Measurement and correlates of physical activity behavior among older minority women

Research has shown that physical activity serves a preventive function against the development of several major chronic diseases. However, studying physical activity and its health benefits is difficult due to the complexity of measuring physical activity. The overall aim of this research is to contribute to the knowledge of both correlates and measurement of physical activity. Data from the Women On The Move study were used for this study (n = 260), and the results are presented in three papers. The first paper focuses on the measurement of physical activity and compares an alternate coding method with the standard coding method for calculating energy expenditure from a 7-day activity diary. Results indicate that the alternative coding scheme could produce similar results to the standard coding in terms of total activity expenditure. Even though agreement could not be achieved by dimension, the study lays the groundwork for a coding system that saves considerable amount of time in coding activity and has the ability to estimate expenditure more accurately for activities that can be performed at varying intensity levels. The second paper investigates intra-day variability in physical activity by estimating the variation in energy expenditure for workers and non-workers and identifying the number of days of diary self-report necessary to reliably estimate activity. The results indicate that 8 days of activity are needed to reliably estimate total activity for individuals who don't work and 12 days of activity are needed to reliably estimate total activity for those who work. Days of diary self-report required by dimension for those who don't work range from 6 to 16 and for those who work from 6 to 113. The final paper presents findings on the relationship between daily living activity and Type A behavior pattern. Significant findings are observed for total activity and leisure activity with the Temperament Scale summary score. Significant findings are also observed for total activity, household chores, work, leisure activity, exercise, and inactivity with one or more of the individual items on the Temperament Scale. However, even though some significant findings were observed, the overall models did not reveal meaningful associations. ^

Functional and physical associations of beta1 integrins in the activation of human T lymphocytes

Adhesion involves interactions between cells or cells with extracellular matrix components and is a fundamental process for all multicellular organisms as well as many pathogenic microbes. Integrins are heterodimeric transmembrane proteins that function as adhesion molecules and transduce signals between the extracellular environment and the intracellular cytoskeletal machinery. β1 integrin subfamily is highly expressed on T lymphocytes and mediates cell spreading, adhesion and coactivation. T lymphocytes have an important role in the regulation and homeostasis of the immune system therefore, the goals of this study were to first to investigate β1 integrin interaction with fibronectin binding protein A (FnbpA), a surface protein expressed on gram-negative bacteria Staphylococcus aureus. Second, characterize the association and function of a non-integrin surface protein, CD98, with β1 integrins on T lymphocytes. ^ FnbpA binds to fibronectin (FN), also a ligand for α5β1 and α4β1 integrins on T lymphocytes. Since both bacterial proteins FnbpA and T cell integrins utilize FN, it was of interest to determine the effects FnbpA on T cell activation. Results demonstrated that recombinant FnbpA (rFnbpA) coimmobilized with OKT3 mediated T cell coactivation in a soluble FN-dependent manner. Integrin α5β1 was identified as the main integrin utilized by Staphylococcus aureus FnbpA from studies using soluble antibodies to inhibit T cell proliferation and parallel plate flow chamber assays. The mechanism of rFnbpA-mediated coactivation was one that used soluble FN as a bridge between rFnbpA and integrin α5β1 on the T lymphocyte. ^ Since integrins are utilized by T lymphocytes and bacterial proteins, it was of interest to identify proteins involved in integrin regulation. Anti-CD98 mAb 80A10 was identified and characterized from a screen to identify surface proteins involved in integrin signaling and functions. CD98 is a non-integrin protein that was sensitive to integrin inhibition in human T lymphocyte aggregation and activation, thus suggested that CD98 shared a common signaling pathway with integrins. These results led to the question of whether CD98 physically associates with β1 integrins. Fluorescence microscopy and biochemical analysis determined that CD98 is specifically associated with β1 integrin on human T lymphocytes and may be part of a larger multimolecular signaling complex. ^

