Body Mass Index Variables Research Articles

Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis

Background/objectivesEvidence on the associations between lifestyle movement behaviors and obesity has been established without taking into account the time-constrained nature of categorized, time-based lifestyle behaviors. We examined the associations of sleep, sedentary behavior (SED), light-intensity physical activity (LPA), and moderate-to-vigorous PA (MVPA) with body mass index (BMI) using Compositional Data Analysis (CoDA), and compared the associations between a report-based method (24-h Physical Activity Recall; 24PAR) and a monitor-based method (SenseWear Armband; SWA).Subjects/methodsReplicate data from a representative sample of 1247 adults from the Physical Activity Measurement Survey (PAMS) were used in the study. Participants completed activity monitoring on two randomly selected days, each of which required wearing a SWA for a full day, and then completing a telephone-administered 24PAR the following day. Relationships among behavioral compositional parts and BMI were analyzed using CoDA via multiple linear regression models with both 24PAR and SWA data.ResultsUsing 24PAR, time spent in sleep (γ = −3.58, p = 0.011), SED (γ = 3.70, p = 0.002), and MVPA (γ = −0.53, p = 0.018) was associated with BMI. Using SWA, time spent in sleep (γ = −5.10, p < 0.001), SED (γ = 8.93, p < 0.001), LPA (γ = −3.12, p < 0.001), and MVPA (γ = −1.43, p < 0.001) was associated with BMI. The SWA models explained more variance in BMI (R2 = 0.28) compared with the 24PAR models (R2 = 0.07). The compositional isotemporal substitution models revealed reductions in BMI when replacing SED by MVPA, LPA (not with 24PAR) or sleep for both 24PAR and SWA, but the effect estimates were larger with SWA.ConclusionsFavorable levels of relative time spent in lifestyle movement behaviors were, in general, associated with decreased BMI. The observed associations were stronger using the monitor-based SWA method compared with the report-based 24PAR method.

Associations between body mass index and breast cancer markers

Body mass index (BMI) and breast cancer biomarkers such as resistin, leptin adiponectin, monocyte chemoattractant protein-1 (MCP-1) and homeostasis model assessment of insulin resistance (HOMA-IR) are highly associated with each other. The report has focused the inter-relationship between BMI and breast cancer biomarkers based on probabilistic modeling. It has been shown that mean BMI is positively associated with leptin (P&lt;0.0001) and MCP-1 (P=0.0002), while it is negatively associated with adiponectin (P=0.0003), HOMA-IR (P&lt;0.0001), and it is higher for healthy women (P=0.0116) than breast cancer women. In addition, variance of BMI is negatively associated with resistin (P=0.1450). On the other hand, mean MCP-1 is positively associated with BMI (P&lt;0.0001). Mean resistin is positively associated with the interaction effect of BMI and leptin (BMI*Leptin) (P=0.0415), while its variance is positively associated with BMI (P=0.0942), and it is negatively associated with BMI*Adiponectin (P=0.1518). Leptin is positively associated with BMI (P&lt;0.0001). Also adiponectin is negatively associated with BMI (P&lt;0.0001), BMI*Leptin (P=0.1729), while it is positively associated with Age*BMI (P=0.0017) and BMI*Resistin (P=0.0615). It can be concluded that BMI and breast cancer biomarkers are strongly associated with each other. Care should be taken on BMI for breast cancer women.

Hunger and BMI modulate neural responses to sweet stimuli: fMRI meta-analysis.

