Physical activity intensity and surrogate markers for cardiovascular health in adolescents

We examined the impact of physical activity (PA) on surrogate markers of cardiovascular health in adolescents. 52 healthy students (28 females, mean age 14.5 ± 0.7 years) were investigated. Microvascular endothelial function was assessed by peripheral arterial tonometry to determine reactive hyperemic index (RHI). Vagal activity was measured using 24 h analysis of heart rate variability [root mean square of successive normal-to-normal intervals (rMSSD)]. Exercise testing was performed to determine peak oxygen uptake ([Formula: see text]) and maximum power output. PA was assessed by accelerometry. Linear regression models were performed and adjusted for age, sex, skinfolds, and pubertal status. The cohort was dichotomized into two equally sized activity groups (low vs. high) based on the daily time spent in moderate-to-vigorous PA (MVPA, 3,000-5,200 counts(.)min(-1), model 1) and vigorous PA (VPA, >5,200 counts(.)min(-1), model 2). MVPA was an independent predictor for rMSSD (β = 0.448, P = 0.010), and VPA was associated with maximum power output (β = 0.248, P = 0.016). In model 1, the high MVPA group exhibited a higher vagal tone (rMSSD 49.2 ± 13.6 vs. 38.1 ± 11.7 ms, P = 0.006) and a lower systolic blood pressure (107.3 ± 9.9 vs. 112.9 ± 8.1 mmHg, P = 0.046). In model 2, the high VPA group had higher maximum power output values (3.9 ± 0.5 vs. 3.4 ± 0.5 W kg(-1), P = 0.012). In both models, no significant differences were observed for RHI and [Formula: see text]. In conclusion, in healthy adolescents, PA was associated with beneficial intensity-dependent effects on vagal tone, systolic blood pressure, and exercise capacity, but not on microvascular endothelial function.

Ethnic Minority Children’s Active Commuting to School and Association with Physical Activity and Pedestrian Safety Behaviors

Background: Children's active commuting to school, i.e. walking or cycling to school, was associated with greater moderate-to-vigorous physical activity, although studies among ethnic minorities are sparse. Objectives: Among a low-income, ethnic minority sample of fourth grade students from eight public schools, we examined (1) correlates of active commuting to school and (2) the relationship between active commuting to school and moderate-to-vigorous physical activity. Methods: We conducted a cross-sectional analysis of baseline measurements from a sample of participants (n=149) aged 9-12 years from a walk to school intervention study in Houston, Texas. The primary outcome was the weekly rate of active commuting to school. Daily moderate-to-vigorous physical activity, measured by accelerometers, was a secondary outcome. Child self-efficacy (alpha=0.75), parent self-efficacy (alpha=0.88), and parent outcome expectations (alpha=0.78) were independent variables. Participant characteristics (age, gender, race/ethnicity, distance from home to school, acculturation, and BMI percentile) were independent sociodemographic variables. We used mixed-model regression analyses to account for clustering by school and a stepwise procedure with backward elimination of non-significant interactions and covariates to identify significant moderators and predictors. School-level observations of student pedestrians were assessed and compared using chi-square tests of independence. Results: Among our sample, which was 61.7% Latino, the overall rate of active commuting to school was 43%. In the mixed model for active commuting to school, parent self-efficacy (std. beta = 0.18, p=0.018) and age (std. beta = 0.18, p=0.018) were positively related. Latino students had lower rates of active commuting to school than non-Latinos ( 16.5%, p=0.040). Distance from home to school was inversely related to active commuting to school (std. beta = 0.29, p<0.001). In the mixed model for moderate-to-vigorous physical activity, active commuting to school was positively associated (std. beta = 0.31, p <0.001). Among the Latino subsample, child acculturation was negatively associated with active commuting to school (std. beta = -0.23, p=0.01). With regard to school-level pedestrian safety observations, 37% of students stopped at the curb and 2.6% looked left-right-left before crossing the street. Conclusion: Although still below national goals, the rate of active commuting was relatively high, while the rate of some pedestrian safety behaviors was low among this low-income, ethnic minority population. Programs and policies to encourage safe active commuting to school are warranted and should consider the influence of parents, acculturation, and ethnicity.

