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Multiple linear regression models were used.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Cross‐sectional analyses at baseline suggest that \u003Cjats:styled-content style=\"fixed-case\">BMIz\u003C\u002Fjats:styled-content> was 0.23 units lower for each additional reported eating occasion (regression coefficient = −0.23; 95% confidence interval [\u003Cjats:styled-content style=\"fixed-case\">CI\u003C\u002Fjats:styled-content>]: −0.44, −0.07). From baseline to 6 months, \u003Cjats:styled-content style=\"fixed-case\">BMIz\u003C\u002Fjats:styled-content> increased by 0.03 units for each additional reported eating occasion (regression coefficient = 0.03; 95% \u003Cjats:styled-content style=\"fixed-case\">CI\u003C\u002Fjats:styled-content>: 0.01, 0.05). This relationship was no longer statistically significant at 1 year (regression coefficient = 0.01; 95% \u003Cjats:styled-content style=\"fixed-case\">CI\u003C\u002Fjats:styled-content>: −0.01, 0.03).\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusions\u003C\u002Fjats:title>\u003Cjats:p>The findings suggest that the relationship of eating frequency with \u003Cjats:styled-content style=\"fixed-case\">BMIz\u003C\u002Fjats:styled-content> differs from that of change in \u003Cjats:styled-content style=\"fixed-case\">BMIz\u003C\u002Fjats:styled-content>. This difference may be due to methodological deficiencies of cross‐sectional studies, challenges of dietary assessment or differences in eating patterns among normal and overweight youth. Controlled trials are needed to further clarify this relationship.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>",{"EN":124},"The role of eating frequency on relative weight in urban school‐age children",{"VOID":126},"25565335",{"VOID":128},"10.1111\u002Fijpo.12004","PUBLICATION","VERIFIED","2025-01-03T00:47:33.047+00:00","Auto Verify",[134],"EN","https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fijpo.12004",[137,156,184,206,224],{"id":138,"sortIndex":25,"researcher":24,"roles":139,"affiliations":140,"properties":149,"displayName":153,"givenName":24,"familyName":24},"1b1d74c4-9e9a-4c2f-b17b-b773c27d7a3e",[],[141],{"id":142,"sortIndex":25,"affiliation":143,"properties":24},"f59c7169-dfa5-4083-bca0-5d36bc1b2956",{"id":142,"createTime":24,"updateTime":24,"relativeEntities":144,"slug":24,"properties":145,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":148,"statistic":24},[],{"title":146},{"EN":147},"Weight Control and Diabetes Research Center, Brown University Medical School, Providence, RI, USA",[],{"orcid":150,"title":152,"openalex":154},{"VOID":151},"https:\u002F\u002Forcid.org\u002F0000-0003-3946-7014",{"EN":153},"E. 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URLhttp:\u002F\u002Fwww.health.gov\u002Fpaguidelines\u002Fguidelines\u002Fappendix1.aspx(accessed 15 June 2012).",{},{"id":24,"text":384,"url":24,"identifiers":385},"Rothman K, 2008, Modern Epidemiology",{},{"id":24,"text":387,"url":24,"identifiers":388},"Ogden C, 2010, Changes in Terminology for Childhood Overweight and Obesity",{},{"id":24,"text":390,"url":24,"identifiers":391},"10.1079\u002FBJN19970104",{"doi":390},{"id":24,"text":393,"url":24,"identifiers":394},"10.1017\u002FS1368980008003108",{"doi":393},{"id":24,"text":396,"url":24,"identifiers":397},"10.1079\u002FBJN20041169",{"doi":396},{"id":24,"text":399,"url":24,"identifiers":400},"Summerbell C, 1996, Relationship between feeding pattern and body mass index in 220 free‐living people in four age groups, Eur J Clin Nutr, 50, 513",{},{"id":24,"text":402,"url":24,"identifiers":403},"10.1038\u002Fsj.ijo.0800380",{"doi":402},{"id":24,"text":405,"url":24,"identifiers":406},"10.1093\u002Facprof:oso\u002F9780195122978.001.0001",{"doi":405},false,{"id":409,"createTime":410,"updateTime":410,"relativeEntities":411,"slug":412,"properties":413,"entityType":129,"verifyStatus":130,"verifyTime":410,"verifyNote":132,"languages":428,"translateLanguages":24,"viewCount":25,"primaryUrl":429,"fullTextUrl":24,"authors":430,"publicationType":250,"publisherRelationship":560,"citationCount":617,"citationInfo":618,"publishDate":622,"publishYear":619,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":623,"openAccess":24,"references":624,"isForceReanalyzing":407},"67657f3b-6db5-407f-9518-6bfad836ad3b","2024-12-21T21:02:15.639+00:00",[],"Comparison-of-total-energy-expenditure-between-school-and-summer-months",{"mag":414,"pmc":416,"openalex":418,"abstract":420,"title":422,"pm":424,"doi":426},{"VOID":415},"1532709338",{"VOID":417},"3740056",{"VOID":419},"W1532709338",{"EN":421},"\u003Cjats:title>Summary\u003C\u002Fjats:title>\u003Cjats:sec>\u003Cjats:title>What is already known about this subject\u003C\u002Fjats:title>\u003Cjats:p>\u003Cjats:list list-type=\"bullet\">\n\u003Cjats:list-item>\u003Cjats:p>Childhood obesity has increased 3 to 4 fold.