Although DSW + GF has been shown to be effective in preventing age‐related weight gain ( 22 , 24 , 25 ), to date, there are no intervention studies aimed at preventing holiday‐associated weight gain using this specific method of DSW. The purpose of this study was to determine the impact of DSW + GF on holiday‐associated weight gain in adults. We hypothesized that DSW + GF would effectively prevent weight and fat gain and that those with OW/OB would respond most favorably to DSW + GF. Further, with greater stress during the holidays, as well as greater temptation for increased food and drink consumption ( 26 ), we aimed to determine whether potential fluctuations in any component of perceptions about food, food selections, stress levels, or sleep patterns would serve as mediators for the effectiveness of DSW + GF on body weight (BW).

Research has shown that daily self‐weighing (DSW) could play an important role in weight maintenance following weight loss, although this is often done in conjunction with other behavior modifications, making it difficult to attribute success solely to DSW ( 11 - 20 ). When investigated as the only weight management intervention, a study in adults with obesity showed that DSW can produce clinically significant weight loss ( 20 ). DSW has also been effective in preventing age‐related weight gain during the first year of college ( 14 , 21 ). Previous research introduced a novel approach for DSW in which graphical feedback (GF) of weight trends is provided to the individual upon weighing by a digital Wi‐Fi scale ( 22 ). This visual GF of weight fluctuations is hypothesized to encourage individuals to adjust their behaviors toward weight maintenance or change in the intended direction ( 22 ). The flexibility and ease of this approach compared with conventional attempts have been shown to enhance successful weight management ( 23 ).

The holiday season has repeatedly been associated with weight gain ranging from 0.4 to 1.5 kg in adults ( 3 - 8 ), with an average of 0.5 kg of weight gain across all studies ( 3 ). This weight gain also persists after the holidays, potentially contributing to annual weight gain ( 4 ). Moreover, individuals with overweight or obesity (OW/OB) are vulnerable to gaining the most weight ( 3 , 4 ). By testing the effect of energy expenditure or physical activity on holiday weight gain, two previous studies indicated that energy intake, rather than energy expenditure, is the culprit ( 5 , 6 ). The increase in energy intake during the holidays could be due to increased portion sizes ( 9 ), dining with other people, longer eating sessions, and easy access to food ( 10 ). With multiple demands, busy schedules, and the frequent presence of palatable foods during the holidays, traditional weight maintenance strategies (dieting and exercising) are less likely to be successful. Therefore, it is crucial to develop novel behavior modification approaches to prevent holiday weight gain.

More than 35% of the US adult population have obesity, and there is a continuing increase in the degree of obesity ( 1 , 2 ). Longitudinal studies show that average annual weight gain is 0.4 to 1.0 kg ( 1 ). Accumulation of this small yet consistent weight gain begins in early adulthood and can lead to substantial weight gain over time. This creeping obesity, however, is not due to a consistent daily energy surplus. Rather, very short periods of time throughout the year are shown to account for a considerable portion of yearly weight gain ( 3 ). One of those critical times is the holiday season (mid‐November to January).

Statistical analyses were performed using JMP Pro 13 (Statistical Discovery; SAS Institute Inc., Cary, North Carolina). A sensitivity power analysis to determine the smallest detectable effect size was performed using G*Power, version 3.1.9.2 (R Foundation for Statistical Computing, Vienna, Austria). Assuming that preholiday and postholiday scores had a correlation of at least r = 0.40, our study was poised to detect differences in change scores from time 1 to time 2 of Cohen f = 0.15 (small to medium) effects. To test the treatment effects on BW across visits, as well as on the change between visits, a full‐factorial repeated‐measures ANOVA (mixed methods) was conducted based on sex and initial BMI (normal weight [NW] and OW/OB). Participants with BMI of 18.5 to 24.9 kg/m 2 were categorized as having NW, and those with BMI of 25 kg/m 2 or more were grouped into the OW/OB category. This grouping was done because of the relatively lower number of subjects in the OW/OB categories compared with the NW category (69% of the control group had NW [ n = 38] and 31% had OW/OB [ n = 17], whereas 75% of the DSW + GF group had NW [ n = 42] and 25% had OW/OB [ n = 14]). A two‐way repeated‐measures ANOVA was used to test the treatment effects on other anthropometrics (body fat, WC, HC, and waist to hip ratio [WHR]), systolic blood pressure (SBP) and diastolic blood pressure (DBP), and blood markers (total cholesterol [TC], triglyceride, high‐density lipoprotein [HDL], low‐density lipoprotein [LDL], and TC/HDL) across all visits. Post hoc analyses were performed using a Tukey test. Significance was set at P < 0.05, and data are presented as the mean ± SEM unless otherwise specified.

