Objectively measured eating behaviors and their relation to food intake in school and hospital settings

Introduction: The measurement of food intake (what and how much we eat and drink) is of great importance due to its involvement in three great challenges facing humanity: 1) obesity/overnutrition, 2) undernutrition and 3) climate change, as well as their related health consequences. However, measuring food and energy intake in humans is complicated since traditional self-reported methods have systematic bias while traditional objective laboratory methods have generalizability and upscaling issues. Therefore, novel methods to measure food and energy intake in humans have often been requested. A plethora of factors have been associated with variation in food intake in humans. For example, internal behavioral factors such as eating rate, internal disease conditions such as Parkinson’s disease (PD) as well as external environmental factors such as food proximity are notable ones. These factors have mainly been investigated by use of the traditional methods listed above. Aims: The overarching aim with this thesis was to use novel technological tools (i.e., portable food scales and video cameras) to measure and explain variance in food intake and body mass index in school, hospital and free-living settings. Aims in school setting: To explain variance in food mass intake during school lunch with objectively measured eating behaviors (how a person eats), the proximity to food and subjective appetite measures. To assess the test-retest reliability of objectively measured food mass intake and eating rate during school lunch. To assess the concurrent validity of self-reported eating rate. Aims in hospital setting: To compare energy intake among healthy controls, early and advanced PD patients and to investigate the association between clinical features of PD as well as objective eating behaviors with energy intake during a hospital lunch. Aim in free-living setting: To distinguish differences in BMI z-scores (BMIz) among self-reported eating rate categories in populations of Swedish and Greek high school students. Methods: School studies Settings: The data collection was conducted in the school lunch cafeteria environment at a high school in central area of Stockholm, Sweden. Study design: A cross-sectional study design was used to explain variance in food intake and to investigate the association between objectively measured eating rate and food intake. An experimental study design was used to investigate the effects of food proximity and a repeat-measures study design was used to assess the test-retest reliability of objectively measured food mass intake and eating rate. Participants: Six high school classes including 187 students were invited to participate in monitored school lunches during 2015-2017. Out of these, 114 unique students provided complete meal data and 103 with a mean (SD) age of 16.7 (0.6) and BMIz of -0.07 (1.05)were included in the food intake variance analysis. All 114 participants (with a mean (SD) age of 16.5 (0.8) and BMIz 0.04 (1.01)) were included in the association between eating rate and BMIz. Out of the 114 unique participants, 50 students came for a repeated meal and provided complete data for test-retest analyses. Study procedures: The lunch study was conducted during normal school lunch hours (11.30-13.00). The students who participated in the snack experiment came back at 15.30 for the one-hour experimental snack session with snack foods, either a) close to the table where they were sitting (proximal condition) or further away from them (distal condition). Served food: During school lunches, usual lunch food at the included school (beef/vegetable patties, brown sauce, potatoes, fish, variety of vegetables, water/milk) was served in a buffet-like setting. For the snack experiment, chocolate lentils, crackers and grapes were served ad libitum. Hospital study Settings: The data collection was conducted in a dedicated room at the Department of Neurology of the Technical University Dresden (TUD), Germany. Study design: A cross-sectional study design was used. Participants: 64 participants (n = 23 healthy controls, n = 20 early and n = 21 advanced PD patients) with a mean (SD) age of 62.4 (7.8) and BMI 27.2 (4.3) were included. Study procedures: Study participants had a medical evaluation before they ate their lunch meal during normal lunch hours (11.00-15.00). Served food: A standardized meal (200g sausages, 400g potato salad, 200g apple mash and 500ml of water) was served to all participants. Free-living study Settings: A smartphone application was developed to gather self-reported eating rate and BMIz. Study design: A cross-sectional study design was used. Participants: Students from multiple high schools in Sweden (n = 748) and Greece (n = 1084) were recruited through school supported actions (n = 1832 in total, mean (SD) age of 15.8 (0.9), BMIz 0.47 (1.41)) that included self-reported measures of weight, height and eating rate. Study procedures: Students who chose to participate downloaded the study mobile application and self-reported their data. Data sources and measurements In the school and hospital setting, weight and height scales were used to measure participants body weight and height, and food mass and energy intake were measured with portable food scales. Video cameras were used to record