Abstract
Objective:
To assess the effects of the COVID-19 pandemic on weight loss, physical activity (PA), and sleep in adults with overweight/obesity participating in a 39-week weight loss intervention.
Methods:
Participants (n=81, 85% female, mean±SD 38.0±7.8 years, BMI 34.1±5.7 kg/m2) were enrolled in 3 separate cohorts. Cohorts 1 and 2 were studied prior to the pandemic (“pre-COVID cohorts”). Cohort 3 (“COVID cohort”) transitioned to a virtual intervention at week 6 when “stay-at-home” orders was implemented in Colorado. Weight was assessed at baseline, week 12, and week 39 with clinic scales before the pandemic, and home scales during the pandemic. Diet was assessed with Likert scales at weeks 4, 8 and 12. PA and sleep were assessed at baseline and week 12 with actigraphy.
Results:
Participants in the COVID cohort reported greater dietary adherence (p=0.004) and lost more weight than those in the pre-COVID cohorts at week 12 (−7.7±3.3 kg vs. −3.7±3.0 kg, p<0.001) and 39 (−8.5±4.4 kg vs. −2.8±4.6 kg, p<0.001). Energy intake did not differ between cohorts (p=0.51). The COVID cohort increased both sedentary time while awake and time-in-bed at night.
Conclusions:
Although the pandemic caused disruptions for the COVID cohort, participants still achieved weight loss with continued behavioral support.
Keywords: Obesity, Weight Management, Behavioral Strategies
Introduction:
Individuals with overweight/obesity are at higher risk for severe disease, hospitalizations, and death from the SARS-CoV-2 virus (1, 2). Social distancing guidelines intended to prevent viral spread during the COVID-19 pandemic resulted in major changes to daily routines (3). Several studies have demonstrated that individuals with overweight/obesity reported worsening mental health (4, 5), poor eating habits (6, 7), less physical activity (PA) (8), decreased sleep quantity and quality (9), and weight gain (4) since the onset of the COVID-19 pandemic. One study demonstrated that out of 723 adults with overweight/obesity, 79% of participants self-reported a decline in behaviors associated with successful weight management (10). However, most studies examined lifestyle parameters on adults with overweight/obesity using self-reported measures. Only a few studies examined PA using objective measures (11, 12) and even fewer assessed weight objectively (13). Studies evaluating the effects of the pandemic on objective measures of PA, sleep, and weight are lacking.
Therefore, this secondary analysis evaluates differences in weight loss, dietary adherence, PA, and sleep in individuals with overweight/obesity participating in a behavioral weight loss intervention prior to the COVID-19 pandemic as compared to those who participated in the same intervention during the pandemic. We hypothesized that “stay-at-home” orders and the transition to virtual classes would result in reduced adherence to the dietary intervention, decreased PA, disrupted sleep, and attenuated weight loss compared to previous cohorts who completed the intervention before COVID-19.
Materials and Methods:
Participants
Men and women aged 18–50 years with a BMI of 27–45 kg/m2 and weight stable (≤5% weight change over the previous 6 months) were recruited in 3 cohorts for a 39-week behavioral weight loss program, including a 12-week intervention followed by a 27-week follow-up period. Following informed consent, each participant underwent a history and physical exam and completed screening laboratory evaluations including HbA1c, lipid panel, comprehensive metabolic panel, TSH, and pregnancy test. Participants were excluded for history of untreated medical conditions (see Supplemental Materials), current night shift work, night eating syndrome, and binge eating behaviors. The Colorado Multiple Institutional Review Board approved the study protocol, and the study was conducted in accordance with the principles expressed in the Declaration of Helsinki (ClinicalTrials.gov: NCT03571048). Cohort 1 began the 39-week intervention in August 2018 and completed in May 2019; Cohort 2 began the intervention in April 2019 and completed in December 2019; and Cohort 3 began the intervention in February 2020 and completed the intervention in October 2020 (Figure 1). Cohorts 1 and 2 were unaffected by the COVID-19 pandemic and are referred to as the “pre-COVID cohorts”. Cohort 3 was at week 6 of the intervention when the stay-at-home order was issued in Colorado and is referred to as the “COVID cohort.”
Figure 1: Timeline of Study Cohorts and the Relationship between COVID-19 Stay-at-Home Orders and Study Outcomes.
(A) Timeline of study cohorts: intervention and follow up. Start of pandemic indicated by graphic in cohort 3. (B) Relationship between COVID-19 Stay-At-Home orders and study outcomes as defined qualitatively in the corresponding manuscript by Caldwell et al. (5).