Consuming sweet foods, even when sated, can lead to unwanted weight gain. Contextual factors, such as longer time fasting, subjective hunger, and body mass index (BMI), may increase the likelihood of overeating. Nevertheless, the neural mechanisms underlying these moderating influences on energy intake are poorly understood. We conducted both categorical meta-analysis and meta-regression of factors modulating neural responses to sweet stimuli, using data from 30 functional magnetic resonance imaging (fMRI) articles incorporating 39 experiments (N = 995) carried out between 2006 and 2019. Responses to sweet stimuli were associated with increased activity in regions associated with taste, sensory integration, and reward processing. These taste-evoked responses were modulated by context. Longer fasts were associated with higher posterior cerebellar, thalamic, and striatal activity. Greater self-reported hunger was associated with higher medial orbitofrontal cortex (OFC), dorsal striatum, and amygdala activity and lower posterior cerebellar activity. Higher BMI was associated with higher posterior cerebellar and insular activity. Variations in fasting time, self-reported hunger, and BMI are contexts associated with differential sweet stimulus responses in regions associated with reward processing and homeostatic regulation. These results are broadly consistent with a hierarchical model of taste processing. Hunger, but not fasting or BMI, was associated with sweet stimulus-related OFC activity. Our findings extend existing models of taste processing to include posterior cerebellar regions that are associated with moderating effects of both state (fast length and self-reported hunger) and trait (BMI) variables.

The Relative Contributions of Socioeconomic and Genetic Factors to Variations in Body Mass Index Among Young Adults.

In light of recent findings on the small proportion of variance in body mass index (BMI) explained by shared environment, and growing interests in the role of genetic susceptibility, we assessed the relative contribution of socioeconomic status (SES) and genome-wide polygenic score for BMI to explaining variation in BMI. Our final analytic sample included 4,918 White and 1,546 Black individuals from the US National Longitudinal Study of Adolescent to Adult Health Wave IV (2007-2008) who had complete measures on BMI, demographics, SES, genetic data, and health behaviors. We used ordinary least-squares regression to assess variation in log(BMI) as a function of the aforementioned predictors, independently and mutually adjusted. All analyses were stratified by race/ethnicity in the main analysis, and further by sex. The age-adjusted variation in log(BMI) was 0.055 among Whites and 0.066 among Blacks. The contribution of SES and polygenic score ranged from less than1% to 6% and from 2% to 8%, respectively, and majority of the variation (87%-96%) in log(BMI) remained unexplained. Differential distribution of socioeconomic resources, stressors, and buffers may interact to produce systematically larger variation in vulnerable populations. More understanding of the contribution of biological, genetic, and environmental factors, as well as stochastic elements, in diverse phenotypic variance is needed in population health sciences.

The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers

BackgroundDNA methylation is associated with body mass index (BMI), but it is not clear if methylation scores are biomarkers for extant BMI or predictive of future BMI. Here, we explore the causal nature and predictive utility of DNA methylation measured in peripheral blood with BMI and cardiometabolic traits.MethodsAnalyses were conducted across the life course using the ARIES cohort of mothers (n = 792) and children (n = 906), for whom DNA methylation and genetic profiles and BMI at multiple time points (3 in children at birth, in childhood and in adolescence; 2 in mothers during pregnancy and in middle age) were available. Genetic and DNA methylation scores for BMI were derived using published associations between BMI and DNA methylation and genotype. Causal relationships between methylation and BMI were assessed using Mendelian randomisation and cross-lagged models.ResultsThe DNA methylation scores in adult women explained 10% of extant BMI variance. However, less extant variance was explained by scores generated in the same women during pregnancy (2% BMI variance) and in older children (15–17 years; 3% BMI variance). Similarly, little extant variance was explained in younger children (at birth and at 7 years; 1% and 2%, respectively). These associations remained following adjustment for smoking exposure and education levels. The DNA methylation score was found to be a poor predictor of future BMI using linear and cross-lagged models, suggesting that DNA methylation variation does not cause later variation in BMI. However, there was some evidence to suggest that BMI is predictive of later DNA methylation. Mendelian randomisation analyses also support this direction of effect, although evidence is weak. Finally, we find that DNA methylation scores for BMI are associated with extant cardiometabolic traits independently of BMI and genetic score.ConclusionThe age-specific nature of DNA methylation associations with BMI, lack of causal relationship and limited predictive ability of future BMI indicate that DNA methylation is likely influenced by BMI and might more accurately be considered a biomarker of BMI and related outcomes rather than a predictor. Future epigenome-wide association studies may benefit from further examining associations between early DNA methylation and later health outcomes.

