COVID-19 Induced Stress, Lifestyle Changes and Weight-gain in Youth during a 4-Month Lockdown: A Prospective Cohort Study


 The COVID-19 (coronavirus disease-19) has resulted in nationwide lockdowns, cessation of school and work, and social distancing. Reducing the negative impacts, such as weight-gain, has garnered global attention. In this dual-center prospective cohort study of 12,889 students, we assessed weight-gain in a youth during the 4-month COVID-19 lockdown, and examined the associations between weight-gain and COVID-19 induced stress, depression and self-reported physical activity, dietary habits and sedentary time. Participants gained an average of 2.6 kg (95% CI: 2.0 to 3.2 kg) for males and 2.1 kg (1.9 to 2.4 kg) for females. An increase in overweight and obese individuals as a demographic percentage by 4.5% and 2.7% and 4.8% and 3.4% in males and females respectively (P<0.001). Weight change was independently associated with severe COVID-19 induced stress, sedentary time, and depression score. Techniques to relieve COVID-19 induced stress, reduce sedentary time through increased physical activity, and improve dietary habits in youth may be warranted to help prevent and/or reverse weight-gain associated with the lockdown period of COVID-19.Registration: Registered with ChiCTR, registration no.: ChiCTR2000033514


Introduction
The sudden emergence of COVID-19 (coronavirus disease-19) has reverberated the world over, pushing peoples and governments into the unchartered territories of countrywide lockdowns and social distancing. On January 20, 2020, China issued a national lockdown as a measure to halt the spread of the deadly virus. While this strategy was largely successful, its negative effects will be of consequence to the health of youth, as for four months they were out of school and for the most part, stuck in the confines of their homes. 1 With these lockdowns comes the possibility of weight change that may be associated with amplified stress, depression, anxiety, sedentary time, unhealthy dietary habits, and more, reducing the negative impacts of lockdown on the general public has attracted global attention.
Weight-gain compared to stable weight during adolescence and early adulthood is associated with a significantly increased morbidity of diabetes and cardiovascular disease, and an increased risk of cardiovascular and all-cause mortality. 2,3 The increase of weight is a multifactorial matter, yet existing evidence on these factors is largely limited due to a tendency in studies to do a univariate analysis of behaviours on weight-gain. Furthermore, trials that focus on weight loss tend to enlist already obese subjects and intervene with specialized diets attenuating short-term weight loss, limiting the extrapolation of the findings to other populations. Notwithstanding, longterm observational studies have found dietary factors, and time spent watching TV were associated with long-term weight-gain in healthy populations. 4 To date, no studies have been published relating to weight change and its associated factors during the COVID-19 lockdown period.
This dual-center prospective cohort study assessed weight change during the pandemic lockdown through a multifactorial analysis of associated exposure variables.
This study is important because it will help identify factors that could be helpful in the prevention and/or reversal of weight-gain during community-wide shutdowns, such as the ongoing COVID-19 pandemic.

Study design and participants
This prospective cohort study enrolled youth from two universities (Hunan Traditional Chinese Medical College, Hunan, China, and Medical College of Jinhua Polytechnic, Zhejiang, China) that performed the Chinese National Student Physical Fitness Standard (CNSPFS) battery between December 1, 2019, to January 20, 2020, when the government issued sanctioned lockdowns and social distancing. A total of 14,059 university students who were free of chronic diseases and had completed the CNSPFS were screened. Of these, 13,013 participants (response rate of 93.2%) completed a follow-up online questionnaire beginning on May 1, 2020, and ending on May 23, 2020. The participants who replied with questionnaires of poor quality were excluded (n = 124). A total of 12,889 participants were finally recruited in the study.
All baseline data were extracted from the CNSPFS system, follow-up data were collected from a professional survey platform (https://www.wjx.cn). The criteria of poor quality were: (1) ID information in the CNSPFS system did not match that in the follow-up questionnaire; or (2) The 81 question survey was completed in less than three minutes.

Characteristics of Lockdown
The first lockdown order in China was delivered on January 23rd, 2020 by the government of Wuhan, Hubei province, followed by the other cities and provinces of China. The main requirements included: (1) all individuals were ordered to stay home or at their place of residence, except for permitted work, local shopping or other permitted errands, or as otherwise authorized. (2) all schools, sports facilities, entertainment, and recreational venues, personal care and beauty services, and the majority of factories and markets were closed.

