2014
DOI: 10.1111/cch.12129
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Relationship among attention‐deficit hyperactivity disorder, dietary behaviours and obesity

Abstract: Our analysis suggested that ADHD was a risk factor for obesity through dietary behavioural change and socio-economic status.

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Cited by 39 publications
(30 citation statements)
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“…Exploratory analysis based on ADHD subtype and medication status did not show any significant association between FTO SNP rs8050136 and ADHD.Choudhry et al (2013b) [31]CanadaCross-sectionalTotal = 284 ADHD children9.15 (1.86), 6–12Obese ADHD children were significantly less likely to be previously on medication (20.3%) compared to subjects in the overweight (25.0%) and normal weight (36.1%) groups ( p  = 0.04).There were no significant differences between normal overweight and obese subjects in their neurocognitive, emotional, and motor profile.Cook et al (2015) [12]USACross-sectionalTotal sample = 45,897ADHD = 50610–17After controlling for demographic variables, participants with ADHD only were 57% less likely to meet recommended levels of physical activity than controls but not significantly more likely to exceed recommended level of sedentarial behavior.Docet et al (2012) [32]SpainCase-controlTotal = 51ADHD = 45Non-ADHD = 6Total = 179ADHD = 52Non-ADHD = 12742.3 (15.5), 18–7650.9 (2.4 years), 19–7988.2% of obese patients with symptoms of ADHD above the threshold of the ASRS-V1.1 scale vs. 70.9% of those without significant symptoms with ADHD presented with abnormal eating behaviors (including eating between-meal snacks and binge eating).Ebenegger et al (2012) [33]SwitzerlandCross-sectionalTotal = 4504–6Scores of hyperactivity and less inattention were significantly associated with a higher level of physical activity ( p  < 0.01) and more television viewing ( p  < 0.04).Graziano et al (2012) [34]USACross-sectionalTotal = 80 ADHD4.5–18Children with ADHD who performed poorly on the neuropsychological battery were more likely to be classified as overweight/obese compared with children with ADHD who performed better on the neuropsychological battery (2.31 (1.01–5.26), p  < 0.05).Participants in the stimulant group had significantly lower BMI z-scores than children in the nonstimulant.Khalife et al (2014) [35•]FinlandLongitudinalTotal (at age 8) = 8106Significant association between probable ADHD at 8 years and obesity at 16 years (OR ¼ 2.01, 95% CI ¼ 1.37–3.00) but nonsignificance in the opposite direction, that is, from obesity at 8 years to probable ADHD at 16 years (OR 0.90, 95% CI 0.69–1.18). There were significant associations between probable ADHD at 8 years and physical inactivity at 16 years (OR 1.30, 95% CI 1.01–1.67), and reduced physically active play at 8 years and inattention at 16 years (OR 1.53, 95% CI 1.15–2.05).The adjusted analyses revealed similar results.Kim et al (2014) [36]South KoreaCross-sectionalTotal = 12,350 childrenNon-ADHD = 11,418With above threshold symptoms ADHD = 9329.4 years (1.7), 5–13 yearsThe association between ADHD symptoms and BMI was ...…”
Section: Resultssupporting
confidence: 54%
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“…Exploratory analysis based on ADHD subtype and medication status did not show any significant association between FTO SNP rs8050136 and ADHD.Choudhry et al (2013b) [31]CanadaCross-sectionalTotal = 284 ADHD children9.15 (1.86), 6–12Obese ADHD children were significantly less likely to be previously on medication (20.3%) compared to subjects in the overweight (25.0%) and normal weight (36.1%) groups ( p  = 0.04).There were no significant differences between normal overweight and obese subjects in their neurocognitive, emotional, and motor profile.Cook et al (2015) [12]USACross-sectionalTotal sample = 45,897ADHD = 50610–17After controlling for demographic variables, participants with ADHD only were 57% less likely to meet recommended levels of physical activity than controls but not significantly more likely to exceed recommended level of sedentarial behavior.Docet et al (2012) [32]SpainCase-controlTotal = 51ADHD = 45Non-ADHD = 6Total = 179ADHD = 52Non-ADHD = 12742.3 (15.5), 18–7650.9 (2.4 years), 19–7988.2% of obese patients with symptoms of ADHD above the threshold of the ASRS-V1.1 scale vs. 70.9% of those without significant symptoms with ADHD presented with abnormal eating behaviors (including eating between-meal snacks and binge eating).Ebenegger et al (2012) [33]SwitzerlandCross-sectionalTotal = 4504–6Scores of hyperactivity and less inattention were significantly associated with a higher level of physical activity ( p  < 0.01) and more television viewing ( p  < 0.04).Graziano et al (2012) [34]USACross-sectionalTotal = 80 ADHD4.5–18Children with ADHD who performed poorly on the neuropsychological battery were more likely to be classified as overweight/obese compared with children with ADHD who performed better on the neuropsychological battery (2.31 (1.01–5.26), p  < 0.05).Participants in the stimulant group had significantly lower BMI z-scores than children in the nonstimulant.Khalife et al (2014) [35•]FinlandLongitudinalTotal (at age 8) = 8106Significant association between probable ADHD at 8 years and obesity at 16 years (OR ¼ 2.01, 95% CI ¼ 1.37–3.00) but nonsignificance in the opposite direction, that is, from obesity at 8 years to probable ADHD at 16 years (OR 0.90, 95% CI 0.69–1.18). There were significant associations between probable ADHD at 8 years and physical inactivity at 16 years (OR 1.30, 95% CI 1.01–1.67), and reduced physically active play at 8 years and inattention at 16 years (OR 1.53, 95% CI 1.15–2.05).The adjusted analyses revealed similar results.Kim et al (2014) [36]South KoreaCross-sectionalTotal = 12,350 childrenNon-ADHD = 11,418With above threshold symptoms ADHD = 9329.4 years (1.7), 5–13 yearsThe association between ADHD symptoms and BMI was ...…”
Section: Resultssupporting
confidence: 54%
“…In fact, we located 28 studies [12, 1922, 25, 2946, 4850, 58] (Table 3). Several of these studies [32, 36, 42–44, 46] provide support to the notion that abnormal eating patterns may contribute to the increased risk of obesity in individuals with ADHD, although the cross-sectional nature of the majority of the studies cannot prove causality. Another series of studies has also pointed to a possible role of decreased physical activity (less involvement in sport activities) or increased hours/day spent watching TV, in individuals with ADHD compared to controls, as a possible mechanism favoring abnormal weigh gain associated with ADHD [12, 33, 35•, 39, 40, 58].…”
Section: Resultsmentioning
confidence: 99%
“…Animal studies have found a direct correlation between prenatal exposure to industrial chemicals such as phthalates and the development of neurodevelopmental disorders as ADHD and autism (Masuo et al, 2004). A Korean study looking at the amounts of phthalate metabolites in the urine of school aged children found a significant positive correlation between higher concentrations of these chemicals and ADHD symptoms, thus confirming earlier animal studies in human samples (Kim et al, 2014). Similarly, in a study focusing on children diagnosed with ADHD, higher levels of phthalates were found in the urine of ADHD Combined and ADHD Hyperactive Impulsive children compared to normally developing children.…”
Section: Environmental Factorssupporting
confidence: 80%
“…The pooled effect across studies shown in the last row of the table is based on a random effects model. Nation = research location: USA=United States, QAT=Qatar, NRL=Netherlands, FRA=France, CAN=Canada, GER=Germany, FIN=Finland, ISR=Israel, SWI=Switzerland, TUR=Turkey, POL=Poland, KOR=Korea, UK=United Kingdom, CHI=China; com= community, clin=clinical, pop=population, LGT=longitudinal, CRX=cross sectional, “Ages” represents age range within study and for longitudinal designs, “Ages” represents age at entry and last analyses. * Nigg studies (#31 and #32) refer to new data presented herein; OHSU = Oregon Health & Science University; NSCH = National Survey of Children’s Health (continued on next page) @ Studies are listed here to correspond to first author names and year: (Anderson, Cohen, Naumova, & Must, 2006); (Bener & Kamal, 2014) ; (Biederman, Spencer, Monuteaux, & Faraone, 2010) ; (Bijlenga et al, 2013) ; (Byrd, Curtin, & Anderson, 2013) ; (Caci, Morin, & Tran, 2014) ; (Chen et al, 2010) ; (Cook, Li, & Heinrich, 2014) ; (Cortese, Ramos Olazagasti, et al, 2013) ; (Cortese, Faraone, et al, 2013) ; (Davis et al, 2006) ; (de Zwaan et al, 2011) ; (Duarte et al, 2010) ; (Dubnov-Raz, Perry, & Berger, 2011) ; (Ebenegger et al, 2012) ; (Erhart et al, 2012) ; (Fuemmeler et al, 2011) ; (Gungor et al, 2013) ; (Halfon et al, 2013) ; (Hanc, Cieslik, Wolanczyk, & Gajdzik, 2012) ; (Hanc et al, 2015) ; (Khalife et al, 2014) ; (Kim et al, 2014) ; (Kim et al, 2011) ; (Korczak et al, 2013) ; (Koshy, Delpisheh, & Brabin, 2011) ; (Lam & Yang, 2007) ; (Lingineni et al, 2012) ; (McClure, Eddy, Kjellstrand, Snodgrass, & Martinez, 2012) ; (Mustillo et al, 2003) ; (Pagoto et al, 2009) ; (Pauli-Pott, Neidhard, Heinzel-Gutenbrunner, & Becker, 2014) ; (Phillips et al, 2014) ; (Ratcliff, 2010) ; (Rojo, Ruiz, Dominguez, Calaf, & Livianos, 2006) ; (Schwartz et al, 2014) ; (Strimas et al, 2008) ; (A. W. van Egmond-Fröhlich et al, 2012) ; (Waring & Lapane, 2008) ; (White, Nicholls, Christie, Cole, & Viner, 2012) ; (Yang, Mao, Zhang, Li, & Zhao, 2013)…”
Section: Figurementioning
confidence: 99%