Physical activity interventions in schools for improving lifestyle in European countries

Background: In the last decades, children’s and adolescents’ obesity and overweight have increased in European Countries. Unhealthy eating habits and sedentary lifestyle have been recognized to determine such an epidemic. Schools represent an ideal setting to modify harmful behaviors, and physical activity could be regarded as a potential way to avoid the metabolic risks related to obesity. Methods: A systematic review of the literature was carried out to summarize the evidence of school-based interventions aimed to promote, enhance and implement physical activity in European schools. Only randomized controlled trials were included, carried out in Europe from January 2000 to April 2014, universally delivered and targeting pupils aged between 3 and 18 years old. Results: Forty-seven studies were retrieved based either on multicomponent interventions or solely physical activity programs. Most aimed to prevent obesity and cardiovascular risks among youths. While few studies showed a decrease in BMI, positive results were achieved on other outcomes, such as metabolic parameters and physical fitness. Conclusion: Physical activity in schools should be regarded as a simple, non-expensive and enjoyable way to reach all the children and adolescents with adequate doses of moderate to vigorous physical activity.

Adherence to a lifestyle physical activity program: Trends over time and associations with processes of change and physical activity

Research on lifestyle physical activity interventions suggests that they help individuals meet the new recommendations for physical activity made by the Centers for Disease Control and Prevention (CDC) and the American College of Sports Medicine (ACSM). The purpose of this research was to describe the rates of adherence to two lifestyle physical activity intervention arms and to examine the association between adherence and outcome variables, using data from Project PRIME, a lifestyle physical activity intervention based on the transtheoretical model and conducted by the Cooper Institute of Aerobics Research, Dallas, Texas. Participants were 250 sedentary healthy adults, aged 35 to 70 years, primarily non-Hispanic White, and in the contemplation and preparation stages of readiness to change. They were randomized to a group (PRIME G) or a mail- and telephone-delivered condition (PRIME C). Adherence measures included attending class (PRIME G), completing a monthly telephone call with a health educator (PRIME C), and completing homework assignments and self-monitoring minutes of moderate- to vigorous physical activity (both groups). In the first results paper, adherence over time and between conditions was examined: Attendance in group, completing the monthly telephone call, and homework completion decreased over time, and participants in PRIME G were more likely to complete homework than those in PRIME C. Paper 2 aimed to determine whether the adherence measures predicted achievement of the CDC/ACSM physical activity guideline. In separate models for the two conditions, a latent variable measuring adherence was found to predict achievement of the guideline. Paper 3 examined the association between adherence measures and the transtheoretical model's processes of change within each condition. For both, participants who completed at least two thirds of the homework assignments improved their use of the processes of change more than those who completed less than that amount. These results suggest that encouraging adherence to a lifestyle physical activity intervention, at least among already motivated volunteers, may increase the likelihood of beneficial changes in the outcomes. ^

Community referral for promoting physical activity among primary care patients

Introduction. There is a need for physical activity interventions based in primary care clinics that take advantage of community resources. The purpose of this randomized controlled trial was to compare the effects of two physical activity interventions: (1) physical activity prescription by a primary care provider plus referral to community physical activity resources and (2) physical activity prescription only. ^ Methods. Sedentary adult patients recruited from a general medicine clinic were randomized to receive a physical activity prescription, delivered by the primary care provider, plus referral to community physical activity resources (n=38) or physical activity prescription only (n=32). Outcomes were use of community resources (exercise facility and personal trainers), physical activity levels (self-report questionnaire and pedometer), and attitudes regarding physical activity assessed at 8 weeks. ^ Results. Three of 38 (7.9%) subjects referred to the community resources and none of the 32 subjects in the prescription only group used the community resources during the 8 week trial. Sixteen of 32 subjects in the prescription plus referral group and 19 of 38 in the prescription group completed the self-report follow-up forms at 8 weeks. For minutes of moderate- or vigorous-intensity physical activity per week, there were no between-group differences at baseline, follow-up, or change from baseline to follow-up. However, for moderate- and vigorous-intensity physical activity, there were significant improvements from baseline to follow-up within each group. For attitudes related to physical activity, there were no between-group differences at baseline, follow-up, or change from baseline to follow-up; neither were there any within-group changes. ^ Discussion. Physical activity prescription delivered by a healthcare provider in the context of a routine primary care visit can improve physical activity levels, with no additional improvement gained by referring to community resources. The intervention was feasible for primary care providers to deliver, but only 50% of subjects returned the self-report physical activity questionnaire at the 8 week assessment. ^