Study Interventions
Following completion of the baseline assessments, all participants received a 39-week group-based behavioral weight loss program. Participants were randomized 1:1 to early time restricted eating plus daily caloric restriction (E-TRE+DCR) or daily caloric restriction alone (DCR). Participants in both groups were given a personalized calorie goal based on resting metabolic rate (indirect calorimetry) reduced by 10%. Suggested macronutrient content was 55% carbohydrates, 15% protein, 30% fat. Participants in the E-TRE+DCR group were also instructed to eat during a 10-hour window, starting within 3 hours of waking, while participants in the DCR group were not given any specific instruction regarding timing of food intake. Both groups received behavioral support provided by registered dieticians and based on the Prevent T2 curriculum (14). Randomized groups met separately on a weekly basis during the first 12 weeks and monthly during the 27-week follow-up period. Group meetings were held in person for Cohorts 1 and 2. The intervention for Cohort 3 transitioned from in-person to a virtual platform at week 6 due to the pandemic. All participants were counseled on the importance of PA and received a recommendation to perform 150 min/week of PA.
Outcome Measures
Anthropometrics:
Height (without shoes to the nearest cm using a stadiometer) was measured once at baseline. Morning fasted weight (in light clothing) was measured to the nearest 0.1 kg using a digital scale (DETECTO 6800) at baseline, week 12, and week 39. Non-fasted weight was collected weekly at in-person class meetings using a standardized scale (Tanita HD-351). For the COVID cohort, in-person weights were collected weekly for the first 6 weeks. After classes were moved to a virtual platform, participants took weekly fasted morning weights on their personal home scales and sent pictures of their weight to the study team during weeks 7 to 12, and monthly from weeks 13 to 39.
Body Composition:
Participants in the pre-COVID cohorts underwent measurement of body composition by dual x-ray absorptiometry (DXA, Hologic Inc., Bedford, MA) at baseline, week 12 and week 39. Measures of body composition were obtained only at baseline and week 39 in the COVID cohort.
Energy Intake:
Photographic food records from a consecutive 3-day period (2 weekdays and 1 weekend day) were used to estimate EI. A registered dietician used these pictures to estimate portion sizes, using the Portion Photos of Popular Foods guide (15). Dietary intake data were collected and analyzed using Nutrition Data System for Research software version 2019 (Nutrition Coordinating Center, University of Minnesota, Minneapolis, MN) (16).
Physical Activity:
Activity levels and postural changes were measured over 7 days, 24h/day using an ActivPAL (PALTechnologies, Glasgow, Scotland) at baseline and week 12. The ActivPAL was placed on the participant’s anterior thigh and used accelerometer-derived information to estimate time spent in different body positions. A time-stamped “event” data file was used to determine time spent sitting, standing, and stepping per day.
Free-living Sleep and Light Patterns:
Participants kept a written log of sleep/wake times and wore a wrist activity and light exposure recorder to document free-living sleep/wake patterns for 7 continuous days at baseline and week 12 (Actiwatch Spectrum, Philips Respironics, Bend, OR). Rest intervals (i.e., time in bed) were determined using a standardized hierarchical approach described by Patel et. al (17). Rest intervals were selected based on the combination of an event marker on the watch, the sleep diary, a light sensor on the watch, and activity data obtained by the watch. Sleep/wake status was then determined from a validated algorithm (Actiware version 6.0.9, Philips Respironics, Bend, OR).
Dietary adherence:
Self-reported adherence to the assigned study diet was assessed every 4 weeks with the question “Please rate your dietary adherence level during the past 7 days. Scores can range from ‘not adherent at all’ (1) to ‘perfect adherence’ (10). Difficulty of adherence to the study diet was assessed with the question “Please rate how hard it was to adhere to your prescribed study diet during the past 7 days. Scores can range from ‘not hard at all’ (1) to ‘extremely hard’ (10).”
Eating behaviors were assessed with the Three Factor Eating Questionnaire (TFEQ) (18) at baseline and week 12. The TFEQ assesses hunger, cognitive restraint, and disinhibition.
Statistical Analysis
There were no statistically significant differences in weight loss between treatment arms in the parent trial (19). The purpose of the present analysis was to evaluate weight loss responses predating COVID-19 compared to during the pandemic. Therefore, participants in the TRE+DCR and DCR groups were combined into the “pre-COVID cohorts” (cohorts 1 and 2) and a “COVID cohort” (cohort 3). Given that weight loss trajectories tend to slow over time, our first question addressed whether an attenuation of weight loss coincided with the onset of the pandemic in the COVID cohort and whether this changepoint differed from the one observed in the pre-COVID cohorts. Within each cohort group, a series of linear mixed effects models using random intercepts and slopes were used to identify whether there was a significant changepoint in weight loss during the intervention and which week the changepoint took place. The changepoints were tested from week 2 to week 11 in one-week intervals. Five-hundred samples created with simple random sampling with replacement were used to create bootstrapped confidence intervals (2.5th and 97.5th percentiles) for the changepoint in each group. If the confidence intervals excluded the start and end of the study, the changepoint was included in the final model. The final model was a linear mixed effects model with a random intercept and slope with week, cohort group, a week*cohort group interaction, as well as significant changepoints identified for each group as predictors. This model is referred to as the Bootstrapped changepoint model. As a sensitivity analysis, we employed a similar model, including a changepoint at week 7 for both cohorts in order to compare the average weight loss over equivalent time periods. This model is referred to as the Fixed changepoint model.
