A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection

Mindy H Lee; Catherine C Applegate; Annabelle L Shaffer; Abrar Emamaddin; John W Erdman, Jr; Manabu T Nakamura

doi:10.1371/journal.pone.0267876

. 2022 May 26;17(5):e0267876. doi: 10.1371/journal.pone.0267876

A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection

Mindy H Lee ¹, Catherine C Applegate ¹, Annabelle L Shaffer ¹, Abrar Emamaddin ², John W Erdman Jr ^1,², Manabu T Nakamura ^1,^2,^*

Editor: John W Apolzan³

PMCID: PMC9135285 PMID: 35617305

Abstract

Obesity is a significant contributor to the development of chronic diseases, some of which can be prevented or reversed by weight loss. However, dietary weight loss programs have shortcomings in the success rate, magnitude, or sustainability of weight loss. The Individualized Diet Improvement Program’s (iDip) objective was to test the feasibility of a novel approach that helps individuals self-select a sustainable diet for weight loss and maintenance instead of providing weight loss products or rigid diet instructions to follow. The iDip study consisted of 22 dietary improvement sessions over 12 months with six months of follow-up. Daily weights were collected, and a chart summarizing progress was provided weekly. Six 24-hour dietary records were collected, and dietary feedback was provided in the form of a protein-fiber plot, in which protein/energy and fiber/energy of foods were plotted two-dimensionally together with a target box specific to weight loss or maintenance. An exit survey was conducted at 12 months. Twelve (nine female, 46.3±3.1 years (mean±SE)) of the initial 14 participants (BMI>28 kg/m²) completed all sessions. Mean percent weight loss (n = 12) at six and 12 months was -4.9%±1.1 (p = 0.001) and -5.4%±1.7 (p = 0.007), respectively. Weight loss varied among individuals at 12 months; top and bottom halves (n = 6 each) achieved -9.7%±1.7 (p = 0.0008) and -1.0%±1.4 weight loss, respectively. The 24-hour records showed a significant increase in protein density from baseline to final (4.1g/100kcal±0.3 vs. 5.7g/100kcal±0.5; p = 0.008). Although mean fiber density showed no significant change from the first month (1.3g/100kcal±0.1), the top half had significantly higher fiber/energy intake than the bottom half group. The survey suggested that all participants valued the program and its self-guided diet approach. In conclusion, half of the participants successfully lost >5% and maintained the lost weight for 12 months without strict diet instructions, showing the feasibility of the informed decision-making approach.

Introduction

With the advancement of food production globally, obesity has become a worldwide epidemic, increasing the risk of morbidity and mortality [1, 2]. In the United States, 70.2% of adults are obese (body mass index, BMI>30 kg/m²) or overweight (BMI>25 kg/m²), with 7.7% having extreme obesity (BMI>40 kg/m²) [3]. Overweight and obesity are risk factors for several comorbidities, including type 2 diabetes mellitus, cardiovascular disease, and cancers. Based on 2013 US medical spending, obesity and its complications cost $342.2 billion annually (28.2% of all medical expenditures) [4]. Modest weight losses of 3–5% initial body weight are capable of lowering blood triglycerides, fasting blood glucose, and improving glycemic control. Further weight losses enhance these benefits, and can also reduce blood pressure, cholesterol, and need for medications [2, 5].

Currently available weight loss methods do not reliably achieve medically significant weight loss as they are insufficient in success rate, sustainability, or magnitude of weight loss. Exclusion of certain food groups is a common approach of popular dieting programs, which can result in some weight loss, but high attrition rates often result due to a lack of dietary adherence [6–8]. For example, commonly used dieting programs, including Atkins (carbohydrate restriction), Zone (substituting carbohydrate with protein), and Ornish (reduction of animal foods), can induce modest weight losses of <5 kg but lack a high success rate and long-term sustainability [9–12]. Participants grow fatigued with the strict recipes and are unable to adapt the plan to their daily lives [13, 14]. This translates to low adherence, unsuccessful weight loss, and lack of diet sustainability.

A negative energy balance is a requirement for weight loss. Calorie monitoring is often proposed to achieve this and is recommended by health professionals [15, 16]. However, it is laborious and frequently inaccurate [17, 18]. Often, programs utilizing calorie counting or food journals lead to high attrition and thus, insignificant long-term weight loss [19–21]. More importantly, the protein requirement increases during periods of negative energy balance compared with the requirement during weight maintenance [22, 23]. Focusing only on energy reduction may result in exacerbating the loss of lean body mass and decreased efficiency in weight loss [23].

Successful, clinically significant weight losses can be achieved using meal replacement products; however, weight maintenance remains a substantial challenge for this approach [5]. Very-low-calorie diets (VLCD) in the form of meal replacements have shown clinically significant weight loss in the short term, but VLCD participants are less successful in weight maintenance compared to a restricted-energy whole-food diet [24–26]. Even when a VLCD was combined with intensive dietary and lifestyle intervention programs using counseling, education, and exercise, participants regained most or all of the lost weight during the follow-up periods [5, 27].

Pharmaceuticals are available for treating obesity, such as orlistat and phentermine/topiramate, and work by reducing fat absorption and suppressing appetite, respectively. However, these medications result in only 3–6% weight loss and can include several side effects such as reduced fat-soluble vitamin absorption or gastrointestinal upset [28]. As a result of the low efficacy in medicine and lifestyle interventions, bariatric surgery remains the most reliable weight-loss treatment and can reduce obesity complications, such as hyperglycemia [29]. Bariatric surgery does have significant drawbacks, including a mean cost of $14,389 per surgery, surgical complications, nutritional deficiencies, and the need for drastic dietary changes [30].

In summary, although dietary weight loss can treat comorbidities associated with obesity, existing programs have shortcomings in sustainability, magnitude, adherence, and success rate. As such, a dietary weight loss program that can be used as a reliable treatment option is yet to be developed. Thus, we tested the feasibility of a new approach to dietary weight loss that does not rely on traditionally used methods. First, in place of common methods such as exclusion of food groups, strict weight-loss meal plans, and dieting products, iDip increases nutritional knowledge allowing participants to create their own weight loss diet by making informed and individualized food choices based on their preferences. Second, we monitored a target range of protein density per energy for participants to create a weight loss diet with increased protein while reducing the overall energy intake to meet an increased protein requirement during weight loss. Third, we replaced calorie counting/food journaling with daily weight monitoring and provision of a weekly progress chart to monitor energy balance.

Materials and methods

This study was approved by the University of Illinois Institutional Review Board (#18069) on August 30^th, 2017. The study was registered at the US National Institutes of Health (ClinicalTrial.gov) #NCT04605653. Registration was delayed due to a lack of knowledge on required clinical trial registration. The authors confirm that all ongoing and related trials for this intervention are registered. Participant recruitment started on September 1^st, 2017, and the follow-up period ended on July 28^th, 2018. Informed consent was obtained from all participants included in the study.

