The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children

Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance h...
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Autor*in:	Halyna PAVLYSHYN [verfasserIn] Kateryna KOZAK [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch ; Französisch

Erschienen:	2019

Schlagwörter:	insulin resistance obesity children multiple regression analysis

Übergeordnetes Werk:	In: Archives of the Balkan Medical Union - Balkan Medical Union, 2018, 54(2019), 3, Seite 514-521
Übergeordnetes Werk:	volume:54 ; year:2019 ; number:3 ; pages:514-521

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

Katalog-ID:	DOAJ017840473

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520			\|a Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis.
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allfields	(DE-627)DOAJ017840473 (DE-599)DOAJ6e8199d501b542d7be608a3cd12d7eff DE-627 ger DE-627 rakwb eng fre R5-920 Halyna PAVLYSHYN verfasserin aut The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis. insulin resistance obesity children multiple regression analysis Medicine R Medicine (General) Kateryna KOZAK verfasserin aut In Archives of the Balkan Medical Union Balkan Medical Union, 2018 54(2019), 3, Seite 514-521 (DE-627)1010165054 2558815X nnns volume:54 year:2019 number:3 pages:514-521 https://doi.org/10.31688/ABMU.2019.54.3.18 kostenfrei https://doaj.org/article/6e8199d501b542d7be608a3cd12d7eff kostenfrei https://umbalk.org/wp-content/uploads/2019/09/18.THE-ROLE-OF-MULTIPLE-REGRESSION-ANALYSIS.pdf kostenfrei https://doaj.org/toc/1584-9244 Journal toc kostenfrei https://doaj.org/toc/2558-815X 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_2014 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 54 2019 3 514-521
spelling	(DE-627)DOAJ017840473 (DE-599)DOAJ6e8199d501b542d7be608a3cd12d7eff DE-627 ger DE-627 rakwb eng fre R5-920 Halyna PAVLYSHYN verfasserin aut The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis. insulin resistance obesity children multiple regression analysis Medicine R Medicine (General) Kateryna KOZAK verfasserin aut In Archives of the Balkan Medical Union Balkan Medical Union, 2018 54(2019), 3, Seite 514-521 (DE-627)1010165054 2558815X nnns volume:54 year:2019 number:3 pages:514-521 https://doi.org/10.31688/ABMU.2019.54.3.18 kostenfrei https://doaj.org/article/6e8199d501b542d7be608a3cd12d7eff kostenfrei https://umbalk.org/wp-content/uploads/2019/09/18.THE-ROLE-OF-MULTIPLE-REGRESSION-ANALYSIS.pdf kostenfrei https://doaj.org/toc/1584-9244 Journal toc kostenfrei https://doaj.org/toc/2558-815X 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_2014 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 54 2019 3 514-521
allfields_unstemmed	(DE-627)DOAJ017840473 (DE-599)DOAJ6e8199d501b542d7be608a3cd12d7eff DE-627 ger DE-627 rakwb eng fre R5-920 Halyna PAVLYSHYN verfasserin aut The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis. insulin resistance obesity children multiple regression analysis Medicine R Medicine (General) Kateryna KOZAK verfasserin aut In Archives of the Balkan Medical Union Balkan Medical Union, 2018 54(2019), 3, Seite 514-521 (DE-627)1010165054 2558815X nnns volume:54 year:2019 number:3 pages:514-521 https://doi.org/10.31688/ABMU.2019.54.3.18 kostenfrei https://doaj.org/article/6e8199d501b542d7be608a3cd12d7eff kostenfrei https://umbalk.org/wp-content/uploads/2019/09/18.THE-ROLE-OF-MULTIPLE-REGRESSION-ANALYSIS.pdf kostenfrei https://doaj.org/toc/1584-9244 Journal toc kostenfrei https://doaj.org/toc/2558-815X 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_2014 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 54 2019 3 514-521
allfieldsGer	(DE-627)DOAJ017840473 (DE-599)DOAJ6e8199d501b542d7be608a3cd12d7eff DE-627 ger DE-627 rakwb eng fre R5-920 Halyna PAVLYSHYN verfasserin aut The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis. insulin resistance obesity children multiple regression analysis Medicine R Medicine (General) Kateryna KOZAK verfasserin aut In Archives of the Balkan Medical Union Balkan Medical Union, 2018 54(2019), 3, Seite 514-521 (DE-627)1010165054 2558815X nnns volume:54 year:2019 number:3 pages:514-521 https://doi.org/10.31688/ABMU.2019.54.3.18 kostenfrei https://doaj.org/article/6e8199d501b542d7be608a3cd12d7eff kostenfrei https://umbalk.org/wp-content/uploads/2019/09/18.THE-ROLE-OF-MULTIPLE-REGRESSION-ANALYSIS.pdf kostenfrei https://doaj.org/toc/1584-9244 Journal toc kostenfrei https://doaj.org/toc/2558-815X 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_2014 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 54 2019 3 514-521
