Body Mass Index Variables Research Articles

Eating behaviors, eating styles and body mass index during COVID-19 confinement in a college sample: a predictive model

BackgroundCOVID-19 confinement affected lifestyles. There is inconclusive evidence about changes in eating patterns, and there are few studies on the impact on body mass index (BMI), the occurrence of dysfunctional behaviors (binge eating, fat intake), and the predictive role of maladaptive eating styles (emotional, external, and restrained eating).Objectives(1) To analyze the differences in binge eating, fat intake, BMI, and maladaptive eating styles before and during COVID-19 confinement, and (2) to analyze whether maladaptive eating styles (before confinement) predicted binge eating, fat intake, and BMI during confinement.MethodsThe sample consisted of 146 Spanish college students, divided into 104 females (71.2%; age: M = 22.20, SD = 2.97) and 42 males (28.8%; age: M = 24.74; SD = 3.53). All completed several dietary measures and BMI twice: before COVID-19 confinement (T1, November 2019) and during COVID-19 confinement (T2, April 2020).ResultsBMI and maladaptive eating styles did not change in T2 (vs. T1). However, binge eating and fat intake decreased in T2. Emotional eating at T1 positively predicted BMI and binge eating at T2. External eating at T1 positively (and marginally) predicted fat intake at T2. Restrained eating at T1 positively predicted binge eating at T2, and negatively (and marginally) predicted BMI and fat intake at T2. The model explained 80.5% of the variance in BMI, 41.5% of the variance in binge eating, and 25.8% of the variance in fat intake during COVID-19 confinement.ConclusionsThe COVID-19 confinement had a positive impact on some eating behaviors. Future policies should focus part of their prevention on maladaptive eating styles to curb dysfunctional eating behaviors and BMI problems in times of stress.

Regional variation in lifestyle patterns and BMI in young children: the GECKO Drenthe cohort

BackgroundA better understanding of lifestyle behaviours of children < 7 years and the relation with childhood overweight is needed. The aim of our prospective study was to examine how lifestyle patterns in young children are associated with the development of childhood overweight. As ecological models suggest focusing on not only the child as an individual, but also their environment, we also considered the role of socio-economic status (SES) and spatial clustering of lifestyle and body mass index (BMI).MethodsIn 1792 children (aged 3–6 years) participating in the GECKO Drenthe cohort, diet, screen time, outdoor play and sleep were assessed by questionnaires and moderate-to-vigorous physical activity and sedentary time by accelerometry (Actigraph GT3X). At 10–11 years, height and weight were measured to calculate age- and sex-specific standardized BMI z-scores (zBMI). Lifestyle patterns were identified using principal component analysis. To assess spatial clustering for the lifestyle patterns and zBMI, we calculated the Global Moran’s I statistic. Linear- and logistic regression models, taking into account SES, were performed to examine the association between the lifestyle patterns and the development of overweight. For the spatial analyses, we added spatial terms for the determinants, the outcome, and the error term.ResultsThree lifestyle patterns were identified: (1) ‘high activity’, (2) ‘low screen time, high sleep and healthy diet’, and (3) ‘high outdoor play’. No associations were observed between the ‘high activity’ or ‘high outdoor play’ patterns at young age with the development of childhood overweight (all p > 0.05). In contrast, children who adhered to the ‘low screen time, high sleep and healthy diet’ pattern had lower odds to become overweight and a lower zBMI at 10–11 years (odds ratio [95% CI] = 0.766 [0.65; 0.90]). These findings remained similar after taking SES into account. Regarding the spatial analyses, we found spatial clustering of zBMI, but no spatial clustering of the lifestyle patterns.ConclusionsLow screen time, high sleep duration and a healthy diet cluster into a pattern that seems favourable in the prevention of childhood overweight, independent of individual SES. The spatial analyses suggest that there are likely other neighbourhood factors that contribute to the spatial clustering of childhood overweight.

Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?

