Weekly, seasonal and holiday body weight fluctuation patterns among individuals engaged in a European multi-centre behavioural weight loss maintenance intervention

Malnutrition in hospitalized adults in the United States, 2016-2019

BACKGROUND

Malnutrition in hospitalized patients is associated increased length of stay, cost, readmission, and death. No recent studies have examined trends in prevalence or outcomes of hospitalized patients with a diagnosis of malnutrition.

OBJECTIVES

To study the prevalence of malnutrition diagnostic codes and associated hospital outcomes in the United States between 2016 and 2019.

METHODS

We conducted a retrospective trends study to identify use of malnutrition codes in hospitalizations in the National Inpatient Sample between 2016 and 2019. We used direct standardization by logistic regression to adjust outcomes of percutaneous gastrostomy tube placement, mechanical ventilation, and death for age, Gagne comorbidity score, and sex. We then used linear regression to test for trends over time by malnutrition type.

RESULTS

Across all hospitalizations, codes for diagnoses of non-severe malnutrition and severe malnutrition were present in 3.7% and 4.1% of hospitalizations, respectively. Codes for any malnutrition increased over time, from 6.6% in 2016 to 8.6% in 2018 (p = .03). Codes for severe malnutrition increased from 3.3% to 4.7% (p = .01). Among hospitalizations with coded severe malnutrition diagnoses, there was a statistically significant decrease in adjusted rate of death over time (-0.54% per year, p = .03) which was not seen in hospitalizations without coded malnutrition diagnoses.

CONCLUSIONS

Use of malnutrition diagnosis codes increased significantly from 2016 to 2019. During this time, mortality among hospitalizations with a diagnosis code for severe malnutrition decreased. Though the increased prevalence of malnutrition codes may represent a change in the clinical characteristics of hospitalized patients, the decline in mortality suggests some of the increase may be due to lower threshold for coding and assignment of the diagnosis to less ill patients.

Women are lean and men are also lean: nutrition titles in women's and men's health magazines

BACKGROUND

Whether nutrition messages in popular health magazines differ by country or season has seldom been studied. We assessed the nutrition topics featured in the headlines of Men's Health® (MH) and Women's Health® (WH) magazines from different countries.

METHODS

We sampled MH and WH magazines from Portugal, South Africa, Spain, the UK and the USA. Nutrition-related headlines were categorized as weight loss, weight gain, micronutrients and other.

RESULTS

The most frequent topics were "Other" (44%) and "weight loss" (41%), while "micronutrients" represented 4%. Topics related to weight gain were more frequent in MH (19% vs. 2% in WH), while no difference was found for weight loss (44% vs. 37% in WH). On multivariable analysis, weight gain had a higher likelihood of being present in MH than in WH, Odds ratio and (95% confidence interval): 8.3 (2.2-90.9), p = 0.002, while no association was found for weight loss: OR 1.1 (0.6-2.0), p = 0.80. Weight loss was absent from the US WH and present in two thirds of the Portuguese WH; in MH, weight gain was evenly distributed between countries. Prevalence of the weight loss topic was lower in March (15% vs. 54% in January, p < 0.01 by logistic regression) and to a lesser degree in June (35%) and July (35%). No seasonality was found for the "weight gain" topic.

CONCLUSION

In WH and MH magazines, nutrition topics vary according to gender, country, and season. Weight gain remains a male topic, while weight loss is equally prevalent in both women's and men's magazines.

The Effects of an Eight-Week Swimming Program on Body Composition and Assessment of Dietary Intake in Post-COVID-19 Patients

COVID-19 infection and its consequences (long-term COVID-19 syndrome) have implications for weight loss, body composition, and diet quality. In the context of the "PostCovSwim" project, which is part of a broader international study, the impact of an eight-week swimming program on post-COVID-19 patients' nutritional status (i.e., body composition and dietary intake) was evaluated. Body composition and dietary intake were assessed by medically approved and calibrated bioelectrical impedance (Tanita 780 S MA) and food frequency questionnaires. At the baseline, most participants were classified as overweight based on their body mass index (BMI). However, their body fat percentage (BF%) classification indicated normal weight, although females were near obesity thresholds. Furthermore, at the baseline, according to the BMI classification, 62% of females and 61% of males were female, whereas according to the BF% for obesity classification, 44% of females and 43% of males were considered overweight or obese. Surprisingly, despite the eight-week program, there were no significant changes in body composition. Additionally, the assessment of dietary intake, which remained consistent throughout the study, revealed dietary imbalances characterized by an unhealthy low-carbohydrate, high-fat dietary pattern. This dietary pattern entailed excessive consumption of ultraprocessed foods; reduced carbohydrate intake (39% E vs. 37% E); increased total fat intake (46% E vs. 47% E); increased saturated fatty acids (14% E vs. 13% E); increased cholesterol (412 mg/d vs. 425 mg/d); increased free sugars (7% E vs. 7% E); and inadequate intake of fibre (24 g/d vs. 20 g/d), polyunsaturated fatty acids (6.6% E vs. 7.7% E), vitamin B12 (in females: 3.1 µg/d), vitamin C (86 mg/d vs. 66 mg/d), vitamin D (2 µg/d vs. 3.2 µg/d), folate (in males: 258 µg/d), calcium (777 mg/d vs. 743 mg/d), and selenium (in males: 66 µg/d). After an eight-week swimming program following COVID-19, no significant changes were observed in the subjects' body composition. Their dietary intake was found to not align with the dietary recommendations. These findings underscore the urgency of implementing comprehensive dietary and lifestyle interventions for post-COVID-19 patients to optimize their recovery and overall well-being. Physical activity, like a swimming program, may positively affect various aspects of human well-being.