At the conclusion of v1, participants in the DSW + GF group received the Wi‐Fi scale (Nokia [Withings], Paris, France). They were asked to start DSW the day after v1 until v2. They weighed themselves first thing in the morning after voiding (and after defecating if that was their normal pattern). Once they stepped on the scale, their data would automatically transfer to their Withings account and their Withings mobile application (Nokia Health Mate). Immediately after a weight measurement, electronic GF of weight fluctuations would appear on the scale’s screen and on the application. The average of the first 4 days of BW served as the “baseline” weight, which was then set as the participant’s “target” weight in the Withings account. This target weight showed up as a straight line on the graph of daily weights (see online Supporting Information for a screenshot of an example of GF). Participants were instructed to try not to gain weight above this target line, and no additional instructions on how to achieve that goal were provided. The GF component of the DSW was the immediate GF of their weight fluctuations from the scale and how their weight compared with their target baseline weight. A description of weight monitoring by research personnel is given in the online Supporting Information.

This visit occurred in the HNL within a 1‐week period prior to Thanksgiving after an 8‐ to 12‐hour overnight fast and 12 hours without exercise. Height, BW, waist circumference (WC) and hip circumference (HC), blood pressure, and body composition using dual‐energy x‐ray absorptiometry (Discovery A; Hologic Inc., Bedford, Massachusetts) were measured. A fasting blood draw was taken for blood lipids. Questionnaires administered at this visit included the Perceived Stress Scale ( 28 , 29 ), Three‐Factor Eating Questionnaire (TFEQ) ( 30 ), Power of Food Scale ( 31 ), National Insomnia Screening Questionnaire ( 32 ), self‐weighing frequency Likert item, Mindful Eating Factors Questionnaire ( 33 ), and Fat Preference Questionnaire ( 34 ). To assess participants’ perceptions of healthy and unhealthy foods, participants categorized a series of 60 images of different foods accompanied by their names (e.g., pizza, pancake, broccoli). Participants selected “healthy” or “unhealthy” for each food item. This was done to examine whether DSW + GF would alter subjects’ perception of foods and whether these perceptions, as well as data from our other questionnaires, would be significant mediators for the effects of DSW + GF on BW.

A total of 111 adults 18 to 65 years of age with BMI ≥ 18.5 kg/m 2 participated in the study. Exclusion criteria included having a current or past eating disorder, involvement in a weight loss or exercise program, pregnancy or nursing, and medications or chronic diseases affecting metabolism or BW. Recruitment was completed through online and paper advertisements and word of mouth, both on and off campus. The off‐campus advertisements were posted throughout the community in restaurants and shopping centers. Online advertisements were sent to LISTSERVs at the university in an effort to recruit individuals with varying ages and both sexes. A single‐blinded, randomized controlled trial was conducted with two parallel groups (1:1 allocation ratio): the control group and the intervention group (DSW + GF). It was critical that all participants were blinded to the study purpose to prevent intentional behavior modifications (outside DSW in the intervention group) that could influence BW. Therefore, participants were told that the project aimed to examine “how the holidays affect health.” All participants were to complete three testing visits including a preholiday visit (v1), a postholiday visit (v2), and a 14‐week follow‐up visit (v3), and they received $10 as monetary compensation upon completion of each visit ($30 total for study completion). This study was approved by the institutional review board at the University of Georgia, and written informed consent was obtained.

We examined the pattern of weight change in the DSW + GF group. Figure 4 shows a graphical illustration of average daily weights during the holidays and depicts five specific time frames during the intervention. Box–Jenkins analysis showed P > 0.05 for all time frames. This indicated that the patterns did not occur randomly or by chance. Therefore, the generated forecasts were significantly adequate in predicting future patterns. These forecast lines (Figure 4 ) show a decreasing trajectory in BW during pre‐Thanksgiving week, which then increased during Thanksgiving week. This elevation persisted throughout Thanksgiving and started to decrease after Thanksgiving until mid‐December. There was a returning increase in BW during pre‐Christmas week, which escalated until the end of the holidays. These increases did not exceed the baseline/target weight prior to the beginning of the holiday season.