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003Cjats:list-item>\u003Cjats:p>Some children gain excess weight in summer.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>What this study adds\u003C\u002Fjats:title>\u003Cjats:p>\u003Cjats:list list-type=\"bullet\">\n\u003Cjats:list-item>\u003Cjats:p>Total energy expenditure increases almost linearly with fat‐free mass.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003Cjats:list-item>\u003Cjats:p>A lower total energy expenditure was not detected in summer.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Objective\u003C\u002Fjats:title>\u003Cjats:p>Recent data report that the youth experience greater weight gain during summer than during school months. We tested the hypothesis that a difference in total energy expenditure (\u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content>) between school and summer months exists and may contribute to summer weight gain.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Subjects and methods\u003C\u002Fjats:title>\u003Cjats:p>A secondary analysis was performed on cross‐sectional \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> data from school‐age, sedentary \u003Cjats:styled-content style=\"fixed-case\">A\u003C\u002Fjats:styled-content>frican–\u003Cjats:styled-content style=\"fixed-case\">A\u003C\u002Fjats:styled-content>merican and \u003Cjats:styled-content style=\"fixed-case\">C\u003C\u002Fjats:styled-content>aucasian youth based in or near the \u003Cjats:styled-content style=\"fixed-case\">D\u003C\u002Fjats:styled-content>istrict of \u003Cjats:styled-content style=\"fixed-case\">C\u003C\u002Fjats:styled-content>olumbia who were at‐risk for adult obesity because they had body mass index (\u003Cjats:styled-content style=\"fixed-case\">BMI)\u003C\u002Fjats:styled-content> ≥ 85th percentile or had overweight parents. \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> was estimated from 18‐\u003Cjats:styled-content style=\"fixed-case\">O\u003C\u002Fjats:styled-content> and deuterium measurements during 1‐week intervals using urine samples collected after ingestion of doubly labelled water. Differences in summer‐ and school‐time \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> were assessed using analysis of covariance. The data were adjusted for fat‐free mass (\u003Cjats:styled-content style=\"fixed-case\">FFM\u003C\u002Fjats:styled-content>) as determined by deuterium dilution to adjust for the effect of body size on \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content>.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Data were collected from 162 youth (average age 10 ± 2 years, \u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content> 28 ± 8 kg m\u003Cjats:sup>−2\u003C\u002Fjats:sup> and \u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content> \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">z\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic>‐score 1.96 + 0.96). Of these, 96 youth had \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> measured during the school year (\u003Cjats:styled-content style=\"fixed-case\">S\u003C\u002Fjats:styled-content>eptember–\u003Cjats:styled-content style=\"fixed-case\">J\u003C\u002Fjats:styled-content>une); 66 different youths had \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> measured during summer months (\u003Cjats:styled-content style=\"fixed-case\">J\u003C\u002Fjats:styled-content>une–\u003Cjats:styled-content style=\"fixed-case\">A\u003C\u002Fjats:styled-content>ugust). After adjustment for \u003Cjats:styled-content style=\"fixed-case\">FFM\u003C\u002Fjats:styled-content>, average summertime \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> was 2450 ± 270 kcal d\u003Cjats:sup>−1\u003C\u002Fjats:sup> and average school‐time \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> was 2510 ± 350 kcal d\u003Cjats:sup>−1\u003C\u002Fjats:sup> (\u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> = 0.26).