Body Mass Index Variables Research Articles

Predictors of Treatment Outcome in Persons With Anorexia Nervosa: On the Practice of Regressing Body Mass Index at the End of Treatment on Body Mass Index at Baseline.

It is often stated that a higher body mass index (BMI) at the beginning of treatment predicts a better weight outcome at the end of treatment in persons with anorexia nervosa (AN). However, this interpretation is based on the between-persons relationship of BMI at the two measurements, which primarily reflects the fact that the rank-ordering of persons according to their BMI is quite stable over time. In contrast, a lower BMI at baseline is related to a larger BMI change, which primarily reflects the fact that the variance of BMI at the end of treatment is larger than that at baseline. This study aimed to demonstrate these relationships empirically and caution against interpreting BMI at baseline as a predictor of BMI at discharge or BMI change. Changes of BMI from admission to discharge were analyzed based on 4863 persons with AN (97% female) who received inpatient treatment between 2015 and 2024. BMI at admission was positively related to BMI at discharge (r = 0.55) but negatively related to BMI change from admission to discharge (r = -0.39). While it is true that a higher BMI at baseline is associated with a higher BMI at the end of treatment, a lower BMI at baseline is actually related to a larger weight gain during treatment. Yet, concluding that the treatment is more effective for patients with low or high BMI at baseline would be incorrect in either case, as the independent and dependent variables are the same variables measured at different time points.

THE RELATIONSHIP BETWEEN BODY MASS INDEX AND ORTHOSTATIC HYPOTENSION AMONG ADULTS

Background: Orthostatic hypotension (OH) is a condition characterized by a significant drop in blood pressure upon standing, potentially leading to dizziness and falls. Body Mass Index (BMI) has been identified as a potential risk factor for OH, yet the relationship remains underexplored, particularly in specific populations. Objective: This study investigates the association between BMI and the prevalence of OH among adults in Ndola City, Copperbelt Province, Zambia, while also examining the influence of gender on this relationship. Methods: A descriptive cross-sectional study was conducted involving adults aged 16 to 60 years, selected through simple random sampling from local health centers. Data on BMI, blood pressure measurements, and demographic information were collected. Chi-square tests were employed to assess associations between BMI and OH, as well as between gender and OH. Results: The analysis revealed a statistically significant association between BMI and the occurrence of OH (Pearson Chi-Square: 63.8815, p < 0.001). In contrast, no significant association was found between gender and OH (Pearson Chi-Square: 1.8646, p = 0.172). These findings suggest that variations in BMI are related to the prevalence of OH among adults in Ndola City, while gender differences appear to have minimal impact. Conclusion: The study highlights the importance of monitoring BMI as a potential risk factor for orthostatic hypotension in adults. While gender does not significantly influence the occurrence of OH, further research is warranted to explore additional contributing factors and develop targeted interventions for the local population. These insights can inform public health strategies aimed at managing OH related to BMI.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0798/a.php" alt="Hit counter" /></p>

Retinol intake and PCOS management: a plasma metabolite and protein analysis via Mendelian randomization and NHANES 2011-2016.

Polycystic Ovary Syndrome (PCOS) represents a complex endocrine disorder characterized by a significant interplay with metabolic dysfunction and obesity. This research endeavors to elucidate the causal dynamics among plasma metabolites, proteins, and PCOS, alongside Body Mass Index (BMI), to pinpoint prospective therapeutic interventions. This investigation employed Mendelian randomization (MR) analyses combined with data derived from the National Health and Nutrition Examination Survey (NHANES) to explore the relationships between 1,400 plasma metabolites and PCOS, factoring in BMI adjustments. Additionally, the study examined the influence of plasma proteins and performed a retrospective cross-sectional analysis focusing on retinol consumption and testosterone levels. MR analyses showed metabolite Glycosyl-N-(2-hydroxynervonoyl)-sphingosine (GNS) and protein Keratin 19 (KRT19) were identified as significant markers in the context of PCOS and BMI adjustments. A Phenome-Wide Association Study (PheWAS) underscored the linkage between KRT19 and BMI, while gene-drug interaction findings demonstrated a connection between KRT19 and retinol. Analysis for NHANES data disclosed a negative correlation between retinol intake and testosterone levels, particularly within normal weight and obese cohorts, suggesting the feasibility of dietary interventions for PCOS management. The study sheds light on the intricate interactions between plasma metabolites, proteins, and PCOS, considering BMI variations, and highlights KRT19 protein as a promising therapeutic target. The outcomes support the integration of retinol consumption into dietary strategies to regulate testosterone levels and potentially alleviate PCOS symptoms, underscoring the necessity for personalized nutritional and therapeutic approaches in the effective management of PCOS.