allfieldsSound	(DE-627)DOAJ017840473 (DE-599)DOAJ6e8199d501b542d7be608a3cd12d7eff DE-627 ger DE-627 rakwb eng fre R5-920 Halyna PAVLYSHYN verfasserin aut The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis. insulin resistance obesity children multiple regression analysis Medicine R Medicine (General) Kateryna KOZAK verfasserin aut In Archives of the Balkan Medical Union Balkan Medical Union, 2018 54(2019), 3, Seite 514-521 (DE-627)1010165054 2558815X nnns volume:54 year:2019 number:3 pages:514-521 https://doi.org/10.31688/ABMU.2019.54.3.18 kostenfrei https://doaj.org/article/6e8199d501b542d7be608a3cd12d7eff kostenfrei https://umbalk.org/wp-content/uploads/2019/09/18.THE-ROLE-OF-MULTIPLE-REGRESSION-ANALYSIS.pdf kostenfrei https://doaj.org/toc/1584-9244 Journal toc kostenfrei https://doaj.org/toc/2558-815X 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_2014 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 54 2019 3 514-521
language	English French
source	In Archives of the Balkan Medical Union 54(2019), 3, Seite 514-521 volume:54 year:2019 number:3 pages:514-521
sourceStr	In Archives of the Balkan Medical Union 54(2019), 3, Seite 514-521 volume:54 year:2019 number:3 pages:514-521
format_phy_str_mv	Article
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topic_facet	insulin resistance obesity children multiple regression analysis Medicine R Medicine (General)
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container_title	Archives of the Balkan Medical Union
authorswithroles_txt_mv	Halyna PAVLYSHYN @@aut@@ Kateryna KOZAK @@aut@@
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Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. 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callnumber-first	R - Medicine
author	Halyna PAVLYSHYN
spellingShingle	Halyna PAVLYSHYN misc R5-920 misc insulin resistance misc obesity misc children misc multiple regression analysis misc Medicine misc R misc Medicine (General) The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children
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topic_title	R5-920 The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children insulin resistance obesity children multiple regression analysis
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title	The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children
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title_full	The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children
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title_sort	role of multiple regression analysis in prediction of insulin resistance in overweight and obese children
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title_auth	The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children
abstract	Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis.
abstractGer	Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis.
abstract_unstemmed	Introduction. Overweight and obesity is a global epidemic among children of all age groups. Obese children are at increased risk of insulin resistance, cardiovascular disease (including arterial hypertension), as well as bone fractures and psychological problems. In this regard, insulin resistance has become one of the most serious health concerns in overweight and obese children. The objective of the study was to investigate the specifics for carbohydrate metabolism in overweight and obese children, to identify the key factors for insulin resistance and to develop a regression analysis-based prognostic model to predict its occurrence. Material and methods. In 90 obese and 20 overweight children aged between 10-17 years, anthropometric measurements, history data collection and laboratory investigations were performed. Multiple regression analysis has been used to develop a mathematical model for prediction of insulin resistance. Results. Such variables as weight, body mass index, waist and hip circumferences, abdominal type obesity, family history, duration of breastfeeding (if any), birth weight, sedentary lifestyle, leptin and adiponectin levels and dyslipidemia were closely related to fasting glucose levels and insulin/insulin resistance indices. Conclusions. Abdominal obesity, male gender, family history of abnormal carbohydrate metabolism, insulin levels, duration of breastfeeding and plasma leptin levels have been defined as main predictors of insulin resistance in overweight and obese children and were included in regression equation for the index of insulin resistance using the method of multiple regression analysis.
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title_short	The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children
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The role of multiple regression analysis in prediction of insulin resistance in overweight and obese children

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