\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusion\u003C\u002Fjats:title>\u003Cjats:p>\u003Cjats:styled-content style=\"fixed-case\">N\u003C\u002Fjats:styled-content>o difference in \u003Cjats:styled-content style=\"fixed-case\">TEE\u003C\u002Fjats:styled-content> was detected between the school year and the summer months. These data suggest that seasonal differences in youth weight gain are not necessarily due to differences in energy expenditures.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>",{"EN":423},"Comparison of total energy expenditure between school and summer months",{"VOID":425},"23637099",{"VOID":427},"10.1111\u002Fj.2047-6310.2012.00120.x",[134],"https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fj.2047-6310.2012.00120.x",[431,448,465,482,499,524,542],{"id":432,"sortIndex":25,"researcher":24,"roles":433,"affiliations":434,"properties":443,"displayName":445,"givenName":24,"familyName":24},"43d37c83-9296-4076-957a-de4084e4078b",[],[435],{"id":436,"sortIndex":25,"affiliation":437,"properties":24},"3ac1be74-b558-494a-8188-c52bef048494",{"id":436,"createTime":24,"updateTime":24,"relativeEntities":438,"slug":24,"properties":439,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":442,"statistic":24},[],{"title":440},{"EN":441},"Department of Nutritional Sciences University of Wisconsin – Madison  Madison WI USA",[],{"title":444,"openalex":446},{"EN":445},"S. 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As breastfeeding can protect against child obesity, disadvantaged infants are less likely to breastfeed relative to more advantaged children. Whether infant feeding patterns, as well as other maternal characteristics mediate the association between social class and obesity has not been established in available research.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Objectives\u003C\u002Fjats:title>\u003Cjats:p>Examine the impact of infant feeding practices on child obesity and identify the mechanisms that link socioeconomic status (\u003Cjats:styled-content style=\"fixed-case\">SES\u003C\u002Fjats:styled-content>) with child obesity.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Methods\u003C\u002Fjats:title>\u003Cjats:p>Based on a nationally representative longitudinal survey (\u003Cjats:styled-content style=\"fixed-case\">ECLS\u003C\u002Fjats:styled-content>‐\u003Cjats:styled-content style=\"fixed-case\">B\u003C\u002Fjats:styled-content>) of early childhood (\u003Cjats:italic>n\u003C\u002Fjats:italic> = 8030), we examine how breastfeeding practices, the early introduction of solid foods and putting an infant to bed with a bottle mediate the relationship between social class and early childhood obesity relative to the mediating influence of other maternal characteristics (\u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content>, age at birth, smoking, depression and daycare use).\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Infants predominantly fed formula for the first 6 months were about 2.5 times more likely to be obese at 24 months of age relative to infants predominantly fed breast milk. The early introduction of solid foods (< 4 months) and putting the child to bed with a bottle also increased the likelihood of obesity. Unhealthy infant feeding practices were the primary mechanism mediating the relationship between \u003Cjats:styled-content style=\"fixed-case\">SES\u003C\u002Fjats:styled-content> and early childhood obesity. Results are consistent across measures of child obesity although the effect size of infant feeding practices varies.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusions\u003C\u002Fjats:title>\u003Cjats:p>The encouragement and support of breastfeeding and other healthy feeding practices are especially important for low socioeconomic children who are at increased risk of early childhood obesity. Targeting socioeconomically disadvantaged mothers for breastfeeding support and for infant‐led feeding strategies may reduce the negative association between \u003Cjats:styled-content style=\"fixed-case\">SES\u003C\u002Fjats:styled-content> and child obesity. 