Differences In Inactivity Research Articles

Accelerometer and Survey Data on Patterns of Physical Inactivity in New York City and the United States.

Inactive lifestyles contribute to health problems and premature death and are influenced by the physical environment. The primary objective of this study was to quantify patterns of physical inactivity in New York City and the United States by combining data from surveys and accelerometers. We used Poisson regression models and self-reported survey data on physical activity and other demographic characteristics to predict accelerometer-measured inactivity in New York City and the United States among adults aged ≥18. National data came from the 2003-2004 and 2005-2006 National Health and Nutrition Examination Surveys. New York City data came from the 2010-2011 New York City Physical Activity and Transit survey. Self-reported survey data indicated no significant differences in inactivity between New York City and the United States, but accelerometer data showed that 53.1% of persons nationally, compared with 23.4% in New York City, were inactive ( P < .001). New Yorkers reported a median of 139 weekly minutes of transportation activity, compared with 0 minutes nationally. Nationally, 50.0% of self-reported activity minutes came from recreation activity, compared with 17.5% in New York City. Regression models indicated differences in the association between self-reported minutes of transportation and recreation and accelerometer-measured inactivity in the 2 settings. The prevalence of physical inactivity was higher nationally than in New York City. The largest difference was in walking behavior indicated by self-reported transportation activity. The study demonstrated the feasibility of combining accelerometer and survey measurement and that walkable environments promote an active lifestyle.

Barren diets increase wakeful inactivity in calves

Inactivity is a vastly understudied behavioural category, which may reflect positive or negative affective states in captive or domesticated animals. Increased inactivity in barren-housed animals, in combination with an increased or decreased interest in stimuli, e.g. novel objects, can indicate boredom or apathy. Another theory is that inactivity is an alternative strategy to stereotypies to cope with sub-optimal conditions. The aim of this study was to further our understanding of inactive behaviours and possible associated negative affective states in intensively raised calves fed different diets. In two separate experiments, Holstein-Friesian veal calves (N=40+160) were fed barren or enriched diets: 1) imposed/restricted diet versus free dietary choice (experiment 1); 2) no additional straw versus ad libitum provision of straw (experiment 2); 3) low versus high solid feed provision (experiment 2); 4) bucket versus automated milk dispenser for milk replacer feeding, with high or low solid feed provision (experiment 2). Inactive behaviours, i.e. experiment 1: lie, idle and sleep; experiment 2: lie idle, stand idle, and sleep, were recorded at two ages (experiment 1: 12 and 26wk; experiment 2: 15 and 24wk) using instantaneous scan sampling. In experiment 2, latency to touch two novel objects was recorded at 15 and 24wk. No differences in inactivity were found between calves with a restricted or free choice diet (experiment 1). However, calves fed the more barren diets in experiment 2 showed more lying idle at 24wk of age, and calves with no ad libitum straw in particular, showed more standing idle at 24wk of age (P<0.05). No differences in latency to touch the novel objects were found. Therefore, although barren diets were generally associated with higher levels of inactivity, we found no support that this inactivity reflected boredom or apathy. Only weak associations were found between inactivity and stereotypies, providing only limited support for the idea that these constitute alternative strategies to cope with sub-optimal conditions.

Shifting the Physical Inactivity Curve Worldwide by Closing the Gender Gap.

The aims of this study were to (i) examine gender differences in physical inactivity in countries with different levels of Human Development Index (HDI); and (ii) assess whether small changes in the prevalence of inactivity in women could achieve the World Health Organization's (WHO) global inactivity target. Data on inactivity were extracted for 142 countries for the year 2010 from the WHO Data Repository. Data for HDI were obtained for the year 2010 from the United Nations Development Program. Absolute and relative gender differences were calculated for countries according to four HDI categories. The potential effects of increasing women's activity levels on achievement of the WHO physical inactivity target were computed. Overall inactivity prevalence was higher in women (27%) than in men (20%). Women were more inactive than men in all except eight countries. Absolute gender differences [median 7.5% (range -10.1 to 33.2)] did not vary by HDI category, but there was a small negative correlation between relative gender difference in inactivity and HDI (rho -0.19; p=0.02), which was mostly influenced by three outlier countries with low HDI. A decrease in inactivity levels of 4.8% points among women across the world would achieve the WHO target of reducing global levels of inactivity by 10%. Gender differences in the prevalence of physical inactivity were highly variable, both within and across categories of HDI. Interventions which result in small changes in inactivity prevalence in women would achieve the 2025 WHO global target for inactivity, without any change to the prevalence in men.