ABSTRACT Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene–environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10−14), ~0.6% (P = 2 × 10−7), and ~8.7% (P = 7 × 10−87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P < 0.05) were found at 61, 14, and 7 CpGs for smoking, alcohol consumption, and BMI, respectively. There was strong evidence that all lifestyle-related phenotypes were positively associated with PhenoAge and GrimAge, except for alcohol consumption with PhenoAge. There was weak evidence that the association of smoking with GrimAge was attenuated in participants genetically predisposed to smoking (interaction term: −0.022, standard error [SE] = 0.012, P = 0.058) and that the association of alcohol consumption with PhenoAge was attenuated in those genetically predisposed to drink alcohol (interaction term: −0.030, SE = 0.015, P = 0.041). In conclusion, genetic susceptibility to unhealthy lifestyles did not strongly modify the association between observed lifestyle behaviour and blood DNA methylation. Potential associations were observed for epigenetic ageing measures, which should be replicated in additional studies.

Different Variation of Intra-familial Body Mass Index subjected to Covid-19 Lockdown

Background and Aims: Coronavirus disease 2019 (COVID-19) lockdown has represented an inedited model of increased metabolic risk in all age groups, due to negative changes in dietary habits, physical activity, lifestyle. These effects have been generally explored at a population level in distinct age groups. Potential intra-familial, specific effects in adults and children sharing the same socio-economic, cultural level and living habits have been scarcely explored. We aimed to characterize changes of anthropometric indices in parents and in their children during COVID-19 lockdown.&#x0D; Methods: A cohort of 149 couple parent/children were prospectively enrolled. By a validated questionnaire we explored changes of body mass index (BMI) and individual lifestyle during a 2-month lockdown (May- July 2020).&#x0D; Results: BMI increased in 70.5% of parents and in 67.8% of their children, with a Δ-BMI of 1.44+0.09 kg/ m 2 and 0.36+0.02 Kg/m 2 , respectively. BMI increments, however, were only significant in adults and did not correlate in the couple parents/children. Most adults (80.5%) and children (71.4%) did not perform regular physical activity during the lockdown. Direct correlations between dietary changes and BMI variations became evident in children, mainly in terms of a decreased consumption of fresh fruit, pulses, fish, and an increased consumption of cereals, carbohydrates, dairy products, olive oil. In normal weight, overweight and obese children, but not in adults, the increase in sleep hours increased with BMI.&#x0D; Conclusions: Despite marked lifestyle changes imposed by the COVID-19 lockdown, BMI variations in parents were independent from those observed in their children, pointing to different outcomes in response to the same external, critical event. Thus, primary prevention measures aimed at maintaining a healthy lifestyle require different approaches according to age.

Association of Genome-Wide Polygenic Risk Score for Body Mass Index With Cardiometabolic Health From Childhood Through Midlife.

Genetic information may help to identify individuals in childhood who are at increased risk for cardiometabolic disease. We included 1201 BHS (Bogalusa Heart Study) participants (832 White participants and 369 Black participants) who were followed up to 42.3 years, starting at a mean age of 9.8 years. A validated genome-wide polygenic risk score (PRS) was tested for association with midlife body mass index (BMI), fasting plasma glucose, and systolic blood pressure using multiple linear regression models. Cox proportional hazards models tested associations of the PRS with incident obesity, diabetes, and hypertension. All analyses were conducted according to race and adjusted for baseline age, sex, ancestry, and BMI. The constructed PRS was significantly and modestly correlated with midlife BMI in both White and Black participants, with correlation coefficients of 0.27 (P=1.94×10-8) and 0.16 (P=5.50×10-3), respectively. In White participants, per SD increase of PRS was associated with an average 1.29 kg/m2 higher BMI (P=4.44×10-9), 2.82 mg/dL higher fasting plasma glucose (P=1.17×10-3), and 1.09 mm Hg higher systolic blood pressure (P=3.57×10-2) at midlife. The PRS also conferred a 26% higher increased risk of obesity (P=3.50×10-6) in White participants. In addition, the variance in midlife BMI explained increased from 0.1973 to 0.2293 when PRS was added to the model including age, sex, principal components, and baseline BMI (P<0.0001). No associations were observed in Black participants. Adiposity-related genetic information independently predicted cardiometabolic health in White BHS participants. Null associations observed in Black BHS participants highlight the urgent need for PRS development in multi-ancestry populations.

Trends and Disparities in Adult Body Mass Index Across the 47 Prefectures of Japan, 1975-2018: A Bayesian Spatiotemporal Analysis of National Household Surveys.