Singapore's Total Diet Study (2021-2023): Study Design, Methodology, and Relevance to Ensuring Food Safety

A total diet study is often used to evaluate a population's baseline dietary exposure to chemical hazards from across the diet. In 2021-2023, Singapore carried out a TDS, and this article presents an overview of the study design and methodological selections in Singapore's TDS, as well as its relevance to ensuring food safety. A food consumption survey was conducted on Singapore citizens and permanent residents, where food consumption patterns of the Singapore population were identified. The selection of chemical hazards and foods for inclusion in Singapore's TDS, as well as principal considerations on sampling, food preparation, and analytical testing are discussed. Commonly consumed foods by the Singapore population in food categories such as grain and grain-based products, meat and meat products, fish and seafood, vegetables, fruits, milk and dairy products were included in this study, and mean concentrations of chemicals tested in each food category were reported, with food categories possessing higher levels identified. Future work will include dietary exposure assessments for the population and analysis of the contributions by food and cooking method.

Models of body weight and fatness regulation

Body weight and fatness appear to be regulated phenomena. Several different theoretical models are available to capture the essence of this idea. These include the set-point, dynamic equilibrium, adiposity force, control theory-settling point, Hall-Guo, operation point and dual intervention point (DIP) models. The set-point model posits a single reference point around which levels of fat are regulated. The dynamic equilibrium model suggests that the apparent regulation of body fat around a reference point is an illusion owing to the necessary impacts of weight change on energy expenditure. Control theory focuses on the importance of feedback gain and suggests set-point and dynamic equilibrium are ends of a continuum of feedback gain. Control theory models have also been called 'settling point' models. The Hall-Guo, operation point and DIP models also bring together the set-point and dynamic equilibrium ideas into a single framework. The DIP proposes a zone of indifference where dynamic equilibrium 'regulation' predominates, bounded by upper and lower intervention points beyond which physiological mechanisms are activated. The drifty gene hypothesis is an idea explaining where this individual variation in the upper intervention point might come from. We conclude that further experiments to test between the models are sorely required. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.

The Activities of the Slovenian Strategic Council for Nutrition 2023/24 to Improve the Health of the Slovenian Population and the Sustainability of Food: A Narrative Review

The health status of individuals in Slovenia across age groups is a matter of concern, as current unsustainable lifestyle choices are already leading to various chronic noncommunicable diseases (NCDs). Outdated national dietary guidelines, their inconsistent implementation, and a lack of structural changes represent obstacles to promoting healthy and sustainable nutrition. Limited access to and rising prices of healthy, sustainable foods, in addition to the high availability of low-priced, highly processed foods, increase the risk of NCDs. The lack of systematic health monitoring and early disease detection poses a challenge. Global and local environmental issues, resistance, and/or the inability to adopt healthier diets hinder individuals from changing their nutritional behaviours. In this narrative review, we provide an overview of the current situation in Slovenia as well as planned activities initiated by the Slovenian government and the Prime Minister's Strategic Council for Nutrition, aiming to make progress in supporting healthy and sustainable nutrition, limiting food waste, and increasing the availability of healthier foods for all. Improving the sustainability of the Slovenian food system can contribute to several Sustainable Development Goals (SDGs), ensuring Slovenia's commitment to internationally agreed-upon targets. This could lead Slovenia to take a role as a pilot country in testing and implementing the necessary systemic changes, which could be further applied in other countries.

Vitis vinifera L. Bioactive Components Modulate Adipose Tissue Metabolic Markers of Healthy Rats in a Photoperiod-Dependent Manner

SCOPE

The beneficial health effects of (poly)phenol-rich foods such as red grapes mainly depend on both the type and concentration of (poly)phenols. Since fruit (poly)phenol content is influenced by growing conditions, the study examines the seasonal effects of red grapes (Vitis vinifera L.), grown under various cultivation conditions, on metabolic markers of adipose tissue in healthy rats.

METHODS AND RESULTS

For this purpose, Fischer 344 rats are exposed into three different light-dark cycles and daily supplemented with 100 mg kg-1 of either conventionally or organically grown red grapes for 10 weeks (n = 6). Seasonal consumption of organic grapes (OGs), which are richer in anthocyanins, increases energy expenditure (EE) of animals exposed to long photoperiod and enhances uncoupling protein 1 (UCP1) protein expression in brown adipose tissue of animals under standard photoperiod. Additionally, red grape consumption affects the gene expression profile of white adipose tissue (WAT), upregulating browning markers of subcutaneous WAT in 12 h light (L12) and 18 h light (L18) photoperiods, and downregulating adipogenic and lipolytic markers of visceral WAT in 6 h light (L6) and L12 photoperiods.