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ShenassaED ParadisAD.Maternal smoking breastfeeding and risk of childhood overweight: findings from a national cohort.Matern Child Health J2012; 20 June. [WWW document]. URLhttp:\u002F\u002Fwww.springerlink.com\u002Fcontent\u002Fm3787n8j8p666140\u002Ffulltext.pdf(accessed March 22 2013).",{},{"id":24,"text":904,"url":24,"identifiers":905},"10.1542\u002Fpeds.2004-1176",{"doi":904},{"id":24,"text":907,"url":24,"identifiers":908},"WangL MamuduHM WuT.The impact of maternal prenatal smoking on the development of childhood overweight in school‐aged children.Pediatr Obes2012; 8 Oct. [WWW document]. URLhttp:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fj.2047‐6310.2012.00103.x\u002Fabstract(accessed March 22 2013).",{},{"id":24,"text":910,"url":24,"identifiers":911},"10.1542\u002Fpeds.2011-2456",{"doi":910},{"id":24,"text":913,"url":24,"identifiers":914},"10.1542\u002Fpeds.2010-0166",{"doi":913},{"id":24,"text":916,"url":24,"identifiers":917},"10.1542\u002Fpeds.2005-2948",{"doi":916},{"id":24,"text":919,"url":24,"identifiers":920},"10.1542\u002Fpeds.2009-2100",{"doi":919},{"id":24,"text":922,"url":24,"identifiers":923},"10.1111\u002Fj.2047-6310.2011.00012.x",{"doi":922},{"id":24,"text":925,"url":24,"identifiers":926},"10.1038\u002Fijo.2011.88",{"doi":925},{"id":24,"text":928,"url":24,"identifiers":929},"10.1016\u002Fj.socscimed.2012.02.048",{"doi":928},{"id":24,"text":931,"url":24,"identifiers":932},"Crume TL, 2012, Selective protection against extremes in childhood body size, abdominal fat deposition, and fat patterning in breastfed children, Arch Pediatr Adolesc Med, 116, 437",{},{"id":24,"text":934,"url":24,"identifiers":935},"10.1542\u002Fpeds.2007-2329E",{"doi":934},{"id":24,"text":937,"url":24,"identifiers":938},"10.3109\u002F17477160902763309",{"doi":937},{"id":24,"text":940,"url":24,"identifiers":941},"10.3109\u002F17477166.2010.490269",{"doi":940},{"id":24,"text":943,"url":24,"identifiers":944},"10.1177\u002F0890334408317617",{"doi":943},{"id":24,"text":946,"url":24,"identifiers":947},"10.1001\u002Fjama.285.19.2461",{"doi":946},{"id":24,"text":949,"url":24,"identifiers":950},"10.1002\u002Fajhb.20982",{"doi":949},{"id":24,"text":952,"url":24,"identifiers":953},"10.3109\u002F17477166.2010.514343",{"doi":952},{"id":24,"text":955,"url":24,"identifiers":956},"10.1001\u002Fjama.285.19.2453",{"doi":955},{"id":24,"text":958,"url":24,"identifiers":959},"10.1038\u002Fsj.ijo.0803160",{"doi":958},{"id":24,"text":961,"url":24,"identifiers":962},"10.1093\u002Fije\u002Fdyr020",{"doi":961},{"id":24,"text":964,"url":24,"identifiers":965},"10.1080\u002F17477160802453530",{"doi":964},{"id":24,"text":967,"url":24,"identifiers":968},"10.1111\u002Fj.2047-6310.2012.00059.x",{"doi":967},{"id":24,"text":970,"url":24,"identifiers":971},"10.1542\u002Fpeds.2009-2549",{"doi":970},{"id":24,"text":973,"url":24,"identifiers":974},"10.1542\u002Fpeds.2008-1315j",{"doi":973},{"id":24,"text":976,"url":24,"identifiers":977},"10.1111\u002Fj.2047-6310.2012.00071.x",{"doi":976},{"id":24,"text":979,"url":24,"identifiers":980},"Li R, 2012, Risk of bottle‐feeding for rapid weight gain during the first year of life, Arch Pediatr Adolesc Med, 155, 431",{},{"id":24,"text":982,"url":24,"identifiers":983},"10.1542\u002Fpeds.2004-0801",{"doi":982},{"id":24,"text":985,"url":24,"identifiers":986},"10.1111\u002Fj.1365-277X.2010.01145.x",{"doi":985},{"id":24,"text":988,"url":24,"identifiers":989},"10.1542\u002Fpeds.2005-1668",{"doi":988},{"id":24,"text":991,"url":24,"identifiers":992},"10.1542\u002Fpeds.2010-0740",{"doi":991},{"id":24,"text":994,"url":24,"identifiers":995},"10.1177\u002F000992280204100808",{"doi":994},{"id":24,"text":997,"url":24,"identifiers":998},"10.2105\u002FAJPH.2005.080812",{"doi":997},{"id":24,"text":1000,"url":24,"identifiers":1001},"10.1177\u002F1536867X0800800104",{"doi":1000},{"id":24,"text":1003,"url":24,"identifiers":1004},"Centers for Disease Control and Prevention.WHO growth charts. Boy's weight‐for‐age percentiles birth to 24 months; girl's weight‐for‐age percentiles birth to 24 months. [WWW document]. URLhttp:\u002F\u002Fwww.cdc\u002Fgov\u002Fgrowthcharts(accessed 3 