Diet Quality and Micronutrient Intake among Long-Term Weight Loss Maintainers

Weight Loss Maintainers Sustain High Diet Quality in Diverse Residential Retail Food Environments

BACKGROUND

The relationship between the retail food environment and diet quality has received minimal investigation among weight loss maintainers.

OBJECTIVE

The aim of this study was to investigate the association between the residential retail food environment and diet quality in weight loss maintainers from WeightWatchers in the United States.

DESIGN

Cross-sectional data were collected between January 2018 and February 2020. The Retail Food Environment Index (RFEI), based on geocoded home addresses, classified the environment as follows: RFEI <1.6 = healthiest; RFEI 1.6 to <2.5 = moderately healthy; RFEI 2.5 to <4.0 = moderately unhealthy; RFEI ≥4.0 = least healthy. Dietary data were obtained using a food frequency questionnaire.

PARTICIPANTS/SETTING

Adult participants (n = 1,159) who had lost weight using WeightWatchers and maintained ≥9.1-kg weight loss for ≥1 year (mean 24.7-kg loss for 3.4 years).

MAIN OUTCOME MEASURES

Healthy Eating Index 2015 (HEI-2015) component and total scores (0-100; higher scores indicate better alignment with the 2015-2020 Dietary Guidelines for Americans).

STATISTICAL ANALYSES PERFORMED

Regression models included RFEI category, the independent variable, and HEI-2015 and component scores (outcomes) controlling for age, sex, race and ethnicity, educational attainment, and household income.

RESULTS

Compared with individuals living in the healthiest food environments (mean HEI-2015 score = 71.5) those in the unhealthiest environments had a mean HEI-2015 score of 70.1 (95% CI 68.8 to 71.3), those in moderately unhealthy environments had a score of 71.3 (95% CI 70.3 to 73.1) and those in moderately healthy environments had a score of 70.3 (95% CI 68.9 to 71.2), indicating a nonlinear relationship. Compared with those in the healthiest environments, those in the least healthy environments had an approximately 0.47 lower added sugar HEI-2015 component score (95% CI -0.86 to -0.08), indicating approximately 5% higher added sugar intake.

CONCLUSIONS

Weight loss maintainers maintained high diet quality in diverse retail food environments. Compared with those in the healthiest food environments, those in the least healthy had a higher consumption of added sugars.

Unraveling the Evolutionary Diet Mismatch and Its Contribution to the Deterioration of Body Composition

Over the millennia, patterns of food consumption have changed; however, foods were always whole foods. Ultra-processed foods (UPFs) have been a very recent development and have become the primary food source for many people. The purpose of this review is to propose the hypothesis that, forsaking the evolutionary dietary environment, and its complex milieu of compounds resulting in an extensive metabolome, contributes to chronic disease in modern humans. This evolutionary metabolome may have contributed to the success of early hominins. This hypothesis is based on the following assumptions: (1) whole foods promote health, (2) essential nutrients cannot explain all the benefits of whole foods, (3) UPFs are much lower in phytonutrients and other compounds compared to whole foods, and (4) evolutionary diets contributed to a more diverse metabolome. Evidence will be presented to support this hypothesis. Nutrition is a matter of systems biology, and investigating the evolutionary metabolome, as compared to the metabolome of modern humans, will help elucidate the hidden connections between diet and health. The effect of the diet on the metabolome may also help shape future dietary guidelines, and help define healthy foods.

