The Association between Parent Diet Quality and Child Dietary Patterns in Nine- to Eleven-Year-Old Children from Dunedin, New Zealand

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

The Association between Sleep Timing with Diet and Physical Activity Levels in School-Aged Children

Background: Several studies have reported associations between shortened sleep durations and obesity in children, through mechanisms such as increased food intake and decreased physical activity levels. Recently, research has begun to look at sleep timing (the combination of sleep onset and sleep offset) as an important predictor of behaviour, independent of total sleep duration. However, no research has used objective assessment methods to examine sleep timing behaviour in relation to both diet and activity in school-aged children. Objectives: The primary objectives were to examine the association between sleep timing with diet and physical activity levels in school-aged children from New Zealand. Design: The Physical activity, Exercise, Diet, And Lifestyle Study was a cross-sectional observational study of children aged 8-11 years old and their parents, conducted in the Otago region of New Zealand between May and October 2015. Methods: A total of 468 child participants from primary schools in Dunedin, New Zealand took part in the study. Children were asked to complete lifestyle questionnaires and have anthropometric measurements taken during one school day, and to wear an accelerometer (Actigraph GT3X+) on their non-dominant wrist for eight consecutive days and seven consecutive nights. The participant’s self-reported frequency of breakfast, fruit and vegetables, and ‘extra’ foods consumption was used to assess diet. Accelerometer-measured sleep and moderate and vigorous physical activity intensity was used to assess sleep behaviour and activity patterns, respectively, while body composition was assessed using the participant’s calculated body mass index. Participants were classified into one of four sleep timing behaviour groups, using the median split for sleep onset (9:37pm) and sleep offset (6:50am) times, rounded to the nearest quarter hour: early sleep-early wake; early sleep-late wake; late sleep-early wake; late sleep-late wake. Late to sleep was defined as after 9:30pm, otherwise classified as early to sleep. Late to wake was defined as after 6:45am, otherwise classified as early to wake. Multivariate mixed regression analysis was used to examine associations, accounting for schools as clustering units. Analyses were undertaken using data from 370 participants who had a complete dataset for the outcome variables and covariates relevant to this thesis available prior to the 7th of November 2015. Results: The study population had a mean age of 10.2 (SD 0.6) years, were predominantly of ‘New Zealand European and Other’ ethnicity (89%), had a higher socio-economic status (49%), indicated by a New Zealand Deprivation Index 2013 score between one and three, and had a ‘normal’ body mass index (89%). Almost all participants (98%) provided at least five valid days of accelerometer data and 80% provided six valid days. Across the whole week, participants slept for an average of 8.6 (SD 0.7) hours per night, went to sleep at a mean time of 9:37pm (SD 0:36) and woke up at a mean time of 6:50am (SD 0:30). Girls slept longer and woke up later than boys, particularly on weekend days, where girls accumulated on average 15 minutes more sleep (8.7 vs 8.4 hours, p=0.011) and woke up 15.4 minutes later (7.04am vs 6.47am, p=0.001). In adjusted multivariate regression models, with the sleep timing behaviour group as the independent variable, no association was found with the consumption frequency of breakfast, fruit and vegetables, or ‘extra’ foods. Participants in the early sleep-early wake sleep timing behaviour group accumulated on average 13 more minutes of moderate and vigorous physical activity per day than those in the late sleep-late wake group (83 mins vs 70 mins, p=0.004), independent of total sleep duration. Participants in the group with sleep timing consistent with the shortest sleep duration (late sleep-early wake) had a significantly higher body mass index z-score than those in the group with sleep timing consistent with the longest sleep duration (early sleep-late wake), independent of total sleep duration (0.40 vs -0.04, p=0.017). Conclusion: This study concludes that sleep timing, independent of total sleep duration, was associated with physical activity and body composition, but not diet in this group of school-aged children. These findings suggest that sleep timing is an important factor to consider in addition to total sleep duration for good health. Further investigation of the causal mechanisms underlying the relationship that sleep timing has with health outcomes is necessary to provide direction for the development of effective strategies for both the treatment and prevention of childhood obesity. Key Words: sleep, diet, physical activity, children, timing, obesit

The Association between Sleep Timing with Diet and Physical Activity Levels in School-Aged Children

