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  1. Higgins S, Stoner L, Lubransky A, Howe AS, Wong JE, Black K, et al.
    Sleep Med, 2020 11;75:163-170.
    PMID: 32858356 DOI: 10.1016/j.sleep.2020.07.030
    INTRODUCTION: Cardiorespiratory fitness (CRF) is a vital sign that can improve risk classification for adverse health outcomes. While lifestyle-related factors are associated with CRF, few have examined the influence of sleep characteristics, especially in youths. Social jetlag, a mismatch between one's biological clock and sleep schedule, is prevalent in adolescents and associated with increased adiposity, though its relationship with CRF is unclear.

    OBJECTIVE: To quantify the relationship between social jetlag and CRF, independent of other sleep characteristics.

    METHODS: This cross-sectional sample includes 276 New Zealand adolescents (14-18 years, 52.5% female). CRF (VO2max) was estimated from a 20-m multi-stage shuttle run. Average sleep duration, sleep disturbances, social jetlag, physical activity, and the number of bedroom screens were estimated from validated self-report surveys. Social jetlag is the difference in hours between the midpoint of sleep during weekdays (school) and weekend days (free). Combined and sex-stratified linear regression assessed the association between sleep outcomes and CRF, controlling for relevant covariates.

    RESULTS: Males slept 17.6 min less, had less sleep disturbances, and a 25.1-min greater social jetlag than their female peers (all p 

  2. Higgins S, Stoner L, Black K, Wong JE, Quigg R, Meredith-Jones K, et al.
    Sleep Med, 2021 08;84:294-302.
    PMID: 34217919 DOI: 10.1016/j.sleep.2021.06.014
    INTRODUCTION: Social jetlag has been reported to predict obesity-related indices, independent of sleep duration, with associations in female adolescents but not males. However, such sex-specific relationships have not been investigated in pre-adolescents.

    OBJECTIVES: To examine: (i) the relationships between sleep characteristics, including social jetlag, and obesity-related outcomes during childhood, and (ii) whether these relationships are moderated by sex.

    METHODS: This cross-sectional study included 381 children aged 9-11 years (49.6% female). Average sleep duration, social jetlag, and physical activity were assessed via wrist-worn accelerometry. Sleep disturbances were quantified from the Children's Sleep Habits Questionnaire. Obesity-related outcomes included age-specific body mass index Z-scores (zBMI) and waist-to-height ratio. Additionally % fat, total fat mass, and fat mass index were assessed via bioelectrical impedance analysis. Linear mixed models that nested children within schools were used to identify relationships among sleep characteristics and obesity-related outcomes.

    RESULTS: Positive associations between social jetlag with zBMI, % fat, and fat mass index were seen in univariable and unadjusted multivariable analyses. Following adjustments for known confounders, social jetlag remained significantly associated with zBMI (β = 0.12, p = 0.013). Simple slopes suggested a positive association in girls (β = 0.19, p = 0.006) but not in boys (β = 0.03, p = 0.703).

    CONCLUSIONS: Obesity prevention efforts, particularly in girls, may benefit from targeted approaches to improving the consistency of sleep timing in youth.

  3. Davison B, Saeedi P, Black K, Harrex H, Haszard J, Meredith-Jones K, et al.
    Nutrients, 2017 May 11;9(5).
    PMID: 28492490 DOI: 10.3390/nu9050483
    Previous research investigating the relationship between parents' and children's diets has focused on single foods or nutrients, and not on global diet, which may be more important for good health. The aim of the study was to investigate the relationship between parental diet quality and child dietary patterns. A cross-sectional survey was conducted in 17 primary schools in Dunedin, New Zealand. Information on food consumption and related factors in children and their primary caregiver/parent were collected. Principal component analysis (PCA) was used to investigate dietary patterns in children and diet quality index (DQI) scores were calculated in parents. Relationships between parental DQI and child dietary patterns were examined in 401 child-parent pairs using mixed regression models. PCA generated two patterns; 'Fruit and Vegetables' and 'Snacks'. A one unit higher parental DQI score was associated with a 0.03SD (CI: 0.02, 0.04) lower child 'Snacks' score. There was no significant relationship between 'Fruit and Vegetables' score and parental diet quality. Higher parental diet quality was associated with a lower dietary pattern score in children that was characterised by a lower consumption frequency of confectionery, chocolate, cakes, biscuits and savoury snacks. These results highlight the importance of parental modelling, in terms of their dietary choices, on the diet of children.
  4. Saeedi P, Black KE, Haszard JJ, Skeaff S, Stoner L, Davidson B, et al.
    Nutrients, 2018 Jul 10;10(7).
    PMID: 29996543 DOI: 10.3390/nu10070887
    Research shows that cardiorespiratory (CRF) and muscular fitness in childhood are associated with a healthier cardiovascular profile in adulthood. Identifying factors associated with measures of fitness in childhood could allow for strategies to optimize cardiovascular health throughout the lifecourse. The aim of this study was to examine the association between dietary patterns and both CRF and muscular fitness in 9⁻11-year-olds. In this study of 398 children, CRF and muscular fitness were assessed using a 20-m shuttle run test and digital hand dynamometer, respectively. Dietary patterns were derived using principal component analysis. Mixed effects linear regression models were used to assess associations between dietary patterns and CRF and muscular fitness. Most children had healthy CRF (99%, FITNESSGRAM) and mean ± SD muscular fitness was 15.2 ± 3.3 kg. Two dietary patterns were identified; “Snacks” and “Fruit and Vegetables”. There were no significant associations between either of the dietary patterns and CRF. Statistically significant but not clinically meaningful associations were seen between dietary patterns and muscular fitness. In an almost exclusively fit cohort, food choice is not meaningfully related to measures of fitness. Further research to investigate diet-fitness relationships in children with lower fitness levels can identify key populations for potential investments in health-promoting behaviors.
  5. Harrex HAL, Skeaff SA, Black KE, Davison BK, Haszard JJ, Meredith-Jones K, et al.
    J Sleep Res, 2018 08;27(4):e12634.
    PMID: 29160021 DOI: 10.1111/jsr.12634
    It is well documented that short sleep duration is associated with excess body weight and poor food intake in children. It has been suggested that sleep timing behaviour may also be an important predictor of weight and other related behaviours, independent of sleep duration; however, there is a lack of research investigating these relationships. The present study investigated sleep timing in association with diet and physical activity levels in 439 children aged 9-11 years old from New Zealand. Sleep and physical activity data were collected using accelerometry, and food choice using a short food-frequency questionnaire. Participants were classified into one of four sleep timing behaviour categories using the median split for sleep-onset and -offset times. Differences between sleep timing groups for weekly consumption frequency of selected food groups, dietary pattern scores and minutes of moderate-to-vigorous physical activity were examined. Children in the late sleep/late wake category had a lower 'Fruit & Vegetables' pattern score [mean difference (95% CI): -0.3 (-0.5, -0.1)], a lower consumption frequency of fruit and vegetables [mean weekly difference (95% CI): -2.9 (-4.9, -0.9)] and a higher consumption frequency of sweetened beverages [mean weekly difference (95% CI): 1.8 (0.2, 3.3)] compared with those in the early sleep/early wake category. Additionally, children in the late sleep/late wake category accumulated fewer minutes of moderate-to-vigorous physical activity per day compared with those in the early sleep/early wake category [mean difference (95% CI): -9.4 (-15.3, -3.5)]. These findings indicate that sleep timing, even after controlling for sleep duration, was associated with both food consumption and physical activity.
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