Differences in adherence, adherence difficulty, cognitive restraint, disinhibition, and hunger between cohort groups over time were assessed using random intercept linear mixed models. Fixed effects were included for time, cohort, and their interaction. Interactions that were not significant at an alpha level of 0.05 were removed from final models.
Differences in dimensions of PA (e.g., sedentary time and stepping time) and sleep (duration and timing) between cohort groups were evaluated using linear regression with week 12 measures as the outcome, adjusting for baseline, and using all available valid data in participants who completed outcome measures at both baseline and 12 weeks. Paired t-tests or Signed rank tests were used to compare baseline to week 12 measurements within cohort groups. Sensitivity analyses were conducted using linear regression to examine the influence of the change in the solar daylength, 24h light exposure, and evening light exposure on any observed changes in sleep duration and timing. Associations between changes in light and sleep outcomes were examined within each cohort group separately given seasonal differences in when the studies were conducted. Analyses were performed using SAS Version 9.4 (SAS Institute Inc., Cary, NC, USA). Comparisons below the alpha level of 0.05 were considered statistically significant.
Results:
Participant Characteristics
The study included a total of 81 participants (pre-COVID [n=55], COVID [n=26]) who started the 39-week intervention. Participant characteristics did not differ between cohort groups and are summarized in Table 1.
Table 1.
Baseline Demographics and Participant Characteristics
| Variable | Pre-COVID Cohort (N=55) | COVID Cohort (N=26) | Total (N=81) | P-value |
|---|---|---|---|---|
| Age, yrs | 37.4 (7.3) | 39.4 (8.7) | 38.0 (7.8) | 0.27 |
| Height, m | 1.7 (0.1) | 1.7 (0.1) | 1.7 (0.1) | 0.12 |
| Weight, kg | 93.6 (19.3) | 97.3 (15.7) | 94.8 (18.2) | 0.39 |
| BMI, kg/m2 | 34.1 (6.0) | 34.3 (5.1) | 34.1 (5.7) | 0.87 |
| Fat mass, kg | 40.9 (12.3) | 40.3 (9.9) | 40.7 (11.5) | 0.84 |
| Fat-free mass, kg | 51.5 (9.1) | 55.8 (9.8) | 52.9 (9.5) | 0.06 |
| Fat mass, % | 43.7 (5.8) | 41.8 (6.4) | 43.1 (6.0) | 0.18 |
| Sex | 0.15 | |||
| Female | 49 (89.1%) | 20 (76.9%) | 69 (85.2%) | |
| Male | 6 (10.9%) | 6 (23.1%) | 12 (14.8%) | |
| Race | 0.08 | |||
| Asian | 5 (9.1%) | 0 (0.0%) | 5 (6.2%) | |
| Black | 8 (14.5%) | 1 (3.8%) | 9 (11.1%) | |
| White | 42 (76.4%) | 24 (92.3%) | 66 (81.5%) | |
| Not Reported | 0 (0.0%) | 1 (3.8%) | 1 (1.2%) | |
| Ethnicity | 0.57 | |||
| Hispanic or Latino | 10 (18.2%) | 3 (11.5%) | 13 (16.0%) | |
| Not Hispanic or Latino | 44 (80.0%) | 23 (88.5%) | 67 (82.7%) | |
| Not Reported | 1 (1.8%) | 0 (0.0%) | 1 (1.2%) | |
| Highest level of education | 0.62 | |||
| High School | 2 (3.6%) | 0 (0.0%) | 2 (2.5%) | |
| Some College | 5 (9.1%) | 3 (11.5%) | 8 (9.9%) | |
| Bachelors | 19 (34.5%) | 12 (46.2%) | 31 (38.3%) | |
| Masters | 19 (34.5%) | 7 (26.9%) | 26 (32.1%) | |
| Doctorate | 7 (12.7%) | 4 (15.4%) | 11 (13.6%) | |
| Not Reported | 3 (5.5%) | 0 (0.0%) | 3 (3.7%) | |
| Employment status | 0.53 | |||
| Full or part-time employment | 46 (83.6%) | 24 (92.3%) | 70 (86.4%) | |
| Graduate student | 6 (10.9%) | 1 (3.8%) | 7 (8.6%) | |
| Unemployed or Not Reported | 3 (5.5%) | 1 (3.8%) | 4 (4.9%) | |
| Job type | 0.64 | |||
| Desk job, sedentary | 37 (67.3%) | 17 (65.4%) | 54 (66.7%) | |
| On feet, walking less than half day | 12 (21.8%) | 8 (30.8%) | 20 (24.7%) | |
| On feet, walking more than half day | 5 (9.1%) | 1 (3.8%) | 6 (7.4%) | |
| Not Reported | 1 (1.8%) | 0 (0.0%) | 1 (1.2%) | |
| Annual household salary | 0.49 | |||
| <25K | 5 (9.1%) | 2 (7.7%) | 7 (8.6%) | |
| 25K – 45K | 5 (9.1%) | 3 (11.5%) | 8 (9.9%) | |
| 45K – 70K | 12 (21.8%) | 3 (11.5%) | 15 (18.5%) | |
| 70K – 110K | 14 (25.5%) | 4 (15.4%) | 18 (22.2%) | |
| >110K | 18 (32.7%) | 12 (46.2%) | 30 (37.0%) | |
| Not Reported | 1 (1.8%) | 2 (7.7%) | 3 (3.7%) | |
| Marital status | 0.26 | |||
| Single | 15 (27.3%) | 6 (23.1%) | 21 (25.9%) | |
| Committed Relationship | 10 (18.2%) | 2 (7.7%) | 12 (14.8%) | |
