Sleep Duration and Quality in Children

Obesity in children is a priority of public health initiatives, and reliable obesity prevalence and severity assessments are needed for policy decisions and study directions. Obesity in childhood raises the risk of insulin resistance, type 2 diabetes, and cardiovascular diseases in later life. To develop preventive strategies, it is essential to identify modifiable lifestyle habits linked to childhood obesity. The four main modifiable lifestyle behaviors affecting body weight are physical activity, sleep, screen time, and eating patterns. Among these factors, sleep is a neglected issue for clinicians, and recent research has shown that sleep patterns can predict BMI and macronutrient intake. Getting enough sleep is essential to a person's physical and mental well-being and development. This study aims to determine the sleep duration and quality of children aged 9-12 during the school year and how sleep impacts food intake and choice. Also, determining any relationships between the sleep and food intake outcomes and screen time, physical activity, and anthropometric indicators.

Childhood obesity remains one of today's most significant public health challenges. Increased obesity among children has contributed to the rise in chronic diseases like obesity in adults, mental health issues, diabetes, cardiovascular disease, and cancer. Childhood obesity is complicated and multifaceted, involving genetic, endocrine causes, environmental, behavioral, and social factors. According to data, human sleep duration has declined rapidly over the past century. Sleep has recently been linked to cardiometabolic health, including obesity risk. The relationship between short sleep duration and body weight is stronger in children and decreases with age. Based on these findings, children may be more at risk of being overweight due to short sleep duration. A study in children aged 5-10 showed that short sleep duration is the most critical risk factor among other factors like parental obesity, more than 3 hours of television viewing, and physical inactivity for obesity and overweight. Sleep restriction was suggested to increase dietary intake, but there was no estimate of how much the increase in dietary intake could be due to restricted sleep. The shorter the sleeping duration (6 hours or less per night for adults), the more irregular the eating habits, the more frequent snacking between meals, the more salt used, and the fewer vegetables consumed. An intervention study showed that energy intake increased when sleep duration was restricted (1 night of 7 hours, two nights of 6 hours, and one night of 4 hours of sleep/night) compared to typical nights (2 nights of more than 8 hours of sleep/night). The rationale for the proposed study is that common lifestyle factors in children and adolescents, such as sedentary behavior, lack of physical activity, and increasing amounts of screen time, can each have independent and varying effects on the factors that affect the development of overweight and obesity. Therefore, a prospective study that objectively measures these lifestyle factors and the outcomes simultaneously and in real-time is needed to understand better the contribution of these lifestyle factors on changes in energy balance, sleep duration and quality, and food choices.

The primary objective of the proposed study is to determine the sleep duration and quality of children aged 9-12, both during the school year and over the summer school break, and how sleep impacts food intake and choices. The secondary objective is to determine any relationship between sleep and food intake outcomes, digital screen time, physical activity levels, and anthropometric indicators. The investigators hypothesize that insufficient sleep duration and low sleep quality would negatively affect lifestyle factors. This proposal aims to generate pilot, cross-sectional data for a future funding application to CIHR (Institute of Human Development, Child and Youth Health and/or Institute of Nutrition, Metabolism, and Diabetes) on implementing an interventional study. Implementation of an intervention study aimed at either increasing sleep duration, improving sleep hygiene, or reducing digital screen time. The study proposed here will help determine the feasibility of conducting a larger-scale cohort or interventional study and provide sufficient data to determine sample size requirements for such a study. This study will also help identify any critical aspects of the design that will need refinement before a full human trial can be undertaken.

The investigators are doing anthropometric measurements based on WHO procedures.

The investigators use the GENEActiv triaxial accelerometer (Activinsights Ltd, Cambs, UK) to objectively assess sleep duration, quality, and physical activity. Also, the investigators use CSHQ (Children's Sleep Habits Questionnaire), CRSP (Children's Report of Sleep patterns), ESS-CHAD (Epworth Sleepiness Scale for Children and Adolescents), and children's sleep diary for subjective data. Data on dietary habits are collected by completing two 24-hour recalls using the US National Cancer Institute web-based diet recording software called ASA24. In ASA24, the investigators can extract data concerning energy, macronutrient, micronutrient, and food groups like meat, dairy, vegetables, fruits, and carbohydrates.

A descriptive statistical analysis will be used to describe the demographic characteristics of the study sample. The investigators will report frequencies and percentages for categorical variables. A mean with standard deviations or a median with an interquartile range will be presented for continuous variables. The investigators will use Chi-square tests to test for differences between girls and boys. An individual's body mass index is calculated by dividing their weight (kg) by height (m2). There is a percentage error of 100 grams and 0.5 centimeters in weight and height. As a result of this calculation, values obtained will be converted into Z scores by the World Health Organization (WHO) growth curves. A binary logistic regression analysis will be conducted to assess the potential influence of sleep duration and quality on dietary habits. The odds ratios (OR) with confidence intervals (CI) will then be calculated and adjusted for confounding factors. A hierarchical binary logistic regression analysis will also be used to assess the potential effects of several demographic and lifestyle factors on sleep duration levels. An adjusted association between covariates will be calculated by calculating an OR with the 95% confidence interval and controlling for confounding. Statistics will be performed using SPSS version 28.0 for Windows (SPSS Inc., Chicago, Illinois, United States). It is decided that P = 0.05 will be the statistical significance level for two-sided hypotheses.

Actigraphy data: In GENEActiv version 3.3, acceleration data will be downloaded as raw binary files for the x,y, and z movement axes and saved in raw format. The accelerometer files will read into R and summarize using GGIR, version 1.5, without imputed values and using the ENMO metric.

In the 21st century, childhood obesity is one of the most important health challenges. It is possible to prevent obesity from escalating into severe psychosocial and somatic complications that could compromise normal growth and development when the disease is treated early. A practical first-line treatment approach is a family-based obesity intervention that addresses diet, physical activity, sedentary behavior, and sleep duration and quality and supports behavior change. Compared to the national average of 28 percent and most other regional health authorities, Newfoundland and Labrador have the greatest percentage of overweight and obese children (e.g., Eastern Health Region between 45 and 65%). This is the first study among Newfoundlander children examining the association between sleep duration and quality and lifestyle characteristics. The investigators are determining the sleep duration and quality of children aged 9-12 both during the school year and over the summer school break; also investigating the relationship between sleep duration and quality and food choices. Our study will also assess any relationship between sleep, screen time, physical activity, and food choices.

Based on our knowledge, this study is novel in some aspects: (A) Most previous studies on populations younger than nine years or above 12 years trying to avoid this age group. (B) This study assesses sleep and physical activity subjectively and objectively (questionnaires and actigraphy). (C) The investigators are trying to convince participants participating in the school phase to come back and partake in the study in the summertime to compare these two times. (D) Food habits is evaluated by the ASA24, which is one of the accurate methods for collecting food data. (E) Based on our knowledge, this study is one of the few studies that have been conducted that has measured the most important lifestyle factors together.

Eligibility Criteria:
Inclusion Criteria:

* Age: 9-12 years old
* One parent or guardian should accompany the child.
* A commitment to complete all the questionnaires daily for both children and parents
* A commitment to wearing the actigraphy during seven days of study.

Exclusion Criteria:

* Remove the watch during the week of study
* Not completing two dietary recalls
* Not completing forms and questionnaires
* Being sick (e.g., Covid-19) during the week of study.