June 2012).",{},{"id":24,"text":1006,"url":24,"identifiers":1007},"10.1136\u002Fbmj.38586.411273.E0",{"doi":1006},{"id":24,"text":1009,"url":24,"identifiers":1010},"WHO Child Growth Standards, 2006, Length\u002FHeight‐for‐Age, Weight‐for‐Age, Weight‐for‐Length, Weight‐for‐Height and Body Mass Index‐for‐Age: Methods and Development",{},{"id":24,"text":1012,"url":24,"identifiers":1013},"10.1136\u002Fbmj.320.7244.1240",{"doi":1012},{"id":24,"text":1015,"url":24,"identifiers":1016},"10.1007\u002Fs10802-008-9279-8",{"doi":1015},{"id":24,"text":1018,"url":24,"identifiers":1019},"Nord C, 2006, Early Childhood Longitudinal Study, Birth Cohort (ECLS‐B) User's Manual for the ECLS‐B Longitudinal 9‐Month–2‐Year Data File and Electronic Codebook (NCES 2006‐046)",{},{"id":24,"text":1021,"url":24,"identifiers":1022},"10.1542\u002Fpeds.2011-3552",{"doi":1021},{"id":24,"text":1024,"url":24,"identifiers":1025},"World Health Organization.The World Health Organization's infant feeding recommendation. [WWW document]. URLhttp:\u002F\u002Fwww.who.int\u002Fnutrition\u002Ftopics\u002Finfantfeeding_recommendation(accessed 11 November 2012).",{},{"id":24,"text":1027,"url":24,"identifiers":1028},"10.1016\u002Fj.eatbeh.2011.01.002",{"doi":1027},{"id":24,"text":1030,"url":24,"identifiers":1031},"10.1016\u002Fj.appet.2005.10.005",{"doi":1030},{"id":24,"text":1033,"url":24,"identifiers":1034},"Farrow CV, 2008, Controlling feeding practices: cause or consequence or early child weight?, Pediatrics, 121, e164, 10.1542\u002Fpeds.2006-3437",{"doi":1035},"10.1542\u002Fpeds.2006-3437",{"id":24,"text":1037,"url":24,"identifiers":1038},"10.1023\u002FB:EJEP.0000036890.72029.7c",{"doi":1037},{"id":24,"text":1040,"url":24,"identifiers":1041},"10.3109\u002F17477166.2011.613651",{"doi":1040},{"id":1043,"createTime":1044,"updateTime":1044,"relativeEntities":1045,"slug":1046,"properties":1047,"entityType":129,"verifyStatus":130,"verifyTime":1044,"verifyNote":132,"languages":1060,"translateLanguages":24,"viewCount":25,"primaryUrl":1061,"fullTextUrl":24,"authors":1062,"publicationType":250,"publisherRelationship":1190,"citationCount":1246,"citationInfo":1247,"publishDate":1250,"publishYear":1248,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":1251,"openAccess":24,"references":1252,"isForceReanalyzing":407},"4d14aae5-531c-4e59-8901-b2f3c0b329cb","2024-09-23T17:07:54.458+00:00",[],"Sex-puberty-and-ethnicity-have-a-strong-influence-on-growth-and-metabolic-comorbidities-in-children-and-adolescents-with-obesity-Report-on-1300-patients-the-Madrid-Cohort-",{"openalex":1048,"mag":1050,"abstract":1052,"title":1054,"pm":1056,"doi":1058},{"VOID":1049},"W2964961506",{"VOID":1051},"2964961506",{"EN":1053},"\u003Cjats:title>Summary\u003C\u002Fjats:title>\u003Cjats:sec>\u003Cjats:title>Background\u003C\u002Fjats:title>\u003Cjats:p>The capacity to correctly assess insulin resistance and its role in further obesity‐associated metabolic derangement in children is under debate, and its determinants remain largely unknown.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Objective\u003C\u002Fjats:title>\u003Cjats:p>We investigated the association of the insulin secretion profile with other metabolic derangements and anthropometric features in children and adolescents with obesity, exploring the role of ethnicity.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Patients and Methods\u003C\u002Fjats:title>\u003Cjats:p>Growth and metabolic features, including fasting insulin levels and insulin secretory profile in an oral glucose tolerance test (OGTT), were analyzed according to ethnicity in 1300 patients with obesity (75.8% Caucasians\u002F19.0% Latinos).\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Height and bone age were influenced by sex, ethnicity, and insulinemia. Latino patients had higher insulin (\u003Cjats:italic>P\u003C\u002Fjats:italic> < .001), but similar glycemia both prepubertally and postpubertally, compared with Caucasians. Type 2 diabetes was uncommon (0.1%). Impaired glucose tolerance was associated to higher age, BMI, uric acid, and triglyceride levels (all \u003Cjats:italic>P\u003C\u002Fjats:italic> < .05), as was fasting hyperinsulinism. Impaired fasting glucose or HbA1c 5.7% to 6.4% showed no association with further metabolic derangement. A delayed insulin peak in the OGTT was associated to more severe metabolic disturbances.