the meals and eating behaviors were annotated onto the videos in computer software. In the free-living setting, students self-reported their age, weight, height, and their speed of eating in comparison to others at their own discretion. Results: Reliability and validity: In the school setting, there was no significant systematic change in mean food mass intake from lunch 1 to lunch 2 (-7.5g, 95% confidence interval: -43.1g to +28.0g). The intraclass correlation between food mass intake during lunch 1 vs. lunch 2 was 0.74 (95% confidence interval 0.58 to 0.84). There was a significant systematic change in eating rate (g/min) from lunch 1 to lunch 2 (+4.4 g/min, 95% confidence interval: +0.7 g/min to +8.1 g/min). The intraclass correlation between eating rate during lunch 1 vs. lunch 2 was 0.73 (95% confidence interval 0.59 to 0.85). When comparing the objective eating rate among the three categories of self-reported eating rate (slow, intermediate, and fast), a significant difference between the groups was obtained [F(2, 111) = 7.104, P = 0.001, partial η2 = 0.113]. Bonferroni post hoc comparisons showed that students who self-reported eating slower than others had significantly lower eating rate (-13.7g/min, 95% confidence interval: -22.5g/min to -4.84g/min) compared to students who self-reported eating faster than others. The weighted Kappa value for self-reported eating rate categories versus objectively established eating rate categories was 0.31 (P < 0.001). Main results: School: Eating rate, number of spoonfuls, sex, number of food additions and food taste (explanatory power in that order) were all significant explanatory variables for variance in food mass intake during school lunch, while BMI and change in fullness were not significant (effect size: adjusted R squared = 0.766 for the total model). There was a significant “large” (R = 0.667) correlation between objectively measured eating rate and food mass intake during school lunch. When dividing students into tertiles of eating rate (slow, intermediate and fast eaters), a significant difference in food mass intake between the three groups was found [F(2, 111) = 30.578, P < 0.001, partial η2 = 0.355]. Bonferroni post hoc comparisons showed that students in the “slow” objective eating rate tertile were eating 133 grams less food (95% confidence intervals = -210g to -56g) than students in the “intermediate” objective eating rate tertile, and 247 grams less (95% confidence intervals = -324g to -170g) than students in the “fast” eating rate tertile. Students who were participating in the distal snack food condition were eating significantly less energy from snacks than students in the proximal condition (mean difference = -222.7 kcal 95% confidence intervals: -428.3 kcal to -17.2 kcal). Hospital: Advanced PD patients consumed significantly less energy during lunch compared to both early PD patients (b = -202.7 kcal, 95% confidence interval: -329.2 kcal to -76.2 kcal) and healthy controls (b = -162.1 kcal, 95% confidence interval: -285.7 kcal to -38.4 kcal) when controlling for sex. Free-living: Self-reported eating rate was found to be a significant explanatory variable for variation in self-reported BMI z-scores [F(2, 1829) = 9.724, P < 0.001, partial η2 = 0.011]. Bonferroni post hoc test showed that students who self-reported eating slower than others had 0.23 units lower BMI z-scores (95% confidence intervals: -0.43 to, -0.03) than students who self-reported intermediate eating rate, and 0.37 units lower (95% confidence intervals: -0.57 to -0.17) than students who self-reported eating faster than others. Outcome synthesis: Overall, eating behaviors were the most powerful explanatory variables, while desire to eat and food taste were the most powerful self-reported variables for food and energy intake variance when controlling for sex in the included studies. Advanced PD status (hospital study) as well as the food proximity (snack experiment) were also powerful explanatory variables, while PD-related symptomatology as well as self-reported eating rate, hunger, change in fullness and BMI had low or no explanatory power. Conclusions: Objectively measured single-meal food mass intake and eating rate could be used to rank individuals in comparison to their peers. Subjective eating rate could be used to distinguish groups with slow and fast eating rates in large scale studies but should not be used on an individual level. The outcomes of this thesis suggest that objectively measured eating behaviors and subjective factors such as food taste and desire to eat, as well as the external condition proximity to food, are all powerful explanatory factors for variance in food mass and energy intake and might be potential targets in future interventions that aim to modify food intake. Additionally, advanced PD condition was associated with lower energy intake. Potential interventions mentioned above might be helpful in this patient group to normalize their energy intake and reduce their risk of undernutrition. Furthermore, the results suggest that novel methods that objectively measure eating behaviors could be utilized in larger-scale nutrition research. Further technological developments of these methods could also give real-time feedback on targeted eating behaviors that are related to food intake, thus ultimately reducing the risk of diseases related to over- and undernutrition