BackgroundAmong high-income countries, Japan has a low prevalence of obesity, but little is understood about subnational trends and variations in body mass index (BMI), largely owing to the lack of data from representative samples of prefectures. We aimed to examine long-term trends and distributions of adult BMI at the prefecture level in Japan from the late 1970s using a spatiotemporal model.MethodsWe obtained cross-sectional data for 233,988 men and 261,086 women aged 20–79 years from the 44 annual National Health and Nutrition Surveys (NHNS) conducted during 1975–2018. We applied a Bayesian spatiotemporal model to estimate the annual time series of age-standardized and age-specific mean BMI by 20-year age group and sex for each of the 47 prefectures. We assessed socioeconomic inequalities in BMI across prefectures using the concentration index, according to population density.ResultsIn men, the age-standardized prefectural mean BMI ranged from 21.7 kg/m2 (95% credible interval, 21.6–21.9) to 23.1 kg/m2 (22.9–23.4) in 1975 and from 23.5 kg/m2 (23.3–23.7) to 24.8 kg/m2 (24.6–25.1) in 2018. In women, the age-standardized prefectural mean BMI ranged from 22.0 kg/m2 (21.9–22.2) to 23.4 kg/m2 (23.2–23.6) in 1975 and from 21.7 kg/m2 (21.6–22.0) to 23.5 kg/m2 (23.2–23.8) in 2018. Mean BMI was highest in the southernmost prefecture for most of the study period, followed by northeast prefectures. The increase in mean BMI was largest in southwest prefectures, which caught up with northeast prefectures over time. The concentration index was negative, indicating higher BMI in less-populated prefectures. Absolute values of the concentration index were greater in women than in men and increased over time.ConclusionsThere were variations in adult mean BMI across prefectures, and geographic distributions changed over time. Further national and local efforts are needed to address the rising trend in mean BMI, particularly among men in rural prefectures, and socioeconomic inequalities among women. Bayesian hierarchical modeling is useful for reconstructing long-term spatiotemporal trends of mean BMI by integrating small-sized survey samples at the prefecture level in the NHNS.

Can adult polygenic scores improve prediction of body mass index in childhood?

Modelling genetic pre-disposition may identify children at risk of obesity. However, most polygenic scores (PGSs) have been derived in adults, and lack validation during childhood. This study compared the utility of existing large-scale adult-derived PGSs to predict common anthropometric traits (body mass index (BMI), waist circumference, and body fat) in children and adults, and examined whether childhood BMI prediction could be improved by combining PGSs and non-genetic factors (maternal and earlier child BMI). Participants (n = 1365 children, and n = 2094 adults made up of their parents) were drawn from the Longitudinal Study of Australian Children. Children were weighed and measured every two years from 0-1 to 12-13 years, and adults were measured or self-reported measurements were obtained concurrently (average analysed). Participants were genotyped from blood or oral samples, and PGSs were derived based on published genome-wide association studies. We used linear regression to compare the relative utility of these PGSs to predict their respective traits at different ages. BMI PGSs explained up to 12% of child BMI z-score variance in 10-13 year olds, compared with up to 15% in adults. PGSs for waist circumference and body fat explained less variance (up to 8%). An interaction between BMI PGSs and puberty (p = 0.001-0.002) suggests the effect of some variants may differ across the life course. Individual BMI measures across childhood predicted 10-60% of the variance in BMI at 12-13 years, and maternal BMI and BMI PGS each added 1-9% above this. Adult-derived PGSs for BMI, particularly those derived by modelling between-variant interactions, may be useful for predicting BMI during adolescence with similar accuracy to that obtained in adulthood. The level of precision presented here to predict BMI during childhood may be relevant to public health, but is likely to be less useful for individual clinical purposes.

P431. The Relation Between Genetic Risk for Greater Body Mass Index (BMI) and BMIz in Children is Mediated by Reward Processing in the Rostral Anterior Cingulate

It has become increasingly clear that higher body mass index (BMI) is associated with altered cortical development. Although variation in BMI is strongly influenced by genetic factors, it is unknown whether cortical differences associated with BMI have a genetic origin. It is also unknown whether BMI affects cortical development or the opposite (differences in cortical development lead to greater BMI).