Background: Several studies have reported associations between shortened sleep durations and obesity in children, through mechanisms such as increased food intake and decreased physical activity levels. Recently, research has begun to look at sleep timing (the combination of sleep onset and sleep offset) as an important predictor of behaviour, independent of total sleep duration. However, no research has used objective assessment methods to examine sleep timing behaviour in relation to both diet and activity in school-aged children. Objectives: The primary objectives were to examine the association between sleep timing with diet and physical activity levels in school-aged children from New Zealand. Design: The Physical activity, Exercise, Diet, And Lifestyle Study was a cross-sectional observational study of children aged 8-11 years old and their parents, conducted in the Otago region of New Zealand between May and October 2015. Methods: A total of 468 child participants from primary schools in Dunedin, New Zealand took part in the study. Children were asked to complete lifestyle questionnaires and have anthropometric measurements taken during one school day, and to wear an accelerometer (Actigraph GT3X+) on their non-dominant wrist for eight consecutive days and seven consecutive nights. The participant’s self-reported frequency of breakfast, fruit and vegetables, and ‘extra’ foods consumption was used to assess diet. Accelerometer-measured sleep and moderate and vigorous physical activity intensity was used to assess sleep behaviour and activity patterns, respectively, while body composition was assessed using the participant’s calculated body mass index. Participants were classified into one of four sleep timing behaviour groups, using the median split for sleep onset (9:37pm) and sleep offset (6:50am) times, rounded to the nearest quarter hour: early sleep-early wake; early sleep-late wake; late sleep-early wake; late sleep-late wake. Late to sleep was defined as after 9:30pm, otherwise classified as early to sleep. Late to wake was defined as after 6:45am, otherwise classified as early to wake. Multivariate mixed regression analysis was used to examine associations, accounting for schools as clustering units. Analyses were undertaken using data from 370 participants who had a complete dataset for the outcome variables and covariates relevant to this thesis available prior to the 7th of November 2015. Results: The study population had a mean age of 10.2 (SD 0.6) years, were predominantly of ‘New Zealand European and Other’ ethnicity (89%), had a higher socio-economic status (49%), indicated by a New Zealand Deprivation Index 2013 score between one and three, and had a ‘normal’ body mass index (89%). Almost all participants (98%) provided at least five valid days of accelerometer data and 80% provided six valid days. Across the whole week, participants slept for an average of 8.6 (SD 0.7) hours per night, went to sleep at a mean time of 9:37pm (SD 0:36) and woke up at a mean time of 6:50am (SD 0:30). Girls slept longer and woke up later than boys, particularly on weekend days, where girls accumulated on average 15 minutes more sleep (8.7 vs 8.4 hours, p=0.011) and woke up 15.4 minutes later (7.04am vs 6.47am, p=0.001). In adjusted multivariate regression models, with the sleep timing behaviour group as the independent variable, no association was found with the consumption frequency of breakfast, fruit and vegetables, or ‘extra’ foods. Participants in the early sleep-early wake sleep timing behaviour group accumulated on average 13 more minutes of moderate and vigorous physical activity per day than those in the late sleep-late wake group (83 mins vs 70 mins, p=0.004), independent of total sleep duration. Participants in the group with sleep timing consistent with the shortest sleep duration (late sleep-early wake) had a significantly higher body mass index z-score than those in the group with sleep timing consistent with the longest sleep duration (early sleep-late wake), independent of total sleep duration (0.40 vs -0.04, p=0.017). Conclusion: This study concludes that sleep timing, independent of total sleep duration, was associated with physical activity and body composition, but not diet in this group of school-aged children. These findings suggest that sleep timing is an important factor to consider in addition to total sleep duration for good health. Further investigation of the causal mechanisms underlying the relationship that sleep timing has with health outcomes is necessary to provide direction for the development of effective strategies for both the treatment and prevention of childhood obesity. Key Words: sleep, diet, physical activity, children, timing, obesit

Relationships between Dietary Patterns and Indices of Arterial Stiffness and Central Arterial Wave Reflection in 9–11-Year-Old Children

Arterial stiffness is an important marker of vascular damage and a strong predictor of cardiovascular diseases (CVD). Given that pathophysiological processes leading to an increased arterial stiffness begin during childhood, the aim of this clustered observational study was to determine the relationship between modifiable factors including dietary patterns and indices of aortic arterial stiffness and wave reflection in 9–11-year-old children. Data collection was conducted between April and December 2015 in 17 primary schools in Dunedin, New Zealand. Dietary data were collected using a previously validated food frequency questionnaire and identified using principal component analysis method. Arterial stiffness (carotid-femoral pulse wave velocity, PWV) and central arterial wave reflection (augmentation index, AIx) were measured using the SphygmoCor XCEL system (Atcor Medical, Sydney, Australia). Complete data for PWV and AIx analyses were available for 389 and 337 children, respectively. The mean age of children was 9.7 ± 0.7 years, 49.0% were girls and 76.0% were classified as “normal weight”. The two identified dietary patterns were “Snacks” and “Fruit and Vegetables”. Mean PWV and AIx were 5.8 ± 0.8 m/s and −2.1 ± 14.1%, respectively. There were no clinically meaningful relationships between the identified dietary pattern scores and either PWV or AIx in 9–11-year-old children

Dietary Patterns, Cardiorespiratory and Muscular Fitness in 9–11-Year-Old Children from Dunedin, New Zealand

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