Biomedical subjects

Jared P Reis

Publications and source records attributed to Jared P Reis.

10 recordsLinked to original sources

PubMed2007

Discrepancies between methods of identifying objectively determined physical activity.

UNLABELLED: Current methods for validating physical activity (PA) questionnaires typically use accelerometers as objective measures for comparison with questionnaire responses and obtain low correlations or agreement. PURPOSE: We examined possible reasons for weak associations in validation studies by comparing published ActiGraph accelerometer intensity cut points with cut points based on intensity thresholds for heart rate response to PA. METHODS: Twelve adults (five men, seven women; age 31.0 +/- 14.3 yr) wore an ActiGraph accelerometer and a Polar Vantage NV heart watch simultaneously for seven consecutive days during their waking hours. We identified PA bouts from the minute-by-minute ActiGraph data using published accelerometer thresholds for defining moderate- and vigorous-intensity PA. We then compared PA bout intensities identified with these criteria with intensity classifications of the PA bouts using mean percent heart rate reserve (HRR). RESULTS: Most of the moderate-intensity PA bouts identified by the Freedson (78.3%), Swartz (88.0%), and Hendelman (94.7%) ActiGraph cut points were associated with a mean %HRR < 45% (very light and light intensities). The estimated mean frequency with which study participants engaged in moderate-intensity PA varied with the cut points and type of bouts used and ranged from 1.1 d.wk(-1) (45-60%HRR) to 7.0 d.wk(-1) (Hendelman cut points). The mean total duration on active days ranged from 17.9 min.d(-1)(45-60%HRR) to 139.2 min.d(-1) (Hendelman cut points). Fewer bouts of vigorous PA were found in the accelerometer data, and most were in the vigorous-intensity category of > or = 60%HRR. CONCLUSIONS: The method used for analyzing ActiGraph activity data can result in large differences in the summary measure of minutes of moderate- to vigorous-intensity activity.

Adult↗

PubMed2007

Race/ethnicity, social class, and leisure-time physical inactivity.

PURPOSE: The aims of this study were to determine 1) prevalence of leisure-time physical inactivity in a nationally representative sample of non-Hispanic white, non-Hispanic black, and Hispanic men and women; 2) prevalence of leisure-time inactivity by racial/ethnic group across social class indicators; and 3) the relationship between leisure-time inactivity and occupational physical activity, independent of other social class indicators. METHODS: The National Physical Activity and Weight Loss Survey was a telephone survey of noninstitutionalized U.S. adults (4695 men, 6516 women) conducted by random digit dialing between September and December 2002. Self-reported physical activity was assessed using questions from the 2001 Behavioral Risk Factor Surveillance System. Respondents who reported no moderate- or vigorous-intensity physical activity during leisure time in a usual week were classified as inactive. Indicators of social class were education, family income, employment status, and marital status. RESULTS: Age-adjusted prevalence of leisure-time inactivity was 9.9% +/- 0.6 SE (standard error) and 12.0 +/- 0.6 for white men and women, respectively; 19.0 +/- 2.5 and 25.2 +/- 2.1 for non-Hispanic black men and women, and 20.9 +/- 2.1 and 27.3 +/- 2.5 for Hispanic men and women. Within each racial/ethnic group, prevalence of leisure-time inactivity was highest among participants of lower social class. Differences in inactivity by racial/ethnic group were less evident after adjustment for social class. Odds of inactivity were similar across quartiles of occupational physical activity after adjustment for age, sex, and social class. CONCLUSIONS: Non-Hispanic blacks and Hispanics were more inactive during their leisure time than were non-Hispanic whites. Social class but not occupational physical activity seems to moderate the relationship between race/ethnicity and leisure-time physical inactivity.

Adolescent↗

PubMed2006

Comparison of the 2001 BRFSS and the IPAQ Physical Activity Questionnaires.