Participant recruitment

Adults aged 18 to 64 years old and with a BMI >28 kg/m² were recruited via posters, flyers, and word of mouth in Urbana-Champaign, Illinois, USA, and surrounding regions from September 2017 through January 2018. A power calculation was performed using an average standard deviation 7.0 for percentage weight loss at 12 months from similar dietary weight loss studies [31]. We set 5% weight loss as a primary outcome to be detected. The minimum sample number required with 95% confidence interval was 7.5. With n = 10, we will be able to detect 5% difference when actual SD is 8.0. Alternatively, we will be able to detect 4.3% difference if SD is 7.0 as estimated. Based on a mean attrition rate of 22.1% from 60 studies [32], we recruited 14 participants assuming 30% attrition rate. A flow diagram of participant enrollment is shown in Fig 1.

Inclusion criteria in addition to age and BMI were access to Wi-Fi at home, working email and smartphone, fluent English communicator, and willingness to self-weigh daily with a provided Wi-Fi scale for a minimum of 18 months. Exclusion criteria were the following: adults with self-reported severe metabolic, cardiovascular or musculoskeletal disease, insulin use, pregnancy, planned pregnancy, or lactating; or unwillingness to attend any of the educational sessions. Among eligible applicants, invitation was prioritized to best reflect the gender and racial composition of the community. Selected applicants were invited for an individual meeting for an additional screening process at the University of Illinois at Urbana-Champaign (UIUC). After receiving explanations about the study, a Food Frequency Questionnaire (FFQ) was administered, and anthropometric measurements were collected. Informed consent was obtained, and a Wi-Fi scale was provided. Other than a Wi-Fi scale, no monetary compensation was provided to the participants for participating in the study.

Study design

The iDip study utilized a non-randomized, single-arm, before-and-after study design with a cohort of participants and comprised of 12 months of intervention followed by six months of follow-up. The objective was to test the feasibility of the informed decision-making approach to dietary weight loss by utilizing two forms of quantitative visual feedback for dietary improvement and weight loss progress. The iDip consisted of four weekly sessions (month one), 12 biweekly sessions (months two-six), and six monthly sessions (months seven-12). Nineteen 60-minute group-based diet improvement sessions and three 30-minute individual advising sessions were delivered by graduate students with registered dietitian credentials at UIUC from January 2018 to January 2019. All group sessions were focused on building knowledge and skills to make informed food selections. Weekly sessions in month one focused on the basic strategy of weight loss; bi-weekly sessions in months two-six focused on protein, fiber, physical activity, weight loss plateauing, and weight maintenance; and months seven-12 of monthly sessions focused on healthy eating and micronutrients beyond weight management (S1 Appendix). All participants received two types of feedback: 1) weekly weight chart and 2) protein-fiber (PF) plot (Fig 2) of their 24-hour diet record analysis at one, two, three, five, seven and 12 months and pre-and-post FFQs to assist individuals in monitoring their weight and dietary pattern, respectively. PF plot was the sole diet feedback and analysis that participants received. No food groups were excluded from participants’ diets, and even no dieting products nor recipes were distributed. Weight and dietary changes were evaluated during individual sessions, and participants were advised using our new approach.

Fig 2 — Foods with green dots are dense in protein or fiber and can be easily fit in the target box when combined, whereas foods with red dots cannot be due to low protein and fiber densities. A yellow food has protein and fiber density between green and red foods. A blue dot with a shadow shows where a meal falls when all foods are combined. Blue box, weight maintenance target; green box, weight loss target.

Development of novel learning tools

A quantitative nutrient display method

The PF plot (Fig 2) is a two-dimensional data-visualization method for easy comparison of quantitative nutrition values in multiple foods designed to improve food selection based on protein and fiber density of foods [33]. The PF plot was developed by our lab, and its efficacy in aiding restaurant customers in selecting healthier menus has been demonstrated previously [33]. Protein and fiber are critical nutrients for weight management as adequate protein intake protects muscle mass from degradation during weight loss [22, 34], and consuming sufficient protein and fiber decreases excessive calorie consumption [35–37]. The fat to carbohydrate ratio was disregarded in this study as previous randomized-controlled trials have not shown that long-term weight loss favors a low-carbohydrate and high-fat diet or vice versa [38–40].

Protein and fiber targets of the PF plot are derived from the Acceptable Macronutrient Distribution Ranges (AMDR) and Adequate Intakes (AI) for weight maintenance in adults, respectively, as previously described [33]. Briefly, for protein, the AMDR is 10–36% daily intake; and for fiber, the AI is 14 g/1000 kcal daily [15]. For the weight maintenance box (blue): using 16–32% kcals from protein, we set 4–8 g/100 kcal as protein target; and for fiber, 1.4–2.8 g/100 kcal (Fig 2). The weight loss target (green) was set assuming a caloric reduction of minimum 25% of the daily requirement as weight loss requires a negative energy balance. By adjusting for 25% calorie reduction and 1.25x increase in protein requirement [22, 23], we set a protein range for weight loss of 7–11 g/100 kcal. Using 14 g fiber/1000 kcals and factoring 25% reduction of caloric intake, the resulting range was set as 1.8–3.2 g/100 kcals (Fig 2). The PF plot with a target box of protein and fiber density for weight loss was used as a key tool for food selection by participants throughout the study in both educational sessions and individual diet analysis.

Energy balance monitoring

In the iDip, calorie counting and daily food journaling were replaced with daily self-weighing and weekly progress summary charts to monitor energy balance. As mentioned in the Introduction, calorie counting and food log methods are conventional in weight management, but these methods are time-consuming and prone to error, resulting in high attrition rates [19–21]. Daily self-weighing using a Wi-Fi-enabled scale (Weight Gurus, Greater Goods LLC, MO) provided a reliable energy balance estimation that requires little time. Participants were provided with a weekly weight feedback chart showing weight, a six month goal weight and an intended weight loss rate in the format shown in Fig 3.

Fig 3 — The red line represents the target weight loss slope (1 lb. loss (0.45 kg) per week) over time, the blue line represents actual daily weights, and the green line represents the target of 25 lbs. (11.3 kg) weight loss (based on a six month weight loss goal of 1 lb. (0.45 kg) loss per week).

Outcome measures

Anthropometrics measures

Anthropometrics measurements were the primary outcomes, and entailed height, weight, waist, and hip circumferences. These were obtained at baseline and at 12 months. Height was recorded to the nearest 0.25 inches with shoes removed via stadiometer (Seca 700, Hanover, MD), and weight was measured to the nearest 0.1 lbs in light clothing on the same instrument. BMI was calculated using measured height and weight. In addition, weights were monitored and obtained daily via a Wi-Fi scale. Waist and hip circumferences were measured using a Retractable Tape Measure (Gulik II, Gay Mills, WI) and recorded to the nearest 0.1 cm. Waist to hip ratio was obtained based on measured waist and hip circumferences.

Dietary assessment

Dietary changes were the secondary outcomes assessed in this study. A paper version of the validated EPIC-Norfolk FFQ questionnaire (S2 Appendix) was used at baseline and at 12 months to assess dietary patterns [41]. Twenty-four-hour dietary records were administered at one, two, three, five, seven and 12 months to evaluate dietary changes. The results were returned to the participants in the form of a PF plot. The US Department of Agriculture National Nutrient Database for Standard Reference (https://fdc.nal.usda.gov/) and manufacturer information were used to calculate protein and fiber density.