Sedentary Behavior and Ultra-Processed Food Consumption Associated to BMI Changes in Brazilian Students During COVID-19.

University students experienced significant changes in their routines with the implementation of remote learning during Covid-19 pandemic, including increase in sedentary behavior (SB) time and ultra-processed foods (UPF's) consumption, which may have influenced changes in body mass index (BMI). To evaluate the association between the variation in SB time and UPF's consumption with the variation in BMI, before and during the pandemic, in university students. This is a cross-sectional study, conducted between November 2020 and February 2021, with students from a public university of Southeast of Brazil, who answered an online questionnaire with questions regarding to the period before and during the pandemic. SB was assessed through questions about time spent on TV and electronic devices. A score of the frequency of UPF's consumption was estimated based on the Brazilian Food Guide. Self-reported information on height and body mass was used to calculate BMI. The sample comprised 3390 university students, with an average age of 28.7 (± 10.0) years. Among them, 65.4% were undergraduates, and 66.9% were women. SB time, UPF score, and BMI increased significantly during the pandemic, compared to the previous period. In this population, there was a significant association between increased SB time (β = 0.06; SE = 0.01; p < 0.001) and UPF score (β = 0.08; SE = 0.01; p < 0.001) with an increase in BMI. Changes in SB time and UPF score were associated with an increase in BMI before and during the COVID-19 pandemic in students from a Brazilian University.

Gender, BMI, and Age-Related Variations in Lower Limb Alignment Parameters and CPAK Phenotypes in Chinese Patients with Knee Osteoarthritis.

Research on the distribution of and the variation in coronal plane alignment of the knee (CPAK) in the Chinese osteoarthritis population is limited. We aimed to establish the CPAK classification based on the characteristics of lower limb alignment in the Chinese osteoarthritis population. We also investigated variations in lower limb alignment parameters and CPAK phenotypes based on gender, body mass index (BMI), and age. A retrospective study was conducted on a total of 944 knees diagnosed with osteoarthritis in 479 patients from January 2017 to December 2023. A scatterplot was used to describe the distribution of the CPAK classification, and the differences in lower limb alignment parameters and the CPAK classification were compared across genders (male, female), ages (middle-aged/<65 years, elderly/≥65 years), and BMI categories (normal/<25 kg/m2, overweight and obese/≥25 kg/m2) using the chi-squared test or Fisher's exact test. The average arithmetic hip-knee-ankle angle and joint line obliquity (JLO) were -3.03° ± 5.69° and 174.45° ± 4.29°, respectively. There was a higher prevalence of constitutional varus alignment in males and the overweight or obese group, while constitutional valgus alignment was more common in females and the normal BMI group (p < 0.05). Additionally, females had a greater apex distal JLO than males (p < 0.05). There were no statistically significant differences in lower limb alignment parameters among different age groups (p > 0.05). Although there were variations in alignment parameters across different genders and BMI categories in the knee osteoarthritis population, the predominant CPAK classifications were type I (38.03%), followed by type II (20.02%) and type IV (17.06%). The most common CPAK types were I, II, and IV, and they were not influenced by gender, BMI, or age, indicating that the CPAK classification can reliably reflect constitutional alignment. A better understanding of native alignment variability can aid in providing patient-specific recommendations when considering orthopedic alignment strategies.