A blended face-to-face and eHealth lifestyle intervention on physical activity, diet, and health outcomes in Hong Kong community-dwelling older adults: a study protocol for a randomized controlled trial

Background

Aging individuals are vulnerable to various Noncommunicable Diseases (NCDs). Different behaviors are closely related to a decreased risk of suffering from NCDs: sufficient Physical Activity (PA) (e.g., at least 150 mins Moderate-to-vigorous Physical Activity (MVPA) per week) and a healthy daily diet (e.g., at least five portions of Fruit and Vegetable Intake (FVI), 5-6 taels (189.0-226.8 g) Meat, Fish, Egg and Alternatives (MFEA)). Traditional face-to-face interventions were effective in behavior change. However, it was revealed to be resource-intensive and limited transfer due to poor self-regulation skills outside of face-to-face sessions. Thus, eHealth could be a supplement for older adults outside traditional face-to-face settings. The blended approach combining these two interventions might optimize the intervention effects on lifestyle behavior initiation and maintenance, but little research can be found among Hong Kong older adults. Therefore, the study aims to test a blended intervention to promote PA, diet, and health outcomes among Hong Kong community-dwelling older adults.

Methods

This study will adopt a 10-week three-arm randomized controlled trial. The blended group will receive weekly (1) two 60-min face-to-face sessions with one for PA and one for diet, and (2) two web-based sessions with one for PA and one for diet. The face-to-face group will receive the same intervention content as the face-to-face sessions in the blended group. The control condition will receive a biweekly telephone call. The outcomes will include MVPA (minutes/week), FVI (portions/day), MFEA consumption (taels/day), social-cognitive factors (self-efficacy, planning, social support, action control), physical health outcomes (clinical indicators, senior physical fitness), mental health outcomes (depression, loneliness) and health-related quality of life. Data collection will be implemented at the pre-test, post-test, and 3-month follow-up test.

Discussion

This is the first study evaluating a blended intervention promoting multiple health behaviors among Hong Kong community-dwelling older adults. If the effect of the blended intervention is superior to the traditional face-to-face group and the control group, it will enrich lifestyle intervention approaches and can be applied to older adults, helping them obtain health benefits. Furthermore, a better understanding of mechanisms will also have implications for theory-building.

Clinical trial registration

https://www.isrctn.com/ISRCTN32329348, ISRCTN32329348.

Association of dietary adherence and dietary quality with weight loss success among those following low-carbohydrate and low-fat diets: a secondary analysis of the DIETFITS randomized clinical trial

BACKGROUND

Eating a high-quality diet or adhering to a given dietary strategy may influence weight loss. However, these 2 factors have not been examined concurrently for those following macronutrient-limiting diets.

OBJECTIVE

To determine whether improvement in dietary quality, change in dietary macronutrient composition, or the combination of these factors is associated with differential weight loss when following a healthy low-carbohydrate (HLC) or healthy low-fat (HLF) diet.

DESIGN

Generally healthy adults were randomly assigned to HLC or HLF diets for 12 mo (n = 609) as part of a randomized controlled weight loss study. Participants with complete 24-h dietary recall data at baseline and 12-mo were included in this secondary analysis (total N = 448; N = 224 HLC, N = 224 HLF). Participants were divided into 4 subgroups according to 12-mo change in HEI-2010 score [above median = high quality (HQ) and below median = low quality (LQ)] and 12-mo change in macronutrient intake [below median = high adherence (HA) and above median = low adherence (LA) for net carbohydrate (g) or fat (g) for HLC and HLF, respectively]. Baseline to 12-mo changes in mean BMI were compared for those in HQ/HA, HQ/LA, LQ/HA subgroups with the LQ/LA subgroup within HLC and HLF.

RESULTS

For HLC, changes (95 % confidence level [CI]) in mean BMI were -1.15 kg/m2 (-2.04, -0.26) for HQ/HA, -0.30 (-1.22, 0.61) for HQ/LA, and -0.80 (-1.74, 0.14) for LQ/HA compared with the LQ/LA subgroup. For HLF, changes (95% CI) in mean BMI were -1.11kg/m2 (-2.10, -0.11) for HQ/HA, -0.26 (-1.26, 0.75) for HQ/LA, and -0.66 (-1.74, 0.41) for LQ/HA compared with the LQ/LA subgroup.