Survey measures

An exit survey was conducted at the end of the 12 month intervention. A questionnaire containing 14 items was developed to explore personal gain, program content, program materials and feedback, engagement, and overall evaluation of the program. Possible responses for each question were “Definitely Yes,” “Yes,” “A little bit,” “Neutral,” “Not really,” “No,” “Definitely Not.” A score was provided for each response from one to seven, with seven being “Definitely Yes”.

Data analysis

Descriptive analysis was used to summarize demographic characteristics. Weight loss of ≥5% from the baseline was considered meaningful as it has been shown to reduce risks associated with obesity [42]. Paired t-test analysis determined the pre-and post-intervention differences in outcome measures for the program completers. Pearson correlation analyses were performed to determine associations between body weight, protein density, and fiber density. Cohen’s d was computed by single sample z-test. Normality of data was tested using Shapiro-Wilk. Repeated measure ANOVA was used to compare 24-hour dietary records. All statistical analyses were performed using Microsoft Office Excel 2016 and R Computing (Version 3.6.1 © 2019), and p<0.05 was considered statistically significant.

Results

Participant characteristics

Fourteen participants started the study (Fig 1). The mean age was 44.6±3.0 years, and mean BMI was 36.7±1.7 kg/m². The demographics and characteristics of participants are presented in Table 1. Enrolled participants had medical histories of hypertension (36%), hypercholesterolemia (21%), thyroid issues (21%), skeletal problems (14%), sleep apnea (14%), and hyperlipidemia (7%). Participants had prior dieting experiences including Weight Watchers (71%), Jenny Craig (14%), liquid diets (14%), Ideal Protein (14%), low carbohydrate (14%), South Beach (7%), low fat (7%), low calories (7%), cabbage soup diet (7%), Atkins (7%), 21-day fix (7%), Human Chorionic Gonadotropin (HCG) diet (7%), and Transformation diet (7%). No significant differences were found in any demographic data between top and bottom groups in weight loss.

Table 1. Demographic data of participants.

	Enrollees (%)	Completers (%)
	N = 14	N = 12
Age in years
18–34	14.3	8.3
35–50	50.0	50.0
51–65	35.7	41.7
Gender
Male	21.4	25.0
Female	78.6	75.0
Marital Status
Married	64.3	75.0
Single	35.7	25.0
Ethnicity
White	57.1	50.0
African American	42.9	50.0
Educational level
Graduate degree	50.0	58.3
Bachelor’s degree	42.9	41.7
High school	7.1	0.0

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Retention

Fourteen participants started the program. Participants who were unable to attend the regular sessions received make-up sessions. One participant dropped out after four weeks, and the other participant dropped out after eight weeks, yielding 85.7% retention. The reasons for leaving the study were as follows: too busy to focus on weight loss (n = 1) and unsatisfying weight loss (n = 1). During the six-month follow-up period, six out of 12 participants continued to weigh daily.

Change in anthropometric measures

Anthropometric changes following the intervention are presented in Table 2 and Figs 4 and 5. At 12 months, six participants (50%) successfully lost >5% of their initial body weights (Fig 4). Of the unsuccessful participants (n = 6), four participants did not reach 5% weight loss during the 12 months, whereas two participants regained lost weight after six months (Fig 4). On average, participants (n = 12) achieved a significant weight loss of -5.4%±1.7% at 12 months (p <0.01) from the baseline (Fig 5). Cohen’s d for 12 month weight loss was -0.21 indicating a small, negative change in weight. A large difference in weight loss outcome was observed among participants at 12 months (p<0.001); the top half (n = 6) showed a significant loss from the baseline reaching -9.7±1.7%, whereas the bottom half (n = 6) lost -1.0±1.4% (Fig 5). The difference between the two groups widened as time progressed from the start to 12 months, particularly during the last five months (Fig 5).

Table 2. Characteristics of participants who completed dietary improvement sessions.

	Baseline (n = 12)	6 months (n = 12)	12 months (n = 12)	Follow-up (n = 6)
Height (cm)	167.4±3.0	167.4±3.0	167.4±3.0	166.5±3.4
WC (cm)	112.9±3.9		109.9±5.7(0.18)
HC (cm)	124.5±2.9		123.5±4.1(0.45)
WHR
Female	0.88±0.02		0.85±0.02(0.17)
Male	1.00±0		0.98±0.04(0.54)
Weight (kg)	103.3±6.5	98.1±6.2(0.001)	98.4±7.4(0.007)	98.2±11.9(0.07)
BMI (kg/m²)	36.7±1.7	34.9±1.7(0.001)	34.9±2.0(0.007)	35.0±2.9(0.07)

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Values are presented as mean±SE for baseline and mean±SE (p-value) for subsequent months. P-values by paired t-test are shown in parenthesis. WC: Waist circumference, HC: Hip circumference, WHR: Waist to hip ratio

Fig 4 — The data are ordered by magnitudes of weight loss at 12 months.

Fig 5 — Participants were divided into two groups of equal size (n = 6 each) based on the weight changes from baseline at 12 months. **p<0.01, ***p<0.001 at 12 months compared with baseline.

Change in dietary components

Changes in diets over 12 months based on FFQ and 24-hour dietary records are shown in Fig 6. A significant increase in fiber density (p = 0.02) but not protein density was found from the FFQ. Twenty-four-hour records showed a significant improvement in protein density in all 5 subsequent records when compared with the first month record, whereas fiber density increased only at three months (p = 0.02). Next, 24-hour records were compared between the groups of the bottom and top half in weight loss at 12 months (Fig 7). While only one out of six records of the bottom half was inside the weight maintenance box, four out of six records of the top half stayed within the weight maintenance box. A significant difference in fiber density was observed between the top half and bottom half (p = 0.04) although there was no difference in protein density (p = 0.19) (Fig 7). There was no significant difference in protein density between the two groups at any time point.

Fig 7 — Twenty-four-hour records conducted at one, two, three, five, seven and 12 months. Dietary records were divided to two groups based on top half (n = 6) and bottom half (n = 6) of weight loss at 12 months. Data are presented as mean. §p = 0.04 significant difference in fiber density between two groups by repeated measure ANOVA when all time points of 24-hour records were combined (n = 35 for each group).

Correlation among weight loss and protein and fiber density

Correlations between diet and weight changes were tested to identify possible determinants of weight loss success (Fig 8). A significant correlation was found between weight loss at three months and weight loss at 12 months, suggesting participants who lost weight during the initial three months continued to lose more (p = 0.03, r_p = 0.64). A positive correlation was observed between protein and fiber densities at three months (p = 0.02, r_p = 0.64). A positive correlation between protein density at three months and its density at six months was also observed (p = 0.002, r_p = 0.80). No significant associations were found between weight loss and either protein or fiber density at any months tested.

Exit survey

The results of the exit survey at 12 months are shown in S3 Appendix. Questions one and three suggested that participants who completed the program found it beneficial for applying skills such as interpreting nutrition information to maintain healthier eating behaviors. A high score was received in program content with instructors being knowledgeable (question 5) and available to offer support (question 8). Finally, participants reported that the visual feedbacks, including the PF plot and weekly weight chart, were easy to understand and helpful (questions 9 and 10). The overall findings from the survey suggested that iDip equipped participants with valuable nutrition knowledge and skills, which enabled some individuals to adhere to dietary changes. However, the scores of questions 2 and 11 showed that the program was lacking in some aspects of satisfaction in overall engagement and individual goal achievements.