Comparative Study on Serum Hepatic Enzymes between Normal Healthy Adults and Obese People of Rajshahi City

Background &amp; objective: Obesity is rapidly emerging as one of the major causes of non-alcoholic fatty liver disease (NAFLD), the early sign of which is elevated liver enzymes. But very few studies have yet been done in our country to find the association between overweight and obesity and levels of serum hepatic enzymes. The present study was undertaken to determine the association between overweight/obesity determined by body mass index (BMI) and serum hepatic enzymes.&#x0D; Methods: This cross-sectional analytical study was conducted in the Department of Physiology, Rajshahi Medical College, Rajshahi over a period of one year between July 2018 to June 2019 in collaboration with the Department of Biochemistry of the same Medical College. Based on certain predefined enrolment criteria, 33 overweight or obese (BMI ≥23 kg/m2) individuals (case) and 33 sex-matched apparently healthy adults (BMI &lt;23 kg/m2) (control) were included from the Rajshahi City. All the study subjects were then tested for serum hepatic enzymes (ALT, AST, ALP and GGT). The investigation findings obtained were compared between case and control groups.&#x0D; Result: The mean ages of the cases and controls were almost similar (31.1 and 29.4 years respectively, p = 0.576).All the serum hepatic enzymes but GGT were found to be significantly raised in the case group than those in the control group. The BMI was found to bear significantly linear relationship with serum ALT, AST and ALP (r = 0.709, p &lt; 0.001, r = 0.718, p &lt; 0.001 and r = 0.545, p &lt; 0.001 respectively) indicating that more than 70% of the variations in ALT and AST and 55% of the variations in ALP might be due to variation in BMI. When waist circumference was correlated with hepatic enzymes, it was found to correlate better than the BMI did with 70.3% of the variations in ALT, 77.2% of variations in AST and 57.4% variation in ALP being explained by waist circumference. However, WHR did not correlate well with hepatic enzymes. AST alone bears a weekly significant correlation with WHR, with only 28% of the variations in AST could be explained by WHR.&#x0D; Conclusion: The study concluded that all the serum hepatic enzymes but GGT are significantly raised in the overweight and obese individuals than those in individuals with normal BMI. The BMI bears significantly linear relationships with serum ALT, AST and ALP. A substantial proportion of the variations in ALT and AST could be explained by BMI. Waist circumference correlates even better than the BMI does. However, WHR is not a good predictor of serum hepatic enzymes.&#x0D; Ibrahim Card Med J 2021; 11 (1): 62-70

Evaluation of the bone mineral density in the Mexican female population using the Radiofrequency Echographic Multi Spectrometry (REMS) technology.

Assessment of the bone health status in an average female Mexican population with REMS. The secondary objective investigated age- and body mass index (BMI)-related effects on the diagnostic classification and the influence of risk factors for osteoporosis. Women aged over 40years underwent a REMS scan at the lumbar spine and both femoral necks. The degree of correlation of the bone mineral density (BMD) across axial sites was assessed by the Pearson correlation coefficient (r), along with the diagnostic discordance. The association between risk factors, age, and BMI and diagnostic classification was determined by the chi-squared test. Four hundred seventy-one women were enrolled. Osteoporosis was diagnosed in 11.0%, 8.1%, and 8.3% of cases at the lumbar spine and right and left femoral neck, respectively. The diagnostic agreement between the lumbar spine and femoral necks was about 73% (85% considering a 0.3T-score tolerance), whereas the agreement between the femoral necks was 97.4% (99.6% considering a 0.3T-score tolerance). Most of discordant cases were minor discordances. The correlation between the lumbar spine and femoral neck was r = 0.82 and 0.85, respectively, whereas both femoral necks correlated with r = 0.97. As expected, the prevalence of osteoporosis increased with age and decreased as BMI increased. The widespread applicability of the non-ionizing REMS technology has been demonstrated in a representative Mexican cohort, covering wide age and BMI ranges. Age and BMI variations correlate with the prevalence of osteoporosis, in line with the recent scientific literature.