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusions\u003C\u002Fjats:title>\u003Cjats:p>Obesity‐associated hyperglycemia is unusual in our environment whereas fasting and late postprandial hyperinsulinemia are highly prevalent, with this being influenced by race and closely related with lipid metabolism impairment.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>",{"EN":1055},"Sex, puberty, and ethnicity have a strong influence on growth and metabolic comorbidities in children and adolescents with obesity: Report on 1300 patients (the Madrid 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list-type=\"bullet\">\n\u003Cjats:title>What is already known about this subject\u003C\u002Fjats:title>\n\u003Cjats:list-item>\u003Cjats:p>Overweight and obesity can be linked to different parental socioeconomic factors already in very young children.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003Cjats:list-item>\u003Cjats:p>In Western developed countries, the association of childhood overweight and obesity and parental socioeconomic status shows a negative gradient.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003Cjats:list-item>\u003Cjats:p>Ambiguous results have been obtained regarding the association between socioeconomic factors and childhood overweight and obesity in different countries and over time.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:label\u002F>\u003Cjats:p>\u003Cjats:list list-type=\"bullet\">\n\u003Cjats:title>What this study adds\u003C\u002Fjats:title>\n\u003Cjats:list-item>\u003Cjats:p>European regions show heterogeneous associations between socioeconomic factors and overweight and obesity in a multi‐centre study with highly standardized study protoco.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003Cjats:list-item>\u003Cjats:p>The strength of association between SES and overweight and obesity varies across European regions.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003Cjats:list-item>\u003Cjats:p>In our study, the SES gradient is correlated with the regional mean income and the country‐specific Human development index indicating a strong influence not only of the family but also of region and country on the overweight and obesity prevalence.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Objective\u003C\u002Fjats:title>\u003Cjats:p>To assess the association between different macro‐ and micro‐level socioeconomic factors and childhood overweight.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Methods\u003C\u002Fjats:title>\u003Cjats:p>Data from the \u003Cjats:styled-content style=\"fixed-case\">IDEFICS\u003C\u002Fjats:styled-content> baseline survey is used to investigate the cross‐sectional association between socioeconomic factors, like socioeconomic status (\u003Cjats:styled-content style=\"fixed-case\">SES\u003C\u002Fjats:styled-content>), and the prevalence of childhood overweight. Differences and similarities regarding this relationship in eight European regions (located in \u003Cjats:styled-content style=\"fixed-case\">B\u003C\u002Fjats:styled-content>elgium, \u003Cjats:styled-content style=\"fixed-case\">C\u003C\u002Fjats:styled-content>yprus, \u003Cjats:styled-content style=\"fixed-case\">E\u003C\u002Fjats:styled-content>stonia, \u003Cjats:styled-content style=\"fixed-case\">G\u003C\u002Fjats:styled-content>ermany, \u003Cjats:styled-content style=\"fixed-case\">H\u003C\u002Fjats:styled-content>ungary, \u003Cjats:styled-content style=\"fixed-case\">I\u003C\u002Fjats:styled-content>taly, \u003Cjats:styled-content style=\"fixed-case\">S\u003C\u002Fjats:styled-content>pain and \u003Cjats:styled-content style=\"fixed-case\">S\u003C\u002Fjats:styled-content>weden) are explored. 11 994 children (50.9% boys, 49.1% girls) and their parents were included in the analyses.