Cross-Cultural Variation in BMI, Sedentary Behavior, and Physical Activity in International School Girls Residing in Saudi Arabia.

Background: The current study was done to assess the cross-cultural difference in physical activity and sedentary behavior among girls from culturally, environmentally, and geographically diverse countries residing in Saudi Arabia. Methods: This was a comparative cross-sectional study conducted among expatriate girls (N = 275), aged 9–16 years. Participants were from India (n = 65), Pakistan (n = 88), Egypt (n = 50), Sudan (n = 49), and other nationals (n = 23). They were randomly selected from different schools in Riyadh and their Body Mass Index (BMI) and screen time was assessed. Physical activity (PA) and leisure-time activity was assessed using Physical Activity Questionnaire for Older Children (PAQ-C) and the Godin-Shephard Leisure-Time Exercise Questionnaire (GSLTPAQ) respectively. Results: Out of 275, 65.8% were active and 34.2% were insufficiently active as per the GSLTPAQ, and half of them were moderately active and only 22.2% were extremely active as per PAQ-C. No statistical significant differences in their BMI status, screen time, or the levels of PA among expatriate girls. Conclusions: This study shows that the expatriate female school children in Saudi Arabia demonstrated a similar pattern in their BMI, sedentary time spent, and PA levels.

Translation and validation of the addiction-like Eating Behavior Scale from English to Portuguese in Brazil

Eating addiction is an important condition related to obesity. The Addiction-like Eating Behavior Scale (AEBS) was recently validated in English to evaluate addictive eating behaviors. To perform the translation, cultural adaptation, and validation of the AEBS scale to Portuguese to identify eating addictions in the Brazilian population. The AEBS translation, adaptation, and validation followed previously published criteria, including the steps of translation, back translation, evaluation by a committee of judges, and a pretest with 40 students. Subsequently, 150 students from the Medical School at the Recife Campus of the Federal University of Pernambuco were tested using the AEBS-Portuguese version (AEBS-p). Of these, 37 were evaluated a second time for a test-retest analysis. For data collection, 5 instruments were used: the AEBS-p, a modified version of the Yale Food Addiction Scale 2.0 (mYFAS 2.0)-Portuguese version, the Patient Health Questionnaire-9, the Binge Eating Scale (BES), and the Socio-demographic Questionnaire. The AEBS-p showed good reliability, based on a significant internal consistency value (Cronbach’s alpha = 0.91), and good correlation in the test-retest evaluation. A committee of judges considered the content validity appropriate. Convergent validation was positive with the mYFAS 2.0 and BES (p < 0.001). The AEBS-p showed a significant correlation with body mass index (BMI) (p < 0.001) and significantly predicted variance in BMI that was accounted for by both the mYFAS 2.0 and BES (p = 0.022). The AEBS-p demonstrated good reliability and validity for evaluating addictive eating behaviors in the Brazilian population.

Factors influencing weight management behavior among college students: An application of the Health Belief Model.