Validity and reliability of using MVP 4 Function Walk4Life digital pedometers to assess physical activity levels among preschool-aged Head Start children

The Surgeon General recommends preschoolers 3-5 years old accumulate 60 minutes of moderate-to-vigorous physical activity (MVPA) per day. However, there is limited data measuring physical activity (PA) and MVPA amongst this population. The purpose of this cross-sectional study is to determine the validity, reliability, and feasibility of using MVP 4 Function Walk4Life digital pedometers (MVP-4) in measuring MVPA among preschoolers using the newly modified direct observational technique, System for Observing Fitness Instruction Time-Preschool Version (SOFIT-P) as the gold standard. An ethnically diverse population of 3-5 year old underserved children were recruited from two Harris County Department of Education (HCDE) Head Start centers. For 2 days at baseline and 2 days at post-test, 75 children enrolled wore MVP-4 pedometers for approximately 6-hours per observation day and were observed using SOFIT-P during predominantly active times. Statistical analyses used Pearson "r" correlation coefficients to determine mean minutes of PA and MVPA, convergent and criterion validity, and reliability. Significance was set at p = <0.05. Feasibility was determined through process evaluation information collected during this study via observations from data collectors and teacher input. Results show mean minutes of PA and MVPA ranged between 30-42 and 11-14 minutes, respectively. Convergent validity comparing BMI percentiles with MVP-4 PA outcomes show no significance at pre-test; however, each measurement at post-test showed significance for MVPA (p = 0.0247, p = 0.0056), respectively. Criterion validity comparing percent MVPA time between SOFIT-P and MVP-4 pedometers was determined; however, results deemed insufficient due to inconsistency in observation times while using the newly developed SOFIT-P. Reliability measures show no significance at pre-test, yet show significant results for all PA outcomes at post-test (p = 0.001, p = 0.001, p = 0.0010, p = 0.003), respectively. Finally, MVP-4 pedometers lacked feasibility due to logistical barriers in design. Researchers feel the significant results at post-test are secondary to increased familiarity and more accurate placement of pedometers across time. Researchers suggest manufacturers of MVP-4 pedometers further modify the instrument for ease of use with this population, following which future studies ought to determine validity using objective measures or all-day direct observation techniques.^

Has the development of a New Urbanist community affected the physical activity levels of residents in surrounding neighborhoods?

Study Aims. The neighborhood environment has been shown to influence physical activity levels, but little is known about how far-reaching these effects are. This study sought to determine whether or not the development of a New Urbanist community in Austin, Texas affected the physical activity levels of residents in surrounding neighborhoods. The results were stratified by demographic characteristics, residential distance from the New Urbanist community, and type of physical activity to determine if any observed changes varied by these factors.^ Methods. Self-report questionnaires were mailed to a random sample of households located within one mile of the New Urbanist development. The questionnaire included questions about physical activity behaviors before and after the community was constructed in 2006. Changes in reported levels of physical activity between the two time points were examined.^ Results. The prevalence and average minutes per week of total physical activity did not change. Significant increases in the frequency and quantity of moderate-intensity leisure-time physical activity were observed. The amount of time spent walking and biking for recreation outside of the neighborhood increased significantly among those living close to Mueller. The weekly time spent in vigorous-intensity activity increased significantly, especially among those living closer to Mueller. There were significant decreases in the prevalence of and time spent walking for transport. The use of Mueller parks and trails was highest among participants living close to Mueller.^ Conclusions. The nearby Mueller development does not appear to have encouraged sedentary members of the surrounding population to become physically active, but might be associated with increased weekly physical activity among those who were already active. The increase in vigorous-intensity physical activity and recreational walking/biking outside of the neighborhood among those subjects living closer to Mueller may be attributed to the use of Mueller parks and trails, which was also considerably higher among this group. People may be substituting the time they spent walking for transport before the Mueller development with moderate-intensity leisure-time physical activity. Future research should seek to identify barriers that may be preventing more nearby residents from using Mueller facilities for physical activity. ^