Vigorous physical activity: A potential ally in adolescent obesity management

ABSTRACT Individual variability may contribute to the modest and inconsistent results reported in obesity-management interventions. This study aimed to investigate the impact of non-modifiable as well as modifiable factors on body mass index (BMI) and body fat variance in adolescents with obesity followed in a clinical obesity-management programme, in order to better understand individual variability. Non-modifiable factors (i.e. socio-economic status, pregnancy BMI, weight progression across pregnancy, BMI at time of delivery, way of delivery, birth weight, breastfeeding duration, age at overweight onset, overweight duration, and FTO rs9939609 polymorphism) and modifiable factors data (i.e. self-determination level, self-efficacy and perception of importance to lose weight, energy intake, physical activity, and sedentary behaviours) from 63 adolescents (93.7% Caucasian, 55.6% girls), with a median age of 15.0 (2.5) years, and a median BMI z-score of 2.88 (0.70), followed for 6 months were analyzed. BMI z-score variance was predicted by vigorous physical activity (VPA) (F(1,57) = 4.55, p = .039), overweight duration (F(1,59) = 5.61, p = .022), way of delivery (F(2,58) = 6.55, p = .003) and self-determination level (F(1,59) = 4.75, p = .034). VPA further predicted body fat mass (%) (F(1,57) = 9.99, p = .003) as well as trunk fat mass variance (F(1,57) = 8.94, p = .006). This study suggests that although both non-modifiable and modifiable factors influence BMI and body fat variance to some extent, in adolescents with obesity, VPA (modifiable factor) stands out as the factor with the best association with both outcomes. VPA may be a potential ally in the success of clinical obesity management in adolescents, and so should be emphasised in this population. Highlights There is a huge individual variability within studies in response to adolescent obesity-management interventions. Both non-modifiable and modifiable factors may influence body mass index (BMI) and body fat variance, influencing interventions’ outcomes. The predictive value of both non-modifiable and modifiable factors largely overlaps, making lighter the burden of the former and highlighting the value of lifestyle changes. Among modifiable factors, vigorous physical activity standouts as the factor with the best (negative) association with BMI and body fat variance.

The association between sexual orientation, BMI, obesity diagnosis, and provider recommendation for weight management

BackgroundNational data show that lesbian and bisexual women are more likely to be obese compared to straight women. However little is known about whether provider recommendation for weight management varies across these populations. Furthermore, health care providers have explicit and implicit preferences for straight people in comparison to lesbian or gay people. There is little research that exists depicting how this preference affects quality of patient care. The purpose of the study is: to compare, among lesbian, bisexual, and straight females with BMIs ≥ 30: (1) the average Body Mass Index (BMI); (2) receipt of a diagnostic code for obesity; and (3) receipt of a provider recommendation for weight management.MethodsWe performed a cross-sectional study of 534 patient records from four outpatient academic internal medicine practices at the University of Pennsylvania between January 1, 2019 to December 31, 2019 to determine variations in average BMI, proportion of International Classification of Diseases (ICD)-10 codes for obesity, and proportion of weight management recommendations offered by providers among lesbian, bisexual and straight females with BMIs ≥ 30. We classified provider recommendations as definite, possible, and absent. Multivariable median (BMI outcome only) or logistic regression was used to evaluate the associations between sexual orientation and each of the following outcomes: BMI, receipt of obesity diagnosis, and weight management recommendations.ResultsThere were no significant differences in BMI, receipt of obesity diagnoses, or weight management recommendations between lesbian, bisexual, and straight females with BMIs ≥ 30. However, only about half the patients with BMIs ≥ 30, regardless of sexual orientation, received a weight management recommendation as recommended by the United States Preventive Services Task Force (USPSTF) guidelines.ConclusionWe did not observe disparities in BMI, receipt of obesity diagnoses, or receipt of weight management recommendations between sexual orientation minority and heterosexual females among this sample from an urban population of patients receiving care in a university medical system. However, provider recommendation for weight management was suboptimal in all the groups.

Findings from the Hispanic Community Health Study/Study of Latinos on the Importance of Sociocultural Environmental Interactors: Polygenic Risk Score-by-Immigration and Dietary Interactions.

