The Influence of Baseline Metabolic Rate and Exercise Training on Cardio-Respiratory Dynamics

Speeding the VO2 kinetics results in a reduction of the O2 deficit. Two factors might determine VO2 kinetics: oxygen delivery to muscle (Tschakovsky and Hughson 1999) and a muscle 'metabolic inertia' (Grassi et al. 1996). Therefore, in study 1 we investigated VO2 kinetics and cardiovascular system adaptations during step exercise transitions in different regions of the moderate domain. In study 2 we investigated muscle oxygenation and cardio-pulmonary adaptations during step exercise tests before, after and over a period of training. Study 1 methods: Seven subjects (26 ± 8 yr; 176 ± 5 cm; 69 ± 6 kg) performed 4 types of step transition from rest (0-50W; 0-100W) or elevate baseline (25-75W; 25-125W). GET and VO2max were assessed before testing. O2 uptake and were measured during testing. Study 2 methods: 10 subjects (25 ± 4 yr; 175 ± 9 cm; 71 ± 12 kg) performed a step transition test (0 to 100 W) before, after and during 4 weeks of endurance training (ET). VO2max and GET were assessed before and after of ET (40 minutes, 3 times a week, 60% O2max). VO2 uptake, Q and deoxyheamoglobin were measured during testing. Study 1 results: VO2 τ and the functional gain were slower in the upper regions of the moderate domain. Q increased more abruptly during rest to work condition. Q τ was faster than VO2 τ for each exercise step. Study 2 results: VO2 τ became faster after ET (25%) and particularly after 1 training session (4%). Q kinetics changed after 4 training sessions nevertheless it was always faster than VO2 τ. An attenuation in ∆[HHb] /∆VO2 was detectible. Conclusion: these investigations suggest that muscle fibres recruitment exerts a influence on the VO2 response within the moderate domain either during different forms of step transition or following ET.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.