Effects of childhood socio-economic conditions on educational differences in leisure-time physical activity

Our purpose was to assess the direct and indirect contribution of childhood socio-economic conditions to educational differences in leisure-time physical activity among women and men. Population-based data were derived from a representative sample of Finns aged >or=30 years (N = 7112) as part of Health 2000 Survey. Multinomial logistic regression analysis was applied. Leisure-time physical activity was divided into inactivity, moderate and high activity. Childhood socio-economic conditions had both a direct and indirect effect through adulthood socio-economic conditions on educational differences in leisure-time physical activity. The direct effect of childhood socio-economic conditions on educational differences in inactivity was stronger than its indirect effects through adulthood socio-economic conditions and other health behaviours and related factors. Adulthood socio-economic conditions had a considerable indirect effect on educational differences in leisure-time physical activity through other adulthood health behaviours and related factors among men. In order to narrow educational differences in leisure-time physical activity, we should secure a childhood environment that enables a physically active lifestyle, support leisure-time physical activity in diverse occupational groups, guarantee equal physical activity possibilities across different educational careers and support those with insufficient material resources.

Can neighborhoods explain racial/ethnic differences in adolescent inactivity?

To determine if neighborhoods and their attributes contribute to racial/ethnic disparities in adolescent inactivity. We undertook a cross-sectional analysis of the National Longitudinal Study of Adolescent Health (n = 17,007), a nationally representative school-based study in the United States. Stratifying by gender, we used multivariate linear regression and multi-level modeling to determine whether neighborhood of residence may partially explain racial/ethnic disparities in adolescent physical inactivity, defined as hours viewing television or videos/DVDs and/or playing computer/video games each week. Participants lived in largely segregated communities. Black and Hispanic adolescent girls reported higher levels of inactivity than White adolescent girls (21 vs. 15 vs. 13 hours/week, respectively, p <0.001). Similar patterns were seen in adolescent boys, with Black adolescent males reporting a mean of 26 hours/week; Hispanic boys a mean of 20 hours/week; and White boys a mean of 17 hours/week of inactivity (p <0.001). After accounting for between-neighborhood variation, there were no residual within-neighborhood differences in inactivity between Hispanic and White adolescent girls (gamma = -0.06, p =0.93); when living in the same neighborhood Hispanic and White girls had similar levels of inactivity. Black adolescent girls and boys were found to have higher levels of inactivity no matter where they lived (gamma =7.00, p <0.001 for girls; gamma = 6.96, p <0.001 for boys). Hispanic boys had similar patterns of inactivity to White boys (gamma =-1.57, p = 0.12). In both males and females, the reported rate of violent crime in the neighborhood was associated with inactivity, despite the individual's perception of his/her neighborhood as safe not being predictive. Although inactivity varies by race/ethnicity and gender, only in Hispanic adolescent girls does neighborhood fully explain the differential use. Our findings suggest that approaches other than changing neighborhood characteristics are needed to eliminate racial/ethnic disparities in adolescent inactivity.

Race/Ethnicity, Social Class, and Leisure-Time Physical Inactivity

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. 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. 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. 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.

Race/ethnicity And Leisure Time Physical Inactivity

Social class and occupational physical activity (PA) are hypothesized to confound the relationship between race/ethnicity and leisure time physical inactivity, yet these variables are rarely measured and analyzed in the health disparity literature. PURPOSE (a) describe the prevalence of leisure time physical inactivity in a nationally representative sample of non-Hispanic white, non-Hispanic black, and Hispanic/Latino men and women, (b) describe the prevalence of inactivity between these racial/ethnic groups across different indicators of social class, and (c) describe the relationship between occupational PA and leisure time inactivity in different racial/ethnic groups, independent of other social class indicators. METHODS The National Physical Activity and Weight Loss Survey (NPAWLS) was a nationwide random-digit-dialed telephone survey conducted between Sept. and Dec. 2002 of non-institutionalized U.S. adults (4,695 men, 6,516 women). Self-reported PA was assessed using the same questions as the 2001 Behavioral Risk Factor Surveillance System (BRFSS). Respondents who reported no moderate- or vigorous-intensity PA during leisure time in a usual week were classified as inactive. Occupational PA was assessed using questions about the time spent sitting and standing, walking, and performing heavy labor at work. Indicators of social class were education level, family income, and employment status. RESULTS Based on responses from 9,806 adults, the age-adjusted prevalence (per 100) of physical inactivity was 10 (SE = 0.6) and 12 (SE = 0.6) among white men and women, respectively; 19 (SE = 2.5) and 25 (SE = 2.1) among non-Hispanic black men and women, and 21 (SE = 2.1) and 27 (SE = 2.5) among Hispanic/Latino men and women. Within each racial/ethnic group, the prevalence of inactivity was highest among participants with lower social class. Differences in inactivity between racial/ethnic groups became less evident after accounting for social class. The odds of being inactive during leisure time did not differ significantly across quartiles of occupational physical activity. This finding was consistent for each racial/ethnic group, and after adjusting for age, sex, and social class. CONCLUSIONS Non-Hispanic blacks and Hispanic/Latinos are more inactive during leisure time than their Non-Hispanic white counterparts. Social class, but not occupational PA, appears to moderate the relationship between race/ethnicity and leisure time inactivity. Supported by a CDC Cooperative Agreement (SIP 20_01), U48/CCU409664.