PURPOSE: The 2001 Behavioral Risk Factor Surveillance System (BRFSS) physical activity module and the International Physical Activity Questionnaire (IPAQ) are used in population studies to determine the prevalence of physical activity. The comparability of the prevalence estimates has not been compared in U.S. adults. This study compares the physical activity prevalence estimates from the BRFSS and the IPAQ. METHODS: A telephone survey was administered to a random sample of 11,211 U.S. adults aged 18-99 yr who were enrolled in the National Physical Activity and Weight Loss Survey. Data were analyzed from 9945 adults who provided complete data on the BRFSS and the IPAQ. Prevalence estimates were computed (1) applying the BRFSS scoring scheme for both questionnaires (2). Kappa statistics were used to compare prevalence estimates generated from the BRFSS and the IPAQ. RESULTS: When scored using the BRFSS protocol, agreement between physical activity categories was fair (kappa = 0.34-0.49). Prevalence estimates were higher on the IPAQ than the BRFSS for the lowest category (inactive) by 0.1-3.9% and for the highest category (meets recommendations) by 0.2-9.7%. When scored using their own scoring, agreement between physical activity categories was lower (kappa = 0.26-0.39). The prevalence estimates on the IPAQ were higher than on the BRFSS for the lowest physical activity category by 0.2-13.3% and for the highest physical activity category by 0-16.4%. Differences in physical activity categories were observed for sex, age, income, education, and body mass index on both questionnaires. CONCLUSION: Because of differences in the physical activity prevalence estimates, direct comparison of the BRFSS and IPAQ prevalence estimates is not recommended.

Adolescent↗

PubMed2005

Reliability and validity of the occupational physical activity questionnaire.

INTRODUCTION: Few questionnaires have been designed for wide-scale, population-based surveillance of occupational physical activity (PA) behaviors. PURPOSE: This study was conducted to determine the test-retest reliability and validity of the Occupational Physical Activity Questionnaire (OPAQ) designed to assess the usual weekly duration of occupational sitting or standing, walking, and heavy labor activities. METHODS: Analyses were based on a convenience sample of 41 adults (13 men, 28 women) (mean+/- SD, 38.8+/- 9.9 yr) who worked in a broad range of occupations. Intraclass correlation coefficients (ICC) were used to evaluate the 2-wk test-retest reliability of the OPAQ. Spearman correlations were used to assess criterion (occupational PA record, Actigraph) and construct (cardiorespiratory fitness, percent body fat) related validity. Convergent validity with the current Behavioral Risk Factor Surveillance System (BRFSS) occupational PA question was evaluated with the kappa coefficient. RESULTS: The 2-wk test-retest reliability coefficients for the OPAQ hours per week ranged from an ICC of 0.55 to 0.91. Fair-to-substantial criterion validity was observed for like activities on the OPAQ and a detailed 7-d occupational PA record for sitting or standing (r=0.37), walking (r=0.74), and heavy labor activity (r=0.31). OPAQ walking was related to PA record moderate-intensity PA (r=0.41), Actigraph occupational light-intensity counts (r=0.41), and Actigraph total counts (r=0.44). Associations observed between the OPAQ and submaximal exercise heart rate or percent body fat were low (r=-0.17 to 0.32). Convergent validity displaying the ability of the OPAQ to correctly identify participants who performed mostly sitting or standing, mostly walking, or mostly heavy labor at work was substantial [kappa=0.71 (95% CI=0.49, 0.94)]. CONCLUSIONS: The test-retest reliability and validity of the OPAQ are similar to other established occupational PA questionnaires. This preliminary study supports the use of the OPAQ in research and surveillance settings.

Adult↗

PubMed2004

The prevalence of leisure-time physical activity among diabetics in South Carolina.

BACKGROUND: Diabetes is the seventh leading cause of death among South Carolinians. The benefit of physical activity on the control and prevention of diabetes has been established. This study determined the prevalence of leisure-time physical activity among South Carolinians with and without diabetes and compared the physical activity of those with diabetes between 1990 and 2000. METHODS: Data from the South Carolina Behavioral Risk Factor Surveillance System were used to classify adults with and without diabetes into categories of physical activity. RESULTS: Physical inactivity was higher among South Carolinians with diabetes (42%) than in those without (27%). A comparison of physical activity in diabetics between 1990 and 2000 demonstrated a slight decrease (2%) in physical inactivity. CONCLUSION: The decrease in physical inactivity among diabetics is encouraging; however, further promotion of physical activity is recommended to encourage diabetics to engage in physical activity on a regular basis.

Adult↗

PubMed2004

A preliminary study of one year of pedometer self-monitoring.