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>In five of the eight investigated regions (in \u003Cjats:styled-content style=\"fixed-case\">B\u003C\u002Fjats:styled-content>elgium, \u003Cjats:styled-content style=\"fixed-case\">E\u003C\u002Fjats:styled-content>stonia, \u003Cjats:styled-content style=\"fixed-case\">G\u003C\u002Fjats:styled-content>ermany, \u003Cjats:styled-content style=\"fixed-case\">S\u003C\u002Fjats:styled-content>pain and \u003Cjats:styled-content style=\"fixed-case\">S\u003C\u002Fjats:styled-content>weden), the prevalence of childhood overweight followed an inverse \u003Cjats:styled-content style=\"fixed-case\">SES\u003C\u002Fjats:styled-content> gradient. In the other three regions (in \u003Cjats:styled-content style=\"fixed-case\">C\u003C\u002Fjats:styled-content>yprus, \u003Cjats:styled-content style=\"fixed-case\">H\u003C\u002Fjats:styled-content>ungary and \u003Cjats:styled-content style=\"fixed-case\">I\u003C\u002Fjats:styled-content>taly), no association between \u003Cjats:styled-content style=\"fixed-case\">SES\u003C\u002Fjats:styled-content> and childhood overweight was found. The \u003Cjats:styled-content style=\"fixed-case\">SES\u003C\u002Fjats:styled-content>‐overweight association in a region was best explained by the country‐specific human development index and the centre‐specific mean income. For the investigated association between other socioeconomic factors and overweight, no clear pattern could be found in the different regions.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusion\u003C\u002Fjats:title>\u003Cjats:p>The association between socioeconomic factors and childhood overweight was shown to be heterogeneous across different European regions. 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Hence the present results provide a more detailed insight into development patterns of obesity.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003Cjats:list-item>\u003Cjats:p>The socio‐demographic predictors of the trajectories offer potential avenues for future obesity interventions.\u003C\u002Fjats:p>\u003C\u002Fjats:list-item>\n\u003C\u002Fjats:list>\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Background\u003C\u002Fjats:title>\u003Cjats:p>A limited number of studies have demonstrated that there may be distinct developmental trajectories of obesity during childhood.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Objective\u003C\u002Fjats:title>\u003Cjats:p>To identify distinct trajectories of body mass index (\u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content>) in a large sample of Australian children.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Methods\u003C\u002Fjats:title>\u003Cjats:p>Participants included 4601 children aged 4–5 years at baseline, who were followed up at ages 6–7 years, 8–9 years and 10–11 years. Height and weight were measured at each of these time points, and used to calculate \u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content>. Growth Mixture Modelling was used to identify the presence of distinct \u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content> trajectories.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Four distinct trajectories were identified (i) High Risk Overweight; (ii) Early Onset Overweight; (iii) Later Onset Overweight and (iv) Healthy Weight. 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However, there are scant and controversial data in this field.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Objective\u003C\u002Fjats:title>\u003Cjats:p>To assess whether puberty and physical growth vary in obese when compared to normal‐weight children.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Methods\u003C\u002Fjats:title>\u003Cjats:p>One hundred obese pre‐pubertal children (44 boys; mean age (±\u003Cjats:styled-content style=\"fixed-case\">SD\u003C\u002Fjats:styled-content>): 9.01 ± 0.62 years; 56 girls; 8.70 ± 0.57 years) were compared to 55 normal‐weight controls (27 boys; 9.17 ± 0.26 years; 28 girls; 8.71 ± 0.62 years). All study participants were followed prospectively with 6‐monthly follow‐up visits. At each study visit, height, weight, body mass index (\u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content>) and pubertal stage were assessed.