CONCLUSIONS

These results clearly show that bioactive compounds of grapes can modulate the metabolic markers of white and brown adipose tissues in a photoperiod and depot-dependent manner, partly affecting EE when consumed out of season.

Weekly, Seasonal, and Festive Period Weight Gain Among Australian Adults

Importance

Obesity is a major global health concern. A better understanding of temporal patterns of weight gain will enable the design and implementation of interventions with potential to alter obesity trajectories.

Objective

To describe changes in daily weight across 12 months among Australian adults.

Design, Setting, and Participants

This cohort study conducted between December 1, 2019, and December 31, 2021 in Adelaide, South Australia, involved 375 community-dwelling adults aged 18 to 65 years. Participants wore a fitness tracker and were encouraged to weigh themselves, preferably daily but at least weekly, using a body weight scale. Data were remotely gathered using custom-developed software.

Exposure

Time assessed weekly, seasonally, and at Christmas/New Year and Easter.

Main Outcomes and Measures

Data were visually inspected to assess the overall yearly pattern in weight change. Data were detrended (to remove systematic bias from intraindividual gradual increases or decreases in weight) by calculating a line of best fit for each individual's annual weight change relative to baseline and subtracting this from each participant's weight data. Multilevel mixed-effects linear regression analysis was used to compare weight across days of the week and seasons and at Christmas/New Year and Easter.

Results

Of 375 participants recruited, 368 (mean [SD] age, 40.2 [5.9] years; 209 [56.8%] female; mean [SD] baseline weight, 84.0 [20.5] kg) provided at least 7 days of weight data for inclusion in analyses. Across the 12-month period, participants gained a median of 0.26% body weight (218 g) (range, -29.4% to 24.0%). Weight fluctuated by approximately 0.3% (252 g) each week, with Mondays and Tuesdays being the heaviest days of the week. Relative to Monday, participants' weight gradually decreased from Tuesday, although not significantly so (mean [SE] weight change, 0.01% [0.03%]; P = .83), to Friday (mean [SE] weight change, -0.18% [0.03%]; P < .001) and increased across the weekend to Monday (mean [SE] weight change for Saturday, -0.16% [0.03%]; P < .001; mean [SE] weight change for Sunday, -0.10% [0.03%]; P < .001). Participants' weight increased sharply at Christmas/New Year (mean [SE] increase, 0.65% [0.03%]; z score, 25.30; P < .001) and Easter (mean [SE] weight change, 0.29% [0.02%], z score, 11.51; P < .001). Overall, participants were heaviest in summer (significantly heavier than in all other seasons), were lightest in autumn (mean [SE] weight change relative to summer, -0.47% [0.07%]; P < .001), regained some weight in winter (mean [SE] weight change relative to summer, -0.23% [0.07%]; P = .001), and became lighter in spring (mean [SE] weight change relative to summer, -0.27% [0.07%]; P < .001).

Conclusions and Relevance

In this cohort study of Australian adults with weekly and yearly patterns in weight gain observed across 12 months, high-risk times for weight gain were Christmas/New Year, weekends, and winter, suggesting that temporally targeted weight gain prevention interventions may be warranted.

Association between the month of starting a weight management program and weight change in people at high risk of type 2 diabetes: A prospective cohort study

OBJECTIVE

Weight loss is one of the most common New Year's resolutions, but it is unclear whether attempting to lose weight in January is more successful than attempting it at other times of the year.

METHODS

In this prospective cohort study from the English National Health Service (NHS) Diabetes Prevention Program, adults with nondiabetic hyperglycemia were enrolled in a structured behavioral weight management program. Repeated measures models assessed the mean difference between baseline and follow-up weight adjusting for monthly variation in weight among those with ≥1 weight measurement.

RESULTS

Among 85,514 participants with a mean baseline BMI of 30.3 kg/m² (range: 13.4 to 84.2), mean weight change at the end of the program after an average 7.9 (SD: 4.5) sessions over 6.4 (SD: 5.6) months was -2.00 kg (95% CI: -2.02 to -1.97 kg) or -2.33% (95% CI: -2.35% to -2.32%). Compared with participants starting in January, participants starting in other months lost less weight, ranging between 0.28 kg (95% CI: 0.10 to 0.45 kg) less weight in those starting in March and 0.71 kg (95% CI: 0.55 to 0.87 kg) less weight in those starting in November. April and May were the only exceptions, in which the estimates followed the same direction but were not statistically significant. Higher session attendance mediated the effects, with participants starting in January attending, on average, 0.2 to 0.7 more sessions than those starting in other months.

CONCLUSIONS

People starting a weight management program in January lost 12% to 30% more weight than people starting it at other times of the year.

