Association between subjective actual sleep duration, subjective sleep need, age, body mass index, and gender in a large sample of young adults

Introduction: Lack of sleep duration is one of the risk factors that cause excess body mass index (BMI). One of the mechanisms are by regulating an increase in appetite and reducing the energy used. This study aimed to identify the relationship between sleep duration and excess BMI in young adults.Methods: This descriptive-analytic observational study with cross-sectional design was conducted on 70 respondents aged 18-25 years old. The primary outcomes measured were sleep duration and BMI. Sleep duration was grouped as <7 hours (short sleepers), and ≥7 hours. BMI was classified as 18.5-22.9 as normal, and ≥23 as excess BMI (including overweight and obesity) according to Asia-Pacific classification. Data were analyzed using SPSS 21 software.Results: The study showed that the prevalence of excess BMI was higher in respondents with sleep deprivation (<7 hours) of 67% compared to respondents with enough sleep of 33%. The average sleep duration was 42 minutes shorter on respondents with excess BMI with an average of 6.1 hours and 6.8 hours on normal-weight respondents. According to the results of the study, there was a significant relationship between sleep duration and excess BMI (p < 0.05).Conclusion: The study revealed that sleep duration was related with excess BMI in young adults.

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Relationships between College Students’ Sedentary Behavior, Sleep Quality, and Body Mass Index

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18083946 ◽

2021 ◽

Vol 18 (8) ◽

pp. 3946

Author(s):

Wenxi Liu ◽

Qin Yuan ◽

Nan Zeng ◽

Daniel J. McDonough ◽

Kun Tao ◽

...

Keyword(s):

College Students ◽

Body Mass Index ◽

Young Adults ◽

Sedentary Behavior ◽

Nutrition Education ◽

Sleep Duration ◽

Body Mass ◽

Sleep Efficiency ◽

South Central ◽

Activity Promotion

Purpose: Sedentary behavior (SB), sleep efficiency (SE), sleep duration (SD), and body mass index (BMI) are crucial determinants of an individual’s health. However, empirical evidence regarding associations between these factors in young adults living in China remains unknown. Therefore, the purpose of this study was to examine the relationships between accelerometer-measured SB, SE, SD, and BMI in Chinese college students. Methods: Two-hundred and twenty college students (115 females, Meanage = 20.29 years, SD = 2.37) were recruited from a south-central Chinese university. Participants’ SB (daily % time spent in SB), SE (number of minutes of sleep duration/number of minutes in bed), and SD were assessed via wrist-worn ActiGraph GT9X Link accelerometers for one week. Body weight was measured using a digital weight scale, height was measured using a stadiometer, and BMI was calculated as weight (kg)/height (m2). Results: Participants’ average time spent in SB was 76.52% (SD = 10.03), SE was 84.12% (SD = 4.79), and BMI was 20.67 kg/m2 (SD = 3.12), respectively. Regression analyses indicated that SB (β = −0.17, p = 0.01) and BMI (β = −0.20, p < 0.01) negatively predicted SE. In addition, BMI negatively predicted SD (β = −0.22, p < 0.01). Conclusion: Prolonged SB (e.g., screen viewing, smartphone use, and computer playing) and higher BMI may link to shorter sleep duration and lower sleep efficiency in Chinese young adults. Future randomized controlled trials are needed to further confirm these findings. Given that increased BMI status and SB may relate to adverse health outcomes, more population-based intervention strategies seeking to lower BMI and reduce SB (e.g., nutrition education and physical activity promotion) are needed in this population.

