Dataset Information

Associations between objective measures of physical activity, sleep and stress levels among preschool children.

ABSTRACT: BACKGROUND:Cortisol is often used as a biological marker for stress. When measured in urine or serum, representing a short-term measurement of the hormone, it has been associated with unfavorable sleep characteristics and both low and high physical activity levels. However, cortisol in hair represents a long-term stress measure and has been suggested as a promising new marker for chronic stress. Therefore, we aimed to examine the association between objectively measured sleep, physical activity and hair cortisol levels in preschool children. METHODS:In order to obtain objective measures of physical activity and sleep habits, 54 children aged 2-6?years wore an ActiGraph for 5 consecutive days and nights. For chronic stress measurements of each child, hair was cut from the back of the head close to the scalp for analysis of cortisol levels. Associations between measured sleep quality and quantity and level of physical activity and hair cortisol levels were estimated using linear regression analysis, presented as ?. Results were adjusted for sex, age and BMI z-score. RESULTS:We found no significant association between log-transformed cortisol (pg/mg) and sleep duration (hours) (??=?-?0.0016, p?=?0.99), sleep efficiency (??=?-?3.1, p?=?0.18), sleep latency (??=?0.015, p?=?0.16) or physical activity level (100 counts per min) (??=?0.014, p?=?0.22). However, sleep latency (min) was directly associated with physical activity (counts per min) levels (??=?35.2, p?=?0.02), while sleep duration (hours) (??=?-?142.1, p?=?0.55) and sleep efficiency (%) (??=?-?4087, p?=?0.26) showed no significant associations. CONCLUSIONS:In our study, a high physical activity level was associated with poorer sleep habits. Neither sleep quality nor physical activity were related to long term cortisol exposure. These results are among the first to study associations between objectively measured sleep, physical activity and chronic cortisol levels among preschool children. More and larger studies are therefore needed.

SUBMITTER: Eythorsdottir DY

PROVIDER: S-EPMC7254697 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Associations between objective measures of physical activity, sleep and stress levels among preschool children.

Eythorsdottir Dagny Y DY Frederiksen Peder P Larsen Sofus C SC Olsen Nanna J NJ Heitmann Berit L BL

BMC pediatrics 20200527 1

<h4>Background</h4>Cortisol is often used as a biological marker for stress. When measured in urine or serum, representing a short-term measurement of the hormone, it has been associated with unfavorable sleep characteristics and both low and high physical activity levels. However, cortisol in hair represents a long-term stress measure and has been suggested as a promising new marker for chronic stress. Therefore, we aimed to examine the association between objectively measured sleep, physical a ...[more]

PMID: 32460881

Similar Datasets

Project description:ObjectivePhysical activity contributes to prevent serious diseases and ailments, and previous research indicates that lifestyle habits are likely to track from early childhood to adulthood. 90% of Norwegian children aged 1-5 are enrolled in preschools, and preschool staff can play an important role in children's activity levels. This study's aim was to identify whether any associations exist between preschool staff's characteristics (initiative, participation, attitudes, and activity levels) and children's activity in preschool.Method289 children aged 4-6 and 72 preschool staff from 13 randomly selected preschools in a region of Nord-Troendelag, Norway, were enrolled in the study. All participants wore an Actigraph accelerometer for seven consecutive days. Questionnaires were also utilized to identify correlates between preschool staff's attitudes and initiative in relation to children's physical activity, in addition to their participation in children's physical activity. A multilevel analysis, the linear mixed model (LMM), was used to elucidate associations between preschool staff and children's activity levels.ResultsA significant association was found between preschool staff's average activity levels during preschool hours and children's corresponding activity levels during preschool hours (t = 2.57; p = 0.021; f2 = 0.013). There were, however, no significant associations identified between the attitudes (t = -0.44; p = 0.67), initiative (t = -0.14; p = 0.89), and participation (t = 0.66; p = 0.52) variables among preschool staff and children's activity levels during preschool hours.ConclusionThe study demonstrated that a significant association exists between preschool staff's aggregated activity levels and 4-6-year-olds' individual activity levels. However, an observational study is requisite in order to determine whether the association is based on preschool staff's impact on children's physical activity or if it is the children that affect the preschool staff's activity levels, or a combination thereof.