Grape-Seed Proanthocyanidins Modulate Adipose Tissue Adaptations to Obesity in a Photoperiod-Dependent Manner in Fischer 344 Rats

Seasonal rhythms drive metabolic adaptations that influence body weight and adiposity. Adipose tissue is a key regulator of energy homeostasis in the organism, and its healthiness is needed to prevent the major consequences of overweight and obesity. In this context, supplementation with proanthocyanidins has been postulated as a potential strategy to prevent the alterations caused by obesity. Moreover, the effects of these (poly)phenols on metabolism are photoperiod dependent. In order to describe the impact of grape-seed proanthocyanidins extract (GSPE) on important markers of adipose tissue functionality under an obesogenic environment, we exposed Fischer 344 rats to three different photoperiods and fed them a cafeteria diet for five weeks. Afterwards, we supplemented them with 25 mg GSPE/kg/day for four weeks. Our results revealed that GSPE supplementation prevented excessive body weight gain under a long photoperiod, which could be explained by increased lipolysis in the adipose tissue. Moreover, cholesterol and non-esterified fatty acids (NEFAs) serum concentrations were restored by GSPE under standard photoperiod. GSPE consumption slightly helped combat the obesity-induced hypertrophy in adipocytes, and adiponectin mRNA levels were upregulated under all photoperiods. Overall, the administration of GSPE helped reduce the impact of obesity in the adipose tissue, depending on the photoperiod at which GSPE was consumed and on the type of adipose depots.

Recruiting participants for ergonomic research using self-reported stature and body mass

BACKGROUND

A valid distribution of key anthropometric parameters among participants is often a perquisite of ergonomics research.

OBJECTIVE

In this paper, we investigated the accuracy of self-reported stature and body mass of the population in the Netherlands.

METHODS

Data from 4 experiments was synthesized where in each experiment, participants self-reported their stature and body mass prior to being measured, of which they were not notified before.

RESULTS

Statistical analysis of 249 records indicated that on average, participants overreported their stature by 1.31 cm and underreported their mass by 1.45 kg. This is especially true for people with a BMI≥25.

CONCLUSION

Two models were proposed to adjust the self-reported stature and body mass for ergonomic researchers in a survey or recruitment. Limitations in using the models are highlighted as well.

Motivational and self‐efficacy reciprocal effects during a 12‐month' weight regain prevention program

OBJECTIVE

Weight regain prevention is a critical public health challenge. Digital behaviour change interventions provide a scalable platform for applying and testing behaviour change theories in this challenging context. This study's goal was to analyse reciprocal effects between psychosocial variables (i.e., needs satisfaction, eating regulation, self-efficacy) and weight over 12 months using data from a large sample of participants engaged in a weight regain prevention trial.

METHODS

The NoHoW study is a three-centre, large-scale weight regain prevention trial. Adults who lost >5% of their weight in the past year (N = 1627, 68.7% female, 44.10 ± 11.86 years, 84.47 ± 17.03 kg) participated in a 12-month' digital behaviour change-based intervention. Weight and validated measures of basic psychological needs satisfaction, eating regulation and self-efficacy were collected at baseline, six- and 12 months. Correlational, latent growth models and cross-lagged analysis were used to identify potential reciprocal effects.

RESULTS

Baseline higher scores of needs satisfaction and self-efficacy were associated with six- and 12-month' weight loss. Baseline weight was linked to all psychosocial variables at six months, and six-months weight was associated with needs satisfaction and self-efficacy at 12 months. During the 12 months, increases in eating regulation, needs satisfaction and self-efficacy were associated with weight loss over the same period, and reciprocal effects were observed between the variables, suggesting the existence of Weight Management Cycles.

CONCLUSIONS

While further studies are needed, during long-term weight regain prevention, weight decrease, needs satisfaction and self-efficacy may lead to Weight Management Cycles, which, if recurrent, may provide sustained prevention of weight regain.

Measured weight loss as a precursor to cancer diagnosis: retrospective cohort analysis of 43 302 primary care patients

BACKGROUND

Unexpected weight loss is a presenting feature of cancer in primary care. Data from primary care are lacking to quantify how much weight loss over what period should trigger further investigation for cancer. This research aimed to quantify cancer diagnosis rates associated with measured weight change in people attending primary care.

METHODS

Retrospective cohort study of primary care electronic health records data linked to the Surveillance, Epidemiology, and End Results cancer registry (Integrated healthcare delivery system in Washington State, United States). Multivariable Cox regression incorporating time varying covariates using splines to model non-linear associations (age, percentage weight change, and weight change interval). Fifty thousand randomly selected patients aged 40 years and over followed for up to 9 years (1 January 2006 to 31 December 2014). Outcome measures are hazard ratios (95% confidence intervals) to quantify the association between percentage weight change and cancer diagnosis for all cancers combined, individual cancer sites and stages; percentage risk of cancer diagnosis within 6 months of the end of each weight change episode; and the positive predictive value for cancer diagnosis.