BACKGROUND: Long-term pedometer monitoring has not been attempted. PURPOSE: The purpose of this project was to collect 365 days of continuous self-monitored pedometer data to explore the natural variability of physical activity. METHODS: Twenty-three participants (7 men, 16 women; M age = 38 +- 9.9 years; M body mass index = 27.7 +- 6.2 kg/m2) were recruited by word of mouth at two southern U.S. universities. Participants were asked to wear pedometers at their waist during waking hours and record steps per day and daily behaviors (e.g., sport/exercise, work or not) on a simple calendar. In total, participants wore pedometers and recorded 8,197 person-days of data (of a possible 8,395 person-days, or 98%) for a mean of 10,090 +- 3,389 steps/day. Missing values were estimated using the Missing Values Analysis EM function in SPSS, Version 11.0.1. RESULTS: A mean of 10,082 +- 3,319 steps/day was computed. Using the corrected data, differences in steps/day were significant for season (summer > winter, F = 7.57, p = .001), day of the week (weekday > weekend, F = 3.97, p = .011), type of day (workday vs. nonworkday, F = 9.467, p = .008), and participation in sport/exercise (day with sport/exercise > day without sport/exercise, F = 102.5, p < .0001). CONCLUSIONS: These data suggest that surveillance should be conducted in the spring/fall or that an appropriate correction factor should be considered if the intent is to capture values resembling the year-round average.

Adult↗

PubMed2004

Descriptive epidemiology of pedometer-determined physical activity.

PURPOSE: The dual purposes of this study were: 1) to provide preliminary descriptive epidemiology data representing pedometer-determined physical activity (PA) and 2) to explore sources of intra-individual variability in steps per day. METHODS: All participants (76 males, age = 48.4 +/- 16.3 yr, body mass index (BMI) = 27.1 +/- 5.1 kg x m(-2); 133 females, age = 47.4 +/- 17.5 yr, BMI = 26.9 +/- 5.7 kg x m(-2)) resided in Sumter County, SC, and were recruited by telephone to receive a mailed kit to self-monitor PA for 1 wk. Statistical analyses compared mean steps per day between sexes, races, age groups, education and income levels, and BMI categories. Mean steps per day were also compared between: 1) weekdays versus weekend days, 2) workdays versus nonworkdays, and 3) days of sport/exercise versus no participation. RESULTS: The entire sample took 5931 +/- 3664 steps x d(-1) (males = 7192 +/- 3596 vs females = 5210 +/- 3518 steps x d(-1), t = 7.88, P < 0.0001). Significant differences were also indicated by race, age, education, income, and BMI. In addition, weekdays were significantly higher than weekend days, workdays were higher than nonworkdays, and sport/exercise days were higher than nonsport/exercise days. CONCLUSIONS: The large standard deviations reflect a wide distribution of ambulatory behavior. Regardless, important differences are still evident by demographic characteristics, BMI categories, day of the week, and reported engagement in work or sport/exercise.

Adolescent↗

PubMed2004

Nonoccupational physical activity by degree of urbanization and U.S. geographic region.

PURPOSE: To estimate levels of nonoccupational leisure-time physical activity (LTPA) by degree of urbanization and geographic region of the United States. METHODS: Participants were respondents to the Behavioral Risk Factor Surveillance System (BRFSS) in 2001 (N = 137,359). Moderate- and vigorous-intensity LTPA was categorized as meeting recommended levels, insufficient, or inactive. The U.S. Department of Agriculture rural-urban continuum codes were used to describe degrees of urbanization (metro, large urban, small urban, and rural). Geographic regions were defined by the U.S. Bureau of the Census (Northeast, Midwest, South, and West). Prevalence estimates were calculated using sample weights to account for the design of the BRFSS. Multivariate logistic regression analyses examined regional differences in the odds of physical inactivity (physically inactive vs insufficient or meets) by degree of urbanization after adjustment for sex, age, race, BMI, education, and occupational physical activity. RESULTS: Large urban areas (49.0%) and the western United States (49.0%) had the highest prevalence of recommended levels of LTPA. Rural areas (24.1%) and the southern United States (17.4%) had the highest prevalence of inactivity. Adults living in the four urbanization categories of the midwestern (metro (OR = 1.47, 95% CI = 1.31, 1.65), large urban (OR = 1.83, 95% CI = 1.51, 2.23), small urban (OR = 1.99, 95% CI = 1.65, 2.40), and rural (OR = 2.59, 95% CI = 1.35, 4.97)); and southern (metro (OR = 1.70, 95% CI = 1.53, 1.88), large urban (OR = 2.04, 95% CI = 1.72, 2.41), small urban (OR = 2.32, 95% CI = 2.02, 2.67), and rural (OR = 5.49, 95% CI = 2.82, 10.68)) U.S. regions were more likely to be inactive than adults living in similar areas of the western United States. Adults in northeast metro and large urban areas (OR = 1.62, 95% CI = 1.45, 1.81; and OR = 1.37, 95% CI = 1.08, 1.74, respectively) were more likely to be inactive than those residing in western metro and large urban areas. CONCLUSION: The prevalence of physical inactivity varies by degree of urbanization and geographic region of the United States.