CONCLUSION

Within both HLC and HLF diet arms, 12-mo decrease in BMI was significantly greater in HQ/HA subgroups relative to LQ/LA subgroups. Neither HQ nor HA alone were significantly different than LQ/LA subgroups. Results of this analysis support the combination of dietary adherence and high-quality diets for weight loss.

CLINICAL TRIAL REGISTRY

clinicaltrials.gov (Identifier: NCT01826591).

Associations of COVID-19 Lockdowns on Eating Behaviors and Body Mass Index in Patients with a History of Bariatric Surgery: a Cross-Sectional Analysis

INTRODUCTION

Few studies have explored the impact of the COVID-19 pandemic on the eating behaviors, dietary quality, and changes in weight of postoperative bariatric surgery patients.

METHODS

A cross-sectional survey on eating behaviors and attitudes toward food was emailed or given to patients who had bariatric surgery before March 2020. Patient charts were reviewed for weight measures.

RESULTS

Seventy-five (71.43%) patients experienced weight recurrence with an average increase in body mass index (BMI) of 2.83 kg/m² (SD: 2.19). The majority of patients reported no symptoms of binge eating (n = 81, 77.14%) with 16 (15.24%) qualifying for loss of control eating (LOCE). LOCE was significantly associated with grazing behavior (p = 0.04), emotional over-eating (p = 0.001), and food responsiveness (p = 0.002). LOCE was negatively associated with dietary quality (p = 0.0009) and satiety responsiveness (p = 0.01). Grazing behavior was significantly associated with emotional over-eating (p < 0.0001) and food responsiveness (p < 0.0001) as well as negatively associated with dietary quality (p < 0.0001). Slow eating was negatively associated with grazing (p = 0.01), emotional over-eating (p = 0.003), and food responsiveness (p < 0.0001). When included in a regression model controlling for age and sex, emotional over-eating was a significant predictor of weight recurrence (β = 0.25; p = 0.04).

CONCLUSION

Our results suggest that maladaptive eating behaviors contributed to LOCE and poor dietary quality during the COVID-19 pandemic; however, slow eating may be protective against grazing, emotional over-eating, and food responsiveness.

Effects of Face-to-Face and eHealth Blended Interventions on Physical Activity, Diet, and Weight-Related Outcomes among Adults: A Systematic Review and Meta-Analysis

An increasing number of studies are blending face-to-face interventions and electronic health (eHealth) interventions to jointly promote physical activity (PA) and diet among people. However, a comprehensive summary of these studies is lacking. This study aimed to synthesize the characteristics of blended interventions and meta-analyze the effectiveness of blended interventions in promoting PA, diet, and weight-related outcomes among adults. Following the PRISMA guidelines, PubMed, SPORTDiscus, PsycINFO, Embase, and Web of Science were systematically searched to identify eligible articles according to a series of inclusion criteria. The search was limited to English language literature and publication dates between January 2002 and July 2022. Effect sizes were calculated as standardized mean difference (SMD) for three intervention outcomes (physical activity, healthy diet, and weight-related). Random effect models were used to calculate the effect sizes. A sensitivity analysis and publication bias tests were conducted. Of the 1561 identified studies, 17 were eligible for the systematic review. Studies varied in participants, intervention characteristics, and outcome measures. A total of 14 studies were included in the meta-analyses. There was evidence of no significant publication bias. The meta-analyses indicated that the blended intervention could lead to a significant increase in walking steps (p < 0.001), total PA level (p = 0.01), and diet quality (p = 0.044), a significant decrease in energy intake (p = 0.004), weight (p < 0.001), BMI (p < 0.001), and waist circumferences (p = 0.008), but had no influence on more moderate-to-vigorous physical activity (MVPA) or fruit and vegetable intake among adults, compared with a control group. The study findings showed that blended interventions achieve preliminary success in promoting PA, diet, and weight-related outcomes among adults. Future studies could improve the blended intervention design to achieve better intervention effectiveness.