There was a treatment visit interaction for total body fat percentage (TBF%; P = 0.001) with a greater decrease in DSW + GF versus control during the holidays (−1.08% ± 0.19% vs. 0.95% ± 0.19%, respectively; P < 0.001) and throughout the entire study (−0.87% ± 0.37% vs. 0.45% ± 0.26%, respectively; P = 0.01) (Table 2 ). No significance was found with WC, HC, WHR, SBP, DBP, triglyceride, HDL, or TC/HDL ratio. For TC and LDL, there was a visit effect ( P = 0.02 and P = 0.04 for TC and LDL, respectively), with both decreasing across all visits (Table 2 ). Results for self‐weighing frequency and questionnaires can be found in the online Supporting Information.

When analyzed by BMI, controls with NW gained a weight amount similar to that gained by controls with OW/OB during the holidays (2.62 ± 0.43 vs. 2.71 ± 0.47 kg for v1 vs. v2, respectively; P = ns) (Table 2 and Figure 3 C). Although both the participants with NW and the participants with OW/OB gained weight throughout the entire study (v1 to v3) (Table 2 ), weight gain in those with OW/OB was greater compared with those with NW (2.99 ± 0.80 vs. 0.87 ± 0.41 kg, respectively; P = 0.02). This was due to the weight loss in those with NW, but not in those with OW/OB, in the follow‐up period (Table 2 ) (−1.72 ± 0.50 vs. 0.25 ± 0.75 kg for NW vs. OW/OB, respectively; P = 0.04) (Figure 3 C). Conversely, in the DSW + GF group, those with OW/OB, but not those with NW, lost weight during the holidays and throughout the entire study (Table 2 ). These changes in weight were different between those with OW/OB and those with NW both during the holidays (−1.46 ± 0.62 vs. 0.33 ± 0.27 kg, respectively; P = 0.001) and over the entire study (−1.49 ± 0.73 vs. 0.47 ± 0.34 kg, respectively; P = 0.03) (Figure 3 D).

Change in body weight grouped by sex or BMI category. Within‐subject change in body weight grouped by sex in ( A ) the control group ( n = 14 males vs. n = 41 females) and ( B ) the daily self‐weighing (DSW) group ( n = 15 males vs. n = 41 females) and grouped by initial weight status in ( C ) the control group ( n = 38 with normal weight [NW] vs. n = 17 with overweight or obesity [OW/OB]) and ( D ) the DSW group ( n = 42 with NW vs. n = 14 with OW/OB). At the follow‐up visit, two subjects (both males, one with NW and one with OW/OB) in the control group and five subjects (two females and two males with NW and one male with OW/OB) in the DSW + graphical feedback (GF) group were missing data. Those subjects remained in the statistical analysis based on the intent‐to‐treat approach. * indicates a difference between males and females ( A , B ) and between those with NW and those with OW/OB ( C , D ) at that time period ( P < 0.05). Preholiday visit occurred within 7 days before Thanksgiving. Postholiday visit occurred within 7 days after New Year’s Day. Follow‐up visit occurred 14 weeks after the postholiday visit (early to mid‐April).

In the control group, both males and females gained weight during the holidays (Table 2 and Figure 3 A). In the follow‐up period, males, but not females, lost weight (Table 2 ), although the difference between the sexes for change in weight was not significant (Figure 3 A). Consequently, significant weight gain was observed only in females from v1 to v3 (2.09 ± 0.48 kg vs. 0.10 ± 0.63 kg; P = 0.02 for females vs. males, respectively; P = 0.02) (Table 2 , Figure 3 A). Conversely, in the DSW + GF group, there were no differences in weight across visits for either sex during the holidays, the follow‐up period, or the entire study (Table 2 ). In addition, there was no difference between sexes for change in weight throughout the entire study (−0.02 ± 0.40 vs. 0.01 ± 0.48 kg for females vs. males, respectively; P = ns) (Figure 3 B).