| Married | 24 (43.6%) | 18 (69.2%) | 42 (51.9%) | |
| Divorced | 1 (1.8%) | 0 (0.0%) | 1 (1.2%) | |
| Not Reported | 4 (7.3%) | 0 (0.0%) | 4 (4.9%) | |
| Number of classes attended during 12-week intervention | 8.02 (2.77%) | 10.23 (3.33%) | 8.73 (3.12%) | 0.45* |
| Number of classes attended during 27-week follow-up | 2.13 (2.08) | 4.95 (1.40) | 2.97 (2.29) | 0.18* |
P-value from Poisson regression
Baseline characteristics of the pre-COVID cohort (n=48) and COVID cohort (n=22) who started the study. Age, height, weight, BMI, fat mass, fat-free mass, and percent fat mass are reported as mean (SD). Sex, race, ethnicity, highest level of education, employment status, job type, annual household salary, marital status, and number of classes attended are reported as number (percentage).
Weight loss
There were no differences between the pre-COVID cohorts and the COVID cohort in baseline body weight, BMI, or fat mass (Table 1). Weights were missing for 15.4% of those in the COVID group and 30.9% of the pre-COVID group at week 12 (p=0.14). At week 39, weights were missing in 26.9% of those in the COVID group and 25.5% of those in the pre-COVID group (p=0.88). Figure 2 shows a comparison of weight loss responses over 12 weeks between the cohort groups. Overall, there was a significant difference in absolute weight loss at week 12 by cohort groups (p<0.001), with the pre-COVID cohorts losing (mean [SD]) 3.87 [2.96] kg while the COVID cohort lost 8.79 [2.67] kg. This translated to a 4.3% [3.21%] weight loss in the pre-COVID cohorts and 7.92% [3.33%] weight loss in the COVID cohort by week 12 (p<0.001). There was also a significant difference in weight loss at week 39 by cohort group, with the pre-COVID cohort losing 2.75 [4.63] kg, while the COVID group lost 8.5 [4.37] kg, p<0.0001.
Figure 2: Comparison of Weight Loss Responses over 12 Weeks between Pre-COVID and COVID Cohorts.
Comparison of weight loss responses over 12 weeks between study cohorts 1 & 2 (pre-COVID cohorts) versus cohort 3 (COVID cohort). (A) Individual-level percent weight change over 12 weeks ranked in descending order with pre-COVID cohorts in grey and COVID cohort in black. The grey and black solid lines indicate average weight loss in each cohort grouping. (B) Raw (actual) weekly scale weights. (C) Significant changepoints in the weight loss trajectory were identified in the pre-COVID cohorts at week 4 and in the COVID cohort at week 7 (denoted by the asterix) using the Bootstrapped changepoint model. (D) Sensitivity analysis of weight loss slopes for both groups during weeks 1–7 using the Fixed changepoint model.
In the Bootstrapped changepoint model, significant changepoints in weight loss over time were identified in the pre-COVID group at week 4 (95% CI: 3, 6) and in the COVID group at week 7 (95% CI: 6, 9). Therefore, both changepoints were included in the final model. During the time periods in which the rates of weight loss were the highest, the pre-COVID group lost 0.73 (95%CI: −0.84, −0.63; p<0.001) kg/wk during weeks 1–4, while the COVID group lost 1.03 (95%: −1.15, −0.91; p<0.001) kg/wk during weeks 1–7. During the time periods in which the rates of weight loss started to slow, those in the pre-COVID group lost 0.18 (95%CI: −0.26, −0.09; p<0.001) kg/wk during weeks 5–12, while those in the COVID group lost 0.47 (95% CI: −0.60, −0.34; p<0.001) kg/wk, on average, during weeks 8–12. The slopes for weight loss before and after the changepoints were significantly different between cohort groups (p<0.001 for both comparisons. Figure 2C). These results were similar in the Fixed changepoint model (Figure 2D). During weeks 1–7, the pre-COVID cohorts lost 0.47 kg/wk (95%CI: −0.55, −0.39; p<0.001), while the COVID cohort lost 1.03 kg/wk (95%CI: −1.15, −0.91; p<0.001). During weeks 8–12, those in the pre-COVID cohorts lost 0.08 kg/wk (95%CI: −0.18, 0.01; p=0.08), while those in the COVID cohort lost 0.47 kg/wk (95%CI: −0.60, −0.34; p<0.001) on average. The slopes for weight loss before and after the changepoints were significantly different between cohort groups (p<0.001 for both comparisons).