Discussion

This non-randomized and single-arm trial demonstrated the feasibility of a new approach to weight loss that utilized two key visual feedback systems: the PF plot and the weekly weight chart. These quantitative feedbacks allowed participants to self-select dietary modifications and monitor their energy balance without calorie counting. iDip uniquely used no calorie counting, meal plans or recipes, meal replacements, or food exclusions. At 12 months, mean weight loss was -5.4±1.7% (p <0.01), and 50% of participants achieved >5% weight loss.

Innovations

iDip was aimed to increase dietary flexibility and easily monitor energy balance, two shortcomings of many existing weight loss programs. To increase dietary flexibility, iDip provided nutrition education and individualized dietary feedback in the form of a PF plot to empower participants to develop a weight loss diet suitable to their taste preferences and lifestyle. Participants were able to create and advance a weight loss diet based on the PF plot. Participants were not given specific meal plans, meal replacement products, or recipes; rather, all dietary modifications were selected and implemented by individuals with guidance from individual counseling and educational sessions delivered by dietitians. Importantly, no macronutrient or food group was excluded or limited in contrast to the practice commonly used in dieting programs, such as the Atkins diet. Also, iDip did not place any focus on the fat and carbohydrate ratios in a diet as modifying fat and carbohydrate ratios has been reported to be ineffective for long-term weight loss [10, 13]. Participants were encouraged to self-select to limit intake of foods that contain minimal fiber and protein, but they were not instructed to exclude any particular foods from their diet. Thus, all diets and macronutrient distributions differed by participants.

The iDip study participants significantly lost weight by creating their weight-loss diet based on feedback in the form of a PF plot. Previously in a 12-week university cafeteria study, we tested if providing nutrient information in a PF plot format could assist customers in making an informed, healthier choice [33]. In the study, no nutritional information was provided during weeks one-three and seven-nine, and a Nutrition Facts Panel and a PF plot were posted on identical menu items, during weeks four-six and weeks 10–12, respectively. Sales data, the primary outcome, showed that when the PF plot was displayed, the protein content and protein + fiber content of purchased meals was significantly higher than no posting periods, whereas the Nutrition Facts Panel had no effect. These results have shown the PF plot’s ease of understanding and its ability to improve consumer food choices [33]. In the current study, all educational session materials and individual diet feedback were provided in the form of a PF plot, demonstrating the applicability of the PF plot to creating a weight-loss diet by individual participants.

iDip utilized daily self-weighing on a Wi-Fi-enabled scale to provide easy and reliable energy balance monitoring without calorie counting or daily food journals. Self-monitoring is a critical factor in behavior changes for weight loss [43, 44]. Bertz et al. showed daily self-weighing and weekly summary feedback can limit weight gain [45]. We provided a cumulative weight loss progress chart every week, eliminating the need for calorie counting entirely and providing means for self-monitoring. The purpose of the six 24-hour records administered was to evaluate progress in dietary improvement, not to monitor energy balance.

iDip had a retention rate of 85.7%, indicating likeability of our program and its flexible dietary approach. This high retention was achieved without monetary compensation. Participants were given the Wi-Fi scale (value ~ $60) to keep after completing the study. The dietary flexibility, self-selection of foods, and no need for daily calorie counting may have at least in part contributed to the low attrition.

Limitations

We chose the minimum number of participants to achieve the study objective of testing the feasibility of a novel dietary weight loss approach, not to test the robustness of the program as a clinical treatment option. Despite achieving a clinically significant mean percent weight loss of >5%, we observed some limitations. First, a success rate of 50% of participants achieving >5% weight loss at 12 months is not sufficient to be used as a reliable treatment program. Also, a greater magnitude of weight loss will be needed for iDip to become a clinical treatment option. Second, the follow-up period (six months) was too short to assess long-term sustainability. At 18 months, 50% of the cohort was lost to follow-up and were no longer weighing regularly, suggesting that half of the participants regarded daily weighing as a requirement of the program, not an essential part of weight management. Among the remaining participants, not all were successful in maintaining their weight between 12 and 18 months, indicating the dietary changes made during the program were not sustained in some. iDip aimed to improve long-term sustainability through non-exclusion of certain food groups and self-selected approach; thus, future studies will include a longer follow-up period with better implementation of sustainable dietary changes and daily weighing for monitoring energy balance. Third, body composition changes were not measured or tracked throughout the study. However, with the focus on increased protein density, we expect little muscle mass loss. Lastly, changes in health parameters, such as blood lipid and glucose levels and changes in medications associated with obesity and other comorbidities, were not tracked. Although a randomized and controlled trial is standard for clinical studies, a large-scale, randomized, controlled weight-loss trial has shown that the weight of the placebo group was unchanged during one year, whereas the metformin and lifestyle modification groups lost significant weight [46]. Therefore, this landmark study suggests that the lack of a no-treatment control group would not pose a major limitation in interpreting the weight loss outcome of our study.

Future directions

This study showed proof of concept for the non-exclusion of certain food groups and self-selected approach to dietary weight loss. Based on this success, steps of future studies will include: 1) increase the magnitude of mean percent weight loss; 2) improve the overall success rate of participants achieving >5% weight loss; 3) monitor body composition to minimize loss of skeletal muscle mass; 4) calculate intervention cost; and 5) collaborate with other health professionals to track health markers, such as blood lipids, and address medical and psychological barriers to weight loss. In the long term, a large-scale, multi-center trial with a comparable control group is required to test general applicability and effectiveness of the program as a treatment option for obesity.

Conclusions

In conclusion, this non-randomized and single-arm trial has shown the feasibility of the informed decision-making approach for dietary weight loss by utilizing two forms of quantitative visual feedback. One was the PF plot to monitor protein per energy and fiber per energy intake, and the other was the daily weight chart to monitor energy balance. Participants understood these visual weight management tools well. Participants significantly improved fiber density from the baseline FFQ to the final FFQ, and protein density significantly increased from the baseline 24-hour record at several time points in the study. The participants achieved a mean percent weight loss of -5.4±1.7%, and half of them successfully lost ≥5% baseline weight. The dietary flexibility and self-selection of foods may have contributed to a low attrition rate. Future studies are warranted to improve success rate, magnitude of weight loss and long-term sustainability.

Supporting information

S1 Checklist. CONSORT for pilot and feasibility study.

(PDF)

Click here for additional data file.^{(90.7KB, pdf)}

S2 Checklist. TIDieR checklist.

(PDF)

Click here for additional data file.^{(234.4KB, pdf)}

S1 Appendix. iDip educational session topics.

(PDF)

Click here for additional data file.^{(95.9KB, pdf)}

S2 Appendix. Food Frequency Questionnaire.

(PDF)

Click here for additional data file.^{(3.5MB, pdf)}

S3 Appendix. Exit survey outcomes.

(DOCX)

Click here for additional data file.^{(16.2KB, docx)}

S1 Protocol. Clinical trial protocol.