Activities of Daily Living↗

PubMed2004

Utility of pedometers for assessing physical activity: construct validity.

Valid assessment of physical activity is necessary to fully understand this important health-related behaviour for research, surveillance, intervention and evaluation purposes. This article is the second in a companion set exploring the validity of pedometer-assessed physical activity. The previous article published in Sports Medicine dealt with convergent validity (i.e. the extent to which an instrument's output is associated with that of other instruments intended to measure the same exposure of interest). The present focus is on construct validity. Construct validity is the extent to which the measurement corresponds with other measures of theoretically-related parameters. Construct validity is typically evaluated by correlational analysis, that is, the magnitude of concordance between two measures (e.g. pedometer-determined steps/day and a theoretically-related parameter such as age, anthropometric measures and fitness). A systematic literature review produced 29 articles published since > or =1980 directly relevant to construct validity of pedometers in relation to age, anthropometric measures and fitness. Reported correlations were combined and a median r-value was computed. Overall, there was a weak inverse relationship (median r = -0.21) between age and pedometer-determined physical activity. A weak inverse relationship was also apparent with both body mass index and percentage overweight (median r = -0.27 and r = -0.22, respectively). Positive relationships regarding indicators of fitness ranged from weak to moderate depending on the fitness measure utilised: 6-minute walk test (median r = 0.69), timed treadmill test (median r = 0.41) and estimated maximum oxygen uptake (median r = 0.22). Studies are warranted to assess the relationship of pedometer-determined physical activity with other important health-related outcomes including blood pressure and physiological parameters such as blood glucose and lipid profiles. The aggregated evidence of convergent validity (presented in the previous companion article) and construct validity herein provides support for considering simple and inexpensive pedometers in both research and practice.

Adolescent↗

PubMed2002

Utility of pedometers for assessing physical activity: convergent validity.

Valid assessment of physical activity is important to researchers and practitioners interested in surveillance, screening, programme evaluation and intervention. The validity of an assessment instrument is commonly considered its most important attribute. Convergent validity is the extent to which an instrument's output is associated with that of other instruments intended to measure the same exposure of interest. A systematic review of the literature produced 25 articles directly relevant to the question of convergent validity of pedometers against accelerometers, observation, and self-reported measures of physical activity. Reported correlations were pooled and a median r-value was computed. Pedometers correlate strongly (median r = 0.86) with different accelerometers (specifically uniaxial accelerometers) depending on the specific instruments used, monitoring frame and conditions implemented, and the manner in which the outputs are expressed. Pedometers also correlate strongly (median r = 0.82) with time in observed activity. Time in observed inactivity correlated negatively with pedometer outputs (median r = -0.44). The relationship with observed steps taken depended upon monitoring conditions and speed of walking. The highest agreement was apparent during ambulatory activity (running, walking) or during sitting (when both observation and pedometers would register few steps taken). There was consistent evidence of reduced accuracy during slow walking. Pedometers correlate moderately with different measures of energy expenditure (median r = 0.68). The relationship between pedometer outputs and energy expenditure is complicated by the use of many different direct and indirect measures of energy expenditure and population samples. Concordance with self-reported physical activity (median r = 0.33) varied depending upon the self-report instrument used, individuals assessed, and how pedometer outputs are expressed (e.g. steps, distance travelled, energy expenditure). Pedometer output has an inverse relationship with reported time spent sitting (r = -0.38). The accumulated evidence herein provides ample support that the simple and inexpensive pedometer is a valid option for assessing physical activity in research and practice.

Activities of Daily Living↗