Comparing measures of general and abdominal adiposity as predictors of blood pressure in college students

Objective: To compare anthropometric measures of body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and sagittal abdominal diameter (SAD) as predictors of blood pressure in college students. Participants: Students (N = 116) were recruited from November 2012 to May 2014 at an urban university and rural community colleges. Methods: Students underwent a brief physical examination during which anthropometric measures were obtained and blood pressure was measured. Covariates were measured using self-reported questionnaires. Hierarchical multiple linear regressions were used for the data analysis. Results: All anthropometric measures were predictive of systolic (SBP) and diastolic blood pressure (DBP). WC was the strongest predictor of SBP (β = .582, p < .01) explaining an additional 3–4% of the variance than BMI, WHtR, or SAD. The measures were similar in predicting DBP. WC predicted SBP independent of BMI. Conclusions: Clinicians should consider using WC to assess the risk for hypertension in college students.     

Visceral adiposity index is associated with premature ejaculation inversely: a cross-sectional study

Objective: Visceral adiposity index (VAI) is a novel indicator for the assessment of visceral obesity. In this study, we aimed to evaluate the relationship between VAI and premature ejaculation (PE).

Materials and method: A total of 300 men were included in the study. Hundred and fifty men with PE and 150 men without PE (control). All men were evaluated for PE by premature ejaculation diagnostic tool (PEDT). VAI levels were calculated using body mass index (BMI), high density lipoprotein and triglyceride (TG) levels.

Results: Mean age of the study groups was 34.3?±?5.2 (30–60) years and the mean age of the controls were 35.9?±?5.3 (30–60) years. The men with PE had lower BMI, TG levels, waist circumference (WC) and higher high-density lipoprotein-cholesterol (HDL-C) levels. Mean VAI level was 4.13?±?0.7 in study group and 5.72?±?1.6 in control group, respectively. VAI levels were statistically higher in men without PE (p?Discussion: Our cross-sectional study demonstrated a negative correlation between VAI and PE. VAI is superior index for the evaluation and calculation the relationship between obesity and PE.     

Visceral adiposity index is associated with benign prostatic enlargement in non-diabetic patients: a cross-sectional study

Objective: To evaluate the association between visceral adiposity index (VAI) - a novel indicator for the assessment of visceral adipose tissue and prostate enlargement in non diabetic patients.

Material and methods: Four hundred patients who were admitted to the Urology clinic between January and December 2014 with complaints of BPH(benign prostatic hyperplasia )/LUTS(male lower urinary tract symptoms)were enrolled in this cross-sectional study. Patients were divided into two groups according to their prostate volume and international prostate symptom score (IPSS) value. They were compared in terms of age, body mass index (BMI), VAI, prostate volume, PSA, post micturional residual volume (PMRV), uroflowmetry Q max value, triglyceride (TG), high density lipoprotein-cholesterol (HDL-C) and fasting blood sugar (FBS).

Results: Although univariate analyses reveal that age, BMI, waist circumference (WC), FBS, TG, HDL-C level and TG/HDL ratio were correlated with prostate volume, only age [1.125 OR (1.088–1.164), p?=?.00001], BMI [1.119 OR (1.040–1.204), p?=?.003], TG [1.043 OR (1.016–1.071), p?=?.002], HDL-C [0.923 OR (0.860–0.990), p?=?.025] and VAI [1.194 OR (1.110–1.305), p?=?.011] were statistically significant in multivariate analysis. A positive correlation was found between VAI value and prostate volume in the Spearman correlation test (r?=?0.29, p?=?.00001). The calculated area under the curve (AUC) for prostate volumes of 30, 40 and 50?ml were 0.680 (0.621–0.738), 0.625 (0.570–0.681) and 0.590 (0.528–0.652), respectively.

Conclusion: Our study revealed a positive correlation between VAI and prostate volume. Our results are needed to be tested with well-designed randomized prospective cohort studies.     

Longitudinal changes in anthropometry and body composition in university freshmen

Objective: We investigated predictors of weight gain in college freshmen. Participants: A longitudinal cohort study followed a representative sample of freshmen (N = 264) from 8/2011 to 6/2012. Methods: Repeated measurements of anthropometry, dual-energy X-ray absorptiometry (DXA), physical activity, and diet were collected. We investigated predictors of 9-month weight gain using regression models. Results: 172 participants completed follow-up: 75% gained >0.5 kg. Mean weight change was +2.3 kg (SD 3.2) and +2.0 kg (SD 3.2) and mean adiposity change was +1.3% (SD 1.6) and +0.7% (SD 2.2) in men and women, respectively. In participants gaining >0.5 kg, weight increased 5.6% and body fat increased 1.6%. Anthropometric change in men occurred in the first semester, while women increased in both semesters. Leaner DXA-defined body composition at baseline was consistently associated with greater weight gain (p-values 0.029–0.049). Conclusions: Freshman weight gain is common and reflects increased adiposity. Leaner body composition at the beginning of college predicted greater weight gain in men and women during the first year of college.     

A trajectory analysis of body mass index for Finnish children

The aim of this study is to investigate the early development of body mass index (BMI), a standard tool for assessing the body shape and average level of adiposity for children and adults. The main aim of the study is to identify the primary trajectories of BMI development and to investigate the changes of certain growth characteristics over time. Based on our longitudinal data of 4223 Finnish children, we took anthropometric measurements from birth up to 15 years of age for birth years 1974, 1981, 1991 and 1995, but only up to 11 years of age for the birth year 2001. As a statistical method, we utilized trajectory analysis with the methods of nonparametric regression. We identified four main trajectories of BMI growth. Two of these trajectories do not seem to follow the normal growth pattern. The highest growth track appears to yield to a track that may yield to overweight and the low birth BMI track shows that the girls’ track differs that of boys on the same track, and on the normal tracks. The so-called adiposity rebound time decreased over time and started earlier for those on the overweight track. According to our study, this kind of acceleration of growth might be more of a general phenomenon that also relates to the other phases of BMI development. The major change seems to occur especially for those children on high growth tracks.