Sleep and BMI: Do (Fitbit) bands aid?

Introduction

The association between sleep and body mass index (BMI) is well known¹. Recently Xu and colleagues² showed that shorter sleep duration, as measured by a Fitbit wristband, was associated with a higher average BMI². These results importantly show the potential value of mainstream consumer devices for scientific research by providing objective sleep and physical activity data. A limitation of the Xu et al. study however, as noted by the authors², is the lack of diversity of ethnicity in their study population, with the majority of participants being of European descent. In order to assess the utility of wearables for global research we used data from a recently published study³ to investigate the relationship between sleep and BMI in a largely Chinese population.

Methods

Data was obtained from the study by Lim and colleagues³. In brief, this study generated Fitbit Charge heart rate (HR) data from a cohort of volunteers tracked for a median duration of 4 days³. The volunteers underwent comprehensive profiling including activity tracking (step count and sleep tracking) using the Fitbit Charge HR wearable sensor and BMI measurement at day of recruitment. From the total cohort of 233 individuals contributing data³, association analyses were conducted on subjects who had valid measurements for all metric types and who had more than one day of sleep data.

To test the association between average hours of sleep and BMI multiple linear regression analyses were conducted using the ‘statsmodels’ package in python.

Results

Useable data was available for 212 individuals; the summary of their clinical and demographic characteristics are shown in Table 1.

A linear regression analysis showed that after adjusting for age, gender, race, and average number of steps taken per day, average hours of sleep per day was negatively associated with BMI (p=0.02): an hour increase in sleep per day was associated with approximately a 0.5 point decrease in BMI (Table 2, Figure 1).

Figure 1. Relationship between body mass index (BMI) and average hours of sleep.

Conclusions

In summary, we found that the findings of Xu and colleagues are consistent in a population of different ancestry. More generally, previous work^2,3 and that described here demonstrates the significant potential for wearables in global biomedical research and further, as we used openly available data, this analysis shows the benefits of sharing observational data⁴.

Data availability

All data used in this study is available from the article by Lim et al. https://doi.org/10.1371/journal.pbio.2004285³