Weight change
Baseline weight was assessed by staff members of the two respective universities.
This was done in accordance with CNSPFS standards for all university students across China. Follow-up body weight was obtained via questionnaire. Concerning the determination of follow-up body weight, all participants were asked to measure their body weight in the morning right after waking up, in a state of fasting, shoes off, no large coat. Weight change was calculated by subtracting baseline weight from followup weight and the results were verified according to perceived weight change. Weight change was further classified as no significant change (-0.9 to 0.9 kg), mild decrease (-3.9 to -1.0 kg), moderate decrease (-6.9 to -4.0 kg), major decrease ( -7.0 kg), mild increase (1.0 to 3.9 kg), moderate increase (4.0 to 6.9 kg), major increase ( 7.0 kg).

COVID-19 induced stress, depression and anxiety
The question used to measure COVID-19 induced stress was designed based on previous research 5 : How concerned are you about yourself, or family members/friends being infected by COVID-19? To which the possible answers were: None; Mild; Moderate; Major; Severe. Two psychological indexes were also used, Becks' Depression Inventory, second edition (BDI-II) 6 and the State-Trait Anxiety Inventory (STAI) (Form Y-1). 7

Physical activity
Physical activity was classified as exercise and free-living activity. Exercise habits were collected through questions regarding exercise pre-and post-lockdown, these included frequency, duration, and intensity of aerobic exercise as well as strength exercise. Exercise volume was expressed in MET-hr/wk, calculated according to the American College of Sports Medicine (ACSM) metabolic equations prior to and during the lockdown. 8 Sedentary time, defined as any waking behaviour where energy expenditure is ≤ 1.5 MET's while reclining or sitting, included the number of hours a day spent using a computer or mobile phone. 8

Dietary habits
In this study, food composition was not assessed due to the high participant burden of such a questionnaire and data collection limitations. The present study evaluated the dietary habits, including breakfast and lunch frequency, alcoholic drinks per week, and snacking times per day. Breakfast and lunch were categorized into three groups: less than once a week, two to six times per week, every day. Snacking was also categorized into three groups: no snacking, snacking once a day (day or late-night), snacking twice per day (day and late-night). Alcohol habits were recorded as the number of drinks, one drink was defined as drinking 100 ml wine or liquor, or 1 glass/bottle/can of beer.

Statistical analysis
The primary outcome (dependent variable) of the present study was weight change over the lockdown, the independent variables were COVID-19 induced stress, depression, anxiety, physical activity, and dietary habits. Paired t-test and Wilcoxon signed-rank test were used for assessment in mean difference between baseline and follow-up of continuous and ordinal variables respectively. The independent relationships of COVID-19 induced stress, depression, anxiety, physical activity, and dietary habits to weight changes within the lockdown, using multivariable linear or binary logistics regression models and accounting for within individual repeated measures were assessed accordingly. Potential nonlinear effects of decreases versus increases in each variable were evaluated by modelling changes in indicator categories, with "no change" as the reference. Multivariable models were used to adjust for sex, age, baseline weight, physical activity, dietary habits, and psychological status simultaneously. To minimize confounding from geolocation and baseline overweight/obesity, university-and BMI-stratified multivariate linear regression were used. Additionally, results were analyzed as relative weight changes (percent), and weight change was a binary variable (weight-gain versus weight loss).
Analyses were carried out with the use of SAS software, version 9.4 (SAS Institute), a two-tailed alpha level of 0.05 was considered significant.

Demographics and Weight-gain
Demographics of 12,889 participants aged 19 1 are presented in Table 1. Female subjects were proportionally a larger percentage of the population, which is due to subjects being selected from medical schools largely populated by females. The average weight-gain across the universities was 2.6 (95% CI, 2.0 to 3.2) kg for males and 2.1 [1.9 to 2.4] kg for females, while across sex was 4.2% of baseline body weight. There was a significant increase in overweight and obese individuals as a percentage of the population by 4.5% and 2.7% and 4.8% and 3.4% in males and females respectively. None of the participants of the study were infected with COVID-19. More details are shown in Figure 1 A-E and supplementary Table 1.

COVID-19 induced stress, depression and anxiety
More than one-third of all participants (34.6% of males and 42.4% of females) suffered COVID-19 induced stress in different degrees, and 6.9% of males and 7.4% of females responded to having severe stress. There was a significant difference in severe COVID-19 induced stress between males and females (P<0.001). The depression score obtained from BDI-II were 5 ± 8 (mean ± SD) and 6 ± 8 in males and females respectively. The anxiety score using STAI was 39 ± 10 both in males and females. More details are shown in Supplementary Table 2.