Physical activity levels and access to places to be physically active

The built environment is recognized as having an impact on health and physical activity. Ecological theories of physical activity suggest that enhancing access to places to be physically active may increase activity levels. Studies show that users of fitness facilities are more likely to be active than inactive and active people are more likely to report access to fitness facilities. The purpose of this study was to examine the ecologic relationship between density of fitness facilities and self-reported levels of physical activity in adults in selected Metropolitan Statistical Areas (MSAs) in the United States.^ The 2007 MSA Business Patterns and the 2007 Behavioral Risk Factor Surveillance System (BRFSS) were used to gather fitness facility and physical activity data for 141 MSAs in the United States. Pearson correlations were performed between fitness facility density (number of facilities/100,000 people) and six summary measures of physical activity prevalence. Regional analysis was done using the nine U.S. Standard Regions for Temperature and Precipitation. ^ Direct correlations between fitness facility density and the percent of those physically active (r=0.27, 95% CI 0.11, 0.42, p=0.0012), those meeting moderate-intensity activity guidelines, (r=0.23, 95% CI 0.07, 0.38, p=0.006), and those meeting vigorous-intensity activity guidelines (r=0.30, 95% CI 0.14, 0.44, p=0.003) were found. An inverse correlation was found between fitness facility density and the percent of people physically inactive (r=-0.45, 95% CI -0.57, -0.31), p<0.0001). Regional analysis showed the same trends across most regions.^ Access to fitness facilities, defined here as fitness facility density, is related to physical activity levels. Results suggest the potential importance of the influence of the built environment on physical activity behaviors. Public health officials and city planners should consider the possible positive effect that increasing the number of fitness facilities in communities would have on activity levels.^

Examining seasonal variations in physical activity among low-income Hispanic walk-trail users living in the Cameron Park Colonia

This study examines variations in physical activity by season, and within seasons by age and gender among park users living in the Cameron Park Colonia, a low-income Hispanic community along the Texas-Mexico border. This is the first study of its kind to evaluate seasonal variations by physical activity among a Hispanic population. We hypothesized that (1) there are no differences in overall physical activity by season; (2) youth engage in more sport-related physical activity compared to adults, (3) males engage in more physical activity than females, and (4) there are differences in physical activity between walk-trail users compared to non walk-trail users in the park.^ Physical activity behavioral data was collected (males n=2,093; females n=1,014) at two time periods (winter 2007; summer 2007) via direct observations and assessed park use, walking trail use, and physical activity (moderate-to-vigorous physical activity (MVPA) by seasons. Frequencies for physical activities were calculated for gender, age groups, and season. Separate Pearson's chi-square analyses were used to address variations in physical activity, age, gender, intensity level of physical activity by season, between walk-trails users and non walk-trail users.^ People visiting the park engaged in more sedentary behavior in winter than summer and a higher percentage engaged in MVPA in the summer than winter (p<.05). More females engaged in light activity compared to males (p<.05). Walk-trail users consisted mostly of females and engaged in more light activity than non walk-trail users (p<.05) who participated in more MVPA.^ Increasing access to parks and walk-trails may be an intervention strategy to increase physical activity among Hispanics. More research is needed to assess promoting trail use and determining long-term effects on physical activity among minority/ethnic groups at greater risk of a sedentary lifestyle and reasons for trail use and non-use. Future studies should focus on the types of activities Hispanics engage in at different parks particularly between men and women. As a result of this study city officials and planners may use this information to build and design parks that cater to the types of activities that Hispanics engage in and may use to meet physical activity guidelines.^

Effects of a health advocacy program to promote physical activity and nutrition behaviors among adolescents: An evaluation of the Young Leaders for Healthy Change program