(PDF)

Click here for additional data file.^{(254.5KB, pdf)}

Data Availability

All relevant data are available in the Illinois Data Bank (DOI: 10.13012/B2IDB-4710255_V1).

Funding Statement

The authors received specific fundings. MN, CA MN: ILLU-698-908; United States Department of Agriculture of the National Institute of Food and Agriculture; https://nifa.usda.gov CA: T32EB019944; National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health; https://www.nibib.nih.gov The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0267876.r001

Decision Letter 0

Jamie I Baum

21 Oct 2020

PONE-D-20-14863

Individualized Diet Improvement Program (iDip), an approach to weight loss by combining self-experimenting and self-monitoring using visual feedback: before and after study design

PLOS ONE

Dear Dr. Lee,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

Kind regards,

Jamie I. Baum, PhD

Academic Editor

PLOS ONE

Additional Editor Comments:

The title of the manuscript inaccurately describes the study. The paper needs the be re-written for syntax.

ABSTRACT

The abstract methodology is vague. What makes this study individualized as described in the title? What was the breakdown of male and female participants and average age? The results are descriptive, with no mention of p-values. Strong conclusions for n=12 finishing the iDip program.

INTRODUCTION

Lines 44-45: These are outdated programs that do not have as large of following as the did when first launched and the authors should include updated diet programs as examples.

Several weight loss/energy reduction methods are described in the introduction. However, the title describes iDip as an individualized program and the introduction should address the importance of addressing individualized needs for successful weight loss.

MATERIALS AND METHODS

Lines 88-132 should come after participant recruitment and study design. This section is actually part of study/intervention design.

-CONSORT guidelines should be followed

-Were medications, alcohol intake, or tobacco use taken into consideration for recruitment?

-No clear power analysis is presented.

-Line 150- reference needed for attrition.

-It is unclear how this study was individualized apart from the 3, 30-minute session offered over the 12 month intervention.

Line 164: be specific beyond periodic. If the objective was to direct food intake based on protein and fiber density, then this feedback seems like it should be more regular than periodic.

Line 183: again, be specific about periodic

How often were participants providing feedback on home weighing

The fiber and protein density plots seem difficult for the lay-person to understand. How was comprehension amongst participants assessed?

How were FFQ collected? Digitally?

RESULTS

Exit survey could become supplemental material

DISCUSSION

-It is unclear how iDip is innovative.

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Partly

Reviewer #2: No

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

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Reviewer #1: The title is too long and should reflect the fact that it is a pilot study to test the feasibility of iDip on weight loss at 12 months.

The initial protocol stated that, 30 participants would be in an intervention group and 30 in the wait-list group. The study design reported in this paper involved only 12 participants in a before-after comparison. Please explain. Rather than using the minimum sample size reported in other published studies, a formal power calculation should be provided to support the selected sample size. With more than one primary outcomes, what was the minimum effect size to detect post intervention?

Data analysis only considered the paired t-tests on the differences before and after the intervention, and Pearson correlation on the associations between body weight and protein/fiber density. For a small sample of 12 participants who completed the intervention, have the authors checked the distribution of outcomes and considered non-parametric tests? The authors also compared the two groups of participants between the top and bottom half in weight loss at 12 months, what test was performed here? The repeated measures ANOVA reported in Figure 7 should also be mentioned in statistical analysis section.

As this is not a randomised trial, baseline demographics and medical histories can be reported in Table 1 on the 12 participants who completed the intervention at 12 months. The two participants that discontinued the intervention can be described separately in text. It is also important to present baseline characteristics of the two groups of participants above or below 5% weight loss at 12 months and see how they may differ.

The raw outcomes presented in Table 2 would be better presented as a full dataset at baseline and 12 months, since the primary and secondary outcomes were measured at these two time points on a total of 12 participants.

There was no Table 3. For Table 4, I would suggest reporting median together with mean (SD) for a score of 1-7. The SE is redundant and should be removed.

Both Pearson and Spearman correlation coefficients should be reported in a small sample.

Note that mean weight loss is different from % weight loss, and the terms should not be used interchangeably.

Reviewer #2: This paper reports on a small study evaluating the Individualized Diet Improvement Program (iDip) at 12 months. The 14 participants are only evaluated pre and post.

Major

1. Study design

This study lacks a comparison group which makes the authors' claims about the success of the program and the critical role of certain aspects of the program (the plot) unfounded. This evaluation is also only completed on a small group of people. If the sample were small, but the study design more rigorous, this alone would not be a major issue. However, in combination, it severely impairs any contribution to scientific knowledge.

2. Intervention

It is unclear what exactly is novel and innovative about this weight management approach. The Protein-Fiber plot seems to be a big part of it. There is no evaluation of whether this plot was really used and all participants received it, so it is impossible to know its actual contribution to the program. The plot itself also appears to present only single foods and does not seem to account for whole diet or mixed foods (like casseroles) which is a major limitation.

In the discussion, the study is described as innovative because it does not use calorie counting, specific food advice and is non-restrictive. But, ultimately the program applies a 25% energy restriction. In the discussion it says that participants were "encouraged to include all foods and self-select to moderate intake of foods with low protein and fiber densities". Given that the program included 19, 60-min meetings and 3 individual sessions delivered by a registered dietician, it would appear that this program is little more than a group-based, dietitian program.

Despite suggestion that this program lacked detailed food or intake monitoring, the participants did monitor their food intake by completing 6 different 24h recalls. Although not a formal part of the program, with no comparator, it is impossible to know the effects of this. Previous studies have shown the importance of monitoring and how it alone can reduce intake.

Minor

1. Why does the program include daily weighing? This can be a controversial recommendation that can result in obsessing over insignificant changes.

2. Figure 8 is an R output that may not be easily interpretable by many readers.

3. In the method, it states that dietary recalls were "periodically" completed. This needs to be specified.

4. The intervention and its specific novelty is not made particularly clear. Parts of the discussion provide better insight than the method, but this should be clear long before

5. The expenditure side of energy balance is not acknowledged in the introduction.

6. The discussion describes the diet as non-restrictive. It includes a 25% restriction.

7. There is no citation for the Power calculation.

8. There may exist an opportunity to explore how participants chose to restrict their diet and whether certain patterns were more successful. This could be more interesting as an outcome of the study and more of a contribution to the field.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2022 May 26;17(5):e0267876. doi: 10.1371/journal.pone.0267876.r002

Author response to Decision Letter 0

4 Dec 2020

Thank you for your careful evaluations of our manuscript and helpful comments. As shown below, we addressed all of the comments and revised the manuscript accordingly. With this revision, we believe that descriptions of the study are clearer, and the manuscript is easier to follow.

Additional Editor Comments:

The title of the manuscript inaccurately describes the study. The paper needs the be re-written for syntax.

• Title has been revised to better summarize the study.

ABSTRACT

• Clarification of individualization: In lines 5-8, the abstract has been reworded to emphasize the self-selected dietary changes by individual participants.

• Average age and gender proportion of the participants are included in line 15.

• P-values are added for results.

• The conclusion relates only to the feasibility of the approach and does not make claims beyond that.

INTRODUCTION

Lines 44-45: These are outdated programs that do not have as large of following as the did when first launched and the authors should include updated diet programs as examples.

