2016
DOI: 10.1136/bmjopen-2016-012919
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Co-occurrence and clustering of health conditions at age 11: cross-sectional findings from the Millennium Cohort Study

Abstract: ObjectivesTo identify patterns of co-occurrence and clustering of 6 common adverse health conditions in 11-year-old children and explore differences by sociodemographic factors.DesignNationally representative prospective cohort study.SettingChildren born in the UK between 2000 and 2002.Participants11 399 11-year-old singleton children for whom data on all 6 health conditions and sociodemographic information were available (complete cases).Main outcome measuresPrevalence, co-occurrence and clustering of 6 commo… Show more

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Cited by 6 publications
(6 citation statements)
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“…The studies are based on doctor-diagnosed AD, 37,[43][44][45][46][47] and few studies adjust for possible confounders. 43,48,49 Older studies have not been able to find this association. However, they often use ISAAC criteria to diagnose AD, 33,36,[50][51][52][53][54][55][56] and the most commonly used questions are "Have you ever had an itchy rash which was coming and going for at least 6 months?…”
Section: Discussionmentioning
confidence: 94%
See 1 more Smart Citation
“…The studies are based on doctor-diagnosed AD, 37,[43][44][45][46][47] and few studies adjust for possible confounders. 43,48,49 Older studies have not been able to find this association. However, they often use ISAAC criteria to diagnose AD, 33,36,[50][51][52][53][54][55][56] and the most commonly used questions are "Have you ever had an itchy rash which was coming and going for at least 6 months?…”
Section: Discussionmentioning
confidence: 94%
“…In general, recent studies have found that prevalence of AD is positively associated with obesity, overweight or high BMI. The studies are based on doctor‐diagnosed AD, and few studies adjust for possible confounders . Older studies have not been able to find this association.…”
Section: Discussionmentioning
confidence: 99%
“…Though seldom-tested, longitudinal invariance is critical to many of the inferences drawn from developmental data, with metric invariance required to compare latent variances and covariances over development, scalar invariance required to compare latent means over development, for example, in the analysis of developmental trajectories, and residual invariance required to compare levels over time/group based on observed scores ( Edwards & Wirth, 2012 ). Given that the SDQ data is commonly analyzed within MCS (e.g., Ahn et al, 2018 ; Carson et al, 2013 ; Heikkilä et al, 2011 ; Hesketh et al, 2016 ; Hope et al, 2014 ; Noonan et al, 2018 ; Patalay & Fitzsimons, 2016 ) and the SDQ is among the most popular omnibus measures of psychopathology in general, our study adds important evidence on the appropriateness of the SDQ as a measure of mental health across childhood and adolescence.…”
Section: Discussionmentioning
confidence: 99%
“…Our study is based on limited number of chronic diseases with a prevalence of ≥ 3% recorded by the KNHANES. Previous studies that used latent class analysis also applied a prevalence cut-off for inclusion of 2–10% [17, 22, 30, 65, 66]. Other studies that applied different statistical techniques also established a minimal prevalence for the inclusion [29].…”
Section: Discussionmentioning
confidence: 99%