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1.
Int J Behav Nutr Phys Act ; 21(1): 27, 2024 Mar 04.
Artículo en Inglés | MEDLINE | ID: mdl-38438945

RESUMEN

BACKGROUND: Parental practices and neighbourhood environmental factors may influence children's movement behaviours. We aimed to investigate the cross-sectional and prospective associations of parental practices and neighbourhood environmental factors with accelerometer-measured 24-hour movement behaviours (24 h-MBs) among school-aged children in Singapore. METHODS: The Growing Up in Singapore Towards healthy Outcomes (GUSTO) study collected information on dimensions of parental practices and neighbourhood environment at age 5.5 years. Confirmatory factor analyses were performed to generate latent variables and used to compute overall parental practices [involvement in PA + support for PA + control of screen viewing context] and environmental scores [facilities for active play + active mobility facilitators + barriers*-1]. Children wore an accelerometer on their non-dominant wrist for seven consecutive days at ages 5.5 and 8 years. The R-package GGIR 2.6 was used to derive moderate-to-vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), inactivity, and total-sleep (napping+night sleep) minutes per day. Associations were determined using compositional data analysis with multivariate linear regression models, taking into account potential confounders. RESULTS: Among 425 children (48% girls, 59% Chinese), higher parental involvement in PA, parental support for PA and overall parental practices were associated with 24 h-MBs at ages 5.5 and 8 years, specifically with greater time spent in MVPA and less time being inactive relative to the remaining movement behaviours. The corresponding mean changes in the overall 24 h-MB for increasing parental practices from lowest to highest scores (- 2 to + 2 z-scores) indicated potential increases of up to 15-minutes in MVPA, 20-minutes in LPA, 5-minutes in sleep duration, and a reduction of 40-minutes in inactivity at age 5.5 years. At age 8 years, this could translate to approximately 15-minutes more of MVPA, 20-minutes more of LPA, a 20-minute reduction in sleep duration, and a 20-minute reduction in inactivity. Parental control of screen viewing contexts and neighbourhood environmental factors were not associated with 24 h-MBs. CONCLUSIONS: Parental practices but not environmental factors were associated with higher MVPA and lower inactivity among Singaporean children, even at a later age. Further research may provide insights that support development of targeted public health strategies to promote healthier movement behaviours among children. STUDY REGISTRATION: This study was registered on 4th August 2010 and is available online at ClinicalTrials.gov: NCT01174875.


Asunto(s)
Pueblo Asiatico , Conducta Sedentaria , Niño , Preescolar , Femenino , Humanos , Masculino , Estudios Transversales , Análisis de Datos , Padres
2.
Int J Behav Nutr Phys Act ; 18(1): 145, 2021 11 06.
Artículo en Inglés | MEDLINE | ID: mdl-34742314

RESUMEN

BACKGROUND: Time spent in movement behaviours, including physical activity (PA), sedentary behaviour (SB) and sleep, across the 24-h day may have distinct health consequences. We aimed to describe 24-h movement behaviour (24 h-MB) profiles in children and how profile membership changed from age 5.5 to 8 years. METHODS: Children in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort were asked to wear an accelerometer (ActiGraph-GT3X+) on their wrist for seven consecutive days at ages 5.5 and 8 years to measure 24 h-MB patterns. Time spent in night sleep, inactivity (proxy for SB), light PA, moderate PA (MPA), and vigorous PA (VPA) per day were calculated using the R-package GGIR 2.0. Using latent profile analyses (n = 442) we identified 24 h-MB profiles, which were given animal names to convey key characteristics. Latent transition analyses were used to describe the profile membership transition from ages 5.5 to 8 years. Associations with sex and ethnicity were examined. RESULTS: We identified four profiles, "Rabbits" (very high-MPA/VPA, low-inactivity and average-night-sleep), "Chimpanzees" (high-MPA, low-inactivity and average-night-sleep), "Pandas" (low-PA, high-inactivity and high-night-sleep) and "Owls" (low-PA, high-inactivity and low-night-sleep), among children at both time points. At ages 5.5 and 8 years, the majority of children were classified into profiles of "Chimpanzees" (51 and 39%, respectively) and "Pandas" (24 and 37%). Half of the sample (49%), particularly "Rabbits", remained in the same profile at ages 5.5 and 8 years: among children who changed profile the predominant transitions occurred from "Chimpanzees" (27%) and "Owls" (56%) profiles to "Pandas". Sex, but not ethnicity, was associated with profile membership: compared to girls, boys were more likely to be in the "Rabbits" profile (adjusted OR [95% CI]: 3.6 [1.4, 9.7] and 4.5 [1.8, 10.9] at ages 5.5 and 8 years, respectively) and less likely to be in the "Pandas" profile (0.5 [0.3, 0.9] and 0.4 [0.2, 0.6]) at both ages. CONCLUSIONS: With increasing age about half the children stayed in the same of four 24 h-MB profiles, while the predominant transition for the remaining children was towards lower PA, higher inactivity and longer sleep duration. These findings can aid development and implementation of public health strategies to promote better health. STUDY REGISTRATION: This study was registered on 4th August 2010 and is available online at ClinicalTrials.gov: NCT01174875 .