Background. This study was designed to evaluate the effects of the Young Leaders for Healthy Change program, an internet-delivered program in the school setting that emphasized health advocacy skills-development, on nutrition and physical activity behaviors among older adolescents (13–18 years). The program consisted of online curricular modules, training modules, social media, peer and parental support, and a community service project. Module content was developed based on Social Cognitive Theory and known determinants of behavior for older adolescents. ^ Methods. Of the 283 students who participated in the fall 2011 YL program, 38 students participated in at least ten of the 12 weeks and were eligible for this study. This study used a single group-only pretest/posttest evaluation design. Participants were 68% female, 58% white/Caucasian, 74% 10th or 11th graders, and 89% mostly A and/or B students. The primary behavioral outcomes for this analysis were participation in 60-minutes of physical activity per day, 20-minutes of vigorous- or moderate- intensity physical activity (MVPA) participation per day, television and computer time, fruit and vegetable (FV) intake, sugar-sweetened beverage intake, and consumption of breakfast, home-cooked meals, and fast food. Other outcomes included knowledge, beliefs, and attitudes related to healthy eating, physical activity, and advocacy skills. ^ Findings. Among the 38 participants, no significant changes in any variables were observed. However, among those who did not previously meet behavioral goals there was an 89% increase in students who participated in more than 20 minutes of MVPA per day and a 58% increase in students who ate home-cooked meals 5–7 days per week. The majority of participants met program goals related to knowledge, beliefs, and attitudes prior to the start of the program. Participants reported either maintaining or improving to the goal at posttest for all items except FV intake knowledge, taste and affordability of healthy foods, interest in teaching others about being healthy, and ease of finding ways to advocate in the community. ^ Conclusions. The results of this evaluation indicated that promoting healthy behaviors requires different strategies than maintaining healthy behaviors among high school students. In the school setting, programs need to target the promotion and maintenance of health behaviors to engage all students who participate in the program as part of a class or club activity. Tailoring the program using screening and modifying strategies to meet the needs of all students may increase the potential reach of the program. The Transtheoretical Model may provide information on how to develop a tailored program. Additional research on how to utilize the constructs of TTM effectively among high school students needs to be conducted. Further evaluation studies should employ a more expansive evaluation to assess the long-term effectiveness of health advocacy programming.^

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

Automatic physical activity pattern recognition and meal intake modelling in type 1 diabetes for their inclusion in artificial pancreas systems

