Beyond sleep duration: Sleep timing is associated with BMI among Brazilian adults

Giovana Longo-Silva; Anny Kariny Pereira Pedrosa; Priscilla Marcia Bezerra de Oliveira; Jéssica Ribeiro da Silva; Risia Cristina Egito de Menezes; Patricia de Menezes Marinho; Renan Serenini Bernardes

doi:10.1016/j.sleepx.2023.100082

Beyond sleep duration: Sleep timing is associated with BMI among Brazilian adults

Sleep Med X. 2023 Jul 26:6:100082. doi: 10.1016/j.sleepx.2023.100082. eCollection 2023 Dec 15.

Authors

Giovana Longo-Silva¹, Anny Kariny Pereira Pedrosa¹, Priscilla Marcia Bezerra de Oliveira¹, Jéssica Ribeiro da Silva¹, Risia Cristina Egito de Menezes¹, Patricia de Menezes Marinho², Renan Serenini Bernardes³

Affiliations

¹ Public Health Nutrition Laboratory, Faculty of Nutrition (FANUT), Federal University of Alagoas (UFAL), Avenida Lourival Melo Mota, S/N, Tabuleiro dos Martins, Maceió, AL, 57072-900, Brazil.
² Faculty Estácio of Alagoas, Rua Pio XII, 70, Jatiuca, Maceió, AL, 57035-560, Brazil.
³ European Ph.D. in Socio-Economic and Statistical Studies, Faculty of Economics, Sapienza University of Rome, Via del Castro Laurenziano, Rome, Italy.

Abstract

Objectives: To examine the association of sleep duration and timing with BMI among adults. Also, to identify obesogenic and unhealthy behaviors (e.g.diet/sleep quality, physical activity, screen time, smoking) associated with short sleep duration and late bedtime.

Participants: Participants (n=755) were part of exploratory, population-based research, with data collection in a virtual environment.

Methods: For purposes of characterizing the population we considered short sleepers<7h/night, and the population bedtime median was used to stratify participants into early and late sleepers (before and after 23:08). Student's t-test and chi-square test were performed to assess differences in characteristics between groups. Linear regression analyses were conducted to determine the association of sleep duration, bedtime, and wake-up time with BMI. Quantile regression was estimated for the 25th, 50th, and 75th quantiles to identify the distributional correlations between BMI and sleep variables. Restricted cubic splines were also used to study the shape of the association between sleep-BMI. Analyses were adjusted for potential confounding variables.

Results: BMI decreased by 0.40Kg/m2 for each additional hour of sleep duration [95%CI=-0.68,-0.12,p=0.005] and increased by 0.37 kg/m² for each additional hour of bedtime [95%CI=0.12,0.61,p=0.003]. The association between bedtime and BMI remained even after adjustment for sleep duration. These effects were higher and stronger with higher BMI values (p75^th). Wake-up time did not show statistically significant associations.

Conclusions: Because we found that beyond sleep duration, bedtime was significantly associated with BMI, our data reflect the pertinence of assessing sleep timing patterns in disentangling sleep-obesity association. Insights into the characteristics, obesogenic and unhealthy behaviors related to short and late sleep may support specific strategies to prevent and treat excess body adiposity and other negative health outcomes.

Keywords: Bedtime; Body mass index (BMI); Lifestyle; Obesity; Overweight; Sleep.