Overweight and obesity have become a significant public health concern in both developing and developed countries. Due to the health implications of weight-reduction behaviors, it is important to explore the factors that predict their occurrence. Therefore, the present study was performed to examine factors affecting the behavioral intention of weight management as well as assess the predictive power of the Health Belief Model (HBM) for body mass index (BMI). This cross-sectional study was conducted among 336 female students recruited from dormitories of Tabriz University of Medical Sciences, using quota sampling technique. Data were collected by a structured questionnaire in seven parts (including perceived severity, perceived susceptibility, perceived benefit, perceived barrier, cue to action, self-efficacy in dieting and physical activity, and behavioral intention of weight management), based on the HBM. Structural equation modeling (SEM) was conducted to identify the relationship between HBM constructs and behavioral intention of weight management. Linear regression model was performed to test the ability of the HBM to predict students' BMIs. Higher level of perceived threats (sum of perceived susceptibility and severity) (β = 0.41, P<0.001), perceived benefits (β = 0.19, P = 0.009), self-efficacy in exercise (β = 0.17, P = 0.001), and self-efficacy in dieting (β = 0.16, P = 0.025) scales was significantly related to greater behavioral intention of weight management. Moreover, perceived threat mediated the relationships between perceived cue to action, perceived benefits, self-efficacy in exercise, and weight management practices. The fit indices of the SEM model seemed acceptable. The final regression model explained approximately 40% of variance in BMI (P<0.001). Additionally, perceived severity, barrier, and self-efficacy in dietary life were the significant variables to predict students' BMIs. These findings suggest that health education programs based on the HBM needs to be integrated in preventive health programs and health interventions strategies to ensure adherence and well-being of the participants.

Could orthodontic fixed appliances and excess weight affect gingival health in adolescents?

The aim of this study was to evaluate the impact of being overweight or obese while wearing orthodontic fixed appliances on the prevalence of gingivitis in adolescents. A total of 334 adolescents, aged between 12 and 18years, were recruited from 3 public schools in Cuiabá, Brazil. Participants were divided in dichotomized categories of body mass index (BMI) (under andnormal weight or overweight and obesity) and fixed orthodontic appliance usage (yes or no). Gingival inflammation was evaluated by Löe & Silness index. Socioeconomic status was determined by the criteria of the Brazilian Association of Research Companies, and sugar consumption was assessed by a questionnaire of dietary habits. The statistical analysis was performed with P<0.05 considered significant. In a multivariate linear regression model, gingivitis was directly related to BMI (%) variation and orthodontic appliance use. In addition, excess weight seemed to be 2 times more relevant in predicting gingivitis than orthodontic fixed appliance usage. A strong positive correlation was observed between BMI (%) variation and gingival index (ρ=0.97, P<0.001). Orthodontic fixed appliance usage and excess weight were associated with increased gingivitis in adolescents; BMI (%) variation was the most significant predictor of gingival inflammation.

Retrospective reports of childhood feeding in mother-daughter dyads

Significant research has linked parents' feeding practices to children's eating habits. However, much less is known about how childhood feeding relates to longer-term outcomes such as eating in adulthood. The current study uses retrospective reports from mother-daughter dyads (N = 217) to compare childhood feeding practices and to examine how recalled feeding is related to current eating (emotional eating, intuitive eating, unrestrained eating) and body mass index (BMI) in adult daughters. Mothers and daughters completed the Comprehensive Feeding Practices Questionnaire (CFPQ), subscales from the Three Factor Eating Questionnaire, and the Intuitive Eating Scale. Results of an exploratory factor analysis indicated that mothers and daughters largely had similar factor structures on retrospective reports, with factor loadings varying on four of twelve original CFPQ subscales: monitoring, restriction for health, child control, and modelling. Paired samples t-tests examined mean differences between mother and daughter reports on each subscale; there was no significant difference between mother and daughter reports on six of the 11 scales. Daughters reported significantly higher levels of pressure to eat; mothers reported significantly higher levels of healthy practices, child control, involvement, and unhealthy environment than their daughters recalled. Hierarchical regressions revealed that daughters' reports of specific childhood feeding practices accounted for significant change in unadjusted variance for uncontrolled eating (18.8%), emotional eating (13.1%), intuitive eating (14.7%), and BMI (16.1%). Similarly, regressions revealed that mothers' reports of childhood feeding practices accounted for significant change in unadjusted variance for emotional eating (11.5%) and BMI (11.2%), but not uncontrolled or intuitive eating. Collectively, results lend strong support to the use of retrospective reports on childhood feeding and provide evidence that recalled childhood feeding practices have lasting relations with adult eating behaviors.