La diabetes comprende un conjunto de enfermedades metabólicas que se caracterizan por concentraciones de glucosa en sangre anormalmente altas. En el caso de la diabetes tipo 1 (T1D, por sus siglas en inglés), esta situación es debida a una ausencia total de secreción endógena de insulina, lo que impide a la mayoría de tejidos usar la glucosa. En tales circunstancias, se hace necesario el suministro exógeno de insulina para preservar la vida del paciente; no obstante, siempre con la precaución de evitar caídas agudas de la glucemia por debajo de los niveles recomendados de seguridad. Además de la administración de insulina, las ingestas y la actividad física son factores fundamentales que influyen en la homeostasis de la glucosa. En consecuencia, una gestión apropiada de la T1D debería incorporar estos dos fenómenos fisiológicos, en base a una identificación y un modelado apropiado de los mismos y de sus sorrespondientes efectos en el balance glucosa-insulina. En particular, los sistemas de páncreas artificial –ideados para llevar a cabo un control automático de los niveles de glucemia del paciente– podrían beneficiarse de la integración de esta clase de información. La primera parte de esta tesis doctoral cubre la caracterización del efecto agudo de la actividad física en los perfiles de glucosa. Con este objetivo se ha llevado a cabo una revisión sistemática de la literatura y meta-análisis que determinen las respuestas ante varias modalidades de ejercicio para pacientes con T1D, abordando esta caracterización mediante unas magnitudes que cuantifican las tasas de cambio en la glucemia a lo largo del tiempo. Por otro lado, una identificación fiable de los periodos con actividad física es un requisito imprescindible para poder proveer de esa información a los sistemas de páncreas artificial en condiciones libres y ambulatorias. Por esta razón, la segunda parte de esta tesis está enfocada a la propuesta y evaluación de un sistema automático diseñado para reconocer periodos de actividad física, clasificando su nivel de intensidad (ligera, moderada o vigorosa); así como, en el caso de periodos vigorosos, identificando también la modalidad de ejercicio (aeróbica, mixta o de fuerza). En este sentido, ambos aspectos tienen una influencia específica en el mecanismo metabólico que suministra la energía para llevar a cabo el ejercicio y, por tanto, en las respuestas glucémicas en T1D. En este trabajo se aplican varias combinaciones de técnicas de aprendizaje máquina y reconocimiento de patrones sobre la fusión multimodal de señales de acelerometría y ritmo cardíaco, las cuales describen tanto aspectos mecánicos del movimiento como la respuesta fisiológica del sistema cardiovascular ante el ejercicio. Después del reconocimiento de patrones se incorpora también un módulo de filtrado temporal para sacar partido a la considerable coherencia temporal presente en los datos, una redundancia que se origina en el hecho de que en la práctica, las tendencias en cuanto a actividad física suelen mantenerse estables a lo largo de cierto tiempo, sin fluctuaciones rápidas y repetitivas. El tercer bloque de esta tesis doctoral aborda el tema de las ingestas en el ámbito de la T1D. En concreto, se propone una serie de modelos compartimentales y se evalúan éstos en función de su capacidad para describir matemáticamente el efecto remoto de las concetraciones plasmáticas de insulina exógena sobre las tasas de eleiminación de la glucosa atribuible a la ingesta; un aspecto hasta ahora no incorporado en los principales modelos de paciente para T1D existentes en la literatura. Los datos aquí utilizados se obtuvieron gracias a un experimento realizado por el Institute of Metabolic Science (Universidad de Cambridge, Reino Unido) con 16 pacientes jóvenes. En el experimento, de tipo ‘clamp’ con objetivo variable, se replicaron los perfiles individuales de glucosa, según lo observado durante una visita preliminar tras la ingesta de una cena con o bien alta carga glucémica, o bien baja. Los seis modelos mecanísticos evaluados constaban de: a) submodelos de doble compartimento para las masas de trazadores de glucosa, b) un submodelo de único compartimento para reflejar el efecto remoto de la insulina, c) dos tipos de activación de este mismo efecto remoto (bien lineal, bien con un punto de corte), y d) diversas condiciones iniciales. ABSTRACT Diabetes encompasses a series of metabolic diseases characterized by abnormally high blood glucose concentrations. In the case of type 1 diabetes (T1D), this situation is caused by a total absence of endogenous insulin secretion, which impedes the use of glucose by most tissues. In these circumstances, exogenous insulin supplies are necessary to maintain patient’s life; although caution is always needed to avoid acute decays in glycaemia below safe levels. In addition to insulin administrations, meal intakes and physical activity are fundamental factors influencing glucose homoeostasis. Consequently, a successful management of T1D should incorporate these two physiological phenomena, based on an appropriate identification and modelling of these events and their corresponding effect on the glucose-insulin balance. In particular, artificial pancreas systems –designed to perform an automated control of patient’s glycaemia levels– may benefit from the integration of this type of information. The first part of this PhD thesis covers the characterization of the acute effect of physical activity on glucose profiles. With this aim, a systematic review of literature and metaanalyses are conduced to determine responses to various exercise modalities in patients with T1D, assessed via rates-of-change magnitudes to quantify temporal variations in glycaemia. On the other hand, a reliable identification of physical activity periods is an essential prerequisite to feed artificial pancreas systems with information concerning exercise in ambulatory, free-living conditions. For this reason, the second part of this thesis focuses on the proposal and evaluation of an automatic system devised to recognize physical activity, classifying its intensity level (light, moderate or vigorous) and for vigorous periods, identifying also its exercise modality (aerobic, mixed or resistance); since both aspects have a distinctive influence on the predominant metabolic pathway involved in fuelling exercise, and therefore, in the glycaemic responses in T1D. Various combinations of machine learning and pattern recognition techniques are applied on the fusion of multi-modal signal sources, namely: accelerometry and heart rate measurements, which describe both mechanical aspects of movement and the physiological response of the cardiovascular system to exercise. An additional temporal filtering module is incorporated after recognition in order to exploit the considerable temporal coherence (i.e. redundancy) present in data, which stems from the fact that in practice, physical activity trends are often maintained stable along time, instead of fluctuating rapid and repeatedly. The third block of this PhD thesis addresses meal intakes in the context of T1D. In particular, a number of compartmental models are proposed and compared in terms of their ability to describe mathematically the remote effect of exogenous plasma insulin concentrations on the disposal rates of meal-attributable glucose, an aspect which had not yet been incorporated to the prevailing T1D patient models in literature. Data were acquired in an experiment conduced at the Institute of Metabolic Science (University of Cambridge, UK) on 16 young patients. A variable-target glucose clamp replicated their individual glucose profiles, observed during a preliminary visit after ingesting either a high glycaemic-load or a low glycaemic-load evening meal. The six mechanistic models under evaluation here comprised: a) two-compartmental submodels for glucose tracer masses, b) a single-compartmental submodel for insulin’s remote effect, c) two types of activations for this remote effect (either linear or with a ‘cut-off’ point), and d) diverse forms of initial conditions.