Psychological inquiries : in an series of essays, intended to illustrate the mutual relations of the physical organization and the mental faculties

by Sir Benjamin C. Brodie

Association of self-reported physical activity and performance in the physical fitness assessment among Airmen

The U.S. Air Force, as with the other branches of military services, has physical fitness standards imposed on their personnel. These standards ensure a healthy and fit combat force. To meet these standards, Airmen have to maintain a certain level of physical activity in their lifestyle. Objective. This was a cross sectional (prevalence) study to evaluate the association of Airmen's self-reported physical activity and their performance in the Air Force Physical Fitness Assessment in 2007. Methods. The self-reported physical activity data were obtained from the Air Force Web Health Assessment (AF WEB HA), a web-based health questionnaire completed by the Airmen during their annual Preventive Health Assessment. The physical activity levels were categorized as having met or not having met the Centers for Disease Control and Prevention (CDC) and the American College of Sports Medicine (ACSM) physical activity recommendations. Physical Fitness scores were collected from the Air Force Fitness Management System (AFFMS), a repository of physical fitness test data. Results. There were 49,029 Airmen who answered the AF WEB HA in 2007 and also took their physical fitness test. 94.4% (n = 46,304) of Airmen met the recommended physical activity guidelines and 79.9% (n = 39,178) passed the fitness test. Total Airmen who both met the physical activity recommendations and passed the fitness test was 75.6% (n = 37,088). Airmen who did not meet the activity recommendations and also failed the fitness test totaled 635 or 1.3% of the study group. The Mantel-Haenszel Chi-Square analysis of the data on the activity levels and the physical fitness test relationship was the following χ2 = 18.52, df 1, and p = <0.0001. The Odds Ratio (OR) was 1.22 (95% CI 1.12, 1.34). Conclusion. The study determined that there was a positive association between Airmen's self-reported physical activity and their performance in the physical fitness 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.^

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.^

The economic cost of type 2 diabetes attributable to physical inactivity in the United States and Texas in 2007

Type 2 diabetes has grown to epidemic proportions in the U.S., and its prevalence has been steadily increasing in Texas. The physical activity levels in the population have remained low despite it being one of the primary preventive strategies for type 2 diabetes. The objectives of this study were to estimate the direct medical costs of type 2 diabetes attributable to not meeting physical activity Guidelines and to physical inactivity in the U.S. and Texas in 2007. This was a cross sectional study that used physical activity prevalence data from the 2007 Behavioral Risk Factor Surveillance System (BRFSS) to estimate the population attributable risk percentage (PAR%) for type 2 diabetes. These data were combined with the prevalence and cost data of type 2 diabetes to estimate the cost of type 2 diabetes attributable to not meeting Guidelines and to inactivity in the U.S. and Texas in 2007.^ The cost of type 2 diabetes in the U.S. in 2007, attributable to not meeting physical activity Guidelines was estimated to be $13.29 billion, and that attributable to physical inactivity (no leisure time physical activity) was estimated to be $3.32 billion. Depending on various assumptions, these estimates ranged from $7.61 billion to $41.48 billion for not meeting Guidelines, and $1.90 billion to $13.20 billion for physical inactivity in the U.S. in 2007. The cost of type 2 diabetes in Texas in 2007 attributable to not meeting physical activity Guidelines was estimated to be $1.15 billion, and that attributable to physical inactivity (no leisure time physical activity) was estimated to be $325 million. Depending on various assumptions, these estimates ranged from $800 million to $3.47 billion for not meeting Guidelines, and $186 million to $1.28 billion for physical inactivity in Texas in 2007. These results illustrate how much money could be saved annually just in terms of type 2 diabetes cost in the U.S. and Texas, if the entire adult population was active enough to meet physical activity Guidelines. Physical activity promotion, particularly at the environmental and policy level should be a priority in the population. ^

Hormone therapy and physical activity as predictors of lung cancer risk and survival: The California Teachers Study