Luteinizing Hormone Variability in Polycystic Ovary Syndrome: A Comparative Analysis

An endocrine with metabolic condition known as Polycystic Ovarian Syndrome (PCOS) affects women who are of reproductive age, women with PCOS are a condition often associated with dysregulation of the hypothalamic-pituitary axis. A Cross-sectional study, the study included 88 patients who visited the outpatient clinic in total. These individuals were split up into two groups. All females are assessed the status of obesity by the body mass index (BMI), [BMI= weight (kg) / height (m)²], LH, FSH, Estradiol and Testosterone levels measured by ELISA technique. There was no discernible variation in BMI between groups A and B. (P ≥ 0.456), The patients' mean FSH and LH values were 5.06 mIU/ml and 5.47 mIU/ml, compared with group B mean that equal to 6.05 mlU/ml, 18.91mlU/ml respectively. Serum testosterone was slightly elevated in group B that was (41.19 ± 5.16 ng/dL), and (39.53 ± 4.98 ng/dL) in group A. Moreover, the level of estradiol (E2) in group A was 79.45ng/dL while in group B the level was 72.65 ng/dL there are no significant difference between two groups. The study found conflicting evidence regarding the impact of high LH levels on oocyte quality, fertilization, and pregnancy outcomes in PCOS patients. According to the research, ovarian theca cells from PCOS patients may be more effective than normal theca cells at converting androgenic precursors to testosterone. While ovulatory dysfunction in PCOS is linked to reduced estradiol production, the study indicates that ovarian tissue may still contribute to circulating estradiol levels in affected women.

Genetic association of FTO gene polymorphisms with obesity and its related phenotypes: A case-control study.

FTO gene belongs to the non-heme Fe (II) and 2 oxoglutarate-dependent dioxygenase superfamily. Polymorphisms within the first intron of the FTO gene have been examined across various populations, yielding disparate findings.The present study aimed to determine the impact of two intronic polymorphisms FTO 30685T/G (rs17817449) and -23525T/A (rs9939609) on the risk of obesity in Punjab, India. Genotypic and biochemical analysis were done for 671 unrelated participants (obese=333 and non-obese=338) (age≥18 years). Genotyping of the polymorphisms was done by PCR-RFLP method. However, 50% of the samples were sequenced by Sanger sequencing. Both the FTO variants 30685 (TT vs GG: odds ratio (OR), 2.30; 95% confidence interval (CI), 1.39-3.79) and -23525 (TT vs AA: odds ratio (OR), 2.78; 95% confidence interval (CI), 1.37-5.64) showed substantial risk towards obesity by conferring it 2 times and 3 times, respectively. The analysis by logistic regression showed a significant association for both the variants 30685T/G (rs17817449) and -23525T/A (rs9939609) (OR=2.29; 95%CI: 1.47-3.57) and (OR=5.25; 95% CI: 2.68-10.28) under the recessive genetic model, respectively. The haplotype combination TA (30685; -23525) develops a 4 times risk for obesity (P=0.0001). Among obese, the G allele of 30685T/G and A- allele of -23525T/A showed variance in Body mass index (BMI), waist circumference (WC), waist-to-height ratio(WHtR), systolic blood pressure (SBP), diastolic blood pressure (DBP) and triglyceride(TG). The present investigation indicated that both the FTO 30685T/G (rs17817449) and -23525T/A (rs9939609) polymorphisms have a key impact on an individual's vulnerability to obesity in this population.

Correlation of anthropometric measurements with body mass index and estimation of the proportion of metabolic syndrome among overweight and obese children: a hospital-based cross-sectional study

BackgroundEarly identification of overweight and obesity with the help of simple anthropometric tests can prevent from development of metabolic complications in these children. Body mass index (BMI) is the most...

Methylome-wide studies of six metabolic traits.