Changes in body weight throughout the study visits. Within‐subject change in body weight in the daily self‐weighing (DSW) group vs. the control group. At the follow‐up visit, two subjects (both males, one with normal weight [NW] and one with overweight or obesity [OW/OB]) in the control group and five subjects (two females and two males with NW and one male with OW/OB) in the DSW + graphical feedback (GF) group were missing data. Those subjects remained in statistical analysis based on intent‐to‐treat approach. * indicates a difference between control vs. DSW at each time period ( P < 0.05). Preholiday visit occurred within 7 days before Thanksgiving. Postholiday visit occurred within 7 days after New Year’s Day. Follow‐up visit occurred 14 weeks after the postholiday visit (early to mid‐April).

There was a main effect of treatment ( P = 0.001), sex ( P < 0.001), and initial BMI ( P < 0.001), and a treatment BMI interaction ( P = 0.01) on BW. All other interaction effects, such as treatment by time, were insignificant. The post hoc analysis showed a significant weight gain in the control group from v1 to v2 (67.02 ± 1.78 vs. 70.17 ± 1.83 kg, respectively; P < 0.001) but a weight loss from v2 to v3 (70.17 ± 1.83 vs. 67.78 ± 1.89 kg, respectively; P = 0.01) (Table 2 ). Despite this postholiday weight loss, the control group overall still showed weight gain throughout the entire study (66.65 ± 1.60 vs. 67.78 ± 1.89 kg for v1 vs. v3, respectively; P < 0.001). Conversely, the DSW + GF group did not significantly differ in BW from v1 to v2 (66.65 ± 1.60 vs. 66.79 ± 1.63 kg, respectively; P = nonsignificant [ns]), during the follow‐up (66.79 ± 1.63 vs. 66.55 ± 1.64 kg for v2 vs. v3, respectively; P = ns), or throughout the entire study (66.65 ± 1.60 vs. 66.55 ± 1.64 kg for v1 vs. v3, respectively; P = ns) (Table 2 ). Not surprisingly, weight change during the holidays was greater for control versus DSW + GF (2.65 ± 0.33 vs. −0.13 ± 0.27 kg, respectively; P < 0.001) and over the entire study period (1.51 ± 0.39 vs. −0.15 ± 0.35 kg for control vs. DSW + GF, respectively; P = 0.002) (Figure 2 ).

A total of 111 participants were enrolled ( n = 55 control, n = 56 DSW + GF), and 104 participants ( n = 53 control, n = 51 DSW + GF) completed all three visits (94% retention rate). Thirty‐five participants were college‐aged students (31.5%), twenty‐seven were graduate students (24.3%), and the remaining participants were other adults such as faculty, staff, university retirees, and out‐of‐university adults (42%). Two participants in the control group and five in the DSW + GF group withdrew from the study because of personal reasons (trips, relocation, and pregnancy) after completion of v2. Therefore, there were no v3 data for these seven individuals (Figure 1 ); however, they were included in data analyses using an intent‐to‐treat approach. During the intervention period, five participants in the DSW + GF group were contacted because of missing three consecutive days of self‐weighing, and they resumed with DSW after that first contact. Table 1 represents participants’ characteristics at baseline. On average, participants in the DSW group missed 1.8 days of DSW out of an average of 51.5 days (96.4% compliance rate). None of the participants was withdrawn from the study because of rapid weight changes or negative effects of DSW.

Discussion

To our knowledge, this is the first study to show that DSW + GF prevented holiday‐associated weight gain in men and women as opposed to weight gain in its absence. Based on initial BMI, weight maintenance (nonsignificant difference in weight between visits) with DSW + GF was driven by a weight loss in those with OW/OB (−1.46 ± 0.62 kg) and weight maintenance in those with NW (0.33 ± 0.27 kg; ns). The decrease in TBF% following DSW also suggested that DSW + GF was effective in improving body composition.