Asunto(s)
Conducta Sedentaria , Sueño , Acelerometría , Animales , Estudios de Cohortes , Humanos , Estudios Prospectivos , Conejos , Singapur
3.
JMIR Res Protoc ; 13: e56749, 2024 Jul 17.
Artículo en Inglés | MEDLINE | ID: mdl-39018103

RESUMEN

BACKGROUND: Integration of mobile health data collection methods into cohort studies enables the collection of intensive longitudinal information, which gives deeper insights into individuals' health and lifestyle behavioral patterns over time, as compared to traditional cohort methods with less frequent data collection. These findings can then fill the gaps that remain in understanding how various lifestyle behaviors interact as students graduate from university and seek employment (student-to-work life transition), where the inability to adapt quickly to a changing environment greatly affects the mental well-being of young adults. OBJECTIVE: This paper aims to provide an overview of the study methodology and baseline characteristics of participants in Health@NUS, a longitudinal study leveraging mobile health to examine the trajectories of health behaviors, physical health, and well-being, and their diverse determinants, for young adults during the student-to-work life transition. METHODS: University students were recruited between August 2020 and June 2022 in Singapore. Participants would complete biometric assessments and questionnaires at 3 time points (baseline, 12-, and 24-month follow-up visits) and use a Fitbit smartwatch and smartphone app to continuously collect physical activity, sedentary behavior, sleep, and dietary data over the 2 years. Additionally, up to 12 two-week-long bursts of app-based ecological momentary surveys capturing lifestyle behaviors and well-being would be sent out among the 3 time points. RESULTS: Interested participants (n=1556) were screened for eligibility, and 776 participants were enrolled in the study between August 2020 and June 2022. Participants were mostly female (441/776, 56.8%), of Chinese ethnicity (741/776, 92%), undergraduate students (759/776, 97.8%), and had a mean BMI of 21.9 (SD 3.3) kg/m2, and a mean age of 22.7 (SD 1.7) years. A substantial proportion were overweight (202/776, 26.1%) or obese (42/776, 5.4%), had indicated poor mental well-being (World Health Organization-5 Well-Being Index ≤50; 291/776, 37.7%), or were at higher risk for psychological distress (Kessler Psychological Distress Scale ≥13; 109/776, 14.1%). CONCLUSIONS: The findings from this study will provide detailed insights into the determinants and trajectories of health behaviors, health, and well-being during the student-to-work life transition experienced by young adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/study/NCT05154227. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56749.


Asunto(s)
Estudiantes , Telemedicina , Femenino , Humanos , Masculino , Adulto Joven , Estudios de Cohortes , Empleo , Conductas Relacionadas con la Salud , Estudios Longitudinales , Estudios Prospectivos , Singapur , Estudiantes/psicología , Estudiantes/estadística & datos numéricos , Encuestas y Cuestionarios , Universidades , Estudios Observacionales como Asunto , Proyectos de Investigación
4.
Front Public Health ; 12: 1412634, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39296832

