Metabolically healthy overweight adolescents: definition and components
Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore fu...
Ausführliche Beschreibung
Autor*in: |
António Videira-Silva [verfasserIn] Silvia Freira [verfasserIn] Helena Fonseca [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2020 |
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In: Annals of Pediatric Endocrinology & Metabolism - Korean Society of Pediatric Endocrinology, 2018, 25(2020), 4, Seite 256-264 |
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Übergeordnetes Werk: |
volume:25 ; year:2020 ; number:4 ; pages:256-264 |
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Link aufrufen |
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DOI / URN: |
10.6065/apem.2040052.026 |
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Katalog-ID: |
DOAJ059346353 |
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520 | |a Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. | ||
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10.6065/apem.2040052.026 doi (DE-627)DOAJ059346353 (DE-599)DOAJ7eaac3b0360641c0acc91db77a74a8cf DE-627 ger DE-627 rakwb eng RJ1-570 António Videira-Silva verfasserin aut Metabolically healthy overweight adolescents: definition and components 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. adolescents overweight weight management metabolic health metabolic syndrome Pediatrics Silvia Freira verfasserin aut Helena Fonseca verfasserin aut In Annals of Pediatric Endocrinology & Metabolism Korean Society of Pediatric Endocrinology, 2018 25(2020), 4, Seite 256-264 (DE-627)80563746X (DE-600)2800460-7 22871292 nnns volume:25 year:2020 number:4 pages:256-264 https://doi.org/10.6065/apem.2040052.026 kostenfrei https://doaj.org/article/7eaac3b0360641c0acc91db77a74a8cf kostenfrei http://e-apem.org/upload/pdf/apem-2040052-026.pdf kostenfrei https://doaj.org/toc/2287-1012 Journal toc kostenfrei https://doaj.org/toc/2287-1292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 25 2020 4 256-264 |
spelling |
10.6065/apem.2040052.026 doi (DE-627)DOAJ059346353 (DE-599)DOAJ7eaac3b0360641c0acc91db77a74a8cf DE-627 ger DE-627 rakwb eng RJ1-570 António Videira-Silva verfasserin aut Metabolically healthy overweight adolescents: definition and components 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. adolescents overweight weight management metabolic health metabolic syndrome Pediatrics Silvia Freira verfasserin aut Helena Fonseca verfasserin aut In Annals of Pediatric Endocrinology & Metabolism Korean Society of Pediatric Endocrinology, 2018 25(2020), 4, Seite 256-264 (DE-627)80563746X (DE-600)2800460-7 22871292 nnns volume:25 year:2020 number:4 pages:256-264 https://doi.org/10.6065/apem.2040052.026 kostenfrei https://doaj.org/article/7eaac3b0360641c0acc91db77a74a8cf kostenfrei http://e-apem.org/upload/pdf/apem-2040052-026.pdf kostenfrei https://doaj.org/toc/2287-1012 Journal toc kostenfrei https://doaj.org/toc/2287-1292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 25 2020 4 256-264 |
allfields_unstemmed |
10.6065/apem.2040052.026 doi (DE-627)DOAJ059346353 (DE-599)DOAJ7eaac3b0360641c0acc91db77a74a8cf DE-627 ger DE-627 rakwb eng RJ1-570 António Videira-Silva verfasserin aut Metabolically healthy overweight adolescents: definition and components 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. adolescents overweight weight management metabolic health metabolic syndrome Pediatrics Silvia Freira verfasserin aut Helena Fonseca verfasserin aut In Annals of Pediatric Endocrinology & Metabolism Korean Society of Pediatric Endocrinology, 2018 25(2020), 4, Seite 256-264 (DE-627)80563746X (DE-600)2800460-7 22871292 nnns volume:25 year:2020 number:4 pages:256-264 https://doi.org/10.6065/apem.2040052.026 kostenfrei https://doaj.org/article/7eaac3b0360641c0acc91db77a74a8cf kostenfrei http://e-apem.org/upload/pdf/apem-2040052-026.pdf kostenfrei https://doaj.org/toc/2287-1012 Journal toc kostenfrei https://doaj.org/toc/2287-1292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 25 2020 4 256-264 |
allfieldsGer |