Bariatric surgery-induced weight loss in patients with and without type 2 diabetes mellitus.

Surgical treatment of obesity leads to weight loss and metabolic improvement, but it is unclear if the response differs between patients with and without type 2 diabetes. Retrospective cohort study comparing weight loss and metabolic outcomes between patients with and without type 2 diabetes, matched for body mass index (BMI), gender and age, 12 months after Roux-en-Y gastric bypass. Forty-eight patients with type 2 diabetes (D) and 48 without type 2 diabetes (ND) were evaluated, 87.5% female, mean age 42.2 ± 0.9 years. The mean baseline weight and BMI of the D and ND groups were, respectively, 120.3 ± 21.6 vs 123.7 ± 20.8 kg (P = .45) and 47.2 ± 7.5 vs 47.2 ± 6.9 kg/m2 (P = .70). After 12 months, there was no significant difference in weight (40.4 ± 16.9 vs 44.1 ± 12.2 kg, P = .28) and BMI (15.8 ± 6.5 vs 16.9 ± 4.5 kg/m2 , P = .26) variation between groups. The parameters that presented significant variation were (D vs ND): fasting blood glucose (41.6 ± 43.0 vs 12.7 ± 17.2 mg/dL, P < .01), HbA1c (1.8 ± 1.6 vs 0.6 ± 0.7%; P < .01), triglycerides (91.1 ± 100.4 vs 54.2 ± 43.8 mg/dL; P = .04), low-density lipoprotein (27.2 ± 41.5 vs 37.5 ± 24.2 mg/dL; P < .01) and gamma glutamyl transferase (46.5 ± 55.3 vs 17.7 ± 11.9 UI/L; P = .04). Weight loss 12 months after a gastric bypass was similar in patients with and without type 2 diabetes, the greater metabolic benefits appearing in patients with type 2 diabetes as they had more pronounced changes at baseline.

Bio-analytical methods for investigating the effect of age, body mass index and gender on the PK/PD ratio of antibiotics.

The effectiveness of antibiotics (ABs) is governed by achieving the adequate pharmacokinetic (PK)/pharmacodynamics (PD) ratio. In this study, fast LC-MS/MS methods were developed and validated for the bioanalysis of cefaclor (CFC), ciprofloxacin (CFC), roxithomycin (RXM) and clindamycin (CLD). Chromatographic separation was performed on a C18 Zorbax-Eclipse Plus (3.5 μm, 100 × 4.6 mm) using isocratic elution. Detection was performed by positive electrospray ionization. The methods were applied for the assessment of PK parameters in volunteers (n = 101, 64 male and 37 female) and the effects of age, body mass index (BMI) and gender were investigated. Good linearity (r2 ≥ 0.99), accuracy (>86%), precision (CV% ≤ 11) and extraction recovery (>83%) were observed for CFC, CFX, RXM and CLD. Application to PK studies revealed that age and BMI affected the Thalf and the AUC of RXM and CLD (p < 0.023). Gender difference affected the critical PK parameters of the four ABs (Thalf (U = 18; P = 0.036) of CFC, the Cmax of CFX (U = 30; P = 0.017), the Thalf (U = 23; P = 0.009) and AUC (U = 26; P = 0.008) of RXM and CLD), respectively. These results highlight the significance of age and BMI variations for RXM and CLD dosing. Furthermore, it indicates that the gender difference may be considered when adjusting the AB dose.