• Excluding certain food groups are a mainstay of dieting books although popularity may come and go. Atkins and Zone diets are still used by many. More importantly the new and trendy diets are often rebranding of old diet programs. For example, the keto diet, which is currently very popular, is essentially the same as the Atkins diet although it is marketed as novel. The paleo and plant-based diets are similar to Zone and Ornish diets, respectively. This point is added to the Introduction in lines 43-48.

• The last paragraph (line 80-94) of the Introduction is revised to highlight the individualized approach of our study.

MATERIALS AND METHODS

Lines 88-132 should come after participant recruitment and study design. This section is actually part of study/intervention design.

• This section has moved to line 146-191.

CONSORT guidelines should be followed

• After confirming with the PLOS ONE editorial office, the TREND checklist should be used due to the non-randomized study design.

Were medications, alcohol intake, or tobacco use taken into consideration for recruitment?

• Medications (except for insulin), alcohol intake, or tobacco use were not taken into consideration for recruitment as described in Participant recruitment.

No clear power analysis is presented.

• Details of power calculation to determine the sample size were added to lines 106-113.

Line 150- reference needed for attrition.

• Reference is added in line 112.

It is unclear how this study was individualized apart from the 3, 30-minute session offered over the 12 month intervention.

• What we meant by “individualized” was that individuals decide and create their weight loss diet, not that instructors provide several one-on-one advising sessions. This point is clarified in both the Abstract (Line 5-8) and Introduction (Line 82-90).

Line 164: be specific beyond periodic. If the objective was to direct food intake based on protein and fiber density, then this feedback seems like it should be more regular than periodic.

• Timepoints were added in line 141.

Line 183: again, be specific about periodic.

• Timepoints were added in lines 208-209.

How often were participants providing feedback on home weighing?

• The weight chart was provided to participants on a weekly basis as mentioned in line 140.

The fiber and protein density plots seem difficult for the lay-person to understand. How was comprehension amongst participants assessed?

• Based on “Improvements in recall and food choices using a graphical method to deliver information of select nutrients,” reported by Pratt et al., the comprehension of the plot was high as 83.8% of participants (n=142) responded that they understood the nutrition graph.

• Our participants also reported the visual feedbacks were easy to understand and helpful as mentioned in lines 331-332.

How were FFQ collected? Digitally?

• The FFQ was collected in a paper version and we clarified this point in lines 205-206.

RESULTS

Exit survey could become supplemental material

• Exit survey was moved to the supplemental materials, as S3 Appendix.

DISCUSSION

It is unclear how iDip is innovative.

• We have revised the Abstract (lines 5-8), Introduction (43-48, 56-59, 80-94), Methods (146-191) to clearly state our innovative approach in the early part of the manuscript.

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• IRB approved the iDip as a part of a series of studies.

• The registry has been revised to publish each trial separately. The first study described in this manuscript is now registered with 14 participants.

• Dates are specified in lines 96-102.

• We used a validated FFQ (S2_Appendix) as shown in lines 205-208.

• We appreciate your kind suggestion. Exit survey is now S3_Appendix.

• In Table 1, we have revised to White from Caucasian.

As per the journal’s editorial policy, please include in the Methods section of your paper:

1) your reasons for your delay in registering this study (after enrolment of participants started);

• We mentioned our reason for our delay in lines 98-99.

2) confirmation that all related trials are registered by stating: “The authors confirm that all ongoing and related trials for this drug/intervention are registered”.

• We made a confirmation in lines 99-100.

• The report date at which the ethics committee approved and the complete data range for recruitment and follow-up are stated in lines 97, 100-101.

• DOI is 10.13012/B2IDB-4710255_V1.

Reviewer #1:

The title is too long and should reflect the fact that it is a pilot study to test the feasibility of iDip on weight loss at 12 months.

• Removed Individualized Dietary Improvement Program (iDip) in title and added “Feasibility”.

• Because of the feasibility nature of the study and logistic limitations, we started with half the size of original plan, n=14 instead of n~30, and planned to repeat the procedure if necessary. However, we were able to achieve the primary objective with the first cohort. Thus, rather than repeating the same trial, we amended the IRB protocol for the second trial, which is currently ongoing. Also, because the number of wait-listed participants declined in the process, we had to adopt the before and after design instead.

Rather than using the minimum sample size reported in other published studies, a formal power calculation should be provided to support the selected sample size. With more than one primary outcomes, what was the minimum effect size to detect post intervention?

• Details of the power calculation to determine the sample size were added to lines 106-113.

• Lines 226-228 are added to show enhanced detail on statistical analyses including distribution of outcomes.

• We did not consider non-parametric tests because Shapiro-Wilk testing indicated our data set was normal.

• Top and bottom groups were divided into two halves by the magnitude of weight loss. No statistics should be applied between their weights. We did run statistics on diet between the two groups (Fig 7). As mentioned in the captions, we used paired t-test.

• The repeated measures ANOVA is added in the methods section.

• We added another column to show the characteristics of completers in Table 1.

• No significance was found in any demographic data between the top and bottom groups in weight loss. A sentence is added to Results in lines 242-243.

• We believe adding 6 and 18 month data is informative.

There was no Table 3. For Table 4, I would suggest reporting median together with mean (SD) for a score of 1-7. The SE is redundant and should be removed.

• We apologize for our mistake and appreciate your pointing this out. We have changed Table 4 to Table 3 and eliminated SE. Table 3 has become S3 Appendix.

Both Pearson and Spearman correlation coefficients should be reported in a small sample.

• Because Shapiro-Wilk testing indicated our sample, while small, was normal. As such, we do not find it necessary to utilize non-parametric testing.

Note that mean weight loss is different from % weight loss, and the terms should not be used interchangeably.

• Revisions have been made throughout the manuscript to not to use these terms interchangeably.

Reviewer #2:

This paper reports on a small study evaluating the Individualized Diet Improvement Program (iDip) at 12 months. The 14 participants are only evaluated pre and post.

Major

1. Study design

• This is a feasibility study to test if the novel, dietary approach can deliver a mean weight loss of >5% initial body weight. A before-and-after design without a control group is frequently used for weight loss studies of 12 months or less because it is very unlikely that a control group achieves >5% weight loss without any intervention in this time span.

• Efficacy of the PF plot for a food selection by customers in a restaurant setting was demonstrated in our previous study “Improvements in recall and food choices using a graphical method to deliver information of select nutrients,” reported by Pratt et al. Applying the PF plot in achieving weight loss was part of the study objectives, but we did not find any overstatement of our study results regarding the PF plot’s efficacy in our manuscript. Based on the editor and the other reviewer’s comments, we revised to present the innovative nature of our approach including the PF plot more clearly in Abstract (lines 5-8) and Introduction (lines 82-90).

• Details of the power calculation to determine the sample size were added to lines 106-113.

2. Intervention

• As mentioned in the reply to the previous query, the innovative approach is better highlighted throughout the revised manuscript

• PF plot is the only analysis and feedback on participants’ diet. Participants were able to create and advance their weight loss diet based on the plot. No single recipe, food exclusions, or meal plans were provided to them. This point is clarified in the Methods section in lines 142-143 and 350-351.