RESULTS

There were 43 302 included in the analysis after exclusions. Over 287 858 patient-years of follow-up, including 24 272 (56.1%) females, 23 980 (55.4%) aged 40 to 59 years, 15 113 (34.9%) 60 to 79 years, and 4209 (9.7%) aged 80 years and over. Adjusted hazard ratios (95% confidence interval) for cancer diagnosis in a 60 years old ranged from 1.04 (1.02 to 1.05, P < 0.001) for 1% weight loss to 1.44 (1.23 to 1.68, P < 0.001) for 10%. An independent linear association was observed between percentage weight loss and increasing cancer risk. The absolute risk of cancer diagnosis increased with increasing age (up to 85 years) and as the weight change measurement interval decreased (<1 year). The positive predictive value for a cancer diagnosis within 1 year of ≥5% measured weight loss in a 60 to 69 years old was 3.41% (1.57% to 6.37%) in men and 3.47% (1.68% to 6.29%) in women. The risk of cancer diagnosis was significantly increased for pancreatic, myeloma, gastro-oesophageal, colorectal, breast, stage II and IV cancers.

CONCLUSIONS

Weight loss is a sign of undiagnosed cancer regardless of the interval over which it occurs. Guidelines should resist giving an arbitrary cut-off for the interval of weight loss and focus on the percentage of weight loss and the patient's age. Future studies should focus on the association between diagnostic evaluation of weight change and risk of cancer mortality.

Agreement Between Clinically Measured Weight and Self-reported Weight Among Patients With Type 2 Diabetes Through an mHealth Lifestyle Coaching Program in Denmark: Secondary Analysis of a Randomized Controlled Trial

Background

Digital health interventions are increasingly used to handle and promote positive health behaviors. Clinical measures are often used, and a certain precision is essential for digital health interventions to have an effect. Only few studies have compared clinically measured weights with self-reported weights. No study has examined the validity of self-reported weight from a mobile app used in a tailored weight loss intervention.

Objective

The aim of this study was to analyze the agreement between clinically measured weight and self-reported weight collected from a mobile health lifestyle coaching program during a 12-month weight loss intervention for obese patients with and without type 2 diabetes. The secondary aim was to investigate the determinants for possible discrepancies between clinically measured and self-reported weights of these patients with different demographic and lifestyle characteristics and achievements of weight loss goals.

Methods

Weight registrations were collected from participants (N=104) in a Danish randomized controlled trial examining the effect of a digital lifestyle intervention on weight loss among obese patients with and without type 2 diabetes. Data were collected at baseline and after 6 and 12 months. Self-reported weight was measured at home and registered in the app.

Results

Self-reported body weight was lower than the weight measured in the clinic after 6 months by 1.03 kg (95% CI 1.01-1.05; P<.001) and after 12 months also by 1.03 kg (95% CI 0.99-1.04; P<.001). After 6 months, baseline weight and BMI were associated with a discrepancy of 0.03 kg (95% CI 0.01-0.04; P=.01) and 0.09 kg (95% CI 0.02-0.17; P=.02) per increment of 1 kg and 1 kg/m2, respectively, between clinically measured weight and self-reported weight. Weight change during the first 6 months was also associated with a difference of 0.1 kg (95% CI 0.04-0.01; P<.001) per kilogram of difference in weight between clinically measured weight and self-reported weight. Participants who did not achieve the 5% weight loss goal underestimated their weight by 0.79 kg (95% CI 0.34-1.23) at 6 months. After 12 months, only baseline weight was associated with a discrepancy of 0.03 kg (95% CI 0.01-0.05; P=.02) per increment of kilogram between clinically measured weight and self-reported weight. None of the other factors showed any significant discrepancy after 12 months.

Conclusions

Self-reported weight obtained from mobile health is a valid method for collecting anthropometric measurements.

Trial Registration

ClinicalTrials.gov NCT03788915; https://clinicaltrials.gov/ct2/show/NCT03788915

A New Body Weight Lifelog Outliers Generation Method: Reflecting Characteristics of Body Weight Data

Lifelogs are generated in our daily lives and contain useful information for health monitoring. Nowadays, one can easily obtain various lifelogs from a wearable device such as a smartwatch. These lifelogs could include noise and outliers. In general, the amount of noise and outliers is significantly smaller than that of normal data, resulting in class imbalance. To achieve good analytic accuracy, the noise and outliers should be filtered. Lifelogs have specific characteristics: low volatility and periodicity. It is very important to continuously analyze and manage them within a specific time. To solve the class imbalance problem of outliers in weight lifelog data, we propose a new outlier generation method that reflects the characteristics of body weight. This study compared the proposed method with the SMOTE-based data augmentation and the GAN-based data augmentation methods. Our results confirm that our proposed method for outlier detection was better than the SVM, XGBOOST, and CATBOOST algorithms. Through them, we can reduce the data imbalance level, improve data quality, and improve analytics accuracy.