Polygenic Risk, Fitness, and Obesity in the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Obesity is a major determinant of disease burden worldwide. Polygenic risk scores (PRSs) have been posited as key predictors of obesity. How a PRS can be translated to the clinical encounter (especially in the context of fitness, activity, and parental history of overweight) remains unclear. To quantify the relative importance of a PRS, fitness, activity, parental history of overweight, and body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) in young adulthood on BMI trends over 25 years. This population-based prospective cohort study at 4 US centers included white individuals and black individuals with assessments of polygenic risk of obesity, fitness, activity, and BMI in young adulthood (in their 20s) and up to 25 years of follow-up. Data collected between March 1985 and August 2011 were analyzed from April 25, 2019, to September 29, 2019. Body mass index at the initial visit and 25 years later. This study evaluated an obesity PRS from a recently reported study of 1608 white individuals (848 women [52.7%]) and 909 black individuals (548 women [60.3%]) across the United States. At baseline (year 0), mean (SD) overall BMI was 24.2 (4.5), which increased to 29.6 (6.9) at year 25. Among white individuals, the PRS (combined with age, sex, self-reported parental history of overweight, and principal components of ancestry) explained 11.9% (at year 0) and 13.6% (at year 25) of variation in BMI. Although the addition of fitness increased the explanatory capability of the model (24.0% variance at baseline and up to 18.1% variance in BMI at year 25), baseline BMI in young adulthood was the strongest factor, explaining 52.3% of BMI in midlife in combination with age, sex, and self-reported parental history of overweight. Accordingly, models that included baseline BMI (especially BMI surveillance over time) were better in predicting BMI at year 25 compared with the PRS. In fully adjusted models, the effect sizes for fitness and the PRS on BMI were comparable in opposing directions. The added explanatory capacity of the PRS among black individuals was lower than among white individuals. Among white individuals, addition of baseline BMI and surveillance of BMI over time was associated with improved precision of predicted BMI at year 25 (mean error in predicted BMI 0 kg/m2 [95% CI, -11.4 to 11.4] to 0 kg/m2 [95% CI, -8.5 to 8.5] for baseline BMI and mean error 0 kg/m2 [95% CI, -5.3 to 5.3] for BMI surveillance). Cardiorespiratory fitness in young adulthood and a PRS are modestly associated with midlife BMI, although future BMI is associated with BMI in young adulthood. Fitness has a comparable association with future BMI as does the PRS. Caution should be exercised in the widespread use of polygenic risk for obesity prevention in adults, and close clinical surveillance and fitness may have prime roles in limiting the adverse consequences of elevated BMI on health.

Body Mass, Nutrition, and Disease: Current Net Nutrition During Us Economic Development

When other measures for material welfare are scarce or unreliable, the use of average stature and body mass index (BMI) values is common. BMI reflects the current difference between calories consumed, calories required for work, and to withstand the physical environment. This study evaluates 19th century macro-level nutrition and diseases associated with US BMI variation. Body mass was positively related to calories from dairy products and inversely related to malaria, which had a larger effect on net-nutrition than cholera. After controlling for nutrition and disease, black BMIs and weights were greater than whites, indicating that 19th century social preferences are an unlikely explanation for taller, fairer complexioned whites.

Heterogeneity in adult anthropometry by socioeconomic factors: Indian National Family Health Survey 2006 and 2016.

Recent evidence suggests nonconstant nature of dispersion in adult women's body mass index (BMI) across sociodemographic groups. The overall variances in BMI and height are also shown to have substantially changed over time. We modeled complex variation in adults' anthropometry-BMI and height-by wealth and education, and assessed their differences over time in India. Data from a total of 768,130 women and 180,691 men from the Indian National Family Health Survey (NFHS) 2006 and 2016 were used for the analysis. The average association between wealth and education with anthropometry was assessed from linear regression models assuming constant variance. Individual heterogeneity was modeled to obtain separate variances in anthropometry for each wealth quintile and education level. All analyses were stratified by survey year and sex. On average, the positive socioeconomic gradient in adult's BMI and height persisted over time with slight attenuation. The residual variance in BMI ranged from 10.1 to 14.9 (7.2-11.3) by education level and 6.1 to 17.4 (5.0-13.0) by household wealth for women (men) in 2006, and they increased over time for the lower socioeconomic groups but remained the same or decreased for the higher socioeconomic groups. No significant pattern was observed for variation in height for both genders. We found potential reversal in the socioeconomic patterning in BMI variability in India as suggested by the increasing dispersion among the least educated and poorest populations. For a comprehensive understanding of nutrition transition in developing countries, it is necessary to assess the changes in means and variances of anthropometry in tandem.