Dietary habits
Males (1.8 ± 2.9 drinks) drank more than females (0.7 ± 1.6 drinks), the mean difference and 95% CI was 1.  Figure 1F and G, and Supplementary Table 1.  Figure 2 A-C, Supplementary Table 3-5). However, the weight of the subjects whose stress is between mild-major had no statistical significance.

Relationships of COVID-19 induced stress, depression and anxiety to weight change
Depression score was also independently associated with weight change in males participants with a greater increase in depression score gained 0.14 kg more ( Figure   2B). There is a significant relationship between anxiety and weight change in females   Figure 3).

Additional Analyses
All results were similar when evaluated as relative (percent) weight changes rather than absolute weight changes, and when weight change as a binary variable (weightgain versus weight loss) ( Table 3, Figure 2 A-C, Supplementary Table 3-5).
Correlations of COVID-19 induced stress to DBI-II depression score, STAI anxiety score, physical activity and dietary habits were generally small (r<0.05).

Discussion
This is the first prospective multivariate analysis aimed at exploring the burden of to be associated with weight-gain. 14 Additionally, instances of high to extreme levels of stress can influence eating behaviours, a factor which is more evident with higher severity of stress. 15 Additionally, stress is thought to affect PA also, a comprehensive review found the majority of 55 longitudinal studies supported an association between stress and lower levels of PA. 16 However, in our study the correlation between stress and changes in PA or dietary habits was quite low (r<0.05). 17 Nevertheless, the mechanism behind this remains unknown and out of the scope of this research.
Furthermore, social isolation and confinement are possible routes towards depression. 18 Our results may be due in part to the interplay between social isolation and depression on weight, as reflected by our findings that BDI-II depression score was associated with increased body weight in males (0.02 [0.01 to 0.05] kg) and females (0.02 [0.01 to 0.03] kg). This is in agreement with a consortium of previous studies, whereby depression appears to have a significant effect on short-term and long-term weight-gain. 19,20 The pathways thought to be responsible for this association, may be the adoption of less healthy eating patterns, such as the excessive intake of carbohydrate-rich foods, or to a lack of motivation towards activities that require physical effort such as exercise or sport. 19,21 In this study anxiety was a minimal contributor to weight-gain in females, but not males ( Table 2). Anxiety during the lockdown also appears to be more commonly present in females rather than males, which supports previous studies that during the pandemic state anxiety appears to affect females more than males. 22 Energy balance and therefore weight-gain is heavily mediated through physical activity. Increased levels of PA, whether as exercise or free-living PA will accordingly increase energy expenditure, any decrease in such will likewise decrease energy expenditure. 23  reason for not exercising. Also, adherence to exercise is often extrinsic, particularly in youth, where exercisers do so because of physical appearance, weight-gain and stress management adding plausibility that exercise may have been increased as management for perceived weight-gain and/or stress and due to more available time.
Weight-gain also comes through increased intake of calorie-rich food, large portions and dependent on food composition 29 leading to weight-gain. Although this study did not report on dietary composition, it did investigate dietary habits using four parameters, namely: snacking, breakfast, and lunch frequency and alcohol intake.

Competing interests
No potential conflicts of interest relevant to this article were reported by any of authors.

Ethical approval
This study received ethical approval from the Medical Ethics Committee of Xiangya Hospital, Central South University (REC reference: 202005126). All participants gave consent before enrolment in the study, which was conducted in accord with the principles of the Declaration of Helsinki.

Data Sharing Statement
The data that support the findings of this study are available on request from the corresponding author, SXL. The data are not publicly available due to their containing information that could compromise the privacy of research participants.

Transparency
The manuscript's guarantor (SXL) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Brief statements of assistance
We would like to thank all participants and investigators in participating centers. We would also like to thank Jiabi Qin and Jing Deng (Xiangya School of Public Health, Central South University, Hunan, China), who provided advice on the statistical analysis plan.   Multivariable model was used to adjust for sex, age, baseline weight, the change in exercise volume, dietary habits (including breakfast and lunch frequency per week, and snacking frequency per day), alcohol, smoking, anxiety score, and all the variables shown in the table simultaneously. Mean variance inflation factors were 1.14, 1.15, and 1.15 for males, females and total analyses respectively. Data were expressed as weight change associated with increase in sedentary time and depression score.
¶ For COVID-19 induced stress, no stress was a reference.   (n = 9,108 subjects with weight-gain, 2,618 with weight loss). P < 0.001 for all comparisons.