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Associations between Body Mass Index, Sleep Duration, and Reported Snoring and Sleepiness Symptoms, By Age Stratification

European Journal of Engineering Research and Science ◽

10.24018/ejers.2020.5.10.2204 ◽

2020 ◽

Vol 5 (10) ◽

pp. 1263-1268

Author(s):

David W. Lin ◽

Weijie V. Lin

Keyword(s):

Body Mass Index ◽

Sleep Duration ◽

Body Mass ◽

Secondary Analysis ◽

The United States ◽

Sample Population ◽

Cross Sectional ◽

Subjective Sleep ◽

Relationship Of ◽

Age Stratification

To further clarify the associations between sleep and body mass index (BMI) using the most recent dataset from the National Health and Nutrition Examination Survey (NHANES). Our study is notable for the inclusion of analyses with age subpopulations and subjective sleep symptoms. Cross-sectional study was performed using the NHANES 2017-18 dataset. Weighted multivariate regressions were utilized. NHANES is a standardized survey conducted biennially in the United States, for a sample population which is weighted to represent national demographics. 6161 participants met inclusion criteria. Measurements were collected via NHANES protocol, with objective measurements collected by trained technicians and self-reported measurements collected via questionnaire. Our results corroborate a roughly U-shaped relationship of sleep duration with BMI, varying with age. Greatest magnitudes were observed in a bimodal age ranges of 18-30 and 61-75, with decreases in BMI of 0.248 and 0.385 associated with each marginal hour of sleep. Our secondary analysis with daytime sleepiness and snoring have a significant association with BMI. Snoring symptoms showed a decreasing magnitude of association with BMI as age increases; for ages 18-30, snoring at least once a week correlated with an increase in BMI of 3.571, while for ages 61-75, this correlated with an increase of 1.619. Our study adds to existing literature on the relationship of sleep and BMI. Age stratification methods were used to further clarify associations. Subjective sleep symptoms were used in a secondary analysis to identify clinical screening questions for adverse effects of sleep on BMI.

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216 Resilience, sleep difficulties, and subjective sleep quality during COVID-19

SLEEP ◽

10.1093/sleep/zsab072.215 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A86-A87

Author(s):

Laura Ramos Socarras ◽

Jérémie Potvin ◽

Geneviève Forest

Keyword(s):

Young Adults ◽

Sleep Quality ◽

Sleep Duration ◽

Sleep Onset ◽

Hierarchical Regression ◽

Unique Contribution ◽

Subjective Sleep Quality ◽

Subjective Sleep ◽

And Gender ◽

Sleep Difficulties

Abstract Introduction We have shown in a previous study that despite significant improvements in sleep patterns and sleep duration during COVID-19 in teens and young adults, only teens reported better sleep quality and satisfaction. Moreover, sleep difficulties seem to be more prominent in the older group during the pandemic, suggesting that there could be additional risk factors involved. The current study aimed to investigate the role of resilience in the association between changes in sleep and the subjective sleep quality (SSQ) in teens and young adults during COVID-19. Methods 289 teens (12-17 years old) and 294 young adults (18-25 years old) completed the Connor-Davidson Resilience Scale-10 and an adapted version of the Pittsburgh Sleep Quality Index online. Teens and young adults were each divided into a resilient and less resilient group. Hierarchical regression models were conducted to examine the unique contribution of weekdays sleep duration, sleep difficulties, and resilience to SSQ. Sleep duration, sleep difficulties and SSQ before COVID-19, and gender were entered as controls. Results Results show that in less resilient teens, changes in sleep onset difficulties (β=-.285, p=.003), nocturnal and early awakenings (β=-.218, p=.019), and weekdays sleep duration (β=.282, p=.001) significantly predicted SSQ and explained 36.5% of the variance. In less resilient young adults, changes in nightmares (β=-.309, p=.027) and sleep onset difficulties (β=-.263, p=.012) significantly predicted SSQ and explained 24.1% of the variance. In resilient teens, changes in weekdays sleep duration (β=.296, p=.007) significantly predicted SSQ and explained 20.1% of the variance. In resilient adults, changes in sleep onset difficulties (β=-.325, p=.001), nocturnal and early awakenings (β=-.374, p=.000), and weekdays sleep duration (β=.192, p=.009) significantly predicted SSQ and explained 46.0% of the variance. Conclusion Our results suggest that resilience appears to be a protecting factor in the impacts of sleep difficulties on sleep quality, but only in adolescents. Indeed, in young adults, sleep difficulties seem to be a more important factor modulating sleep quality than changes in sleep duration. These results underline the importance of focusing on the intrinsic characteristics of each population to better target interventions. Support (if any):

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