Validation of a Visually Aided Dietary Assessment Tool to Estimate Dietary Intake in an Adult Swiss Population

Background

Accurately assessing dietary intake is crucial for understanding how diet affects a person’s health. In large cohorts, paper-based dietary assessment tools (DAT) such as food recalls or food frequency questionnaires have emerged as valid tools with a low burden for participants.

Objective

To validate a visually aided DAT for use in studies with Swiss adults against the gold standard of a weighed 7-day food record (7 d-FR).

Design

Fifty-one adults (n = 24 women, n = 27 males) participated in the study and were recruited within two age groups (20–40 and 50–70 y). Each participant filled out the visually aided DAT, then the 7 d-FR. The DAT was compared to the 7 d-FR for total energy intake, macronutrients, sugar, water, and portions of fruits and vegetables. Pearson correlation and Bland–Altman analyses were used for statistical analyses.

Results

Total correlations ranged from 0.288 (sugar, p &lt; 0.05) to 0.729 (water, p &lt; 0.01). The older age group showed higher correlations for total energy intake, protein, fats, carbohydrates, and sugar, but not for water (p &lt; 0.05). Correlations were moderate at r &gt; 0.5, whereas only water and protein reached those values in the young group. Both groups overestimated total calories in kcal (+14.0%), grams of protein (+ 44.6%), fats (+36.3%), and portions of fruits and vegetables (+16.0%) but strongly underestimated sugar intake (−50.9%).

Conclusion

This DAT showed that all macronutrients and total energy intake were estimated more accurately by the older age group and therefore might be adequate to capture dietary habits in older Swiss adults.

Geographic, Gender, and Seasonal Variation of Diabetes: A Nationwide Study With 1.4 Million Participants

CONTEXT

China has experienced a rapid increase in the prevalence of diabetes.

OBJECTIVE

We assessed the prevalence of diabetes among Chinese adults who attended preventive physical examinations and analyzed geographical and gender difference in seasonal variation of fasting blood glucose (FBG).

METHODS

The study used data from 1 390 088 participants attending preventive health examination at 430 health screening centers in 220 cities. Diagnosis of diabetes and prediabetes were based on FBG and glycated hemoglobin A1c and self-reported physician's diagnosis. We calculated age- and sex-standardized prevalence of diabetes according to the sixth Chinese population census data in 2010. Geographical distribution of diabetes and prediabetes were represented on a country map. FBG levels were analyzed to detect seasonal variation adjusted for age and gender by geographic location.

RESULTS

The standardized prevalence of diabetes was 8.70% (95% CI, 8.22%-9.19%), 10.7% in men and 6.61% in women. Among those with diabetes, 43.7% (95% CI, 40.9%-46.5%) were aware of their conditions and 38.5% (95% CI, 36.0%-41.1%) were treated. Only 49.3% (95% CI, 47.0%-51.6%) of treated patients achieved glycemic control. The mean level of FBG was higher in winter than summer and in the northern than the southern region.

CONCLUSION

The prevalence of diabetes was high while the percentages of awareness, treatment, and glycemic control were low among adults. Effective measures are needed to prevent and manage diabetes in China. Geographic and seasonal variation of diabetes should be considered for its prevention and control.

Is there seasonal variation in gallstone related admissions in England?

BACKGROUND

Gallstone related pathology (GRP) accounts for a significant proportion of general surgery admissions. The aim of this study is to investigate if seasonal variation for GRP admissions exist in England allowing improved resource allocation and planning.

METHODS

This multicentre retrospective cohort study included only emergency adult (≥18 years old) admissions to acute secondary care with ICD-10 codes associated with gallstones between 01/01/2010 to 31/12/2019 in England using Hospital Episode Statistics data. Seasons were defined according to United Kingdom Met Office.

RESULTS

A total of 396 879 GRP related admissions were recorded during the specified period, accounting for 1.44% of all emergency admissions. Our study suggests a significant seasonal peak in Summer (n = 102 620) based cumulative admissions per season and a linear regression model (p < 0.001), followed by Autumn (n = 102 267), then Spring (n = 97 807) and finally Winter (n = 94 185). Spectral analysis confirmed there is seasonality in the emergency GRP admissions every 12 months. A forecasting model was shown to be reliable; all observed admissions for 2019 were within the 95% prediction intervals for each month for the proportion of emergency GRP admissions.

CONCLUSION

Resource allocation towards the Summer months to target seasonal peaks in GRP should be considered.

Frequency of Self-Weighing and Weight Change: Cohort Study With 10,000 Smart Scale Users

Background

Frequent self-weighing is associated with successful weight loss and weight maintenance during and after weight loss interventions. Less is known about self-weighing behaviors and associated weight change in free-living settings.

Objective

This study aimed to investigate the association between the frequency of self-weighing and changes in body weight in a large international cohort of smart scale users.

Methods

This was an observational cohort study with 10,000 randomly selected smart scale users who had used the scale for at least 1 year. Longitudinal weight measurement data were analyzed. The association between the frequency of self-weighing and weight change over the follow-up was investigated among normal weight, overweight, and obese users using Pearson’s correlation coefficient and linear models. The association between the frequency of self-weighing and temporal weight change was analyzed using linear mixed effects models.

