Impact du confinement et du déconfinement sur l’évolution pondérale au sein d’une cohorte française

The containment related to the COVID-19 pandemic was a major event that could have affected our behaviors. The objective of this work was to evaluate the weight change during and after deconfinement. We also collected data related to eating habits, stress and lifestyle. The questionnaire (about thirty questions), carried out on Sphinx, assessed diet, physical activity, anxiety, lifestyle, professional situation and anthropometric data. The data obtained is self-declared. This questionnaire was disseminated via social media. The study sample was made up of 608 individuals (42 years old [SD15 years old], M/F/: 31/69) who answered the 4 successive waves of questionnaires (beginning of confinement, middle, end and 1 month later) . At inclusion, 24.3% of the sample was overweight (BMI>25kg/m²), and 6.3% had a lean build (BMI<18.5kg/m²). During lockdown, the mean weight change was +0.4kg (SD 6.2kg); an average weight gain which stabilized after deconfinement (+0.1 kg [SD 5.7 kg]). In multivariate logistic regression models, age, sex and corpulence were not significantly associated with weight change during the confinement phase, although a trend was observed for more marked weight gain in women compared to men over this period (OR=1.54, 95% CI: 0.99–2.38). Similar results are seen during the post-lockdown period. No statistically significant interaction was observed between age, gender and body size. Among people who gained weight during the confinement period, this weight gain continued for 28.7% (while 53.8% declared weight loss). Our results are partly comparable to work in the literature which reports an average weight gain during the confinement period, although this weight variation is less in our partly selected study sample. The originality of this survey is based on the weight assessments after the confinement period, which assume that more than a quarter of the study sample showed a lasting weight gain. Lifestyles (place of residence, physical activity, etc.), stress and eating behaviors will be analyzed to better understand and explain, in a multifactorial way, these observations.