• As shown in Figures one, five and six as well as Pratt et al 2016, the advantage of the PF plot is it can plot individual foods, a dish (like casserole), meal, or meals. Alternatively, a dish can be plotted by individual ingredients as well to improve a recipe. In a previous study (Pratt et al), there were significant improvements in cafeteria food choices when the plot was displayed, whereas the presence of a nutrition facts label had no effect. Additionally, the blue total dot, as mentioned in Figure one caption, displays the meal or day’s average nutritional value.

• The expression “non-restrictive” may be misleading. We replaced it with “no exclusion of certain food groups.” This point is clarified by rewording in lines 405 and 414.

• We made it clear to the participants that their daily energy intake must be reduced to achieve weight loss. This is the rationale for the two target boxes for weight maintenance and weight loss in the PF plot (Figure one and lines 163-168). However, the participants reduced the energy intake by choosing from green foods in the PF plot to move their meal closer to the target weight loss box. Energy balance was monitored via daily self-weighing. The difference is that participants achieved negative energy balance without traditional daily calorie counting or following portion controlled daily menus.

In the discussion it says that participants were "encouraged to include all foods and self-select to moderate intake of foods with low (high) protein and fiber densities".

• We rephrased it to make our point clear as follows: “Participants were encouraged to self-select to limit intake of foods that contain minimal fiber and protein, but they were not instructed to exclude any particular foods from their diet.” (lines 358-360)

Given that the program included 19, 60-min meetings and 3 individual sessions delivered by a registered dietician, it would appear that this program is little more than a group-based, dietitian program.

• We assume the reviewer is questioning the individualized nature of our program. What we meant by “individualized” was that individuals decide and create their weight loss diet, not that instructors provide several one-on-one advising sessions. This point is clarified in Abstract (lines 5-8) and Introduction (lines 82-90).

• The participants achieved significant weight loss with only six 24-hour records in the 12-month period and daily weighing (this is a daily monitoring although not food intake monitoring). An important difference is time required for participants for 6 24-hour records and daily weighing was much less than daily food intake monitoring. Previous studies did show monitoring alone could reduce intake. However, to our knowledge, there is no study that reported weight loss success comparable to ours in magnitude, duration, and retention by daily food intake monitoring alone.

Minor

1. Why does the program include daily weighing? This can be a controversial recommendation that can result in obsessing over insignificant changes.

• As stated in lines 178-184, daily weighing is the easiest and fastest way to monitor energy balance. “Frequent self-weighing with electronic graphic feedback to prevent age-related weight gain in young adults,” by Bertz et al. has shown that providing weekly feedback prevents weight gain in young adults. Daily weighing shows the fluctuations but more importantly displays an overall trend. We emphasized that participants should look at weekly and monthly trends, not daily fluctuations. Our participants reported no problems with daily weighing.

2. Figure 8 is an R output that may not be easily interpretable by many readers.

• The matrix was used in Figure eight as it displays relatively minor findings and saves space.

3. In the method, it states that dietary recalls were "periodically" completed. This needs to be specified.

• The months were data was collected are specified in the legend of Figure seven, and also added to the methods (lines 141 and 208-209).

4. The intervention and its specific novelty is not made particularly clear. Parts of the discussion provide better insight than the method, but this should be clear long before

• Thank you for your helpful comment. We have revised the Abstract (lines 5-8), Introduction (43-48, 56-59, 80-94), Methods (146-191) to state our innovative approach clearly in the early part of the manuscript.

5. The expenditure side of energy balance is not acknowledged in the introduction.

• If the “expenditure side of energy balance” refers to exercise, it is very challenging to achieve the large negative energy balance necessary for weight loss via physical activity only. As such, we focused on the dietary aspect of weight loss in our program.

6. The discussion describes the diet as non-restrictive. It includes a 25% restriction.

• What we meant by “non-restrictive” was not to exclude any food groups from diet. This point is clarified by changing wording in lines 405 and 414.

7. There is no citation for the Power calculation.

• The details of power calculation to determine the sample size were added to lines 106-113.

• Thank you for an interesting suggestion. We will explore it in future, larger studies.

Attachment

Submitted filename: Response to Reviewers.docx

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PLoS One. doi: 10.1371/journal.pone.0267876.r003

Decision Letter 1

John W Apolzan

9 Aug 2021

PONE-D-20-14863R1

A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection

PLOS ONE

Dear Dr. Lee,

Please submit your revised manuscript by Sep 23 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

John W. Apolzan, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

As a reviewer notes, the tone of the manuscript needs to ensure that it is a feasibility study without a control group. The lack of a control group is a study limitation that needs to be stated. Please ensure the reviewer responses are addressed. Use of terms such as non-randomized and single arm trial would be beneficial throughout the manuscript including the conclusions. Further, the pilot or feasibility consort should be utilized. Also, the (TIDieR) checklist and guide should be used to describe the intervention.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: No

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #2: Major

Issues raised about the study design previously remain. Without a control group, the authors cannot conclude that the PF plot has efficacy over and above the methodological aspects of the study which included an extensive amount of dietary recall and FFQ and dietary coaching with a health professional. Further, as a feasibility study, it lacks any in-depth evaluation of the innovative components of the intervention (eg, the PF plots).

The authors state that they could not find any overstatement in their conclusions. Two concrete examples are provided below. Each shows a lack of acknowledgement of study limitations while also being worded too strongly.

1) “The individualized PF plot played a critical role in dietary improvement and allowed participants to use the knowledge gained from education sessions to self select foods to increase or decrease.”

Regular and intensive dietary recall and meetings with a dietician were much more likely the cause of this and the study design does not allow these to be teased apart. There is no evaluation of the possible mechanisms either. This statement suggests a linear process that has been demonstrated. The study provides no data to support this strongly worded statement. Furthermore, the ethics application notes that the purpose of the dietary recall is to “check adequacy of their diet and to troubleshoot if a participant is not losing weight effectively” so the recall process is seemingly a significant part of the overall intervention which is conveniently overlooked in favor of the PF plots in the paper conclusions.

2) “The dietary flexibility, self-selection of foods, and no need for daily calorie counting likely contributed to the low attrition.”

Data do not support this. Once again with no comparison, it is impossible to know. The study design was very intensive and personal and more likely a contributor to high retention.

If the study is a feasibility study and the main focus is on the PF plot, then there should have been an evaluation of this plot and how it was received, used, evaluated etc. Yet, questions in the Exit Survey do not ask anything about this. The authors failed to address this concern from the previous review. It remains difficult to determine the relevance of this core component in the absence of a comparator group and any thorough evaluation of these components.

Minor

SI Appendix 5: Blood pressure was measured according to the original protocol, why is this not presented?

It is unclear what this means: “Registration was delayed due to lack of knowledge.”

Reviewer #3: The authors have addressed the comments satisfactorily. I believe that calling the study "individualized diet..." sounds misleading because it appears to refer to personalized nutrition. While not a good term, it seems like it should be called "self-guided diet individualization..."