Integration of molecular profiles in a longitudinal wellness profiling cohort

An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine

Food Intake during School Lunch Is Better Explained by Objectively Measured Eating Behaviors than by Subjectively Rated Food Taste and Fullness: A Cross-Sectional Study

School lunches contribute significantly to students&rsquo; food intake (FI) and are important to their long-term health. Objective quantification of FI is needed in this context. The primary aim of this study was to investigate how much eating rate (g/min), number of food additions, number of spoonfuls, change in fullness, food taste, body mass index (BMI), and sex explain variations in school lunch FI. The secondary aim was to assess the reliability of repeated FI measures. One hundred and three (60 females) students (15&ndash;18 years old) were monitored while eating lunch in their normal school canteen environment, following their usual school schedules. A subgroup of students (n = 50) participated in a repeated lunch (~3 months later). Linear regression was used to explain variations in FI. The reliability of repeated FI measurements was assessed by change in mean, coefficient of variation (CV), and intraclass correlation (ICC). The regression model was significant and explained 76.6% of the variation in FI. Eating rate was the strongest explanatory variable, followed by spoonfuls, sex, food additions, food taste, BMI, and change in fullness. All explanatory variables were significant in the model except BMI and change in fullness. No systematic bias was observed in FI (&minus;7.5 g (95% CI = &minus;43.1&ndash;28 g)) while individual students changed their FI from &minus;417 to +349 g in the repeated meal (CV 26.1% (95% CI = 21.4&ndash;33.5%), ICC 0.74 (95% CI = 0.58&ndash;0.84)). The results highlight the importance of objective eating behaviors for explaining FI in a school lunch setting. Furthermore, our methods show promise for large-scale quantification of objectively measured FI and eating behaviors in schools

The Effect of Food Unit Sizes and Meal Serving Occasions on Eating Behaviour Characteristics: Within Person Randomised Crossover Studies on Healthy Women

Manipulating food properties and serving environment during a meal can significantly change food intake at group level. However, the evaluation of the usefulness of such manipulations requires an understanding of individual behavioural changes. Three studies were conducted to explore the effect of unit size and meal occasion on eating behaviour characteristics (food intake, meal duration, number of bites and chews). All studies used a randomised crossover design, with a one-week wash-out period, starting with a familiarisation meal, with the participation of healthy, normal weight females between the ages of 18&ndash;35 years. In Study 1 (n = 19) three cube sizes (0.5, 1.0 and 1.5 cm3) of vegetable hash and chicken were compared. In Study 2 (n = 18) mashed potatoes and mincemeat were compared to whole potatoes and meatballs. In Study 3 (n = 29) meals served at lunch time (11:00&ndash;13:00) were compared to identical meals served at dinner time (17:00&ndash;19:00). The largest food unit size lead to significantly increased meal duration in Study 2 (mean difference 0.9 min, 95% confidence interval (CI) 0.0&ndash;1.8), but not in Study 1 (mean difference 1 min, 95% CI 0.1&ndash;2.0). There was a significant increase in number of chews in the large unit size condition of both Study 1 (mean difference 88, 95% CI 12&ndash;158) and Study 2 (mean difference 95, 95% CI 12&ndash;179). Different serving occasions did not significantly change any of the eating behaviours measured. Except for number of bites in Study 2 (R2 = 0.60), most individuals maintained their eating behaviour relative to the group across unit sizes and serving occasions conditions (R2 &gt; 0.75), which suggests single meal testing can provide information about the behavioural characteristics of individual eating styles under different conditions

Ultra-processed food advertisements dominate the food advertising landscape in two Stockholm areas with low vs high socioeconomic status. Is it time for regulatory action?

Background Ultra-processed food consumption is a risk factor for obesity and has a negative environmental impact. Food companies spend billions of dollars on advertisements each year to increase the consumption of ultra-processed food. In Australia, USA, and New Zealand, most food advertisements around schools and in train stations promote ultra-processed food, but no similar studies have been conducted in Sweden. The aim of this study was to explore the proportion of ultra-processed food advertisements in two districts of Stockholm, Sweden with low vs. high socioeconomic status (SES). Methods Two independent researchers (per area) mapped all advertisements, including storefronts, in two Stockholm districts. During consecutive days, all advertisements were photographed in Skärholmen (low SES district), and Östermalmstorg (high SES district), on the streets inside and outside the subway stations, as well as inside and outside of local shopping malls. Advertisements promoting food products were identified and a trained dietician categorized whether they promoted ultra-processed foods. Chi-Square test was conducted to test for differences in the proportion of ultra-processed food advertisements between the two study areas. Results In total, 4092 advertisements were photographed in Skärholmen (n = 1935) and Östermalm (n = 2157). 32.8% of all advertisements promoted food, while 65.4% of food advertisements promoted ultra-processed foods. A significantly higher proportion of ultra-processed food advertisements out of total food advertisements was identified in the low SES area, irrespective of the researcher taking the pictures (74.6% vs. 61.8%, p &lt; 0.001 and 70.4% vs. 54.8%, p = 0.001). There was no significant difference in the proportion of food advertisements out of total advertisements between the two areas. Conclusions This study provides initial evidence about the scale and the differences in exposure to food advertisements across areas in Stockholm. The observed high proportion of ultra-processed food advertisements is concerning and is in sharp contrast to the Swedish dietary guidelines that recommend reduced consumption of such foods. Based on our results, residents in low SES areas might be more exposed to ultra-processed food advertisements than those in high SES areas in Stockholm. If such findings are confirmed in additional areas, they should be considered during the deployment of food advertisement regulatory actions.Funding Agencies|European Communitys ICT Programme [727688]</p

Stability of personality traits over a five-year period in Swedish patients with schizophrenia spectrum disorder and non-psychotic individuals: a study using the Swedish universities scales of personality

Background Personality is considered as an important aspect in persons with psychotic disorders. Several studies have investigated personality in schizophrenia. However, no study has investigated stability of personality traits exceeding three years in patients with schizophrenia. This study aims to investigate the stability of personality traits over a five-year period among patients with schizophrenia and non-psychotic individuals and to evaluate case-control differences. Methods Patients with psychotic disorders (n = 36) and non-psychotic individuals (n = 76) completed Swedish universities Scales of Personality (SSP) at two occasions five years apart. SSP scores were analysed for effect of time and case-control differences by multiple analysis of covariance (MANCOVA) and within-subjects correlation. Results MANCOVA within-subjects analysis did not show any effect of time. Thus, SSP mean scale scores did not significantly vary during the five-year interval. Within subject correlations (Spearman) ranged 0.30–0.68 and 0.54–0.75 for the different SSP scales in patients and controls, respectively. Patients scored higher than controls in SSP scales Somatic Trait Anxiety, Psychic Trait Anxiety, Stress Susceptibility, Lack of Assertiveness, Detachment, Embitterment, and Mistrust. Conclusion The stability of the SSP personality trait was reasonably high among patients with psychotic disorder, although lower than among non-psychotic individuals, which is in accordance with previous research

Swedish universities scales of personality: Relation to other personality instruments

Objective To investigate associations between Swedish universities Scales of Personality (SSP) and scales of the following personality instruments: Structured Clinical Interview for DSM-III-R axis II screening questionnaire (SCID-II screen), revised NEO personality inventory (NEO-PI-R), revised Chapman scales (Chapman) and the psychotic traits questionnaire (STQ).Methods Healthy individuals (n=406) completed self-report personality questionnaires including SSP and at least one more personality inventory. Correlations were calculated between the 13 different SSP subscales as well as SSP’s three factors and factors and scales/subscales in SCID-II screen, NEO-PI-R, Chapman and STQ. The main factors of the various instruments were factor analysed. ICC were calculated.Results SSP Neuroticism factor correlated with SCID-II cluster C (r=0.71), NEO Neuroticism (r=0.80) and Chapman Social anhedonia (r=0.62). SSP Extraversion factor correlated with NEO Extraversion (r=0.63) and SSP Aggressiveness factor with NEO Agreeableness (r=-0.62). Strong correlations between SSP factors and scales and scales of the other instruments were sparse, although weaker correlations were common.Conclusion SSP is a useful investigation tool when measuring personality traits related to temperament-like features. SSP partly correlates well to especially three of the NEO-PI-R factors. The different personality inventories are not completely comparable to each other. Instead, they measure personality aspects in partly different ways

Correction to: Stability of personality traits over a five-year period in Swedish patients with schizophrenia spectrum disorder and nonpsychotic individuals: a study using the Swedish universities scales of personality

After publication of the original article [1], it was brought to our attention that some of the numbers in Table 3were incorrect