Exploring the molecular correlates of metabolic health measures may identify the shared and unique biological processes and pathways that they track. Here, we performed epigenome-wide association studies (EWASs) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio (WHR), and blood-based measures of glucose, high-density lipoprotein (HDL) cholesterol, and total cholesterol. We considered blood-based DNA methylation (DNAm) from >750,000 CpG sites in over 17,000 volunteers from the Generation Scotland (GS) cohort. Linear regression analyses identified between 304 and 11,815 significant CpGs per trait at P<3.6×10-8, with 37 significant CpG sites across all six traits. Further, we performed a Bayesian EWAS that jointly models all CpGs simultaneously and conditionally on each other, as opposed to the marginal linear regression analyses. This identified between 3 and 27 CpGs with a posterior inclusion probability ≥ 0.95 across the six traits. Next, we used elastic net penalised regression to train epigenetic scores (EpiScores) of each trait in GS, which were then tested in the Lothian Birth Cohort 1936 (LBC1936; European ancestry) and Health for Life in Singapore (HELIOS; Indian-, Malay- and Chinese-ancestries). A maximum of 27.1% of the variance in BMI was explained by the BMI EpiScore in the subset of Malay-ancestry Singaporeans. Four metabolic EpiScores were associated with general cognitive function in LBC1936 in models adjusted for vascular risk factors (Standardised βrange: 0.08 - 0.12, PFDR < 0.05). EpiScores of metabolic health are applicable across ancestries and can reflect differences in brain health.

Preserved seasonal variation in glycemic control in patients with type 2 diabetes mellitus during COVID-19: a 3-year-long retrospective cohort study in older adults in Japan.

The coronavirus disease 2019 (COVID-19) pandemic has changed our lifestyle by imposing restrictions, such as physical distancing. The effect of COVID-19 prevalence on seasonal variations in glycemic control in patients with diabetes mellitus (DM) remains unknown. This single-center retrospective cohort study evaluated glycemic control in patients with type 2 DM who visited Sugi Cardiovascular Hospital in December 2021. We evaluated the clinical findings of all patients treated regularly between March 1, 2019, and December 31, 2021, including the periods both before and after the COVID-19 pandemic. All the standard treatments were approved. Furthermore, seasonal changes in hemoglobin A1c (HbA1c) levels were evaluated using stratified analyses based on age. This study analyzed 86 patients (mean age, 69.6 ± 9.2years; men, 57). Median HbA1c (National Glycohemoglobin Standardization Program [Union of Clinical Chemistry]) levels in spring (March) were 7.70% (interquartile range (IQR):7.23%-8.30%) [60.6mmol/mol (IQR:55.4-67.2mmol/mol)], 7.35% (IQR:6.90%-7.90%) [56.8mmol/mol (IQR:51.9-62.8mmol/mol)], and 7.50% (IQR:7.10%-8.00%) [58.5mmol/mol (IQR:54.1-63.9mmol/mol)] in 2019, 2020, and 2021, respectively. During these periods, HbA1c levels and body mass index (BMI) revealed significant seasonal variations "high in spring" and "low in autumn." Median HbA1c levels in spring (March) and autumn (September) were 7.86% [61.2 mmol/mol] and 7.48% [57.4 mmol/mol] in 2019 (P < 0.001), 7.50% [57.7 mmol/mol] and 7.17% [54.2 mmol/mol] in 2020 (P < 0.001), and 7.61% [58.3 mmol/mol] and 7.19% [53.8 mmol/mol] in 2021 (P < 0.001). Seasonal variations in HbA1c levels and BMI were maintained over the past 3years, including the pandemic period. None of the patients in this study developed COVID-19 during the study period. Seasonal variations in glycemic control in patients with DM were not influenced by lifestyle modifications associated with COVID-19. Maintenance of physical activity is necessary to prevent the development of sarcopenia. Moreover, seasonal variations in glycemic metabolism should be considered an independent factor for DM management. Additional extensive multifacility investigations are necessary to corroborate our findings.