The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study.

Background and aims: Obesity is a major health problem worldwide. Given the heterogeneous obesity phenotype, an optimal obesity stratification would improve clinical management. Since obesity has a strong genetic component, we aimed to develop a polygenic risk score (PRS) to stratify obesity according to the genetic background of the individuals. Methods: A total of 231 single nucleotide polymorphisms (SNP) significantly associated to body mass index (BMI) from 21 genome-wide association studies were genotyped or imputed in 881 subjects from the Quebec Family Study (QFS). The population was randomly split into discovery (80%; n = 704) and validation (20%; n = 177) samples with similar obesity (BMI ≥ 30) prevalence (27.8% and 28.2%, respectively). Family-based associations with obesity were tested for every SNP in the discovery sample and a weighed and continuous PRS231 was constructed. Generalized linear mixed effects models were used to test the association of PRS231 with obesity in the QFS discovery sample and validated in the QFS replication sample. Furthermore, the Fatty Acid Sensor (FAS) Study (n = 141; 27.7% obesity prevalence) was used as an independent sample to replicate the results. Results: The linear trend test demonstrated a significant association of PRS231 with obesity in the QFS discovery sample (ORtrend = 1.19 [95% CI, 1.14-1.24]; P = 2.0x10-16). We also found that the obesity prevalence was significantly greater in the higher PRS231 quintiles compared to the lowest quintile. Significant and consistent results were obtained in the QFS validation sample for both the linear trend test (ORtrend = 1.16 [95% CI, 1.07-1.26]; P = 6.7x10-4), and obesity prevalence across quintiles. These results were partially replicated in the FAS sample (ORtrend = 1.12 [95% CI, 1.02-1.24]; P = 2.2x10-2). PRS231 explained 7.5%, 3.2%, and 1.2% of BMI variance in QFS discovery, QFS validation, and FAS samples, respectively. Conclusions: These results revealed that genetic background in the form of a 231 BMI-associated PRS has a significant impact on obesity, but a limited potential to accurately stratify it. Further studies are encouraged on larger populations.

Effects of body weight variation in obese kidney recipients: a retrospective cohort study.

BackgroundObese kidney allograft recipients have worse results in kidney transplantation (KT). However, there is lack of information regarding the effect of body mass index (BMI) variation after KT. The objective of the study was to evaluate the effects of body weight changes in obese kidney transplant recipients.MethodsIn this study we used data from the Catalan Renal Registry that included KT recipients from 1990 to 2011 (n = 5607). The annual change in post-transplantation BMI was calculated. The main outcome variables were delayed graft function (DGF), estimated glomerular filtration rate (eGFR) and patient and graft survival.ResultsObesity was observed in 609 patients (10.9%) at the time of transplantation. The incidence of DGF was significantly higher in obese patients (40.4% versus 28.3%; P < 0.001). Baseline obesity was significantly associated with worse short- and long-term graft survival (P < 0.05) and worse graft function during the follow-up (P < 0.005). BMI variations in obese patients did not improve eGFR or graft or patient survival.ConclusionsOur conclusion is that in obese patients, decreasing body weight after KT does not improve either short-term graft outcomes or long-term renal function.