Cigarette smoking is responsible for the majority of lung cancer cases worldwide; however, a proportion of never smokers still develop lung cancer over their lifetime, prompting investigation into additional factors that may modify lung cancer incidence, as well as mortality. Although hormone therapy (HT), physical activity (PA), and lung cancer have been previously examined, the associations remain unclear. This study investigated exposure to HT and PA that may modulate underlying mechanisms of lung cancer etiology and progression among women by using existing, de-identified data from the California Teachers Study (CTS).^ The CTS cohort, established in 1995–1996, has 133,479 active and retired female teachers and administrators, recruited through the California State Teachers Retirement System, and followed annually for cancer diagnosis, death, and change of address. Each woman enrolled in the CTS returned a questionnaire covering a wide variety of issues related to cancer risk and women's health, including recent and past HT use and physical activity, as well as active and environmental cigarette smoke exposure. Complete data to assess the associations between HT and lung cancer risk and survival were available for 60,592 postmenopausal women. Between 1995 and 2007, 727 of these women were diagnosed with invasive lung cancer; 441 of these died. Complete data to assess the associations between PA and lung cancer risk and survival were available for 118,513 women. Between 1995 and 2007, 853 of these women were diagnosed with invasive lung cancer; 516 of these died.^ After careful adjustment for smoking habits and other potential confounders, no measure of HT use was associated with lung cancer risk; however, any HT use (vs. no use) was associated with a decrease in lung-cancer-specific mortality. Specifically, among women who only used estrogen (E-only), decreases in lung cancer mortality were seen for recent use, but not for former use; no association was observed for estrogen plus progestin (E+P). Furthermore, among former users of HT, a statistically significant decrease in lung cancer mortality was observed for E-only use within 5 years prior to baseline, but not for E-only use >5 years prior to baseline. Neither long-term recreational PA nor recent recreational PA alone were associated with lung cancer risk; however, among women with a BMI<25 and ever smokers, high long-term moderate+strenuous PA was associated with a decrease in lung cancer risk. Women with non-local disease showed a decrease in lung cancer mortality associated with increasing duration of strenuous long-term activity, and 1.50-3.00 h/wk/y of recent moderate or recent strenuous PA. Long-term moderate PA was associated with decreased lung cancer mortality in never smokers, whereas recent moderate PA was associated with increased lung cancer mortality in current smokers. ^ Placing our findings in the context of the current literature, HT does not appear to be associated with lung cancer risk and previous studies reporting a protective effect of HT use on lung cancer risk may be subject to residual confounding by smoking. Looking at our findings regarding PA overall, the evidence still remains inconclusive regarding whether or not physical activity influence lung cancer risk or mortality. Our results suggest that recreational PA may associated with decreased lung cancer risk among women with BMI<25 and ever smoking-women; however, residual confounding by smoking should be strongly considered. To our knowledge, this is the first study to investigate lifetime recreational PA and lung cancer mortality among women. Our results contribute to the growing body of knowledge regarding non-smoking-related risk factors for lung cancer incidence and mortality among women. Given the potential clinical and interventional significance, further study and validation of these findings is warranted.^