Introduction: Hispanic/Latinos experience a disproportionate burden of obesity. Acculturation to US obesogenic diet and practices may lead to an exacerbation of innate genetic susceptibility. We examined the role of gene–environment interactions to better characterize the sociocultural environmental determinants and their genome-scale interactions, which may contribute to missing heritability of obesity. We utilized polygenic risk scores (PRSs) for body mass index (BMI) to perform analyses of PRS-by-acculturation and other environmental interactors among self-identified Hispanic/Latino adults from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Methods: PRSs were derived using genome-wide association study (GWAS) weights from a publicly available, large meta-analysis of European ancestry samples. Generalized linear models were run using a set of a priori acculturation-related and environmental factors measured at visit 1 (2008–2011) and visit 2 (2014–2016) in an analytic subsample of 8,109 unrelated individuals with genotypic, phenotypic, and complete case data at both visits. We evaluated continuous measures of BMI and waist-to-hip ratio. All models were weighted for complex sampling design, combined, and sex-stratified. Results: Overall, we observed a consistent increase of BMI with greater PRS across both visits. We found the best-fitting model adjusted for top five principal components of ancestry, sex, age, study site, Hispanic/Latino background genetic ancestry group, sociocultural factors and PRS interactions with age at immigration, years since first arrival to the United States (p < 0.0104), and healthy diet (p < 0.0036) and explained 16% of the variation in BMI. For every 1-SD increase in PRS, there was a corresponding 1.10 kg/m2 increase in BMI (p < 0.001). When these results were stratified by sex, we observed that this 1-SD effect of PRS on BMI was greater for women than men (1.45 vs. 0.79 kg/m2, p < 0.001). Discussion: We observe that age at immigration and the adoption of certain dietary patterns may play a significant role in modifying the effect of genetic risk on obesity. Careful consideration of sociocultural and immigration-related factors should be evaluated. The role of nongenetic factors, including the social environment, should not be overlooked when describing the performance of PRS or for promoting population health in understudied populations in genomics.

Modeling Interaction and Dispersion Effects in the Analysis of Gene-by-Environment Interaction.

Genotype-by-environment interaction (GxE) studies probe heterogeneity in response to risk factors or interventions. Popular methods for estimation of GxE examine multiplicative interactions between individual genetic and environmental measures. However, risk factors and interventions may modulate the total variance of an epidemiological outcome that itself represents the aggregation of many other etiological components. We expand the traditional GxE model to directly model genetic and environmental moderation of the dispersion of the outcome. We derive a test statistic, [Formula: see text], for inferring whether an interaction identified between individual genetic and environmental measures represents a more general pattern of moderation of the total variance in the phenotype by either the genetic or the environmental measure. We validate our method via extensive simulation, and apply it to investigate genotype-by-birth year interactions for Body Mass Index (BMI) with polygenic scores in the Health and Retirement Study (N = 11,586) and individual genetic variants in the UK Biobank (N = 380,605). We find that changes in the penetrance of a genome-wide polygenic score for BMI across birth year are partly representative of a more general pattern of expanding BMI variation across generations. Three individual variants found to be more strongly associated with BMI among later born individuals, were also associated with the magnitude of variability in BMI itself within any given birth year, suggesting that they may confer general sensitivity of BMI to a range of unmeasured factors beyond those captured by birth year. We introduce an expanded GxE regression model that explicitly models genetic and environmental moderation of the dispersion of the outcome under study. This approach can determine whether GxE interactions identified are specific to the measured predictors or represent a more general pattern of moderation of the total variance in the outcome by the genetic and environmental measures.

Low-frequency Coding Variants Associated With Body Mass Index Affect the Success of Bariatric Surgery.

A recent study identified 14 low-frequency coding variants associated with body mass index (BMI) in 718 734 individuals predominantly of European ancestry. We investigated the association of 2 genetic scores (GS) with i) the risk of severe/morbid obesity, ii) BMI variation before weight-loss intervention, iii) BMI change in response to an 18-month lifestyle/behavioral intervention program, and iv) BMI change up to 24 months after bariatric surgery. The 14 low-frequency coding variants were genotyped or sequenced in 342 French adults with severe/morbid obesity and 574 French adult controls from the general population. We built risk and protective GS based on 6 BMI-increasing and 5 BMI-decreasing low-frequency coding variants that were polymorphic in our study. While the risk GS was not associated with severe/morbid obesity status, BMI-decreasing low-frequency coding variants were significantly less frequent in patients with severe/morbid obesity than in French adults from the general population. Neither the risk nor the protective GS was associated with BMI before intervention in patients with severe/morbid obesity, nor did they affect BMI change in response to a lifestyle/behavioral modification program. The protective GS was associated with a greater BMI decrease following bariatric surgery. The risk and protective GS were associated with a higher and lower risk of BMI regain after bariatric surgery. Our data indicate that in populations of European descent, low-frequency coding variants associated with BMI in the general population also affect the outcomes of bariatric surgery in patients with severe/morbid obesity.

