Determinants of weight, psychological status, food contemplation and lifestyle changes in obese patients during the COVID-19 lockdown: a nationwide study using multiple correspondence analysis

Survey Responses

Twenty-six centers (46% of those invited) agreed to recruit participants. Details about each center are listed at the end of the manuscript in the Study Network Members section. The total number of telephone contacts was 2319. Of these, 1087 patients (46%) did not complete the questionnaire due to time pressure or privacy reasons. Of the 1,232 patients enrolled in the study, 875 respondents (71%) were interviewed by phone, while 357 (29%) completed the online questionnaire. No differences in baseline characteristics and responses were observed between the two groups. The median number of patients enrolled in each center was 48 (range 4-160).

Respondent demographics and anthropometry

The mean age of the respondents was G50.5 ± 14.3 years (range 11-85). More than 50% of the participants lived in Southern Italy, while about 30% lived in Northern Italy. Seventy-two respondents were female and the proportion was consistent across regions. Respondents had completed secondary school (29%) or high school (41%) and were employed (37%), housewife (16%) or retired (15%). The mean weight was 94.9 kg (range 57-200) at the time of the interview, with a mean BMI of 34.5 ± 7.49 kg/m22 (range 21.8–58.6). BMI categories were overweight 24%, obesity class I 30%, obesity class II 22% and obesity class III 18%.

Lifestyle changes during lockdown

During the lockdown period, 48.8% (N = 601) of PWO experienced weight gain and 27.1% (N = 334) weight loss, while body weight remained unchanged in 24.1% (N = 297) (Table 1† The mean weight change was +2.3 (±4.8 kg). The weight gain was 4.2 kg (±2.6 kg) under PWO gaining weight, with a percentage increase of 4.7 ± 2.9%. Differences in weight gain between individual job categories did not reach statistical significance.

Table 1 General characteristics of participants by weight change. ADI STUDY. May June. 2020. Italy.

Table 1 summarize the results by categorizing participants by weight change status (unchanged, lost, and gained). No statistically significant differences were found between the three groups of patients for age, gender, education level, work status, working from home or not, and residential area based on the incidence (low-medium-high) of positive COVID cases. The lifestyle and emotional characteristics of the participants due to weight change are presented in table 2† About 37% of all respondents had more emotional problems, mainly anxiety and dissatisfaction, while boredom and depression were less frequent. Sixty-one percent of all PWOs reduced their PA, and approximately 55% of participants who experienced a change in sleep quality/quantity with insomnia or early awakening were weight gain (p > 0.001).

Table 2 Lifestyle and emotional characteristics of participants according to weight change. ADI STUDY, May-June 2020, Italy.

Correlations with weight gain

Table 2 lists significant correlations between the variables studied and weight gain (p < 0.001). Psychophysical well-being was reduced in 69.6% of PWO with weight gain and in 17% and 13% of obese patients with unchanged weight or weight loss, respectively. Emotional problems (weight gain 62%, unchanged 17% and weight loss 21%), changes in sleep quality/quantity (54%, 23% and 22%), decreased PA (56%, 21%, 22%) and difficulty tracking the diet (68%, 15%, and 15%) were more common in those who reported weight gain.

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Use of telemedicine

The majority (62.5%) of PWO had the ability to stay in touch with their healthcare consultant via phone, social media, video calls, or emails. Lack of contact was found to be significantly associated with weight gain (weight gain 57.8%, stable weight 28.2% and weight loss 13.9%) (pvalue < 0.001).

Fifteen percent of the participants considered using obesity medications. This statement was made by 68.4% of those who gained weight, 21.8% of those of stable weight and 9.8% of the PWO who experienced weight loss (pvalue < 0.001).

Multiple Linear Regression Analysis

The effect of some determinants on the weight difference (weight after lockdown vs weight before lockdown) was also examined. Table 3 shows that compared with participants with unchanged psychophysical well-being, those who reported increased psychophysical well-being experienced a statistically significant mean weight decrease of 2.27 kg (p< 0.001), while those with reduced psychophysical well-being gained 1.02 kg (p= 0.001). Compared to participants who identified themselves as physically inactive, those who reported an increase in PA lost an average of 1.94 kg. Respondents who indicated that they started to think more about food compared to those who reported no changes had a coefficient of +1.81 (p< 0.001) (a mean weight gain of 1.81 kg), while participants with "reduced food contemplation" had a statistically significant weight change of − 1.87 kg (p<0.001) compared to those who reported no weight change. Respondents who "attributed greater value to food than before" compared to those who "attributed "unchanged value to food" had a coefficient of +1.15 (p< 0.001). PWO in contact with their OCs had a coefficient of −1.10 (p< 0.001). This means that they had an average weight loss of 1.10 kg compared to the reference group, ie those who had no contact with their OCs. Respondents without reference OC at the time of the survey/study had a coefficient of +1.01 (p= 0.005). The interpretation is that they had an average weight gain of 1.01 kg compared to the reference group, that is, those who had referred OC but had no contact.

Table 3 Multiple linear regression. effect of some determinants on weight change. ADI study. May June. 2020. Italy.

Age and gender were not associated with weight change.

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Multiple Correspondence Analysis

As a previous step, we performed a simple correspondence analysis to examine the association between variables. Each single variable showed a strong statistically significant association with each other (p< 0.001). We choose only two dimensions, i.e. two axes from a Cartesian plane, as they explained the highest percentage of variability.

The results of MCA are visually shown in Fig. 1† In addition to all the variables expressing the moods associated with emotional problems, such as anxiety, boredom, and anxiety, we also included the variables associated with weight change and the “work” variable. Cluster 1 shows a lifestyle prior to the COVID-19 lockdown that has improved or has not changed, and Cluster 2 shows a deteriorated lifestyle.

fig. 1: Analysis of multiple correspondence.
Figure 1

Weight changes and emotional characteristics.

Cluster 1 (unchanged or improved lifestyle) is linked to job categories 3 and 4 (craftsmen/traders/farmers, private workers, self-employed; civil servants, pensioners). These individuals seem to have coped well with the emotional problems associated with the lockdown: unchanged or decreased weight, no anger, no depression, no boredom, no dissatisfaction, normal anxiety level and unchanged emotional problems.

Cluster 2 is linked to a different employment status than that mentioned for Cluster 1. The majority of the unemployed and home workers were in this cluster and reported experiencing depression, boredom, dissatisfaction, weight gain and a deteriorated lifestyle. This cluster included those who were unable to leave the house, those who thought more about food, those who ate more than before, and those who sought help from obesity medication. It should be noted that housewives seem to form a cluster of their own: they gained weight, became angry and confined themselves at home.

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