Recovery from weight regain among long-term weight loss maintainers in WW

OBJECTIVE

This study sought to understand the process and strategies to recover from regain among weight loss maintainers.

METHODS

Participants in WeightWatchers (WW; n = 2457) had lost ≥9 kg for ≥1 year and were grouped based on self-reported weight change after maximum loss: sustained maintenance ("Stable"), ups and downs ("Gain-Lose"), and regain ("Gain"). The groups were compared on weight control strategies, and the Gain-Lose and Gain groups reported on attempts to reverse weight regain.

RESULTS

Mean weight loss was 28.5 kg and duration of ≥9 kg loss was 3.5 years. During this time, 48% reported weight stability, and the remaining reported some regain (Gain-Lose, 29% or Gain, 23%). Among Gain and Gain-Lose, action to lose regained weight occurred after gaining >4 kg. Compared with Gain, Gain-Lose sustained reengagement efforts longer (16 vs. 10 weeks) and had better dietary choices (3.4 vs. 3.2), self-monitoring (2.9 vs. 2.7), and psychological coping (2.5 vs. 2.4) scores. Among Gain-Lose, the most successful (< 2.3 kg vs. >2.3 kg regain) initiated weight loss efforts after less regain (2.3 vs. 4.5 kg).

CONCLUSIONS

Reengaging with weight loss after regains may be most successful if focused on diet, self-monitoring, and psychological coping and initiated with less regain.

Higher protein intake during caloric restriction improves diet quality and attenuates loss of lean body mass

OBJECTIVE

Higher protein intake during weight loss is associated with better health outcomes, but whether this is because of improved diet quality is not known. The purpose of this study was to examine how the change in self-selected protein intake during caloric restriction (CR) alters diet quality and lean body mass (LBM).

METHODS

In this analysis of pooled data from multiple weight loss trials, 207 adults with overweight or obesity were examined before and during 6 months of CR (approximately 10 food records/person). Body composition was measured by dual-energy x-ray absorptiometry. Diet quality was assessed using the Healthy Eating Index in 2 groups: lower (LP) and higher (HP) protein intake.

RESULTS

Participants (mean [SD], 54 [11] years; 29 [4] kg/m² ) lost 5.0% (5.4%) of weight. Protein intake was 79 (9) g/d (1.0 [0.2] g/kg/d) and 58 (6) g/d (0.8 [0.1] g/kg/d) in the HP and LP groups, respectively (p < 0.05), and there was an attenuated LBM (kilograms) loss in the HP (-0.6% [1.5%]) compared with the LP (-1.2% [1.4%]) group (p < 0.01). The increased Healthy Eating Index score in the HP compared with the LP group was attributed to greater total protein and green vegetable intake and reduced refined grain and added-sugar intake (p < 0.05).

CONCLUSIONS

Increasing dietary protein during CR improves diet quality and may be another reason for reduced LBM, but it requires further study.

In their own words: Topic analysis of the motivations and strategies of over 6,000 long-term weight-loss maintainers

OBJECTIVE

This study aimed to identify major themes of a large cohort experiencing long-term weight-loss maintenance who answered open-ended questions about weight-loss triggers, current motivations, strategies, and experiences.

METHODS

Machine learning and topic modeling were used to analyze responses to six open-ended questions among 6,139 WW International, Inc., (formerly Weight Watchers) members with weight-loss maintenance; inclusion criteria included ≥9.1-kg loss with weight-loss maintenance for ≥1 year.

RESULTS

Participants (mean age = 53.6 years; 94.3% White; mean BMI = 27.8 kg/m² ) had lost 24.5 kg and maintained the loss for 3.4 years. Descriptions of factors triggering weight loss coalesced into five topics: medical status, appearance, mobility, social prompts, and change needed. Factors currently motivating weight-loss maintenance yielded two topics: looking back at experiences at higher weight and health/appearance concerns. Advice for others to succeed in weight-loss maintenance coalesced on two recommendations: perseverance in the face of setbacks and consistency in tracking. Rewards for weight management included improved confidence, pain, mobility, fitness, body image, medical status, and affect. Two thematic negative consequences were clothing costs and sagging skin.