Results

The eligible sample consisted of 9768 participants (6515/9768, 66.7% men; mean age 41.5 years; mean BMI 26.8 kg/m2). Of the participants, 4003 (4003/9768, 41.0%), 3748 (3748/9768, 38.4%), and 2017 (2017/9768, 20.6%) were normal weight, overweight, and obese, respectively. During the mean follow-up time of 1085 days, the mean weight change was –0.59 kg, and the mean percentage of days with a self-weigh was 39.98%, which equals 2.8 self-weighs per week. The percentage of self-weighing days correlated inversely with weight change, r=–0.111 (P<.001). Among normal weight, overweight, and obese individuals, the correlations were r=–0.100 (P<.001), r=–0.125 (P<.001), and r=–0.148 (P<.001), respectively. Of all participants, 72.5% (7085/9768) had at least one period of ≥30 days without weight measurements. During the break, weight increased, and weight gains were more pronounced among overweight and obese individuals: 0.58 kg in the normal weight group, 0.93 kg in the overweight group, and 1.37 kg in the obese group (P<.001).

Conclusions

Frequent self-weighing was associated with favorable weight loss outcomes also in an uncontrolled, free-living setting, regardless of specific weight loss interventions. The beneficial associations of regular self-weighing were more pronounced for overweight or obese individuals.

Self-weighing among young adults: who weighs themselves and for whom does weighing affect mood? A cross-sectional study of a population-based sample

BACKGROUND

Self-weighing is widespread among young adults and is sometimes recommended by healthcare providers for weight management. The present study aims to deepen our understanding of who is frequently self-weighing among young adults, and to examine for whom self-weighing impacts mood based on weighing frequency and other eating and weight-related characteristics.

METHODS

Survey data were collected from a large population-based sample of young adults (31.1 ± 1.6y) participating in Project EAT-IV (n = 1719). Cross-sectional data were stratified across sex and analyzed with chi-square, t-tests, and linear and logistic regressions controlling for age, ethnicity/race, education level, and income.

RESULTS

Self-weighing frequency was higher among male and female young adults with a current eating disorder, those trying to lose weight or who endorsed any disordered eating behaviors or cognition, and females with higher BMI. Young adult females were significantly more likely than males to report that self-weighing impacted their mood (53% vs 27%, p < 0.05). Among both male and female young adults, there was a higher probability of participants reporting that self-weighing impacted their mood among those who were self-weighing more frequently, had higher BMI, were trying to lose weight, and endorsed disordered eating behaviors or cognitions.

CONCLUSION

Findings suggest that for many young adults, particularly females and those with weight-related concerns, self-weighing is a behavior that comes with emotional valence. The emotional consequences of self-weighing should be considered when making public health and clinical recommendations regarding the usefulness of self-weighing.

From famine to therapeutic weight loss: Hunger, psychological responses, and energy balance-related behaviors

Understanding physiological and behavioral responses to energy imbalances is important for the management of overweight/obesity and undernutrition. Changes in body composition and physiological functions associated with energy imbalances provide the structural and functional context in which to consider psychological and behavioral responses. Compensatory changes in physiology and behavior are more pronounced in response to negative than positive energy balances. The physiological and psychological impact of weight loss (WL) occur on a continuum determined by (i) the degree of energy deficit (ED), (ii) its duration, (iii) body composition at the onset of the energy deficit, and (iv) the psychosocial environment in which it occurs. Therapeutic WL and famine/semistarvation both involve prolonged EDs, which are sometimes similar in magnitude. The key differences are that (i) the body mass index (BMI) of most famine victims is lower at the onset of the ED, (ii) therapeutic WL is intentional and (iii) famines are typically longer in duration (partly due to the voluntary nature of therapeutic WL and disengagement with WL interventions). The changes in psychological outcomes, motivation to eat, and energy intake in therapeutic WL are often modest (bearing in mind the nature of the measures used) and can be difficult to detect but are quantitatively significant over time. As WL progresses, these changes become more marked. It appears that extensive WL beyond 10%-20% in lean individuals has profound effects on body composition and physiological function. At this level of WL, there is a marked erosion of psychological functioning, which appears to run in parallel to WL. Psychological resources dwindle and become increasingly focused on alleviating escalating hunger and food seeking behavior. Functional changes in fat-free mass, characterized by catabolism of skeletal muscle and organs may be involved in the drive to eat associated with semistarvation. Higher levels of body fat mass may act as a buffer to protect fat-free mass, functional integrity and limit compensatory changes in energy balance behaviors. The increase in appetite that accompanies therapeutic WL appears to be very different to the intense and all-consuming drive to eat that occurs during prolonged semistarvation. The mechanisms may also differ but are not well understood, and longitudinal comparisons of the relationship between body structure, function, and behavior in response to differing EDs in those with higher and lower BMIs are currently lacking.

