Secretory immunity in overweight and obese versus normal-weight early-and late-pubertal females

Obesity is a condition associated with a wide variety of health problems including hypertension, dyslipidemia, diabetes mellitus, certain forms of cancer, cardiovascular disease, and gallstones (157). TTiere is growing evidence that obesity may also be related to compromised immune function due to altered metabolic, psychological, and physical attributes (93). The aim of this study was to compare: a) immunity-related variables such as frequency of upper respiratory tract infections (URTI) and salivary secretory immunoglobulin A (sIgA) levels between overweight/obese (OB) and normal weight (NW) early-pubertal and late-pubertal girls, and b) stress-related variables such as Cortisol, melatonin, the melatonin/cortisol ratio, testosterone and the testosterone/cortisol ratio. Physical activity levels, stress indicators, and fatigue were used to explain potential differences in the dependent variables. It was hypothesized that the OB females would have lower melatonin (M) and higher Cortisol (C) and testosterone (T) levels compared with NW girls, regardless of maturity status. The altered levels of melatonin, Cortisol, and testosterone, would result in decreased M/C and T/C ratios, despite the increase in testosterone in OB females. It was hypothesized that this altered hormonal status results in a compromised immunity marked by higher frequency of upper respiratory tract infections (URTI) and decreased levels of secretory immunoglobulin A (sIgA). It was also hypothesized that OB girls would participate in less hours of physical activity than their NW counterparts and that this would relate to their stress and immunity levels. Forty (16 early- and 24 late-pubertal) overweight and obese females were compared to fifty-three (27 eariy- and 26 late-pubertal) age-matched normal-weight control subjects. Participants were categorized as early-pubertal (EP) or late-pubertal (LP) using Tanner self-staging of secondary sex characteristics. Subjects were classified into the two adiposity groups according to relative body fat (%BF), where normal weight (NW) subjects had a %BF less than 25%, and overweight and obese (OB) subjects had a %BF greater than 27.5%. Participants completed a number of questionnaires and information was collected on menstrual history, smoking history, alcohol and caffeine consumption, and medical history. Following the determination of maturity status, a complete anthropometric assessment was made including height, body mass, and body composition. All questionnaires and measurements were completed during a one-hour visit between 1 500 and 1900 hours Relative body fat was assessed using bioelectrical impedance analysis. Resting saliva samples were obtained and assayed (ELISA) for testosterone, Cortisol, melatonin and secretory immunoglobulin A. Physical activity was self-reported using the Godin- Shephard Leisure time questionnaire, and quantified using Actigraph GTIM accelerometers, which participants wore for seven consecutive days from the time they woke up in the morning, until the time they went to bed. Late-pubertal girls also completed questionnaires on their perceived stress and fatigue. Finally, all participants also filled out a one-month health log to record frequency of symptoms of upper respiratory tract infections (URTI). Significant age effects were found for testosterone, Cortisol, incidence of sickness, and sIgA when controlling for physical activity, however there were no significant effects of adiposity on any of the variables. There was a trend which neared-significance for an effect of adiposity on sIgA (p=0.01). There were no significant differences between the groups on the total selfreported leisure-time physical activity in METs per week, however EP girls recorded significantly greater levels of moderate, hard, and very hard physical activity from accelerometers. Results of the perceived stress and fatigue questionnaires in late-pubertal girls demonstrated that contrary to what was hypothesized, NW girls reported more stress and more fatigue than OB girls. Results of the present study suggest that excess adiposity in early- and latepubescent girls may not have a negative impact on immunity as hypothesized.

Comparison of non-HDL cholesterol and waist circumference vs. triglyceride levels and waist circumference in predicting coronary heart disease risk

BACKGROUND: Dyslipidemia is recognized as a major cause of coronary heart disease (CHD). Emerged evidence suggests that the combination of triglycerides (TG) and waist circumference can be used to predict the risk of CHD. However, considering the known limitations of TG, non-high-density lipoprotein (non-HDL = Total cholesterol - HDL cholesterol) cholesterol and waist circumference model may be a better predictor of CHD. PURPOSE: The Framingham Offspring Study data were used to determine if combined non-HDL cholesterol and waist circumference is equivalent to or better than TG and waist circumference (hypertriglyceridemic waist phenotype) in predicting risk of CHD. METHODS: A total of3,196 individuals from Framingham Offspring Study, aged ~ 40 years old, who fasted overnight for ~ 9 hours, and had no missing information on nonHDL cholesterol, TG levels, and waist circumference measurements, were included in the analysis. Receiver Operator Characteristic Curve (ROC) Area Under the Curve (AUC) was used to compare the predictive ability of non-HDL cholesterol and waist circumference and TG and waist circumference. Cox proportional-hazards models were used to examine the association between the joint distributions of non-HDL cholesterol, waist circumference, and non-fatal CHD; TG, waist circumference, and non-fatal CHD; and the joint distribution of non-HDL cholesterol and TG by waist circumference strata, after adjusting for age, gender, smoking, alcohol consumption, diabetes, and hypertension status. RESULTS: The ROC AUC associated with non-HDL cholesterol and waist circumference and TG and waist circumference are 0.6428 (CI: 0.6183, 0.6673) and 0.6299 (CI: 0.6049, 0.6548) respectively. The difference in the ROC AVC is 1.29%. The p-value testing if the difference in the ROC AVCs between the two models is zero is 0.10. There was a strong positive association between non-HDL cholesterol and the risk for non-fatal CHD within each TO levels than that for TO levels within each level of nonHDL cholesterol, especially in individuals with high waist circumference status. CONCLUSION: The results suggest that the model including non-HDL cholesterol and waist circumference may be superior at predicting CHD compared to the model including TO and waist circumference.