Variables Affecting Opening Intra-Abdominal Pressure in Laparoscopic Surgery

<h3>Study Objective</h3> To evaluate the correlation between patient characteristics and opening pressures noted during laparoscopy. <h3>Design</h3> Retrospective observational study. <h3>Setting</h3> The operating room of a single institution; standardized laparoscopic closed-entry technique performed. <h3>Patients or Participants</h3> All patients who underwent laparoscopy for gynecologic indications between January 1, 2020, and December 31, 2020, were eligible. Exclusion criteria included: unknown opening pressure, unavailable demographic information or unsuccessful intra-abdominal entry via closed-entry technique. 210 patients were included in the final analysis. <h3>Interventions</h3> N/A. <h3>Measurements and Main Results</h3> Patient demographics including: Parity, age, race, mode of previous deliveries, previous abdominal surgeries, and body mass index (BMI) were collected; and the opening pressure was recorded intraoperatively. Linear regression was performed to assess the contribution of age, parity, previous surgeries and BMI on the opening pressure. Data analysis showed average opening pressure of 3.64 mmHg. The data showed a positive correlation between obesity and opening pressure (correlation coefficient 0.27, p <0.001). The data also showed a negative correlation between patient age and opening pressure (correlation coefficient 0.14, p 0.04). Neither variation in parity nor number of previous surgeries explained the variation in opening pressure (p > 0.05). By contrast, variation in BMI explained 7.1% of the observed variation in opening pressure (p < 0.001), and variation in age explained 1.9% of the observed variation in opening pressure (p 0.04). <h3>Conclusion</h3> Current teaching in laparoscopy is that an opening pressure ≤10 mmHg reliably predicts successful intraperitoneal entry. However, there is little published data on which demographic characteristics affect opening pressure, and no study has evaluated several characteristics simultaneously while directly comparing them to data collected within the operating room. Based on the outcome of this study, surgeons can expect an average opening pressure of 3.64 mmHg and should expect an increase in this value with elevated patient BMI, and a decrease with increasing patient age.

Impact of COVID-19 Pandemic and Lockdown Measures on the Nutrition Plan Service Cohort

Objective: This study analyses the patients' factors can influence the attitude to follow or not the therapeutic weight-loss plan after national lockdown measures adopted from March 2020 to May 2020. Materials and Methods: Patients that visited a private nutritional center in March 2020 were included in this retrospective observational study. All relevant characteristics were noted. In May 2020, patients who did not attend the follow-up visit were labeled as "abandoned". Variation in Body Mass Index (BMI) was noted in the second visit. Univariate logistic regression was performed to test the influence on dependent variables (lost follow-up). Odds Ratio (OR) was calculated. According to BMI distribution, we performed a Student T-test (α= 0.05) or Wilcoxon test (α= 0.05) to test BMI variation in patients that attended the follow-up visit. A P-value&lt; 0.05 was considered statistically significant. Results: Our population consisted of 77 patients, and 26 patients (33.8%, CI95% 23.4-45.4%) were labelled as "abandoned". Age≥ 54 years old (OR= 8.9048, CI95%:1.888-41.9822, P-value= 0.0057) and suffering from hypertension (OR= 4.8706, CI95%:1.4284-16.6076, Pvalue= 0.0114) were factors associated with the abandon follow-up visits. Wilcoxon test for BMI variation resulted statistically significant (May BMI 29.5 kg/m2 vs March BMI 29.4 kg/m2 , Pvalue= 0.0094). Conclusion: Age and hypertension are related to the risk of abandoning healthcare services after ending the national lockdown. The losing follow-up phenomenon could worsen clinical conditions and reduce life expectancy. An increase in BMI during lockdown should be interpreted as a personal difficulty in complying with therapeutic prescriptions.

Association between Variations in Body Mass Index and Cognitive Function in Older Korean Adults.

BackgroundAlthough several studies have assessed obesity and cognitive impairment, most of these studies focus on body mass index (BMI) and cognitive impairment. Therefore to better understand the importance of weight maintenance with aging, this study investigated the relationship between variations in weight and cognitive impairment using the Korean version of the Mini-Mental State Examination (K-MMSE) in individuals aged 45 years or older in Korea.MethodsData on 3,477 adults with normal cognitive function (K-MMSE ≥24) at baseline were acquired from the Korean Longitudinal Study of Aging (KLoSA) 2006-2016. The association between weight variability and risk of cognitive impairment was assessed using multiple logistic regression models. We also assessed weight variability and change in cognitive function over the 6-year follow-up using multiple linear regression.ResultsOverall, higher variations in BMI were associated with cognitive impairment. Patients in the quintile with the highest variation (Q5) in BMI (mean of BMI changes, 2.69) showed the greatest degree of cognitive impairments (adjusted odds ratio, 1.52; 95% confidence interval [CI], 1.08-2.14; P for trend=0.016). Furthermore, a higher frequency in the number of times (3 times) the patient’s body weight changed was associated with a lower cognitive function (adjusted odds ratio, 3.42; 95% CI, 1.67-7.03; P for trend<0.001).ConclusionIn this nationally representative study, weight variability was associated with a higher risk of cognitive decline during mid- and late-life stages.