Adherence
Self-reported adherence to the diets were assessed at weeks 4 (n=67), 8 (n=70), and 12 (n=66). The change in diet adherence and adherence difficulty did not differ by cohort group over time (p=0.49 and p=0.07, respectively). Adherence to the diet prescription decreased among all participants over time by 0.10 (95% CI: −0.17, −0.02; p=0.01) units per week on average, while adherence difficulty did not change (p=0.88). The COVID cohort rated adherence higher by an average of 1.14 units (95% CI: 0.37, 1.91) compared to the pre-COVID cohorts (p=0.004). However, there was not a significant difference in adherence difficulty between cohort groups (p=0.31).
Eating Behaviors
At baseline, cognitive restraint was higher in the pre-COVID cohorts than in the COVID cohort (pre-COVID cohorts 10.7 [4.1] vs. COVID cohort 7.7 [3.1], p=0.001). Neither disinhibition (pre-COVID cohorts 9.7 [3.4] vs. COVID cohort 9.4 [3.3], p=0.73) nor hunger (pre-COVID cohorts 6.2 [3.4] vs. COVID cohort 5.7 [2.5], p=0.49) were statistically different between the cohort groups at baseline. Between baseline and week 12, the pre-COVID cohorts increased cognitive restraint by 3.35 units (95%CI: 1.94, 4.76; p<0.001) while the COVID cohort increased by 7.64 units (95%CI: 5.55, 9.72; p<0.001). However, there was not significant difference between groups in cognitive restraint at week 12 (p=0.203) and the interaction between time and cohort group was not significant for disinhibition or hunger (p=0.90 and 0.46, respectively).
Energy Intake
Dietary energy and macronutrient content of participants in both groups at baseline and week 12 are reported in Table 2. Total energy intake decreased at week 12 as compared to baseline in both cohort groups with no significant difference between groups (Δ kcal/day pre-COVID cohorts −644 [710] vs. COVID cohort −662 [493], p=0.48).
Table 2.
Energy Intake
| Variable | Pre-COVID Cohorts, Baseline | Pre-COVID Cohorts, Week 12 | P-value, Within Group Change | COVID Cohort, Baseline | COVID Cohort, Week 12 | P-value, Within Group Change | P-value, Between Group Change |
|---|---|---|---|---|---|---|---|
| Sample size | N=49 | N=42 | N=40 | N=26 | N=22 | N=22 | |
| Total EI, kcal | 1712.6 ± 642.4 | 1196.7 ± 497.1 | <0.001 | 1975.4 ± 588.4 | 1279.2 ± 289.9 | <0.001 | 0.48 |
| Carbohydrate, kcal | 736.2 ± 342.0 | 520.3 ± 221.6 | <0.001 | 880.3 ± 281.2 | 608.0 ± 186.9 | <0.001 | 0.21 |
| Carbohydrate, % | 43.3 ± 9.4 | 45.0 ± 10.1 | 0.33 | 45.5 ± 6.9 | 47.6 ± 6.1 | 0.30 | 0.56 |
| Fat, kcal | 657.0 ± 262.6 | 437.9 ± 210.0 | <0.001 | 723.8 ± 259.3 | 433.7 ± 106.5 | <0.001 | 0.91 |
| Fat, % | 39.4 ± 7.9 | 35.9 ± 7.3 | 0.01 | 36.6 ± 5.4 | 34.4 ± 4.8 | 0.18 | 0.87 |
| Protein, kcal | 283.0 ± 108.8 | 222.5 ± 109.6 | <0.001 | 343.2 ± 122.8 | 220.4 ± 55.5 | <0.001 | 0.82 |
| Protein, % | 17.3 ± 4.2 | 19.1 ± 5.1 | 0.007 | 17.9 ± 3.8 | 18.0 ± 4.0 | 0.87 | 0.15 |
All results reported as mean ± SD. Values in the table include all available data at each timepoint. The p-values reflect between group changes in the N=40 in the pre-COVID cohorts and N=22 in the COVID cohort that had valid EI data at both timepoints.
Physical Activity/Sedentary Behavior
Activity behaviors at baseline and week 12 are shown in Table 3. There were no between-group differences in changes in stepping time, number of steps per day, step cadence, and total sitting time. However, there were significant differences between cohort groups in number of sitting bouts longer than 30 minutes and 60 minutes (p<0.001 and p=0.001, respectively) at week 12. On average, those in the COVID cohort had 1.55 higher sitting bouts longer than 30 minutes (95%CI: 0.8, 2.3) and 0.73 higher sitting bouts longer than 60 minutes (95%CI: 0.4, 1.1) at week 12, adjusting for baseline.
Table 3.