CONCLUSIONS

Future weight-maintenance research should include more diverse populations and investigate weight-loss maintenance as a journey with highs and lows, perseverance in the face of setbacks, sustained tracking, and making changes in medical status more salient during the weight-maintenance journey.

Factors associated with food choice among long-term weight loss maintainers

Background

The present study aimed to examine motivations for food choice among long‐term weight loss maintainers (WLM) in a widely used commercial weight management program.

Methods

A cross‐sectional study was employed where determinants of food choice were measured in the USA using validated scales: Food Choice Questionnaire, Consideration of Future Consequences, and Eating in the Absence of Hunger. Participants were 3806 WLM following a commercial weight management program (WW International, Inc.) who had maintained a weight loss ≥ 9.1 kg (mean 24.7 kg) for 3.3 years and had a body mass index (BMI) of 27.6 kg m². A control group of weight stable individuals with obesity (controls; n = 519) had a BMI of 38.9 kg m² and a weight change < 2.3 kg over the previous 5 years.

Results

WLM vs. controls made food decisions more based on health (18.9 vs. 16.3; η_p² = 0.052) and weight control (9.9 vs. 7.5; η_p² = 0.16) and less based on price (8.4 vs. 9.1; η_p² = 0.10). WLM also scored higher than controls with respect to considering future consequences of behaviours (44.3 vs. 38.4; η_p² = 0.060) and reported less external eating in the absence of hunger (7.1 vs. 7.5; η_p² = 0.058). Standard canonical coefficients indicated that making food choices based on weight (0.717) with less value placed on price (−0.33) and greater consideration of future consequences (0.262) contributed independently and most (overall r = 0.593; p = 0.0001) to discriminating WLM from controls.

Conclusions

In a widely used commercial weight management program, successful WLM reported food decisions based more on weight and less on price and considered future consequences of current behaviours.

Long‐term weight loss maintainers consume a diet that is low in calories and micronutrient rich, although the diverse factors that govern these food choices remain unclear.

The present study examined diverse factors associated with food choice among weight loss maintainers in a widely used commercial weight management program (WW International, Inc.) compared to weight stable individuals with obesity (“controls”).

Weight loss maintainers more than controls made food decisions based on health and weight control and less based on price. Both groups scored similarly in the role of convenience, mood, sensory appeal, natural content, familiarity and ethical concerns.

Weight loss maintainers were overall more likely to consider future consequences.

In a widely used commercial weight management program (WW International, Inc.), successful weight loss maintainers reported food decisions based more on weight and health and less on price. They also considered future consequences of current behaviours.

Dietary carbohydrates and weight loss maintenance

PURPOSE OF REVIEW

Aim of the present review is to provide an overview of the effect of manipulating dietary carbohydrates (content, type) after a period of weight loss on weight loss maintenance and its potential underlying mechanisms.

RECENT FINDINGS

Few recent studies directly tested whether lower carbohydrate/glycaemic load or higher fibre diets help to limit weight regain after weight loss and they did not provide evidence supporting a role of a reduction of the carbohydrate or an increase of the fibre content of the diet in the prevention of weight regain after weight loss. Some evidence is emerging that personal characteristics (gut microbiota, glycaemia) may interact with diet composition. but randomized clinical trials are needed to substantiate these claims.

SUMMARY

There is currently no convincing evidence that lowering dietary carbohydrates has a clinically relevant effect on weight regain after weight loss, unless there is an increase in protein intake at the same time. Further randomized trials are needed to investigate potential interactions with personal characteristics while improving strategies for long-term adherence.

Sitting Time, Type, and Context Among Long-Term Weight-Loss Maintainers

OBJECTIVE

This study aimed to investigate sitting time, the home sedentary environment, and physical activity among weight-loss maintainers in WW (formerly Weight Watchers).

