T17:14:01ZPredictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity10.3390/children81109662227-9067https://doaj.org/article/54beddbe163e4c17aa5c2327e297af672021-10-01T00:00:00Zhttps://www.mdpi.com/2227-9067/8/11/966https://doaj.org/toc/2227-9067Body mass index (BMI), usually used as a body fatness marker, does not accurately discriminate between amounts of lean and fat mass, crucial factors in determining metabolic syndrome (MS) risk. We assessed the predictive ability of the estimate of FM (eFM) calculated using the following formula: FM = weight − exp(0.3073 × height<sup>2</sup> − 10.0155 ×d-growth-standards/standards/body-mass-index-for-age-bmi-for-age weight− 1 + 0.004571 × weight − 0.9180 × ln(age) + 0.6488 × age<sup>0.5</sup> + 0.04723×male + 2.8055) (exp = exponential function, score 1 if child was of black (BA), south Asian (SA), other Asian (AO), or other (other) ethnic origin and score 0 if not, ln = natural logarithmic transformation, male = 1, female = 0), to detect MS in 185 prepubertal obese children compared to other adiposity parameters. The eFM, BMI, waist circumference (WC), body shape index (ABSI), tri-ponderal mass index, and conicity index (C-Index) were calculated. Patients were classified as having MS if they met ≥ 3/5 of the following criteria: WC ≥ 95th percentile; triglycerides ≥ 95th percentile; HDL-cholesterol ≤ 5th percentile; blood pressure ≥ 95th percentile; fasting blood glucose ≥ 100 mg/dL; and/or HOMA-IR ≥ 97.5th percentile. MS occurred in 18.9% of obese subjects (<i>p</i> < 0.001), with a higher prevalence in females vs. males (<i>p</i> = 0.005). The eFM was correlated with BMI, WC, ABSI, and Con-I (<i>p</i> < 0.001). Higher eFM values were present in the MS vs. non-MS group (<i>p</i> < 0.001); the eFM was higher in patients with hypertension and insulin resistance (<i>p</i> < 0.01). The eFM shows a good predictive ability for MS. Additional to BMI, the identification of new parameters determinable with simple anthropometric measures and with a good ability for the early detection of MS, such as the eFM, may be useful in clinical practice, particularly when instrumentation to estimate the body composition is not available.Valeria CalcaterraElvira VerduciAnnalisa De SilvestriVittoria Carlotta MagenesFrancesca SiccardoLaura SchneiderSara VizzusoAlessandra BosettiGianvincenzo ZuccottiMDPI AGarticlepediatric obesityfat massadiposity indexmetabolic syndromechildrenadolescentsPediatricsRJ1-570ENChildren, Vol 8, Iss 966, p 966 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
pediatric obesity fat mass adiposity index metabolic syndrome children adolescents Pediatrics RJ1-570 |
| spellingShingle |
pediatric obesity fat mass adiposity index metabolic syndrome children adolescents Pediatrics RJ1-570 Valeria Calcaterra Elvira Verduci Annalisa De Silvestri Vittoria Carlotta Magenes Francesca Siccardo Laura Schneider Sara Vizzuso Alessandra Bosetti Gianvincenzo Zuccotti Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity |
| description |
Body mass index (BMI), usually used as a body fatness marker, does not accurately discriminate between amounts of lean and fat mass, crucial factors in determining metabolic syndrome (MS) risk. We assessed the predictive ability of the estimate of FM (eFM) calculated using the following formula: FM = weight − exp(0.3073 × height<sup>2</sup> − 10.0155 ×d-growth-standards/standards/body-mass-index-for-age-bmi-for-age weight− 1 + 0.004571 × weight − 0.9180 × ln(age) + 0.6488 × age<sup>0.5</sup> + 0.04723×male + 2.8055) (exp = exponential function, score 1 if child was of black (BA), south Asian (SA), other Asian (AO), or other (other) ethnic origin and score 0 if not, ln = natural logarithmic transformation, male = 1, female = 0), to detect MS in 185 prepubertal obese children compared to other adiposity parameters. The eFM, BMI, waist circumference (WC), body shape index (ABSI), tri-ponderal mass index, and conicity index (C-Index) were calculated. Patients were classified as having MS if they met ≥ 3/5 of the following criteria: WC ≥ 95th percentile; triglycerides ≥ 95th percentile; HDL-cholesterol ≤ 5th percentile; blood pressure ≥ 95th percentile; fasting blood glucose ≥ 100 mg/dL; and/or HOMA-IR ≥ 97.5th percentile. MS occurred in 18.9% of obese subjects (<i>p</i> < 0.001), with a higher prevalence in females vs. males (<i>p</i> = 0.005). The eFM was correlated with BMI, WC, ABSI, and Con-I (<i>p</i> < 0.001). Higher eFM values were present in the MS vs. non-MS group (<i>p</i> < 0.001); the eFM was higher in patients with hypertension and insulin resistance (<i>p</i> < 0.01). The eFM shows a good predictive ability for MS. Additional to BMI, the identification of new parameters determinable with simple anthropometric measures and with a good ability for the early detection of MS, such as the eFM, may be useful in clinical practice, particularly when instrumentation to estimate the body composition is not available. |
| format |
article |
| author |
Valeria Calcaterra Elvira Verduci Annalisa De Silvestri Vittoria Carlotta Magenes Francesca Siccardo Laura Schneider Sara Vizzuso Alessandra Bosetti Gianvincenzo Zuccotti |
| author_facet |
Valeria Calcaterra Elvira Verduci Annalisa De Silvestri Vittoria Carlotta Magenes Francesca Siccardo Laura Schneider Sara Vizzuso Alessandra Bosetti Gianvincenzo Zuccotti |
| author_sort |
Valeria Calcaterra |
| title |
Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity |
| title_short |
Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity |
| title_full |
Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity |
| title_fullStr |
Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity |
| title_full_unstemmed |
Predictive Ability of the Estimate of Fat Mass to Detect Early-Onset Metabolic Syndrome in Prepubertal Children with Obesity |
| title_sort |
predictive ability of the estimate of fat mass to detect early-onset metabolic syndrome in prepubertal children with obesity |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/54beddbe163e4c17aa5c2327e297af67 |
| work_keys_str_mv |
AT valeriacalcaterra predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT elviraverduci predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT annalisadesilvestri predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT vittoriacarlottamagenes predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT francescasiccardo predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT lauraschneider predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT saravizzuso predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT alessandrabosetti predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity AT gianvincenzozuccotti predictiveabilityoftheestimateoffatmasstodetectearlyonsetmetabolicsyndromeinprepubertalchildrenwithobesity |
| _version_ |
1718412587481169920 |