Mindful Eating Practice Predicts Lower Body Mass Index Among University Students

Background and Objective: The hectic life of university students may contribute to mindless eating and eventually may lead to obesity. Previous studies suggested that adopting mindful eating practice has a positive influence on eating habit modification and obesity rate reduction. Hence, this study aimed to assess the role of mindful eating practice and health attitudes in predicting the body mass index (BMI) of university students. Materials and Methods: A cross-sectional study was conducted among 300 university students at the International Islamic University Malaysia (IIUM). Participants’ weight and height were measured and they were required to complete the Mindful Eating Questionnaire (MEQ) and Health Attitude Scale (HAS). Results: The mean body mass index (BMI) of participants was 22.53±4.00 kg mG2 . The highest mean reported for the mindful eating practice subscale is the awareness subscale (mean = 2.7852±0.475). The results showed that a higher MEQ score predicted a lower BMI (p<0.05) and this explained 2% of the variance in BMI. However, BMI was not predicted by health attitudes. Conclusion: The results suggested that the concept of mindfulness has a positive impact on body weight, which could be incorporated into weight loss and weight maintenance intervention programmes.

Examining the distinctiveness of body image concerns in patients with anorexia nervosa and bulimia nervosa.

This study examined the distinctiveness of specific constructs of body-image disturbance in patients with anorexia nervosa (AN) and bulimia nervosa (BN). We compared weight/shape dissatisfaction, weight/shape overvaluation, weight/shape preoccupation, and fear of weight gain in patients with AN and BN and examined how each specific body-image construct relates to clinical measures within and between AN and BN. A clinical sample of 490 treatment-seeking patients diagnosed with DSM-5 AN (N = 310) or BN (N = 180) by clinicians using structured interviews in Portugal completed the Eating Disorder Examination-Questionnaire to assess body image and eating-disorder (ED) psychopathology. Both within and between AN and BN, the four body-image constructs varied in their strengths of association among themselves, with ED psychopathology, and body mass index (BMI). Analyses revealed considerable variability in variance accounted for in clinical measures by body-image constructs. Body-image constructs predicted significant, albeit small, variance in BMI within BN (dissatisfaction, preoccupation significant) but not within AN. Body-image constructs predicted significant, albeit small, variance in the frequencies of binge eating and purging in AN (with preoccupation significant for both and fear for purging) but not within BN. Body-image constructs predicted significant variance in ED psychopathology (large amounts of variance for Eating Concern and Restraint) within both AN and BN (with overvaluation, preoccupation, and fear significant). Clinical manifestations of body-image disturbances are complex and show important differences across AN and BN. Understanding distinctions and differential salience of different body-image constructs across different EDs can inform refinement of specific case conceptualization.

Anthropometric heritability and child growth in a Caribbean village: A quantitative genetic analysis of longitudinal height, weight, and body mass index in Bwa Mawego, Dominica.

Body size and composition vary widely among individuals and populations, and long-term research in diverse contexts informs our understanding of genetic, cultural, and environmental impacts on this variation. We analyze longitudinal measures of height, weight, and body mass index (BMI) from a Caribbean village, estimating the extent to which these anthropometrics are shaped by genetic variance in a small-scale population of mixed ancestry. Longitudinal data from a traditionally horticultural village in Dominica document height and weight in a non-Western population that is transitioning to increasingly Westernized lifestyles, and an 11-generation pedigree enables us to estimate the proportions of phenotypic variation in height, weight, and BMI attributed to genetic variation. We assess within-individual variation across growth curves as well as heritabilities of these traits for 260 individuals using Bayesian variance component estimation. Age, sex, and secular trends account for the majority of anthropometric variation in these longitudinal data. Independent of age, sex, and secular trends, our analyses show high repeatabilities for the remaining variation in height, weight, and BMI growth curves (>0.75), and moderate heritabilities (h2height = 0.68, h2weight = 0.64, h2BMI = 0.49) reveal clear genetic signals that account for large proportions of the variation in body size observed between families. Secular trends show increases of 6.5% in height and 16.0% in weight from 1997 to 2017. This horticultural Caribbean population has transitioned to include more Westernized foods and technologies over the decades captured in this analysis. BMI varies widely between individuals and is significantly shaped by genetic variation, warranting future exploration with other physiological correlates and associated genetic variants.