METHODS

Participants were 4,305 weight-loss maintainers who had maintained ≥9.1 kg of weight loss (24.7 kg on average) for 3.3 years and had an average current BMI of 27.6 kg/m² . A control group of weight-stable individuals with obesity (n = 619) had an average BMI of 38.9 kg/m² . The Multicontext Sitting Time Questionnaire and Paffenbarger physical activity questionnaire were administered.

RESULTS

Weight-loss maintainers versus controls spent 3 hours less per day sitting during the week (10.9 vs. 13.9; η p 2 = 0.039; P = 0.0001) and weekends (9.7 vs. 12.6; η p 2 = 0.038). Weight-loss maintainers versus controls spent 1 hour less per day in non-work-related sitting using a computer or video games during the week (1.4 vs. 2.3; η p 2 = 0.03; P = 0.0001) and weekends (1.5 vs. 2.5; η p 2 = 0.03; P = 0.0001). Weight-loss maintainers versus controls had similar numbers of sedentary-promoting devices (15.8 vs. 14.8) and expended significantly more calories per week in physical activity (1,835 vs. 785; η p 2 = 0.036; P = 0.0001).

CONCLUSIONS

Weight-loss maintainers reported less time sitting than weight-stable individuals with obesity. Future research should test the efficacy of targeting sitting time to help promote long-term weight-loss maintenance.

Protein-Rich Diets for Weight Loss Maintenance

PURPOSE OF REVIEW

High-protein diets in the management of obesity have been around for many years and have been rigorously tested for their ability to induce weight loss. Comparably less is known about their effects on the maintenance of lost weight.

RECENT FINDINGS

Several small and a few large randomized trials have evaluated the efficacy of high-protein diets (20-35% of calories from protein; 1.2-1.9 g/kg∙day) compared with normal-protein diets (10-20% of calories from protein; 0.8-1.3 g/kg∙day), consumed mostly ad libitum during weight loss maintenance, i.e., after clinically significant weight loss. Most of these studies indicate that weight regain in the short term (3-12 months) is lower by 1-2 kg with high-protein diets than low-protein diets. This effect is attenuated with longer periods of observation, likely because of decreasing dietary compliance. In line with findings during the active weight loss phase, studies assessing the efficacy of protein-rich diets to improve weight loss maintenance report beneficial effects in the short term, which nevertheless dissipate over time.

Malnutrition, low diet quality and its risk factors among older adults with low socio-economic status: a scoping review

Low socio-economic status (SES) is often associated with various health-related problems. Therefore, the present paper aims to review the available literature to identify the prevalence of malnutrition, prevalence of poor diet quality and its associated risk factors among older adults with low SES. A literature search was performed using four databases, namely PubMed, Google Scholar, Springer and Science Direct. The search terms used were 'diet quality', 'nutritional status', 'dietary intake', 'overweight', 'obesity', 'underweight', 'older people' and 'low socioeconomic status (SES)'. The overall prevalence of undernutrition among older adults with low SES worldwide was in the range of 28·9 to 48 %, while overnutrition was reported to be between 8·1 to 28·2 %. In Asia, the prevalence of undernourished older adults ranged from 3 to 64·9 %, while 2·5 to 32·8 % were overnourished. Most of the studies (60 %) included in the present review used BMI as the tool to identify malnutrition, but none of the nutritional screening tools were considered to be the 'gold standard'. For dietary assessment, FFQ and multiple 24 h dietary recall improved the estimation of individual dietary intake. Risk factors for poor diet quality included financial hardship, functional limitation, sex, place of residence, smoking and oral health. Poor nutritional status, especially lack of good-quality diet, and thinness are prevalent among older adults with low SES. Hence, it is important to establish nutrition-related programmes and intervention studies among this group of individuals for improving their health status and quality of life.