**********

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Reviewer #2: No

Reviewer #3: No

PLoS One. 2022 May 26;17(5):e0267876. doi: 10.1371/journal.pone.0267876.r004

Author response to Decision Letter 1

3 Sep 2021

Response to Reviewers

We truly appreciate your thoughtful review of our manuscript and helpful comments. As shown below, we addressed the comments and revised the manuscript accordingly. With this revision, we believe that descriptions of the study are clearer, and the manuscript is easier to follow.

Additional Editor Comments:

• Thank you for your kind suggestion. We stated non-randomized and single-arm trial in lines 123, 343, and 433.

• We do not consider the lack of a non-treatment control group as a major limitation of this study. Although we agree that a randomized and controlled trial (RCT) is a gold standard of clinical studies, in the case of weight loss study, a large-scale RCT (DPP Research Group, 2002) has shown that the weight of the placebo group was unchanged after one year, whereas metformin and lifestyle group significantly lost weight. This point was added to the Discussion in line 416-421.

Further, the pilot or feasibility consort should be utilized. Also, the (TIDieR) checklist and guide should be used to describe the intervention.

CONSORT for pilot and feasibility study

• We added the timeline of intervention in line 131-132 to follow the guideline.

• We added the CONSORT as S4 Appendix.

TIDieR

• We added the objective of the study in line 125-127 and the location of study administration in line 131.

• We added the checklist as S5 Appendix.

Reviewer #2:

Major

• Thank you for raising questions, which seem to be due to unclear descriptions of our objectives and intervention protocol.

• The objective of this study is not to compare the efficacy of our approach with certain conventional approaches. The objective of this feasibility study is to determine if our new approach that replaced conventional methods works. Revisions are made to clarify this point in the revised last paragraph (line 80-87) of Introduction, Study Deign (line 125-127; 129-132; 141-144), and Development of novel learning tools (line 147-151; 169-172) in Methods

• For this objective, a control group should be a non-treatment group, not a certain traditional weight-loss method. The lack of non-treatment control is addressed in the reply to the editor above.

• Although graduate students with RDN credentials in this research project provided lectures and coaching, the entire interactions in both group sessions and individual advice were performed to test the new approach:

o Feedback of FFQ, 24-hour records were always provided using the PF plot.

o No food was excluded from participant’s diet, and even no recipe was provided to them. As the manuscript title shows, what dietitians provided was a visual comparison of food properties for participants to make informed decisions.

o Efficacy of visualization of nutrient values with PF plot was previously reported (Pratt, 2016).

• These points were stated clearly in the revised Methods (lines 125-127, 137-144, and 147-151) and Discussion (lines 352-366 and 368-381).

• In-depth evaluation of innovative components would be optional because weight loss was set as the primary outcome in our study design. This reviewer’s comment overlaps with the comment on the exit survey, which is addressed below.

• The wording of the statement is revised to reflect our results accurately (line 367-368).

• The purpose of the 24-hour records was exactly as quoted above, and advice based on the record was an important part of the study design. Please note that analysis of all dietary records was provided in the form of a PF plot, and advice was based on the PF plot and aimed at enhancing informed decisions by participants.

• The above points were clarified in Study Design (line 138-141) as well as Discussion (line 352-356).

2) “The dietary flexibility, self-selection of foods, and no need for daily calorie counting likely contributed to the low attrition.” (434-435)

Data do not support this. Once again with no comparison, it is impossible to know. The study design was very intensive and personal and more likely a contributor to high retention.

• The sentence is revised to reflect our results more accurately (line 393-394).

• Thank you for raising a good point. In the exit survey, we asked about only our overall approach. In retrospect, it would have been more informative if we had added questions on specific components as well.

• That said, because the PF plot was shown to enhance informed decision-making in a restaurant setting, and this entire study was an application of the PF plot to create a self-guided weight loss diet, the outcome of significant weight loss is sufficient to conclude the PF plot-based weight loss is feasible (as clarified in the responses above) without “a comparator group” (addressed in the response to the editor and introduction) or more specific exit survey questions (an optional, not essential component).

Minor

SI Appendix 5: Blood pressure was measured according to the original protocol, why is this not presented?

• We failed to measure blood pressure throughout the study.

It is unclear what this means: “Registration was delayed due to lack of knowledge.”

• We apologize for the confusion. We restated to make the statement clear in line 93-94.

• Thank you for your helpful suggestion. The expression “individualized diet” in some parts may be misleading. We edited the “individualized diet” to “self-guided” in line 24.

Attachment

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Click here for additional data file.^{(26.7KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0267876.r005

Decision Letter 2

John W Apolzan

19 Apr 2022

A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection

PONE-D-20-14863R2

Dear Dr. Lee,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

John W. Apolzan, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0267876.r006

Acceptance letter

John W Apolzan

18 May 2022

PONE-D-20-14863R2

A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection

Dear Dr. Lee:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. John W. Apolzan

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. CONSORT for pilot and feasibility study.

(PDF)

Click here for additional data file.^{(90.7KB, pdf)}

S2 Checklist. TIDieR checklist.

(PDF)

Click here for additional data file.^{(234.4KB, pdf)}

S1 Appendix. iDip educational session topics.

(PDF)

Click here for additional data file.^{(95.9KB, pdf)}

S2 Appendix. Food Frequency Questionnaire.

(PDF)

Click here for additional data file.^{(3.5MB, pdf)}

S3 Appendix. Exit survey outcomes.

(DOCX)

Click here for additional data file.^{(16.2KB, docx)}

S1 Protocol. Clinical trial protocol.

(PDF)

Click here for additional data file.^{(254.5KB, pdf)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(39.6KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(26.7KB, docx)}

Data Availability Statement

All relevant data are available in the Illinois Data Bank (DOI: 10.13012/B2IDB-4710255_V1).

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PERMALINK

A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection

Mindy H Lee

Catherine C Applegate

Annabelle L Shaffer

Abrar Emamaddin

John W Erdman Jr

Manabu T Nakamura

Roles

Abstract

Introduction

Materials and methods

Participant recruitment

Fig 1. Flow diagram of the participants.

Study design

Fig 2. Protein and fiber plot with example food items.

Development of novel learning tools

A quantitative nutrient display method

Energy balance monitoring

Fig 3. A weekly weight chart feedback.

Outcome measures

Anthropometrics measures

Dietary assessment

Survey measures

Data analysis

Results

Participant characteristics

Table 1. Demographic data of participants.

Retention

Change in anthropometric measures

Table 2. Characteristics of participants who completed dietary improvement sessions.

Fig 4. Weight changes (%) of each participant at six, 12, and 18 months.

Fig 5. Weight changes (%) of all, top-half and bottom-half groups over 12 months.

Change in dietary components

Fig 6. Changes in protein and fiber density of the whole group assessed by FFQ and 24-hour records.

Fig 7. Changes in protein and fiber density of top and bottom half groups in weight loss at 12 months.

Correlation among weight loss and protein and fiber density

Fig 8. Correlation matrix showing the interrelationship among weight loss and protein and fiber density at three months, six months, and 12 months.

Exit survey

Discussion

Innovations

Limitations

Future directions

Conclusions

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Jamie I Baum

Roles

Author response to Decision Letter 0

Decision Letter 1

John W Apolzan

Roles

Author response to Decision Letter 1

Decision Letter 2

John W Apolzan

Roles

Acceptance letter

John W Apolzan

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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