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Obese children entered puberty and achieved later stages of puberty earlier than controls (onset of puberty: boys: 11.66 ± 1.00 vs. 12.12 ± 0.91 years, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> = 0.049; girls: 9.90 ± 0.78 vs. 10.32 ± 1.70, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> = 0.016; late puberty: boys: 13.33 ± 0.71 vs. 14.47 ± 1.00 years, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> < 0.001; girls: 11.54 ± 0.99 vs. 12.40 ± 1.02, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> = 0.001). Pre‐pubertal \u003Cjats:styled-content style=\"fixed-case\">BMI\u003C\u002Fjats:styled-content> standard deviation score (\u003Cjats:styled-content style=\"fixed-case\">SDS\u003C\u002Fjats:styled-content>) was inversely associated with both age at the onset of puberty (β = −0.506, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> < 0.001) and age at late puberty (β = −0.514, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> < 0.001). Obese children also showed an earlier age at peak height velocity (\u003Cjats:styled-content style=\"fixed-case\">PHV\u003C\u002Fjats:styled-content>) (boys: 12.62 ± 0.82 vs. 13.19 ± 0.96 years, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> = 0.01; girls: 11.37 ± 0.89 vs. 12.77 ± 0.76, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> < 0.001) and a lower \u003Cjats:styled-content style=\"fixed-case\">PHV\u003C\u002Fjats:styled-content> (boys: 7.74 ± 1.49 vs. 9.28 ± 1.64 cm year\u003Cjats:sup>−1\u003C\u002Fjats:sup>, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> < 0.001; girls: 7.60 ± 1.64 vs. 8.29 ± 1.03, \u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> = 0.03). Height \u003Cjats:styled-content style=\"fixed-case\">SDS\u003C\u002Fjats:styled-content> progressively declined over the study period in the obese group (\u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> for trend <0.001), whereas there were no significant changes in the control group (\u003Cjats:italic>\u003Cjats:styled-content style=\"fixed-case\">P\u003C\u002Fjats:styled-content>\u003C\u002Fjats:italic> for trend = 0.5).\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Conclusions\u003C\u002Fjats:title>\u003Cjats:p>Obese boys and girls presented an earlier onset of puberty and completion of puberty and an impaired height gain during puberty.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>",{"EN":2101},"Timing of puberty and physical growth in obese children: a longitudinal study in boys and girls",{"VOID":2103},"23713062",{"VOID":1266},[134],"https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fj.2047-6310.2013.00176.x",[2108,2135,2158,2181,2202,2225],{"id":2109,"sortIndex":25,"researcher":24,"roles":2110,"affiliations":2111,"properties":2128,"displayName":2132,"givenName":24,"familyName":24},"ac7a26ab-6d2d-4e37-bdc1-f2a8f4b20f3f",[],[2112,2120],{"id":2113,"sortIndex":25,"affiliation":2114,"properties":24},"56485ae9-b9bc-4dd2-b0f4-a01bd06a1362",{"id":2113,"createTime":24,"updateTime":24,"relativeEntities":2115,"slug":24,"properties":2116,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":2119,"statistic":24},[],{"title":2117},{"EN":2118},"Center of Excellence on Aging, “G. 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study aimed to project the societal cost and benefit of an expansion of a water access intervention that promotes lunchtime plain water consumption by placing water dispensers in New York school cafeterias to all schools nationwide.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Methods\u003C\u002Fjats:title>\u003Cjats:p>A decision model was constructed to simulate two events under Markov chain processes – placing water dispensers at lunchtimes in school cafeterias nationwide vs. no action. The incremental cost pertained to water dispenser purchase and maintenance, whereas the incremental benefit was resulted from cases of childhood overweight\u002Fobesity prevented and corresponding lifetime direct (medical) and indirect costs saved.\u003C\u002Fjats:p>\u003C\u002Fjats:sec>\u003Cjats:sec>\u003Cjats:title>Results\u003C\u002Fjats:title>\u003Cjats:p>Based on the decision model, the estimated incremental cost of the school‐based water access intervention is $18 per student, and the corresponding incremental benefit is $192, resulting in a net benefit of $174 per student. Subgroup analysis estimates the net benefit per student to be $199 and $149 among boys and girls, respectively. Nationwide adoption of the intervention would prevent 0.57 million cases of childhood overweight, resulting in a lifetime cost saving totalling $13.1 billion. 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