Prospective study of physical activity and depressive symptoms in middle-aged women

Background: Although many studies support an inverse association between physical activity (PA) and depressive symptoms, prospective relationships between these variables have been confounded by pre-existing psychological and physical health problems. Methods: This study examined the dose-response relationships between self-reported PA and depressive symptoms, using cross-sectional and prospective data from a population-based cohort of middle-aged women who participated in the Australian Longitudinal Study on Women's Health (ALSWH) between 1996 and 2001. Participants completed three mailed surveys (SI, 1996; S2, 1998; S3, 2001), which included questions about time spent in walking, moderate- and vigorous-intensity PA, and measures of psychological health (Center for Epidemiologic Studies Depression scale [CESD-10], and Mental health [MH] subscale of the Short Form 36 survey). Relationships between previous (SI, S2), current (S3), and habitual (S1, S2, S3) PA and depressive symptoms were examined, adjusting for sociodemographic and health-related variables (n = 9207). Results: Mean CESD-10 scores decreased, and MH scores increased with increasing levels of previous, current, and habitual activity. Odds ratios for CESD-10 scores >= 10 or MH scores = 60 minutes of moderate-intensity PA per week, compared with those who reported less PA than this. Women who were in the lowest PA category at SI, but who subsequently reported >= 240 metabolic equivalent minutes (MET.mins) per week had lower odds of CESD-10 scores of >= 10 or MH scores

Validity of accelerometry for measurement of activity in people with brain injury

Purpose: To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods: Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results: Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions: Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

Levels of physical activity for colon cancer prevention compared with generic public health recommendations: Population prevalence and sociodemographic correlates

Background: The proportion of Australian adults achieving physical activity levels believed to be sufficient for colon cancer prevention was estimated, and sociodemographic correlates (age, gender, educational attainment, occupation, marital status, and children in household) of meeting these levels of activity were analyzed. Methods: Data from the 2000 National Physical Activity Survey were used to estimate the prevalence of participation in physical activity in relation to three criteria: generic public health recommendations, weekly amount of at least moderate-intensity physical activity currently believed to reduce risk of colon cancer, and weekly amount of vigorous-intensity physical activity believed to reduce risk of colon cancer. Results: Overall, 46% of adults met the generic public health criterion, 26% met the colon cancer criterion based on participation in at least moderate-intensity physical activity, and 10% met the colon cancer criterion based on vigorous-intensity physical activity. Women were less likely than men to meet the colon cancer criteria. Younger and more educated persons were more likely to meet all three criteria. The most pronounced differences between gender, age, and educational attainment groups were found for meeting the amount of vigorous-intensity physical activity believed to reduce risk of colon cancer. Conclusions: The population prevalence for meeting proposed physical activity criteria for colon cancer prevention is low and much lower than that related to the more generic public health recommendations. If further epidemiologic studies confirm that high volumes and intensities of activity are required, the public health challenges for colon cancer will be significant.