Daily supplementation with the Lab4P probiotic consortium induces significant weight loss in overweight adults

This 9-month randomised, parallel, double-blind, single-centre, placebo-controlled study (PROBE, ISRCTN18030882) assessed the impact of probiotic supplementation on bodyweight. Seventy overweight Bulgarian participants aged 45-65 years with BMI 25-29.9 kg/m² received a daily dose of the Lab4P probiotic comprising lactobacilli and bifidobacteria (50 billion cfu/day). Participants maintained their normal diet and lifestyle over the duration of the study. The primary outcome was change from baseline in body weight and secondary outcomes included changes in waist circumference, hip circumference and blood pressure. A significant between group decrease in body weight (3.16 kg, 95% CI 3.94, 2.38, p < 0.0001) was detected favouring the probiotic group. Supplementation also resulted in significant between group decreases in waist circumference (2.58 cm, 95% CI 3.23, 1.94, p < 0.0001) and hip circumference (2.66 cm, 95% CI 3.28, 2.05, p < 0.0001) but no changes in blood pressure were observed. These findings support the outcomes of a previous shorter-term Lab4P intervention study in overweight and obese participants (PROMAGEN, ISRCTN12562026). We conclude that Lab4P has consistent weight modulation capability in free-living overweight adults.

The impact of early body-weight variability on long-term weight maintenance: exploratory results from the NoHoW weight-loss maintenance intervention

BACKGROUND

Weight-loss programmes often achieve short-term success though subsequent weight regain is common. The ability to identify predictive factors of regain early in the weight maintenance phase is crucial.

OBJECTIVE

To investigate the associations between short-term weight variability and long-term weight outcomes in individuals engaged in a weight-loss maintenance intervention.

METHODS

The study was a secondary analysis from The NoHoW trial, an 18-month weight maintenance intervention in individuals who recently lost ≥5% body weight. Eligible participants (n = 715, 64% women, BMI = 29.2 (SD 5.0) kg/m², age = 45.8 (SD 11.5) years) provided body-weight data by smart scale (Fitbit Aria 2) over 18 months. Variability in body weight was calculated by linear and non-linear methods over the first 6, 9 and 12 weeks. These estimates were used to predict percentage weight change at 6, 12, and 18 months using both crude and adjusted multiple linear regression models.

RESULTS

Greater non-linear weight variability over the first 6, 9 and 12 weeks was associated with increased subsequent weight in all comparisons; as was greater linear weight variability measured over 12 weeks (up to AdjR² = 4.7%). Following adjustment, 6-week weight variability did not predict weight change in any model, though greater 9-week weight variability by non-linear methods was associated with increased body-weight change at 12 (∆AdjR² = 1.2%) and 18 months (∆AdjR² = 1.3%) and by linear methods at 18 months (∆AdjR² = 1.1%). Greater non-linear weight variability measured over 12 weeks was associated with increased weight at 12 (∆AdjR² = 1.4%) and 18 (∆AdjR² = 2.2%) months; and 12-week linear variability was associated with increased weight at 12 (∆AdjR² = 2.1%) and 18 (∆AdjR² = 3.6%) months.

CONCLUSION

Body-weight variability over the first 9 and 12 weeks of a weight-loss maintenance intervention weakly predicted increased weight at 12 and 18 months. These results suggest a potentially important role in continuously measuring body weight and estimating weight variability.

Data Imputation and Body Weight Variability Calculation Using Linear and Nonlinear Methods in Data Collected From Digital Smart Scales: Simulation and Validation Study

Background

Body weight variability (BWV) is common in the general population and may act as a risk factor for obesity or diseases. The correct identification of these patterns may have prognostic or predictive value in clinical and research settings. With advancements in technology allowing for the frequent collection of body weight data from electronic smart scales, new opportunities to analyze and identify patterns in body weight data are available.

Objective

This study aims to compare multiple methods of data imputation and BWV calculation using linear and nonlinear approaches

Methods

In total, 50 participants from an ongoing weight loss maintenance study (the NoHoW study) were selected to develop the procedure. We addressed the following aspects of data analysis: cleaning, imputation, detrending, and calculation of total and local BWV. To test imputation, missing data were simulated at random and using real patterns of missingness. A total of 10 imputation strategies were tested. Next, BWV was calculated using linear and nonlinear approaches, and the effects of missing data and data imputation on these estimates were investigated.

Results

Body weight imputation using structural modeling with Kalman smoothing or an exponentially weighted moving average provided the best agreement with observed values (root mean square error range 0.62%-0.64%). Imputation performance decreased with missingness and was similar between random and nonrandom simulations. Errors in BWV estimations from missing simulated data sets were low (2%-7% with 80% missing data or a mean of 67, SD 40.1 available body weights) compared with that of imputation strategies where errors were significantly greater, varying by imputation method.

Conclusions

The decision to impute body weight data depends on the purpose of the analysis. Directions for the best performing imputation methods are provided. For the purpose of estimating BWV, data imputation should not be conducted. Linear and nonlinear methods of estimating BWV provide reasonably accurate estimates under high proportions (80%) of missing data.