Physical Activity
| Variable | Pre-COVID Cohorts, Baseline | Pre-COVID Cohorts, Week 12 | P-value, Within Group Change | COVID Cohort, Baseline | COVID Cohort, Week 12 | P-value, Within Group Change | P-value, Between Group Change |
|---|---|---|---|---|---|---|---|
| Sample size | N=55 | N=47 | N=47 | N=25 | N=22 | N=21 | |
| Average stepping time min/d | 95.4 ± 30.3 | 105.7 ± 31.4 | 0.005 | 90.4 ± 21.2 | 88.6 ± 31.5 | 0.72 | 0.09 |
| Average number of steps/d | 7733.3 ± 2657.5 | 8562.9 ± 2762.0 | 0.01 | 7383.3 ± 1973.4 | 7197.7 ± 3104.0 | 0.91 | 0.18 |
| Average number of steps accumulated in stepping bouts with cadence > 75 steps/d | 5164.5 ± 2307.5 | 5634.3 ± 2183.0 | 0.04 | 4815.0 ± 1696.5 | 4633.2 ± 2820.4 | 0.83 | 0.33 |
| Average number of steps accumulated in stepping bouts with cadence > 100 steps/d | 2582.7 ± 1999.9 | 2870.2 ± 1886.2 | 0.08 | 2506.3 ± 1685.4 | 2729.6 ± 2638.3 | 0.51 | 0.69 |
| Average sitting time min/d | 624.9 ± 88.9 | 622.2 ± 88.5 | 0.25 | 637.5 ± 98.4 | 635.2 ± 116.1 | 0.98 | 0.52 |
| Average number of sitting bouts longer than 30 min/d | 4.6 ± 1.5 | 4.3 ± 1.4 | 0.17 | 5.0 ± 1.4 | 6.1 ± 1.6 | 0.001 | <0.001 |
| Average number of sitting bouts longer than 60 min/d | 1.1 ± 0.8 | 0.8 ± 0.7 | 0.03 | 1.2 ± 0.7 | 1.6 ± 0.7 | 0.11 | 0.001 |
Activity levels and postural changes were measured continuously over 7 days, 24h/day using the ActivPAL device at baseline and week 12. During COVID “stay-at-home” orders, study staff dropped off the ActivPAL device to the participants in the COVID cohort and instructed participants how to place the device on themselves. Study staff then picked up the devices at the end of the data collection period. All results reported as mean ± SD. Values in the table include all available data at each timepoint. The p-values reflect between group changes in the N=47 in the pre-COVID cohorts and N=21 in the COVID cohort that had valid PA data at both timepoints.
Sleep
Table 4 summarizes sleep patterns during weekdays and weekends at baseline and week 12. Participants in the pre-COVID cohorts reduced time spent in bed on weekdays from baseline to week 12, whereas participants in the COVID cohort increased time in bed on weekdays (Δ time in bed [hrs/d] pre-COVID cohorts −00:07 [00:46] vs. COVID cohort 00:23 [01:01], p=0.04). While the time for sleep onset on weekdays did not differ between the groups across time, the pre-COVID cohorts woke up slightly earlier at week 12 compared to baseline, whereas participants in the COVID cohort woke up later at week 12 (Δ sleep end pre-COVID cohorts −00:02 [00:59] vs. COVID cohort 00:51 [00:55], p=0.001). This translated to a shift in sleep timing on weekdays with the pre-COVID cohorts sleeping earlier than the COVID cohort (Δ sleep midpoint pre-COVID cohorts −00:02 [00:50] vs. COVID cohort 00:40 [00:45], p=0.005). In contrast, there were no differences between groups regarding changes in the same dimensions of sleep on the weekends. In a separate sensitivity analysis, solar day length and overall light exposure were not significant predictors of the delay in sleep observed in the COVID cohort (see Supplemental Materials).
Table 4.
Comparison of the change sleep duration and timing on the weekdays and weekends between the Pre-COVID and COVID-19 cohorts.