Project description:The purpose of this study was to examine associations between the Walk Score and physical activity in young, overweight/obese urban women. Project Health included 45 White or African American women (BMI 31.5±3.9 kg/m2; age 26.5±4.6 years; 62% African American) living in the Boston area. An accelerometer estimated steps/day and mins/day in light physical activity (100-2019 counts-per-minute) and moderate-to-vigorous-physical activity (≥2020 cpm). Walk Score was used to estimate the walkability of home address by analyzing proximity to nearby amenities. General linear regression models estimated associations between total Walk Score and physical activity (light physical activity, moderate-to-vigorous-physical activity, steps, total activity counts, METs), adjusting for body mass index, age, race/ethnicity, seasonality, wear time, employment and student status. For physical activity variables that had significant associations with Walk Score (steps/day and steps/min), regression models were estimated for Walk Score sub-scores (parks, grocery, errands, shopping, dining/drinking, culture/entertainment and schools). Logistic regression models estimated the odds of meeting the guidelines for steps (≥10,000/day) and moderate-to-vigorous-physical activity (≥150mins MVPA/week) based on Walk Score. Participants had a Walk Score of 63.9±26.4, took 14,143±3,934 steps/day, and spent 206.2±66.0 mins/day in light physical activity and 46.7±17.5 mins/day in moderate-to-vigorous- physical activity. Walk Score was significantly and positively associated with steps/day (β = 51.4, p = 0.01) and steps/min (β = 0.06, p = 0.009) but was not associated with mins/day of light physical activity, moderate-to-vigorous-physical activity, total activity counts or METs. Parks, grocery, errands, shopping, dining/drinking, and culture/entertainment Walk Score sub-scores were significantly associated with steps and steps/min (all p<0.05), but not significantly associated for schools. Participants who lived in higher Walk Score neighborhoods were more likely to meet the step guidelines (OR, 95% CI: 1.59, 1.04-2.99) and moderate-to-vigorous-physical activity guidelines (1.63, 1.06-3.02), respectively, per 10-unit increase in Walk Score. These results indicate that living in a more walkable neighborhood may support walking behavior in young, urban-dwelling overweight/obese women and provide further evidence for the expanded use of urban planning and transportation policies to improve the walkability of urban neighborhoods.

Project description:ObjectiveThe aim of this study was to investigate the association between preschool playground size, formalized physical activity (PA) policies, time spent outdoors and preschool teacher's levels of PA and children's objectively assessed levels of PA and sedentary time (ST) during preschool hours.MethodsIn total, 369 children and 84 preschool teachers from 27 preschools in Södermalm municipally, Stockholm Sweden wore an Actigraph GT3X+ accelerometer during 7 consecutive days. Preschool environmental and structural characteristics were measured via the Environment and Policy Evaluation Self-Report (EPAO-SR) instrument and time in- and outdoors was recorded by preschool teachers during the PA measurements. Weight and height of children were measured via validated scales and parents filled out a questionnaire on demographical and descriptive variables. Linear mixed models, nested on preschool level, were used to assess the association between predictors and outcomes.ResultsThe mean child age was 4.7 years (SD 0.8) and 45% were girls. We found that children were more active in preschools with a formalized PA policy, compared to preschools without such a policy, but not less sedentary. The association between policy and activity seemed to be more pronounced when accounting for other environmental factors. Similar associations were found in children spent most time outdoors (uppermost quartile) compared with children spent least time outdoors (Lowermost quartile). Preschool teachers' light PA (LPA) (ß = 0.25, P = 0.004) and steps (ß = 0.52, P<0.001) were associated with children's LPA and steps while the preschool playground size showed no association with PA in children, when accounting for other environmental factors.ConclusionThe current study showed that preschool structural characteristics such as formalized PA policies and more time spent outdoors were positively associated with children's PA. These findings suggest that formalized PA policies and time outdoors may be of importance for promoting children's PA during preschool hours.

Project description:PURPOSE:Although physical activity is an established risk factor for chronic disease prevention, the specific mechanisms underlying these relationships are poorly understood. We examined the associations between total activity counts and moderate-vigorous physical activity (MVPA) measured by accelerometer, and physical activity energy expenditure measured by doubly labeled water, with plasma levels of proinsulin, insulin, c-peptide, insulin growth factor binding protein-3, insulin growth factor-1, adiponectin, leptin, and leptin-sR. METHODS:We conducted a cross-sectional analysis of 526 healthy US women in the Women's Lifestyle Validation Study, 2010 to 2012. We performed multiple linear regression models adjusting for potential lifestyle and health-related confounders to assess the associations between physical activity, measured in quartiles (Q) and biomarkers. RESULTS:Participants in Q4 versus Q1 of total activity counts had lower proinsulin (-20%), c-peptide (-7%), insulin (-31%), and leptin (-46%) levels, and higher adiponectin (55%), leptin-sR (25%), and insulin growth factor-1 (9.6%) levels (all P trend ? 0.05). Participants in Q4 versus Q1 of MVPA had lower proinsulin (-26%), c-peptide (-7%), insulin (-32%), and leptin (-40%) levels, and higher adiponectin (31%) and leptin-sR (22%) levels (all P trend ? 0.05). Further adjustment for body mass index (BMI) attenuated these associations, but the associations with adipokines remained significant. Those in Q4 versus Q1 of physical activity energy expenditure had lower leptin (-21%) and higher leptin-sR (10%) levels (all P trend ? 0.05), after additional adjustment for BMI. In the sensitivity analysis, the associations were similar but attenuated when physical activity was measured using the subjective physical activity questionnaire. CONCLUSIONS:Our data suggest that greater physical activity is modestly associated with favorable levels of cardiometabolic and endocrine biomarkers, where the strongest associations were found with accelerometer-measured physical activity. These associations may be only partially mediated through BMI, further supporting the role of physical activity in the reduction of cardiometabolic and endocrine disease risk, independent of adiposity.

Dataset Information

Associations between objective measures of physical activity, sleep and stress levels among preschool children.

Publications

Associations between objective measures of physical activity, sleep and stress levels among preschool children.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets