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Nature Oct 2023
Topics: Humans; Body Mass Index; Obesity; Body Height; Body Weight; Adipose Tissue; Health
PubMed: 37821595
DOI: 10.1038/d41586-023-03143-x -
Aerospace Medicine and Human Performance Sep 2023The modern aircraft cockpit has evolved into a complex system of systems. Numerous performance evaluation metrics and techniques exist that can measure the...
The modern aircraft cockpit has evolved into a complex system of systems. Numerous performance evaluation metrics and techniques exist that can measure the effectiveness of cockpit components in terms of how they influence the human operator's ability to perform tasks relevant to mission success. As no prior review of these metrics has been found in the literature, this effort attempts to do so, albeit without applying the metrics to a novel cockpit evaluation. These metrics and techniques are discussed and presented in five defined categories as they relate to evaluating cockpit subsystems: ergonomics and anthropometrics; human-computer interaction; data management and presentation; crew resource management and operations; and ingress and egress. While this effort is significant and novel, it is not necessarily comprehensive. In conclusion, it is noted that no single holistic quantitative metric to evaluate cockpit design and performance yet exists. Utilizing some of the preexisting metrics presented to develop such a metric would be beneficial in efforts to evaluate aircraft cockpit designs and performance, as well as aiding future cockpit designs.
Topics: Humans; Aircraft; Anthropometry; Ergonomics
PubMed: 37587638
DOI: 10.3357/AMHP.6185.2023 -
PloS One 2023General obesity is a recognized risk factor for various metabolically related diseases, including hypertension, dyslipidemia, and pre-diabetes. In epidemiological...
General obesity is a recognized risk factor for various metabolically related diseases, including hypertension, dyslipidemia, and pre-diabetes. In epidemiological studies, anthropometric variables such as height and weight are often self-reported. However, misreporting of self-reported data may bias estimates of associations between anthropometry and health outcomes. Further, few validation studies have compared self-reported and measured waist circumference (WC). This study aimed to quantify the agreement between self-reported and measured height, weight, body mass index (BMI), WC, and waist-to-height ratio (WHtR), and to investigate associations of these anthropometric measures with cardiometabolic biomarkers. A total of 39,514 participants aged above 18 years were included into the Diet, Cancer, and Health-Next Generation Cohort in 2015-19. Self-reported and measured anthropometric variables, blood pressure, and cardiometabolic biomarkers (HbA1c, lipid profiles, C-reactive protein and creatinine) were collected by standard procedures. Pearson correlations (r) and Lin's concordance correlations were applied to evaluate misreporting. Misreporting by age, sex and smoking status was investigated in linear regression models. Multivariable regression models and Receiver Operating Characteristic analyses assessed associations of self-reported and measured anthropometry with cardiometabolic biomarkers. Self-reported height was overreported by 1.07 cm, and weight was underreported by 0.32 kg on average. Self-reported BMI and WC were 0.42 kg/m2 and 0.2 cm lower than measured, respectively. Self-reported and measured height, weight, BMI, WC and WtHR were strongly correlated (r = 0.98, 0.99, 0.98, 0.88, 0.86, respectively). Age, sex, smoking, and BMI contributed to misreporting of all anthropometric measures. Associations between self-reported or measured anthropometric measures and cardiometabolic biomarkers were similar in direction and strength. Concordance between self-reported and measured anthropometric measures, including WC, was very high. Self-reported anthropometric measures were reliable when estimating associations with cardiometabolic biomarkers.
Topics: Humans; Aged; Cohort Studies; Self Report; Anthropometry; Body Mass Index; Risk Factors; Hypertension; Waist Circumference; Biomarkers; Denmark; Waist-Height Ratio
PubMed: 37498855
DOI: 10.1371/journal.pone.0279795 -
Appetite Sep 2023Examining typical developmental trajectories of infant eating behaviors, correlates of those trajectories, and cross-lagged associations between eating behaviors and...
Examining typical developmental trajectories of infant eating behaviors, correlates of those trajectories, and cross-lagged associations between eating behaviors and anthropometry, is important to understand the etiology of these behaviors and their relevance to growth early in the lifespan. Mothers (N = 276) completed the Baby Eating Behavior Questionnaire (BEBQ) and infant anthropometrics were measured at ages 1, 2, 4, 6, and 10 months. Infant and maternal characteristics were collected by maternal report. Trajectories of eating behaviors were identified using latent class growth modeling and bivariate analyses examined associations of infant eating behavior trajectory membership with infant and maternal characteristics. Cross-lagged analyses examined associations between BEBQ subscales and infant weight-for-length z-score. Infant eating behavior trajectories included: Consistently High (62%) and Consistently Moderate (38%) Enjoyment of Food; Consistently High (9%), Moderate & Decreasing (43%), and Low & Decreasing (48%) Food Responsiveness; and Consistently High (62%) and Moderate & Decreasing (38%) General Appetite. Trajectory group membership was not associated with infant sex, gestational age, birthweight, or having been exclusively fed breastmilk at 2 months. Consistently High trajectories for Enjoyment of Food, Food Responsiveness, and General Appetite were associated with maternal demographic markers of psychosocial risk (e.g., lower maternal age and educational attainment). Food Responsiveness and General Appetite tracked strongly across infancy within individuals. Cross-lagged associations of Enjoyment of Food, Food Responsiveness, and General Appetite with weight-for-length z-score across infancy were generally null. Much additional work is needed to understand eating behaviors in infancy, their development, and their etiology. Further understanding of infant eating behaviors will provide the basis for future interventions to improve life course nutrition, growth, and health.
Topics: Female; Infant; Humans; Feeding Behavior; Mothers; Appetite; Anthropometry; Surveys and Questionnaires
PubMed: 37495177
DOI: 10.1016/j.appet.2023.106978 -
EBioMedicine Dec 2023Maternal lipidomic profiling offers promise for characterizing lipid metabolites during pregnancy, but longitudinal data are limited. This study aimed to examine...
BACKGROUND
Maternal lipidomic profiling offers promise for characterizing lipid metabolites during pregnancy, but longitudinal data are limited. This study aimed to examine associations of longitudinal lipidomic profiles during pregnancy with multiple neonatal anthropometry using data from a multiracial cohort.
METHODS
We measured untargeted plasma lipidome profiles among 321 pregnant women from the NICHD Fetal Growth Study-Singletons using plasma samples collected longitudinally during four study visits at gestational weeks (GW) 10-14, 15-26, 23-31, and 33-39, respectively. We evaluated individual lipidomic metabolites at each study visit in association with neonatal anthropometry. We also evaluated the associations longitudinally by constructing lipid networks using weighted correlation network analysis and common networks using consensus network analysis across four visits using linear mixed-effects models with the adjustment of false discover rate.
FINDINGS
Multiple triglycerides (TG) were positively associated with birth weight (BW), BW Z-score, length and head circumference, while some cholesteryl ester (CE), phosphatidylcholine (PC), sphingomyelines (SM), phosphatidylethanolamines (PE), and lysophosphatidylcholines (LPC 20:3) families were inversely associated with BW, length, abdominal and head circumference at different GWs. Longitudinal trajectories of TG, PC, and glucosylcermides (GlcCer) were associated with BW, and CE (18:2) with BW z-score, length, and sum of skinfolds (SS), while some PC and PE were significantly associated with abdominal and head circumference. Modules of TG at GW 10-14 and 15-26 mainly were associated with BW. At GW 33-39, two networks of LPC (20:3) and of PC, TG, and CE, showed inverse associations with abdominal circumference. Distinct trajectories within two consensus modules with changes in TG, CE, PC, and LPC showed significant differences in BW and length.
INTERPRETATION
The results demonstrated that longitudinal changes of TGs during early- and mid-pregnancy and changes of PC, LPC, and CE during late-pregnancy were significantly associated with neonatal anthropometry.
FUNDING
National Institute of Child Health and Human Development intramural funding.
Topics: Infant, Newborn; Child; Pregnancy; Humans; Female; Lipidomics; Anthropometry; Fetal Development; Birth Weight; Lipids
PubMed: 38006745
DOI: 10.1016/j.ebiom.2023.104881 -
Maternal & Child Nutrition Oct 2023Nutrition-sensitive agriculture programmes have the potential to improve child nutrition outcomes, but livestock intensification may pose risks related to water,... (Randomized Controlled Trial)
Randomized Controlled Trial
Effects of an integrated poultry value chain, nutrition, gender and WASH intervention (SELEVER) on hygiene and child morbidity and anthropometry in Burkina Faso: A secondary outcome analysis of a cluster randomised trial.
Nutrition-sensitive agriculture programmes have the potential to improve child nutrition outcomes, but livestock intensification may pose risks related to water, sanitation and hygiene (WASH) conditions. We assessed the impact of SELEVER, a nutrition- and gender-sensitive poultry intervention, with and without added WASH focus, on hygiene practices, morbidity and anthropometric indices of nutrition in children aged 2-4 years in Burkina Faso. A 3-year cluster randomised controlled trial was implemented in 120 villages in 60 communes (districts) supported by the SELEVER project. Communes were randomly assigned using restricted randomisation to one of three groups: (1) SELEVER intervention (n = 446 households); (2) SELEVER plus WASH intervention (n = 432 households); and (3) control without intervention (n = 899 households). The study population included women aged 15-49 years with an index child aged 2-4 years. We assessed the effects 1.5-years (WASH substudy) and 3-years (endline) post-intervention on child morbidity and child anthropometry secondary trial outcomes using mixed effects regression models. Participation in intervention activities was low in the SELEVER groups, ranging from 25% at 1.5 years and 10% at endline. At endline, households in the SELEVER groups had higher caregiver knowledge of WASH-livestock risks (∆ = 0.10, 95% confidence interval [CI] [0.04-0.16]) and were more likely to keep children separated from poultry (∆ = 0.09, 95% CI [0.03-0.15]) than in the control group. No differences were found for other hygiene practices, child morbidity symptoms or anthropometry indicators. Integrating livestock WASH interventions alongside poultry and nutrition interventions can increase knowledge of livestock-related risks and improve livestock-hygiene-related practices, yet may not be sufficient to improve the morbidity and nutritional status of young children.
Topics: Animals; Humans; Child; Female; Infant; Child, Preschool; Nutritional Status; Poultry; Water; Sanitation; Burkina Faso; Hygiene; Morbidity; Anthropometry; Livestock
PubMed: 37244872
DOI: 10.1111/mcn.13528 -
Endocrinologia, Diabetes Y Nutricion Sep 2023Childhood obesity is an extremely prevalent pathology and, in order to be able to address it, it is necessary to understand the factors that influence on its genesis and...
INTRODUCTION
Childhood obesity is an extremely prevalent pathology and, in order to be able to address it, it is necessary to understand the factors that influence on its genesis and maintenance. We hypothesise that the timing of meals and sleep, the regularity of these throughout the week and a sedentary lifestyle influence the degree of obesity.
MATERIAL AND METHODS
We included children and adolescents with obesity who attended a first check-up visit at the Childhood Obesity Unit between January 2018 and February 2020. The data were obtained from a questionnaire on food (36-h intake, frequency of consumption, eating times and habits) and sleep.
RESULTS
The degree of obesity was influenced to a greater extent by later meal times and the distribution of calories throughout the day (less at breakfast, more at dinner) than by the total number of calories ingested. In addition, a lower consumption of vegetables was related to a higher degree of obesity. The difference between the hours of sleep at weekends and on weekdays correlated positively with a higher degree of obesity. Finally, the anthropometric data correlated negatively with the number of hours of physical activity. Almost half of the children did not exercise after school.
CONCLUSION
In the approach to childhood obesity, it is necessary to include recommendations on the regularity of meal and sleep times, as well as the distribution of calories throughout the day. Additionally, it is necessary to encourage the practice of physical exercise.
Topics: Child; Adolescent; Humans; Pediatric Obesity; Exercise; Anthropometry; Sleep; Feeding Behavior
PubMed: 37596175
DOI: 10.1016/j.endien.2023.08.001 -
European Journal of Clinical Nutrition Sep 2023Body image scanners are used in industry and research to reliably provide a wealth of anthropometric measurements within seconds. The demonstrated utility of the... (Review)
Review
BACKGROUND
Body image scanners are used in industry and research to reliably provide a wealth of anthropometric measurements within seconds. The demonstrated utility of the scanners drives the current proliferation of more commercially available devices that rely on their own reference body sites and proprietary algorithms to output anthropometric measurements. Since each scanner relies on its own algorithms, measurements obtained from different scanners cannot directly be combined or compared.
OBJECTIVES
To develop mathematical models that translate anthropometric measurements between the three popular commercially available scanners.
METHODS
A unique database that contained 3D scanner measurements in the same individuals from three different scanners (Styku, Human Solutions, and Fit3D) was used to develop linear regression models that translate anthropometric measurements between each scanner. A limits of agreement analysis was performed between Fit3D and Styku against Human Solutions measurements and the coefficient of determination, bias, and 95% confidence interval were calculated. The models were then applied to normalized scanner data from four different studies to compare the results of a k-means cluster analysis between studies. A scree plot was used to determine the optimal number of clusters derived from each study.
RESULTS
Correlations ranged between R = 0.63 (Styku and Human Solutions mid-thigh circumference) to R = 0.97 (Human Solutions and Fit3D neck circumference). In general, Fit3D had better agreement with Human Solutions compared to Styku. The widest disagreement was found in chest circumference (Fit3D (bias = 2.30, 95% CI = [-3.83, 8.43]) and Styku (bias = -5.60, 95% CI = [-10.98, -0.22]). The optimal number of body shape clusters in each of the four studies was consistently 5.
CONCLUSIONS
The newly developed models that translate measurements between the scanners Styku and Fit3D to predict Human Solutions measurements make it possible to standardize data between scanners allowing for data pooling and comparison.
Topics: Humans; Body Image; Imaging, Three-Dimensional; Algorithms; Models, Theoretical; Anthropometry; Reproducibility of Results
PubMed: 37165098
DOI: 10.1038/s41430-023-01289-5 -
Nutrients Dec 2023Cardiovascular diseases are the main cause of mortality worldwide. Patients with phenylketonuria (PKU) may be at increased cardiovascular risk. This review provides an... (Review)
Review
Cardiovascular diseases are the main cause of mortality worldwide. Patients with phenylketonuria (PKU) may be at increased cardiovascular risk. This review provides an overview of clinical and metabolic cardiovascular risk factors, explores the connections between body composition (including fat mass and ectopic fat) and cardiovascular risk, and examines various methods for evaluating body composition. It particularly focuses on nutritional ultrasound, given its emerging availability and practical utility in clinical settings. Possible causes of increased cardiometabolic risk in PKU are also explored, including an increased intake of carbohydrates, chronic exposure to amino acids, and characteristics of microbiota. It is important to evaluate cardiovascular risk factors and body composition in patients with PKU. We suggest systematic monitoring of body composition to develop nutritional management and hydration strategies to optimize performance within the limits of nutritional therapy.
Topics: Humans; Anthropometry; Body Composition; Cardiovascular Diseases; Biomarkers; Phenylketonurias; Body Mass Index
PubMed: 38140392
DOI: 10.3390/nu15245133 -
Nutrients Apr 2024The effects of intermittent fasting (IF) on health promotion in the healthy population remain controversial. Therefore, our study aimed to analyse the efficacy and... (Randomized Controlled Trial)
Randomized Controlled Trial
The effects of intermittent fasting (IF) on health promotion in the healthy population remain controversial. Therefore, our study aimed to analyse the efficacy and feasibility of different IF protocols and evaluated the effects within a cohort with a controlled-run in phase on the body mass index (BMI) as the primary outcome, the body composition, and metabolic and haematological markers in healthy participants. A total of 25 individuals were randomised into three fasting groups: 16/8 fasting ( = 11), 20/4 fasting ( = 6), and alternate-day fasting (ADF, = 8). Assessments were conducted at baseline (visit 1), after a four-week controlled-run in phase (visit 2), and after eight weeks of fasting (visit 3). Both the BMI ( = 0.01) and bodyweight ( = 0.01) were significantly reduced in the ADF group, which was not seen in the 16/8 and 20/4 groups ( > 0.05). Adherence was different but not statistically among the groups (16/8: 84.5 ± 23.0%; 20/4: 92.7 ± 9.5%; and ADF: 78.1 ± 33.5%, = 0.57). Based on our obtained results, the data suggest that some fasting interventions might be promising for metabolic health. However, adherence to the specific fasting protocols remains challenging even for the healthy population.
Topics: Humans; Fasting; Male; Female; Adult; Body Mass Index; Body Composition; Middle Aged; Young Adult; Healthy Volunteers; Body Weight; Biomarkers; Blood Glucose; Intermittent Fasting
PubMed: 38674802
DOI: 10.3390/nu16081114