Correlation of Carrying Angle with Body Mass Index among Females of Hyderabad Pakistan

Background: The carrying angle (CA) of the elbow is a critical biomechanical feature that varies between genders and with physical characteristics like Body Mass Index (BMI). Past studies have shown mixed results regarding the influence of BMI on CA, making it an area ripe for further investigation. Objective: To explore the correlation between BMI and the CA of the elbow among adult females in Hyderabad, Pakistan, and to assess how variations in BMI affect the elbow's CA. Methods: This cross-sectional study involved 385 adult females from Hyderabad, Pakistan, selected through non-probability convenient sampling. Participants were required to be over 18 years of age and without any prior upper limb surgeries. The CA was measured using a manual goniometer while standing in the anatomical position. BMI was calculated using measured weight and height. Statistical analysis was conducted using SPSS version 25, with the Pearson correlation test determining the relationship between BMI and CA. Results: Among the participants, 71.9% exhibited a normal CA, 23.6% displayed a decreased CA, and 4.4% had an increased CA. The Pearson correlation test showed a significant positive correlation between BMI and CA (p-value = 0.006), indicating that higher BMI is associated with an increased CA. Conclusion: The study found a significant association between BMI and CA among females in Hyderabad, Pakistan. This suggests that BMI is a relevant factor in the biomechanical characteristics of the elbow, which may have implications for the clinical assessment of joint function and health.

Effect of Aerobic Exercise on Sleep, Depression, and Quality of Life in Postmenopausal Women

Objectives: Menopause is a normal life stage that frequently brings with it emotional and physical difficulties that affect women’s Quality of life (QoL) and interfere with their ability to sleep. The objective of this study was to examine how postmenopausal women (PMWs) responded to supervised aerobic exercise training versus unsupervised Walking in terms of sleep, QoL, and depression. In addition, the impact on body composition was also assessed as a secondary outcome measure. Material and Methods: Fifty PMWs (aged 45–60) were divided into two groups at random: The control group (n = 25) performed standard unsupervised Walking, and the experimental group (n = 25) performed scheduled supervised aerobic exercise training. The Pittsburgh sleep quality index (PSQI), the 36-item short-form survey, the beck depression inventory (BDI), and the body mass index (BMI) were among the evaluations used in the 6-week, 3-day program. Results: Remarkable advancements (P &lt; 0.05) were noted in the aerobic training cohort. The experimental group increased total sleep duration by 37.9% and fell asleep 44.8% faster, resulting in a noteworthy 61.7% improvement in the PSQI score. BDI scores improved by 55.6%, and there was a 6.8% variation in BMI between the groups. Conclusion: A 6-week aerobic intervention can improve sleep quality, reduce menopausal symptoms, and enhance life quality in PMW. Furthermore, the results revealed that a regulated exercise group may offer more benefits than an unregulated one. This observation underscores the potential advantages of structured and monitored aerobic exercise program in achieving specific health and fitness goals.

Functional gas exchange measures on 129Xe MRI and spectroscopy are associated with age, sex, and BMI in healthy subjects.

Hyperpolarized 129Xe MRI and spectroscopy is a rapidly growing technique for assessing lung function, with applications in a wide range of obstructive, restrictive, and pulmonary vascular disease. However, normal variations in 129Xe measures of gas exchange across healthy subjects are not well characterized, presenting an obstacle to differentiating disease processes from the consequences of expected physiological heterogeneity. Here, we use multivariate models to evaluate the role of age, sex, and BMI in a range of commonly used 129Xe measures of gas exchange. Healthy subjects (N = 40, 16F, age 44.3 ± 17.8 yrs., min-max 22-87 years) with no history of cardiopulmonary disease underwent 129Xe gas exchange MRI and spectroscopy. We used multivariate linear models to assess the associations of age, sex, and body mass index (BMI) with the RBC:Membrane (RBC:M), membrane to gas (Mem:Gas), and red blood cell to gas (RBC:Gas) ratios, as well as measurements of RBC oscillation amplitude and RBC chemical shift. Age, sex, and BMI were all significant covariates in the RBC:M model. Each additional 10 years of age was associated with a 0.05 decrease in RBC:M (p < 0.001), each additional 10 points of BMI was associated with a decrease of 0.07 (p = 0.02), and males were associated with a 0.17 higher RBC:M than females (p < 0.001). For Mem:Gas, male sex was associated with a decrease and BMI was associated with an increase. For RBC:Gas, age was associated with a decrease and male sex was associated with an increase. RBC oscillation amplitude increased with age and RBC chemical shift was not associated with any of the three covariates. 129Xe MRI and spectroscopy measurements in healthy subjects, particularly the widely used RBC:M measurement, exhibit heterogeneity associated in part with variations in subject age, sex, and BMI. Elucidating the contributions of these and other factors to 129Xe gas exchange measurements is a critical component for differentiating disease processes from expected variation in healthy subjects. Notably, the Mem:Gas and RBC chemical shift appear to be stable with aging, suggesting that unexplained deviations in these metrics may be signs of underlying abnormalities.

Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index

Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI.

The neighourhood obesogenic built environment characteristics (OBCT) index: Practice versus theory

BackgroundObesity is a key risk factor for major chronic diseases such as type 2 diabetes and cardiovascular diseases. To extensively characterise the obesogenic built environment, we recently developed a novel Obesogenic Built environment CharacterisTics (OBCT) index, consisting of 17 components that capture both food and physical activity (PA) environments. ObjectivesWe aimed to assess the association between the OBCT index and body mass index (BMI) in a nationwide health monitor. Furthermore, we explored possible ways to improve the index using unsupervised and supervised methods. MethodsThe OBCT index was constructed for 12,821 Dutch administrative neighbourhoods and linked to residential addresses of eligible adult participants in the 2016 Public Health Monitor. We split the data randomly into a training (two-thirds; n = 255,187) and a testing subset (one-third; n = 127,428). In the training set, we used non-parametric restricted cubic regression spline to assess index's association with BMI, adjusted for individual demographic characteristics. Effect modification by age, sex, socioeconomic status (SES) and urbanicity was examined. As improvement, we (1) adjusted the food environment for address density, (2) added housing price to the index and (3) adopted three weighting strategies, two methods were supervised by BMI (variable selection and random forest) in the training set. We compared these methods in the testing set by examining their model fit with BMI as outcome. ResultsThe OBCT index had a significant non-linear association with BMI in a fully-adjusted model (p<0.05), which was modified by age, sex, SES and urbanicity. However, variance in BMI explained by the index was low (<0.05%). Supervised methods increased this explained variance more than non-supervised methods, though overall improvements were limited as highest explained variance remained <0.5%. DiscussionThe index, despite its potential to highlight disparity in obesogenic environments, had limited association with BMI. Complex improvements are not necessarily beneficial, and the components should be re-operationalised.

Interrelations of physical state parameters and biological age of students in the process of physical education