Association of Obesity With Lower Rates of Remission in a Colombian Cohort of Patients With Rheumatoid Arthritis.

Modifiable risk factors associated with the severity of rheumatoid arthritis have been studied, including the body mass index (BMI). The aim was to compare the evolution of disease activity during 24 months of follow-up in different initial BMI groups of patients with rheumatoid arthritis. Patients were classified based on their initial BMI (normal weight, overweight, and obese). Data were collected during 24 months of follow-up. At 24 months, they were reclassified based on their BMI. The proportion of patients in each BMI category was calculated. The mean differences between the initial and final DAS-28 (Disease Activity Score 28) were calculated using the Kruskal-Wallis test. Results were stratified based on sex and age. Survival analysis and Mantel-Cox test for the achievement of sustained remission during follow-up were calculated. A total of 269 patients were included. Most patients were at the normal weight category (n = 111). Normal weight group had the highest initial score (DAS-28, 4.01). Women present higher variability in BMI and greater disease activity compared with men. Based on age group, patients between the ages 31 and 50 years are more stable in their BMI, whereas those older than 50 years had lower BMI with time. Sustained remission was achieved by 58% of patients from the normal weight group, by 57% of patients from the overweight group, and by 42% of patients from the obese group. Survival curves of the initial normal and obese groups were significantly different (p = 0.0209). Patients with initial obesity were less likely to achieve remission compared with patients with initial overweight or normal weight. Sex and age affects disease activity and BMI variation.

Multivariate Analysis of Blood Pressure and Body Mass Index (BMI) for the Aged in Calabar South: The Counselors Intervention Strategy on Awareness Creation on Stress Related Disorder

Multivariate analytical study was carried out for the blood pressure (BP) indicators and body mass indices (BMI) for the aged in Calabar South Local Government area of Cross River State, Nigeria using the systolic, diastolic and pulse rate and for weight over the square of heights as indices for stress related disorders. The research focuses on multivariate analysis using principal component analysis, factor analysis, Cronbach’s alpha statistics, biplot analysis, matrix plot, linear trend model and Turkey’s multiple comparative statistics between age, blood pressure and body mass index among the aged of 60 – 90 years. The study evaluated one hundred and twenty aged people separated into six groups based on age. Appropriate equipment and tools were used to measure the systolic and diastolic blood pressures and pulse rates. The body mass index was determined using weight over square of height (kg/m2). The data generated was analyzed using multivariate statistical analysis of Minitab v17 statistical software. The results revealed that all six age brackets evaluated for the aged showed 66- 70 and 81 -85 yrs showed pre –obese conditions while the other four age brackets showed obese class 1 hypertension respectively. The results further showed that five principal components accounted for 100 percent of total variations in BMI and BP for the aged in the study area with principal component one (PC1) with eigen value of 0.398 contributing 56.90% to the observed total variation. The principal loading variable for this component was obtained from pulse rate (0.470). A trend linear model of Yt = 23.94 + 1.233 x t was obtained for the trend analysis indicating the high dependence of the BMI and BP (Y) on age (t). The results of Cronbach’s alpha statistics revealed a high level of low precision and high standard errors among all variables evaluated showing less than 70 percent. The Turkey’s multiple comparative analysis revealed high level of inconsistency among the variables as we compared one variable to another. The counselor’s intervention strategy focuses on the creation of awareness on the need for a regular and routine blood pressure check - up for the aged, the need to create awareness on the potential risk factors that predisposes aged to increased blood pressure and pulse rates, the need for urgent guidance and counseling program for the aged on the dangers of drug abuse, smoking and poor dieting and the need for government safety nets intervention program for the aged to reduce increasing stress related disorders which is highly prevalence among the aged in the area.