Control subjects gained a substantial amount of holiday weight (2.65 ± 0.33 kg), which coincided with an increase in TBF%. Some of that holiday weight was lost during the follow‐up period; however, as a group, they retained almost 57% of the weight gain, so that overall weight gain from November to May was significant. Interestingly, male controls lost ~95% of their holiday weight gain at follow‐up, whereas females retained ~77% of their holiday weight gain. This pattern suggests that although holiday weight gain may be similar between sexes, men are more likely to lose some or most of that weight after the holidays, whereas women may retain more of that weight. When considering initial BMI, weight loss in subjects with NW and maintaining holiday weight gain in subjects with OW/OB were observed during the follow‐up period. This extends previous findings that those with OW/OB are more susceptible to weight or fat gain during the holidays (4, 8, 37) and may be more likely to retain that additional weight. Based on the successful implementation of DSW + GF in the group with OW/OB, along with the risk of greatest weight gain and retention in the absence of an intervention, DSW + GF may be an ideal target for all adults, but especially for those with OW/OB. However, because of the insignificant treatment time interaction in our results, the potential success of DSW + GF should neither be overstated nor disregarded. Future research is warranted to verify the effectiveness of this intervention.

To better understand the patterns of BW change during the holidays with DSW, we generated the graph of daily weight fluctuations. The initiation of DSW + GF resulted in a noticeable decreasing trend in BW for a week. Although our participants started to gain weight during Thanksgiving week, this increase was compensated for over the next 3‐week period. Although weight gain resumed a week before Christmas and continued through New Year’s Day, the participants were successful in weight maintenance at or below baseline weights, likely because of the initial loss with DSW + GF and the post‐Thanksgiving compensation. This indicates that DSW does not completely protect against holiday weight gain; rather, it prompts individuals to compensate for increases in weight. We believe this may be attributed to self‐monitoring under the social cognitive theory of self‐regulation because of the provision of immediate feedback of weight fluctuations in reference to the target weight. Under this theory, continuous self‐monitoring motivates human behavior by providing constant exposure to the consequences (38). With almost 80% of participants continuing self‐weighing at least weekly after the intervention, DSW + GF could positively influence or motivate future self‐weighing practices. It is also possible that individuals doing DSW + GF were motivated to change their behaviors because they knew research personnel would access their daily weights, whereas control subjects may not have felt this similar motivation. It remains to be seen whether the same degree of success would occur in the absence of accountability or other individuals viewing a person’s weight patterns. We also cannot definitively conclude whether the effects of DSW + GF were due to receiving weight maintenance instructions or simply the act of DSW. To elucidate this, future research would need to have the control group perform DSW in the absence of weight maintenance instructions from research personnel. There was also some increased contact with participants in the DSW + GF group if they missed > 3 consecutive days of weighing; however, this occurred for only five participants. Therefore, this intervention showed promise and deserves further investigation in a larger sample with a greater number of participants with OW/OB, a longer follow‐up period, objective weighing in the control group, and more restrictive blinding.

Although none of the questionnaires was a mediator of DSW, the decrease in the uncontrolled eating score (subscale of TFEQ) after the follow‐up in the DSW group (Table 3) suggests that DSW + GF may result in better control over quantity and frequency of food intake. Conversely, in the absence of DSW, the increase in the external cues score (subscale of Mindful Eating Factors Questionnaire) verifies the appetizing components of the holidays, such as larger portions, more social eating, and more access to food. We also do not have a mechanistic explanation for the stronger responses to DSW + GF in those with OW/OB versus those with NW because the mediators we tested were not significant. It is possible that other mediators aside from those assessed were stronger contributors to the success of DSW + GF in those with OW/OB. Additionally, those with OW/OB in the DSW group underreported BW by 1.55% from the phone screening, whereas those with NW overreported BW by 1.02%. Therefore, participants with OW/OB may have been more surprised about their actual BW and were hence more motivated to modify their behavior. We are unsure of the reasons behind the surprisingly large weight gain in our control subjects (2.65 kg) compared with that seen in prior observational studies (0.4 to 1.5 kg) (3-5, 7, 8, 37). It could be due to several factors, including geographic differences (our sample was in the southeastern United States). Also, compared with some studies (4, 8, 37, 39), we had a higher ratio of females to males. However, with similar weight gain in both sexes, sex distribution is unlikely to explain this outcome. Finally, the age and BMI of our participants were lower than those in some studies but higher than those of other previous studies. Therefore, we are unable to make meaningful conclusions regarding these variables (3-6, 8, 37).

