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1.
Brain Dev ; 36(1): 35-44, 2014 Jan.
Article in English | MEDLINE | ID: mdl-23305729

ABSTRACT

OBJECTIVE: The aim of the present school-based questionnaire was to analyze the sleep problems of children with developmental disorders, such as pervasive developmental disorder and attention deficit hyperactivity disorder. METHODS: The sleep problems of 43 children with developmental disorders were compared with those of 372 healthy children (control group). All children attended one public elementary school in Kurume, Japan; thus, the study avoided the potential bias associated with hospital-based surveys (i.e. a high prevalence of sleep disturbance) and provided a more complete picture of the children's academic performance and family situation compared with a control group under identical conditions. Children's sleep problems were measured with the Japanese version of the Children's Sleep Habits Questionnaire (CSHQ). RESULTS: Children with developmental disorders had significantly higher total CSHQ scores, as well as mean scores on the parasomnias and sleep breathing subscales, than children in the control group. The total CSHQ score, bedtime resistance, sleep onset delay, and daytime sleepiness worsened with increasing age in children with developmental disorders; in contrast, these parameters were unchanged or became better with age in the control group. In children with developmental disorders, there was a significant association between a higher total CSHQ score and lower academic performance, but no such association was found in the control group. For both groups, children's sleep problems affected their parents' quality of sleep. There were no significant differences in physical, lifestyle, and sleep environmental factors, or in sleep/wake patterns, between the two groups. CONCLUSIONS: Children with developmental disorders have poor sleep quality, which may affect academic performance. It is important for physicians to be aware of age-related differences in sleep problems in children with developmental disorders. Further studies are needed to identify the association between sleep quality and school behavioral performance.


Subject(s)
Attention Deficit Disorder with Hyperactivity/complications , Developmental Disabilities/complications , Sleep Wake Disorders/epidemiology , Sleep Wake Disorders/etiology , Age Factors , Child , Child, Preschool , Developmental Disabilities/classification , Educational Status , Female , Health Surveys , Humans , Japan/epidemiology , Linear Models , Male , Parents/psychology , Schools , Sleep Stages , Surveys and Questionnaires
2.
Hepatol Res ; 42(10): 982-9, 2012 Oct.
Article in English | MEDLINE | ID: mdl-22536921

ABSTRACT

AIM: Dietary habits are involved in the development of chronic inflammation; however, the impact of dietary profiles of hepatitis C virus carriers with persistently normal alanine transaminase levels (HCV-PNALT) remains unclear. The decision-tree algorithm is a data-mining statistical technique, which uncovers meaningful profiles of factors from a data collection. We aimed to investigate dietary profiles associated with HCV-PNALT using a decision-tree algorithm. METHODS: Twenty-seven HCV-PNALT and 41 patients with chronic hepatitis C were enrolled in this study. Dietary habit was assessed using a validated semiquantitative food frequency questionnaire. A decision-tree algorithm was created by dietary variables, and was evaluated by area under the receiver operating characteristic curve analysis (AUROC). RESULTS: In multivariate analysis, fish to meat ratio, dairy product and cooking oils were identified as independent variables associated with HCV-PNALT. The decision-tree algorithm was created with two variables: a fish to meat ratio and cooking oils/ideal bodyweight. When subjects showed a fish to meat ratio of 1.24 or more, 68.8% of the subjects were HCV-PNALT. On the other hand, 11.5% of the subjects were HCV-PNALT when subjects showed a fish to meat ratio of less than 1.24 and cooking oil/ideal bodyweight of less than 0.23 g/kg. The difference in the proportion of HCV-PNALT between these groups are significant (odds ratio 16.87, 95% CI 3.40-83.67, P = 0.0005). Fivefold cross-validation of the decision-tree algorithm showed an AUROC of 0.6947 (95% CI 0.5656-0.8238, P = 0.0067). CONCLUSION: The decision-tree algorithm disclosed that fish to meat ratio and cooking oil/ideal bodyweight were associated with HCV-PNALT.

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