| Variable | Pre-COVID Cohorts, Baseline | Pre-COVID Cohorts, Week 12 | P-value, Within Group Change | COVID Cohort, Baseline | COVID Cohort, Week 12 | P-value, Within Group Change | P-value, Between Group Change |
|---|---|---|---|---|---|---|---|
| Weekdays | N=55 | N=46 | N=46 | N=26 | N=21 | N=21 | |
| Time in Bed | 07:21 ± 00:50 | 07:09 ± 00:48 | 0.34 | 07:06 ± 00:45 | 07:29 ± 00:57 | 0.09 | 0.04 |
| Sleep Duration | 06:50 ± 00:45 | 06:41 ± 00:46 | 0.43 | 06:37 ± 00:41 | 06:58 ± 00:54 | 0.11 | 0.06 |
| Sleep Onset | 23:07 ± 01:14 | 23:18 ± 01:13 | 0.51 | 23:14 ± 01:01 | 23:37 ± 01:12 | 0.03 | 0.10 |
| Sleep End | 06:29 ± 01:07 | 06:28 ± 01:06 | 0.86 | 06:20 ± 00:45 | 07:07 ± 01:00 | <0.001 | 0.001 |
| Sleep Mid-Point | 02:48 ± 01:06 | 02:53 ± 01:05 | 0.82 | 02:47 ± 00:48 | 03:22 ± 01:00 | <0.001 | 0.005 |
| Weekends | N=55 | N=44 | N=44 | N=25 | N=21 | N=20 | |
| Time in Bed | 07:42 ± 01:30 | 07:29 ± 01:50 | 0.44 | 07:14 ± 01:26 | 07:23 ± 01:12 | 0.85 | 0.86 |
| Sleep Duration | 07:07 ± 01:22 | 06:59 ± 01:44 | 0.48 | 06:48 ± 01:21 | 06:50 ± 01:09 | 0.90 | 0.73 |
| Sleep Onset | 23:32 ± 01:27 | 23:51 ± 01:41 | 0.22 | 23:28 ± 01:09 | 23:58 ± 01:20 | 0.02 | 0.60 |
| Sleep End | 07:28 ± 01:10 | 07:32 ± 01:17 | 0.95 | 06:58 ± 01:31 | 07:36 ± 00:58 | 0.08 | 0.41 |
| Sleep Mid-Point | 03:30 ± 01:08 | 03:41 ± 01:14 | 0.31 | 03:13 ± 01:10 | 03:47 ± 01:01 | 0.01 | 0.28 |
All results reported as mean ± SD. Values in the table include all available data at each timepoint. The p-values reflect between group changes in participants that had valid sleep data at both timepoints.
Discussion:
This analysis evaluated how weight loss, diet adherence, PA, and sleep patterns changed during the early phase of the COVID-19 pandemic in individuals with overweight/obesity participating in a behavioral weight loss trial. Participants in the COVID cohort reported greater dietary adherence and lost more weight than those in the pre-COVID cohorts at 12 weeks and 39 weeks. In addition, the COVID cohort increased sedentary time during the day and time in bed attempting to sleep during the weekdays.
Several studies using self-report surveys have demonstrated increased anxiety and declining mood in conjunction with difficulty maintaining weight (20), eating well (21), engaging in PA (22), and sleep (23) during the pandemic. Using data from the same individuals included in the present analysis, we recently reported a significant increase in stress and anxiety as individuals adjusted to stay-at-home orders (5). The participants in our study cited challenges such as difficulty obtaining fresh foods from grocery stores and decreased exercise due to gym closures. Only 26% of participants reported an improvement in eating behaviors and 22% reported an easier time obtaining PA. Given the strains on mental health, access to resources, and disrupted work-life schedules (Figure 1), we expected that participants who participated in our behavioral weight loss trial virtually as a consequence of stay-at-home orders would struggle more with weight loss and adherence to diet. Interestingly, the findings of the present analysis suggest otherwise.
Despite the disruptions that COVID-19 lockdown orders posed to our participants, weight loss was significantly higher overall in the COVID cohort compared to those in the pre-COVID cohorts. Of note, those in the COVID cohort reported better adherence to dietary prescriptions at baseline and throughout the intervention. It is possible that greater adherence to the intervention was due to higher motivation at baseline or greater group cohesiveness. Qualitative data from surveys in the COVID cohort did suggest that many participants found group support to be helpful in the face of the pandemic (5). The COVID cohort had lower cognitive restraint at baseline but similar restraint to the pre-COVID cohorts at 12 weeks, so it is possible that changes in restraint contributed to improved weight loss in the COVID cohort, as previous dietary intervention studies have shown that a greater increase in cognitive restraint during an intervention predicts greater weight loss (24, 25). The COVID cohort also had a faster rate of weight loss in the first half of the intervention, which is known to predict greater overall weight loss (26). It is likely that the greater weight loss response in the COVID cohort was due to better adherence throughout the intervention, consistent with previous studies showing that higher dietary adherence predicts greater weight loss (27).
Physical activity was another behavior that we predicted would be negatively impacted by COVID-19. In a recent descriptive study evaluating step counts of more than 450,000 unique users across 187 countries of the health and wellness using a smartphone app, there was a 27.3% decrease in mean steps, although there was wide regional variation (8). A systematic review by Stockwell & Trott et al. (22) evaluated articles published during November 2019 to October 2020 of the pandemic and found that the majority reported a decrease in PA. In our recent study, participants reported that decreased PA was the third greatest challenge to weight loss, with 68% of survey respondents stating that it was harder for them to adhere to PA. Though participants in the COVID cohort had more bouts of sitting for more than 30–60 minutes at week 12, this may have been due to increased time spent working from home. Further, our qualitative data paired with the present study’s quantitative findings suggest that despite perceptions, the median time spent exercising remained at 45 minutes/day, with more PA taking place on weekdays. Similarly, there were no differences between the cohort groups in step counts. This further supports our findings that dietary adherence and behavioral support during the pandemic were more impactful for weight loss in the COVID cohort at 12 weeks.
We predicted an increase in sleep duration due to reduced time required to commute to work for participants who had shifted to working from home. Studies to date have found variable effects of the early phase of the pandemic on sleep. For example, Wright et al. (28) evaluated university students before and during “stay-at-home” orders. Participants spent more time in bed devoted to sleep and sleep timing became delayed (29). Sinha et al. (30) showed a discordance between social and natural cues with later sleep onset and wake times. The present study demonstrated similar patterns. Specifically, participants in the COVID cohort spent more time in bed during the weekdays by week 12 but had no changes in sleep patterns on the weekends. As such, participants adopted a sleep schedule that led to a delay in sleep timing on the majority of days across the week of recording, which could have metabolic consequences if sustained long-term (31).
Our study underscores the importance of behavioral support for successful weight loss, particularly in the face of stress and anxiety. We were able to adapt the delivery of our support to a virtual platform, and participants indicated that this helped them overcome some of the barriers to weight loss posed by the pandemic (5). In contrast to other studies reporting weight gain during the pandemic (4), our data show that in the context of behavioral support, weight loss was not only possible but greater than previous cohorts in the same study.
A limitation of this study was the use of home weights in the COVID cohort between weeks 7 and 39 due to institutional measures which prevented in-person visits. However, to ensure reliable reporting, participants in this cohort took pictures while standing on the scale to verify the weight reading and confirm that the same scale was used. In addition, weight at week 39 was assessed in person, and weight loss was similar in the COVID group at week 39 and week 12, suggesting that the home weights were reliable. Nonetheless, the use of various home scales may have impacted the rates of overall weight loss seen. Dietary adherence was self-reported via Likert scales, which is another limitation to our study. Finally, our study population consisted primarily of highly educated Caucasian women, making our findings potentially less generalizable. It is possible that findings would have differed with a more diverse sample given that individuals of lower socioeconomic status have been more adversely affected by the pandemic (32). Ninety-two percent of participants in the COVID cohort were white, compared to only 76% in the pre-COVID cohorts. Although identical recruitment strategies were used, racial differences may have contributed to the attenuated weight loss in the pre-COVID cohorts (33). However, distribution of racial and Hispanic or Latino minorities was similar to or exceeded the breakdown of racial/ethnic groups in Denver (34).
Obesity is associated with increased risk of severe COVID-19 illness, hospitalization, and mortality (35, 36). These findings suggest a need to focus on weight loss and improving healthy lifestyle behaviors in adults as a protective measure against severe COVID-19. This study showed that although the COVID-19 pandemic and associated stay-at-home orders disrupted traditional weight loss strategies and generated increased stress and anxiety, weight loss was greater in those affected by COVID-19 than prior cohorts not affected by COVID-19. The ability to adapt the behavioral support components of a weight loss trial appears to have been central to ensuring continued weight loss in participants in the face of adversity. This is relevant to future behavioral weight loss studies as major life changes and stressors are common outside of a global pandemic. Offering a virtual support platform is also likely to play a major role in future weight loss trials as working from home and use of virtual platforms have become a mainstay in society.
Supplementary Material
STUDY IMPORTANCE QUESTIONS:
- What is already known about this subject?
- Individuals with overweight/obesity are at higher risk for severe disease, hospitalizations, and death from the SARS-CoV-2 virus.
- Studies to date have demonstrated that individuals with overweight/obesity reported worsening mental health, poor eating habits, less physical activity, decreased sleep quantity and quality, and increased weight gain in the face of COVID-19 lockdown measures, but these studies have not included objective measures of body weight, physical activity, and sleep.
- What are the new findings in your manuscript?
- Despite COVID-19 disruptions, participants in a 39-week behavioral weight loss intervention had greater weight loss at weeks 12 and 39 compared to two cohorts that participated in the same study prior to COVID-19.
- Participants in the cohort conducted during the COVID-19 pandemic demonstrated greater dietary adherence as well as greater increases in sedentary time, time in bed, and time asleep from baseline (pre-pandemic) to week 12 as compared to the cohorts conducted prior to the pandemic.
- How might your results change the direction of research or the focus of clinical practice?
- While the general population of adults with obesity struggled to lose or maintain weight during the COVID-19 pandemic lockdown, participants who received behavioral support while enrolled in a behavioral weight loss trial were successful in losing weight.
Acknowledgements:
We would like to thank our study participants.
FUNDING:
This research was supported NIH/National Center for Research Resources Colorado Clinical and Translational Sciences Institute Grant UL1 RR025780 (CAR, EAT); NIH/National Institute of Diabetes and Digestive and Kidney Diseases R21 DK117499 (EAT, MAC, VAC, CAR, LG, KJS), KL2 TR002534 (EAT), K01 DK113063 (CAR), F32 DK123878-01A1 (AZ), and K01 HL143039 (AEC); and Doris Duke Charitable Foundation Grant 2015212.
Footnotes
ClinicalTrials.gov Identifier: NCT03571048
DISCLOSURES: No conflict of interest to declare.
Data Sharing Plan: Individual deidentified data used for this article, study protocol, statistical analysis plan, and analytic code are available upon a reasonable request to the corresponding author.
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