RESUMEN

Background: Physical activity (PA), sedentary behavior (SB), and sleep are collectively referred to as 24-h movement behaviors, which may be linked to cognitive development in children. However, most of the evidence was based on cross-sectional studies and/or solely relied on parent-reported information on children's behaviors, and it remains uncertain whether all domains/contexts of PA and SB are similarly associated with executive function and academic achievement. Objective: We investigated the prospective associations of accelerometer-measured 24 h-movement behaviors and domain-specific PA and SB with executive function and academic achievement among school-aged children in Singapore. Methods: The Growing Up in Singapore Toward healthy Outcomes (GUSTO) cohort used a wrist-worn accelerometer (Actigraph-GT3x+) to measure 24 h-movement behaviors data at ages 5.5 and 8 years. Executive function and academic achievement were assessed using NEuroPSYchology (NEPSY) and Wechsler Individual Achievement Tests at ages 8.5 and 9-years, respectively. Compositional data analyses were conducted to explore the associations of 24 h-movement behavior with outcomes, and multiple linear regression models to examine the associations of domain-specific PA and SB with outcomes (n = 432). Results: Among 432 children whose parents agreed to cognitive assessments (47% girls and 58% Chinese), the composition of 24 h-movement behaviors at ages 5.5 and 8 years was not associated with executive function and academic achievement. However, higher moderate-to-vigorous PA (MVPA) relative to remaining movement behaviors at age 5.5 years was associated with lower academic achievement [Mean difference (95% confidence interval): -0.367 (-0.726, -0.009) z-score], and reallocating MVPA time to sleep showed higher academic achievement scores [30 min from MVPA to sleep: 0.214 (0.023, 0.404) z-score]. Certain domains of PA and SB, notably organized PA/sports, outdoor play, and reading books were favorably associated with outcomes of interest, while indoor play and screen-viewing were unfavorably associated. Conclusion: The associations between movement behaviors and cognitive outcomes are multifaceted, influenced by specific domains of PA and SB. This study underscores the importance of participation in organized PA/sports, outdoor active play, and reading books, while ensuring adequate sleep and limiting screen viewing, to enhance cognitive outcomes. These findings underscore the need for further research into time-use trade-offs. Such studies could have major implications for revising current guidelines or strategies aimed at promoting healthier 24 h-movement behaviors in children. Study registration: https://clinicaltrials.gov/, NCT01174875.


Asunto(s)
Éxito Académico , Acelerometría , Función Ejecutiva , Ejercicio Físico , Conducta Sedentaria , Niño , Preescolar , Femenino , Humanos , Masculino , Función Ejecutiva/fisiología , Ejercicio Físico/psicología , Estudios Prospectivos , Singapur , Sueño/fisiología
5.
JMIR Pediatr Parent ; 5(2): e33312, 2022 Jun 24.
Artículo en Inglés | MEDLINE | ID: mdl-35749208

RESUMEN

BACKGROUND: Existing modes of collecting self-reported 24-hour movement information from children, including digital assessments, have not been demonstrated to be of acceptable validity when compared to objective measurements. My E-Diary for Activities and Lifestyle (MEDAL) is an interactive web-based diary developed to collect time-use information from children aged 10 years and older. OBJECTIVE: This study evaluated the validity of MEDAL for assessing children's movement behaviors by comparing self-reported and accelerometer-measured time spent in movement behavior among children in Singapore aged 10-11 years. METHODS: Funding for this study was obtained in October 2017, and data were collected between April and August 2020. Participants recorded their daily activities using MEDAL over 2 specified weekdays and 2 weekend days and wore an Actigraph accelerometer on their nondominant wrist throughout the study to objectively assess movement behaviors. Spearman correlation coefficient and intraclass correlation coefficient (ICC) were used to compare the accelerometer measurements and self-reports for each movement behavior. Bland-Altman plots were generated to investigate trends of bias in the self-reports. RESULTS: Among the participants aged 10-11 years (29/49, 59% boys), we observed that children reported lower light physical activity (LPA) and higher moderate-to-vigorous physical activity (MVPA), inactivity, and night sleep than that measured by the accelerometer. There was a moderate-to-strong correlation between self-reported and accelerometer-measured MVPA (r=0.37; 95% CI 0.20-0.54), inactivity (r=0.36; 95% CI 0.18-0.54), and night sleep (r=0.58; 95% CI 0.43-0.74); the correlation for LPA was poor (r=0.19; 95% CI 0.02-0.36). Agreement was poor for all behaviors (MVPA: ICC=0.24, 95% CI 0.07-0.40; LPA: ICC=0.19, 95% CI 0.01-0.36; inactivity: ICC=0.29, 95% CI 0.11-0.44; night sleep: ICC=0.45, 95% CI 0.29-0.58). There was stronger correlation and agreement on weekdays for inactivity and night sleep; conversely, there was stronger correlation and agreement for MVPA and LPA on weekend days. Finally, based on Bland-Altman plots, we observed that with increasing MVPA, children tended to report higher MVPA than that measured by the accelerometer. There were no clear trends for the other behaviors. CONCLUSIONS: MEDAL may be used to assess the movement behaviors of children. Based on self-reports, the children are able to estimate their time spent in MVPA, inactivity, and night sleep although actual time spent in these behaviors may differ from accelerometer-derived estimates; self-reported LPA warrant cautious interpretation. Observable differences in reporting accuracy exist between weekdays and weekend days.

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