COMPREHENSIVE CALCULATION-BASED IMRT QA USING R&V DATA, TREATMENT RECORDS, AND A SECOND TREATMENT PLANNING SYSTEM

Purpose: Traditional patient-specific IMRT QA measurements are labor intensive and consume machine time. Calculation-based IMRT QA methods typically are not comprehensive. We have developed a comprehensive calculation-based IMRT QA method to detect uncertainties introduced by the initial dose calculation, the data transfer through the Record-and-Verify (R&V) system, and various aspects of the physical delivery. Methods: We recomputed the treatment plans in the patient geometry for 48 cases using data from the R&V, and from the delivery unit to calculate the “as-transferred” and “as-delivered” doses respectively. These data were sent to the original TPS to verify transfer and delivery or to a second TPS to verify the original calculation. For each dataset we examined the dose computed from the R&V record (RV) and from the delivery records (Tx), and the dose computed with a second verification TPS (vTPS). Each verification dose was compared to the clinical dose distribution using 3D gamma analysis and by comparison of mean dose and ROI-specific dose levels to target volumes. Plans were also compared to IMRT QA absolute and relative dose measurements. Results: The average 3D gamma passing percentages using 3%-3mm, 2%-2mm, and 1%-1mm criteria for the RV plan were 100.0 (σ=0.0), 100.0 (σ=0.0), and 100.0 (σ=0.1); for the Tx plan they were 100.0 (σ=0.0), 100.0 (σ=0.0), and 99.0 (σ=1.4); and for the vTPS plan they were 99.3 (σ=0.6), 97.2 (σ=1.5), and 79.0 (σ=8.6). When comparing target volume doses in the RV, Tx, and vTPS plans to the clinical plans, the average ratios of ROI mean doses were 0.999 (σ=0.001), 1.001 (σ=0.002), and 0.990 (σ=0.009) and ROI-specific dose levels were 0.999 (σ=0.001), 1.001 (σ=0.002), and 0.980 (σ=0.043), respectively. Comparing the clinical, RV, TR, and vTPS calculated doses to the IMRT QA measurements for all 48 patients, the average ratios for absolute doses were 0.999 (σ=0.013), 0.998 (σ=0.013), 0.999 σ=0.015), and 0.990 (σ=0.012), respectively, and the average 2D gamma(5%-3mm) passing percentages for relative doses for 9 patients was were 99.36 (σ=0.68), 99.50 (σ=0.49), 99.13 (σ=0.84), and 98.76 (σ=1.66), respectively. Conclusions: Together with mechanical and dosimetric QA, our calculation-based IMRT QA method promises to minimize the need for patient-specific QA measurements by identifying outliers in need of further review.

Baseline evaluation of environmental physical activity and nutrition support of Texas Medical Center hospital worksites

Background: Obesity is a major health problem in the United States that has reached epidemic proportions. With most U.S adults spending the majority of their waking hours at work, the influence of the workplace environment on obesity is gaining in importance. Recent research implicates worksites as providing an 'obesogenic' environment as they encourage overeating and reduce the opportunity for physical activity. Objective: The aim of this study is to describe the nutrition and physical activity environment of Texas Medical Center (TMC) hospitals participating in the Shape Up Houston evaluation study to develop a scoring system to quantify the environmental data collected using the Environmental Assessment Tool (EAT) survey and to assess the inter-observer reliability of using the EAT survey. Methods: A survey instrument that was adapted from the Environmental Assessment Tool (EAT) developed by Dejoy DM et al in 2008 to measure the hospital environmental support for nutrition and physical activity was used for this study. The inter-observer reliability of using the EAT survey was measured and total percent agreement scores were computed. Most responses on the EAT survey are dichotomous (Yes and No) and these responses were coded with a '0' for a 'no' response and a '1' for a 'yes' response. A summative scoring system was developed to quantify these responses. Each hospital was given a score for each scale and subscale on the EAT survey in addition to a total score. All analyses were conducted using Stata 11 software. Results: High inter-observer reliability is observed using EAT. The percentage agreement scores ranged from 94.4%–100%. Only 2 of the 5 hospitals had a fitness facility onsite and scores for exercise programs and outdoor facilities available for hospital employees ranged from 0–62% and 0–37.5%, respectively. The healthy eating percentage for hospital cafeterias range from 42%–92% across the different hospitals while the healthy vending scores were 0%–40%. The total TMC 'healthy hospital' score was 49%. Conclusion: The EAT survey is a reliable instrument for measuring the physical activity and nutrition support environment of hospital worksites. The study results showed a large variability among the TMC hospitals in the existing physical activity and nutrition support environment. This study proposes cost effective policy changes that can increase environmental support to healthy eating and active living among TMC hospital employees.^