Altered nutrition behavior during COVID-19 pandemic lockdown in young adults

Abstract

Purpose: The COVID-19 pandemic and the implemented lockdown strongly impact on everyone's daily life. Stressful situations are known to alter eating habits and increase the risk for obesity. In our study, we aimed to investigate the effect of the lockdown measures on nutrition behavior among young adults.

Methods: In this cross-sectional study, we enrolled 1964 voluntary participants from Bavarian universities. All participants were asked to complete an online questionnaire, semi-quantitatively evaluating the amount and type of food before and during pandemic lockdown. Study subjects were inquired to give information about acquisition and food procurement. The primary outcome was the change in food amount, secondary outcomes included alterations of food composition and procurement.

Results: Our study cohort (mean age 23.3 ± 4.0 years, 28.5% male) had a mean body mass index of 22.1 ± 4.5 kg/m². The overall food amount increased in 31.2% of participants (n = 610) during lockdown and decreased in 16.8% (n = 328). A multinominal regression model revealed that an increased food intake was less likely in male participants (OR, 0.7 [CI 0.6-0.9]) and more likely with increasing BMI (OR, 1.4 [CI 1.3-2.0]), increased sports activity (OR, 1.3 [CI 1.2-1.8]), augmented mental stress (OR 1.4 [1.1-1.7]), and an alteration of alcohol consumption (reduced alcohol amount, OR, 1.4 [CI 1.1-1.7], increased alcohol, OR, 1.9 [CI 1.4-2.5]). Increase in food intake was mainly triggered by consumption of bread (increased in 46.8%, n = 284) and confectionary (increased in 64.4%, n = 389).

Conclusion: The COVID-19 pandemic lockdown significantly affected eating habits in young adults. Further investigation to evaluate long-term effects on weight change and comorbidities are warranted.

Trial registration: ClinicalTrials.gov NCT04361877.

Keywords: COVID-19 pandemic lockdown; Cardiovascular prevention; Dietary habits; Eating behavior; SARS-CoV-2; Students.

Fig. 1

Daily new cases in Bavaria: timeline showing the number of new confirmed infections with SARS-CoV-2 in Bavaria per day (gray bars) and the cumulative number of cases (red line). The first confirmed case of COVID-19 in Bavaria was on the 27th of January (dotted line), which was also the first case in Germany. Lockdown was implemented by the local authorities in Bavaria on the 21st of March (line). Study participants were asked to compare their eating habits before the lockdown (pastel green area) to during the study period (yellow box) since implementation of the lockdown (pastel red area)

Fig. 2

Food procurement before and during lockdown: Participants were asked in multiple choice questions to name their main ways of food procurement before and during COVID-19 lockdown. Home cooking is the main food source before (94.8%, n = 1861) and during (98.5%, n = 1935) lockdown. A dramatic decline was seen in restaurants (46.4%, n = 911 to 1.9%, n = 37) and cafeterias (48.5%, n = 953–2.5%, n = 50). No changes were seen for food deliveries or readymade food (18.0, n = 353–16.0, n = 315)

Fig. 3

Quantification of food quantity before and during lockdown: (A) participants were asked if the amount of food intake had changed after the lockdown. Most participants, 52.1% (n = 1019) reported to not have altered their food amount. 16.8% (n = 328) stated to eat less and 31.2% (n = 610) to eat more compared to before the lockdown

Fig. 4

Alteration of food amount stratified by BMI: participants were stratified by BMI. Numbers are given in Table 2. Alterations in food intake were significantly different for the three categories (p = 0.018). More participants with a high BMI (> 25 kg/m²) (57.3%, n = 146) than with a low BMI (< 20 kg/m²) (45.9%, n = 208) or a normal BMI (20–25 kg/m²) (47.0%, n = 581) changed the amount of food they eat compared to before implementation of lockdown

Fig. 5

Forest plots depicting odds ratios for variables impacting a decreased or an increased food amount. Subgroups of decreased and increased overall food intake were referenced to a constant food intake. Odds ratios (OR) and 95% confidence intervals (CI) are depicted with balls and bars, respectively, for the different categories. Changes in food consumption were promoted by gender, BMI, sports activity, alcohol consumption and smoking status. Detailed data and reference categories are shown in Table 2

Fig. 6

Change in food categories in participants with an increased or decreased overall food intake. In all participants, bread and confectionary intake changed more than other food categories. Among people reporting to have increased their food amount, confectionary consumption increased more compared to people who reported to have decreased their total food amount (64.4%, n = 389, vs. 25.0%, n = 82, p < 0.001). Significant differences were also seen for the amount of meat and bread consumed. No differences were observed for vegetables or fruits. Dairy product consumption was affected the least (eat less, 57.2%, n = 187, vs. eat more, 59.6%, n = 362, did not change the amount)