Table 3. Questionnaire scores at all study visits Control group DSW + GF group Preholiday visit Postholiday visit Follow‐up visit Preholiday visit Postholiday visit Follow‐up visit TFEQ Cognitive restraint score 15 ± 3 15 ± 2 18 ± 3a, b 16 ± 2 16 ± 2 17 ± 2a, b Uncontrolled eating score 23 ± 3 24 ± 4 24 ± 4 24 ± 3 24 ± 3 23 ± 4a Emotional eating score 8 ± 2 9 ± 2 9 ± 2 8 ± 2 9 ± 2c 8 ± 2 Power of Food Scale 44 ± 16 47 ± 15 49 ± 14 48 ± 14 50 ± 15 51 ± 17 Mindful Eating Factors (overall score) d 3.1 ± 0.8 3.1 ± 0.5 3.0 ± 0.5 3.1 ± 0.4 3.1 ± 0.4 3.2 ± 0.4 Disinhibition 3.0 ± 0.5 3.1 ± 0.4 3.0 ± 0.5 3.0 ± 0.5 3.0 ± 0.5 3.0 ± 0.5 Awareness 3.2 ± 1.0 3.3 ± 0.9 3.3 ± 0.9 3.4 ± 0.8 3.5 ± 0.7 3.5 ± 0.6 External cues 3.4 ± 0.9 3.8 ± 0.9c 3.7 ± 0.9b 3.8 ± 0.7 3.8 ± 0.7 3.9 ± 0.6 Emotional response 2.5 ± 1.0 2.4 ± 0.9 2.5 ± 0.9 2.5 ± 0.9 2.4 ± 0.9 2.5 ± 0.9 Distraction 3.2 ± 2.7 2.7 ± 0.8 2.7 ± 0.8 2.9 ± 0.9 2.9 ± 0.8 3.1 ± 0.8 Fat Preference Questionnaire Taste score (%) 57.5 ± 20.8 59.8 ± 19.9 60.5 ± 22.5 56.9 ± 20.5 60.5 ± 24.5 58.5 ± 27.8 Frequency score (%) 36.7 ± 22.8 38.6 ± 22.3 35.6 ± 20.4 35.8 ± 21.1 32.9 ± 23.3 35.9 ± 23.4 Difference score (%) e 20.7 ± 19.3 21.3 ± 17.3 24.7 ± 20.2 21.2 ± 18.2 27.9 ± 20.4c 23.8 ± 21.7 Perceived Stress Scale 32 ± 3 30 ± 4c 31 ± 3b 31 ± 5 31 ± 4 31 ± 3 National Insomnia Screening 30 ± 9 30 ± 8 29 ± 8 28 ± 7 28 ± 7 29 ± 10 Perceptions of foods Unhealthy foods 13.4 ± 1.2 13.1 ± 1.0 13.4 ± 1.0 12.9 ± 2.4 14.2 ± 1.2 14.0 ± 2.6 Healthy foods 0.1 ± 0.2 0.1 ± 0.3 0.1 ± 0.4 0.1 ± 0.3 0.1 ± 0.4 0.1 ± 0.4 Ambiguous foods 11.5 ± 4.3 12.0 ± 5.0 11.2 ± 4.4 10.8 ± 4.3 10.5 ± 5.0 11.2 ± 5.0

There were some limitations to this study. We used a convenience sample, so we did not have an equal ratio of participants with NW to participants with OW/OB, although the numbers were balanced between DSW + GF versus control. Although the blinding aspect of this study minimized the chances of behavioral modifications in the control group, it remains unknown how the study intent was obscured in the DSW + GF group, given the attention these participants received about BW. Although we tried to put equal emphasis on the collection of all health‐related measures besides BW, future research could use minimal contact with participants to better isolate the potential effects of DSW. In addition, the group assignments were not masked to the study coordinator because she performed the computer randomization and provided DSW instructions to the DSW + GF participants. Future studies could be designed to incorporate a double‐blinded setting to eliminate any potential bias. Additionally, because the DSW + GF participants were given instructions to try not to gain weight above their baseline weight, it is possible that these instructions could be a distinguishing factor between the intervention and the control group, either in addition to, or independent of, the actual act of DSW. Furthermore, our higher proportion of female participants somewhat limits the generalizability of our conclusions about sex. Because there were sex differences in the control group during the follow‐up period, this should be examined more closely in future work. Importantly, DSW + GF was equally effective in both men and women.