Background and Study Aim. The objective of the study is to investigate the relationships of students' biological age (BA) with the parameters of functional and physical fitness (PF) in the process of adaptation to standard (university) and experimental physical education programs. Material and Methods. The studies were conducted at the National University of Telecommunications of Ukraine and involved 140 students aged 17-18 years old, comprising 80 boys and 60 girls. We recorded 55 indices of students' functional state and physical fitness, and determined their Body Mass Index (BMI). The experimental data were processed using methods of correlation, dispersion, and regression analysis. Mathematical models describing the relationships between BMI and key indicators of students' physical well-being were developed. Results. The impact of the program on 17-18-year-old students is marked by a decrease in BMI, an increase in the levels of physical fitness and overall well-being among both the experimental group of girls and boys. Additionally, there is a reduced correlation between BMI and the parameters of their physical health. The key indices of functional state and physical fitness determining the BMI of male and female students were identified. Multiple regression models were developed to illustrate the dependence of male and female BMI on somatic and functional indices. Quantitative characteristics of the degree of partial and total impact of key indices on male and female BMI were provided. It was found that the key indicators of students' physical state (PS) structure, which exerted the most significant influence on BMI, differ between young men and women. In young men, the key indicators influencing BMI include the following: Vital capacity (VC) accounts for 51.9% of BMI variation; self-perceived health status (SPHS) contributes 15.3%; static balancing (SB) affects 8.5%; inspiration breath-hold time (IBH) influences 8.4%; expiration breath-hold time (EBH) has a 0.8% impact; systolic blood pressure (SBP) plays a role with 4.6%; the number of sit-ups in 30 seconds (SU30s) is associated with 0.9%; and left hand muscle strength has a 0.6% influence. In girls, the key indicators are VC (34.5% of BMI variation), SBP (23.1%), and SB (7.9%). Conclusions. The experimental program of increased motor activity leads to an increase in the functional and motor capabilities of students, while simultaneously decreasing their BMI. Among the parameters studied, changes in vegetative parameters have the greatest impact on reducing students' BMI during the annual cycle of long-term adaptation to physical loads. In contrast, changes in somatic parameters and physical fitness parameters have a lesser influence on students' BMI. The calculated equations of multiple regression serve as model characteristics that reflect the relationships between BMI and the key indicators of functional state and physical fitness in 17-18-year-old students. These equations can be utilized to estimate, model, and predict the BMI of 17-18-year-old students of different genders when altering the parameters of their physical state in various conditions of daily life and activity.

Social determinants of health and diabetes: using a nationally representative sample to determine which social determinant of health model best predicts diabetes risk

ObjectivesSocial determinants of health (SDOH) research demonstrates poverty, access to healthcare, discrimination, and environmental factors influence health outcomes. Several models are commonly used to assess SDOH, yet there is limited understanding of how these models differ regarding their ability to predict the influence of social determinants on diabetes risk. This study compares the utility of four SDOH models for predicting diabetes disparities.Study designWe utilized The National Longitudinal Study of Adolescent to Adulthood (Add Health) to compare SDOH models and their ability to predict risk of diabetes and obesity.MethodsPrevious literature has identified the World Health Organization (WHO), Healthy People, County Health Rankings, and Kaiser Family Foundation as the conventional SDOH models. We used these models to operationalize SDOH using the Add Health dataset. Add Health data were used to perform logistic regressions for HbA1c and linear regressions for body mass index (BMI).ResultsThe Kaiser model accounted for the largest proportion of variance (19%) in BMI. Race/ethnicity was a consistent factor predicting BMI across models. Regarding HbA1c, the Kaiser model also accounted for the largest proportion of variance (17%). Race/ethnicity and wealth was a consistent factor predicting HbA1c across models.ConclusionPolicy and practice interventions should consider these factors when screening for and addressing the effects of SDOH on diabetes risk. Specific SDOH models can be constructed for diabetes based on which determinants have the largest predictive value.

Hedonic hunger, food addiction, and night eating syndrome triangle in adolescents and ıts relationship with body mass ındex

BackgroundThe relationship between adolescent obesity and eating disorders is an issue that needs urgent attention. Screening for eating disorders is as important as dietary interventions to treat obesity. This study aimed to determine the relationship between hedonic hunger, food addiction, and night eating syndrome, which are considered potential risk factors for obesity, and body mass index (BMI) in adolescents.MethodsThe data were collected through an online questionnaire. The “Power of Food Scale (PFS)” was used to assess hedonic hunger; the “Yale Food Addiction Scale for Children 2.0 (dYFAS-C 2.0)” was used to assess food addiction; and the “Night Eating Questionnaire (NEQ)” was used to assess night eating syndrome (NES)”. BMI was calculated using self-reported height and weight values of adolescents. The mediated structural model analysis was performed to evaluate the effect of hedonic hunger on BMI z score via food addiction and NES.ResultsThe study was conducted with 614 voluntary adolescents aged between 11 and 18 years. The dYFAS-C 2.0 and NEQ scores were found to be higher in adolescents with overweight and obesity, and the BMI z-score of the adolescents had significant positive correlation with their PFS scores (p < .001). Hedonic hunger has no direct effect on BMI independent of food addiction and NES (β = − 0.051, p = .468), but when the total indirect effect is evaluated with the bootstrap analysis, it was found that one-unit increase in hedonic hunger score increases BMI z-score by approximately 0.22 units (β = 0.223, SE = 0.046, 95% CI 0.131–0.313). Hedonic hunger, food addiction, and NES together explained 5.2% of the total variance in BMI z score.ConclusionThis study showed that hedonic hunger significantly predicted BMI z-score in adolescents through food addiction and NES. This emphasizes the critical importance of evaluating adolescents in terms of hedonic hunger, food addiction, and NES in the prevention, diagnosis, and treatment of obesity.