10.6065/apem.2040052.026 doi (DE-627)DOAJ059346353 (DE-599)DOAJ7eaac3b0360641c0acc91db77a74a8cf DE-627 ger DE-627 rakwb eng RJ1-570 António Videira-Silva verfasserin aut Metabolically healthy overweight adolescents: definition and components 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. adolescents overweight weight management metabolic health metabolic syndrome Pediatrics Silvia Freira verfasserin aut Helena Fonseca verfasserin aut In Annals of Pediatric Endocrinology & Metabolism Korean Society of Pediatric Endocrinology, 2018 25(2020), 4, Seite 256-264 (DE-627)80563746X (DE-600)2800460-7 22871292 nnns volume:25 year:2020 number:4 pages:256-264 https://doi.org/10.6065/apem.2040052.026 kostenfrei https://doaj.org/article/7eaac3b0360641c0acc91db77a74a8cf kostenfrei http://e-apem.org/upload/pdf/apem-2040052-026.pdf kostenfrei https://doaj.org/toc/2287-1012 Journal toc kostenfrei https://doaj.org/toc/2287-1292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 25 2020 4 256-264 |
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10.6065/apem.2040052.026 doi (DE-627)DOAJ059346353 (DE-599)DOAJ7eaac3b0360641c0acc91db77a74a8cf DE-627 ger DE-627 rakwb eng RJ1-570 António Videira-Silva verfasserin aut Metabolically healthy overweight adolescents: definition and components 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. adolescents overweight weight management metabolic health metabolic syndrome Pediatrics Silvia Freira verfasserin aut Helena Fonseca verfasserin aut In Annals of Pediatric Endocrinology & Metabolism Korean Society of Pediatric Endocrinology, 2018 25(2020), 4, Seite 256-264 (DE-627)80563746X (DE-600)2800460-7 22871292 nnns volume:25 year:2020 number:4 pages:256-264 https://doi.org/10.6065/apem.2040052.026 kostenfrei https://doaj.org/article/7eaac3b0360641c0acc91db77a74a8cf kostenfrei http://e-apem.org/upload/pdf/apem-2040052-026.pdf kostenfrei https://doaj.org/toc/2287-1012 Journal toc kostenfrei https://doaj.org/toc/2287-1292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 25 2020 4 256-264 |
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Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. |
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Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. |
abstract_unstemmed |
Purpose In adolescents, the definition and clinical implications of metabolically healthy overweight (MHO) status have not been established. This study aimed to investigate the prevalence of MHO according to its most widespread definition, which is based on metabolic syndrome (MS), and to explore further metabolic indicators such as Homeostatic Model Assessment of Insulin Resistance, total cholesterol, low-density lipoprotein cholesterol, alanine aminotransferase, and C-reactive protein levels, together with metabolic health predictors in a sample of adolescents attending a pediatric obesity clinic. Methods Data from 487 adolescents categorized as overweight (52.6% females, 88.1% white), with a mean body mass index (BMI) z-score of 2.74 (±1.07 standard deviation [SD]), and a mean age of 14.4 years (±2.2 SD) were cross-sectionally analyzed. From this original sample, a subsample of 176 adolescents underwent a second assessment at 12 (±6 SD) months for longitudinal analysis. Results From the 487 adolescents originally analyzed, 200 (41.1%) were categorized as MHO, but only 93 (19.1%) had none of the metabolic indicators considered in this study. According to longitudinal analysis, 30 of the 68 adolescents (44%) categorized as MHO at baseline became non-MHO over time. BMI z-score was the best predictor of metabolic health both in cross-sectional and longitudinal analyses. Increased BMI z-score reduced the odds of being categorized as MHO (odds ratio [OR], 0.6; 95% confidence interval [CI], 0.4–0.9; P=.008) and increased the odds of having hypertension (OR 2.1, 95% CI: 1.4–3.3, P=0.001), insulin resistance (OR, 2.4; 95% CI, 1.4–4.1, P=0.001), or a proinflammatory state (OR, 1.2; 95% CI, 1.1–1.3, P=0.002). Conclusions Diagnosis of MHO should not be exclusively based on MS parameters, and other metabolic indicators should be considered. Adolescents categorized as overweight should participate in weight-management lifestyle interventions regardless of their metabolic health phenotype. |
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Metabolically healthy overweight adolescents: definition and components |
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https://doi.org/10.6065/apem.2040052.026 https://doaj.org/article/7eaac3b0360641c0acc91db77a74a8cf http://e-apem.org/upload/pdf/apem-2040052-026.pdf https://doaj.org/toc/2287-1012 https://doaj.org/toc/2287-1292 |
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