The impact of BMI on life expectancy in Portugal

The overweight represents a serious public health problem in Portugal, with a prevalence that exceeds 50%. Obesity-related diseases constitute the health system's main causes of death and economic issues. Despite this, there is no consensus on the relationship between the Body Mass Index (BMI) and the risk of early mortality. In this context, assessing the impact of the average BMI on life expectancy in Portugal is important. A retrospective cross-sectional observational study was carried out using an Autoregressive Distributed Lag model. The dependent variable is life expectancy at birth, expressed in the total years obtained from the World Development Indicators (WDI). The independent variables are: (i) the average BMI of the population (calculated based on the average male and female BMI obtained from Our World in Data); and (ii) the total population obtained from the WDI. The population's mean BMI variable limited the study's time horizon, comprising annual statistical data from 1975 to 2016. The increase in BMI negatively affects the life expectancy of the Portuguese population in the short term. A 1% variation in BMI reflects a 1.98% reduction in life expectancy. The result was statistically significant at 1%, and the p-value was 0.0001. In the long term, there was no statistically significant effect of the mean BMI on the population's life expectancy. Also, in the long term, population growth has a positive and statistically significant effect on life expectancy. Although there is no consensus in the literature that BMI is associated with increased mortality, the results obtained through this model captured this trend in Portugal in the short term. Therefore, promoting life expectancy by improving the Portuguese's health and quality of life is necessary. The adoption of measures that favor the recovery or maintenance of normal weight is essential.

Lifestyle factors, genetic susceptibility to obesity and their interactions on coronary artery disease risk: A cohort study in the UK Biobank

ObjectiveWe aimed to evaluate potential modifying effects of genetic susceptibility to obesity on the association of lifestyle factors with coronary artery disease (CAD) risk. MethodsA total of 328,606 participants (54% women) were included using data from the UK Biobank. We evaluated the risk of developing CAD associated with obesity-related polygenic scores (PGSs) and healthy lifestyle scores (HLSs). HLSs were constructed using six lifestyle factors. Obesity PGSs were created using genetic variants identified by genome-wide association studies, including 941 variants for body mass index (BMI) and 457 for waist-to-hip ratio (WHR). Both HLSs and PGSs were categorized into three groups. ResultsDuring a 9-year median follow-up, 14,541 participants developed CAD. An unhealthy lifestyle was significantly associated with an increased CAD risk (hazard ratio [HR] = 2.24, 95% confidence interval [CI] = 2.09–2.40). High BMI and WHR PGSs were each significantly associated with an increased CAD risk (HRBMI = 1.23, 1.17–1.29; HRWHR = 1.15, 1.09–1.21). Lifestyle factors explained 41% (95% CI = 38%–45%) of CAD, while genetic variants for BMI explained only 10% (7%–14%). Risks of CAD were increased with poorer HLS independent of obesity-related PGSs. Individuals with the most unhealthy lifestyle and highest BMI PGS had the highest risk of CAD risk (HR = 2.59, 95% CI = 2.26–2.97), compared with participants with the healthiest lifestyle and lowest BMI PGS. ConclusionsWhile the observational nature of the study precludes the establishment of causality, our study provides supports for a causal association between obesity and CAD risk and the importance of lifestyle modification in the prevention of CAD.