File Name: a colorado statewide survey of walking and its relation to excessive weight .zip
The magnitude of the association between physical activity PA and obesity has been difficult to establish using questionnaires. The aim of the study was to evaluate patterns of PA across BMI-defined weight categories and to examine the independent contribution of PA on weight status, using accelerometers. The study was a cross-sectional population-based study of 3, adults and older people aged 20—85 years, living in Norway.
Background: Although walking is the most popular leisure-time activity for adults, few long-term, longitudinal studies have examined the association between walking, an affordable and accessible form of physical activity, and weight gain. Objective: The objective was to evaluate the association between changes in leisure-time walking and weight gain over a y period. After accounting for nonwalking physical activity, calorie intake, and other covariates, we found a substantial association between walking and annualized weight change; the greatest association was for those with a larger baseline weight.
For example, for women at the 75th percentile of baseline weight, 0. Conclusion: Walking throughout adulthood may attenuate the long-term weight gain that occurs in most adults. See corresponding editorial on page Walking, a relatively inexpensive and easily accessible form of physical activity, has been shown to be acceptable for adults of all ages 1 , 2.
Because it is suitable for most people, walking is generally reported as the most popular leisure-time physical activity for adults 3 — 5 and has been specifically promoted as a targeted activity to achieve national physical activity recommendations 1 , 6.
Walking may contribute to the longitudinal change in overall activity patterns over time. Research findings suggest an inverse relation between walking and adiposity 14 , However, very little data have been published on longitudinal trends in walking, how such trends might impact weight change over the course of adulthood, and whether changes in walking behavior and weight outcomes differ by sex.
Of particular relevance is whether walking, a relatively low-intensity activity, can play a positive role in the reduction of long-term weight gain. In this study we used longitudinal data from the CARDIA Study spanning 15 y and 6 measurement occasions to investigate the association of longitudinal changes in walking, total physical activity, and weight change over a y follow-up. The CARDIA Study is a population-based prospective epidemiologic study of the determinants and evolution of cardiovascular disease risk factors among young adults.
At baseline — , eligible participants aged 18—30 y were enrolled with balance according to race black and white , sex, education high school or less and more than high school , and age 18—24 and 25—30 y from the populations of Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. Specific recruitment procedures were described elsewhere Of the initial participants, there were a total possible 30, observations across the 6 examination periods.
The final sample for analysis included all available exposure, outcome, and covariate data across the 6 examination periods, totaling 23, observations for individuals. Weight was measured to the nearest 0. Weight change was treated as a continuous variable, calculated as the difference between measurements. In statistical models, we used annualized weight change to correct for the unequal time between observations. At each examination, self-reported physical activity was ascertained with the use of an interviewer-administered questionnaire designed for the CARDIA Study.
Participants were asked about the frequency of participation in 13 different activity categories 8 vigorous and 5 moderate of recreational sports, exercise, leisure, and occupational activities over the previous 12 mo.
Moderate activities included nonstrenuous sports eg, softball , walking, bowling, golf, home maintenance eg, gardening and raking , and calisthenics. Physical activity scores are expressed in exercise units EU computed by multiplying the frequency of participation by the intensity of the activity separately for heavy ie, vigorous and moderate activities and summing the 2 subscores for a total physical activity score.
The reliability and validity of the instrument is comparable with that of other activity questionnaires 17 , We created a specific walking score derived from walking items in the physical activity questionnaire described above.
We also categorized walking: period-specific nonwalkers walking score: 0 , tertiles within walking scores ranging from 1 to [level 1 score: 1—24 , level 2 score: 24—48 , and level 3 score: 49— ], and consistent level 4 walkers score: A nonwalking physical activity score total physical activity score minus walking score was also created.
Time-varying measures included age, educational attainment, marital status, smoking status current, former, or never , and calorie intake, calculated from the participants dietary questionnaires at baseline and at the year 7 examinations. The CARDIA diet-history questionnaire collected information about usual dietary practices and quantitative food frequency over the previous 28 d 19 , with reliability and validity based on correlations between daily nutrient intakes and calorie-adjusted nutrient values from 2 histories ranging from 0.
To make use of the temporal data, we used the baseline measure for examination years 0—5 and the year 7 measure for examination years 7— Given the fair to moderate tracking of calorie intake shown in the literature, regardless of cohort age, study duration, or diet collection method 21 — 23 , we used the baseline and year 7 measures as a rough control for calorie intake. Statistical analyses were conducted by using Stata software version 9. Descriptive statistics were computed for walking and physical activity scores, weight status, calorie intake, smoking, and sociodemographic factors.
Percentages were calculated for categorical variables. Continuous variables are presented either as means and SEs or as medians and interquartile ranges for skewed measures. We used longitudinal, repeated-measures conditional regression modeling to estimate the longitudinal association between walking and weight change.
These models, conditioned on the subject, do not estimate parameters for variables constant within subjects ie, race, sex, and study center , but have the advantage of adjusting for potential confounding by all measured and unmeasured characteristics of individuals or within-person effects.
The models adjust for the correlation between repeated observations taken in the same subject and have the advantage of handling longitudinal data on subjects with varying number and unequally spaced observations, thereby allowing for inclusion of the maximum number of data points 25 — These models used all available data across 15 y and 6 examination periods.
Final models were stratified by sex and included an interaction term for walking score and baseline weight. Given the interaction terms and complexity of interpretation of the repeated-measures conditional regression model results, we present predictions based on model coefficients from the estimation equation, which estimate predicted cumulative y weight changes, adjusted for model covariates.
Using longitudinal, repeated-measures conditional regression modeling, we also predicted a categorical y weight change. Tests for interaction cross product term effect measures and likelihood ratio tests were undertaken. On the basis of this model, interaction terms were not warranted and thus were not retained in the final model. At baseline, the sample was approximately equally balanced with respect to race and sex Table 1.
Full sample included subjects at baseline. Exclusion criteria: women pregnant at time of examination and subjects missing adjacent weight measures to derive weight change. EU, exercise units calculated on the basis of frequency and intensity of activity. Testing only applied for outcome body weight and main exposure physical activity data. Differences between control variables were not tested. Values are medians interquartile ranges presented because of skewness of the physical activity score.
Intake at examination years 0—5 is based on baseline intake; intake at examination years 7—15 is based on intake at year 7. Because of the skewed distribution, we presented medians and interquartile ranges for walking and physical activity scores, although mean differences were tested. In a crude regression model, on average across all examination years, a 1-unit increase in the walking score predicted a 0.
Across all years, women had significantly higher mean walking scores than did men Table 2. Women had a higher mean annualized weight gain than did men at year 10 only. Using the longitudinal, repeated-measures conditional regression model predicting annualized weight change, we found a substantial association of walking with weight change, after accounting for nonwalking physical activity, calorie intake, and other relevant covariates.
We found a significant interaction between baseline weight and walking score and between walking score and sex. Associations were tested by using the 25th, 50th, and 75th percentiles of baseline weight given linear fit and to illustrate effects. These associations were greatest for those with the highest baseline weight and were strongest among women.
However, at the 50th percentile of baseline weight, each 0. At the 75th percentile of baseline weight BMI equivalent to overweight , 0. To facilitate interpretation of the walking and baseline weight interaction term from the repeated-measures conditional regression model, we present predictions generated from the model coefficients Figure 3 , interpreted as the average association of a change in walking score with total annualized weight change over 15 y for different levels of baseline weight.
In contrast, for men, the greatest difference in predicted weight gain was 4 kg for the comparison between those at the highest baseline weight walking score: EU of walking relative to those with no walking walking score: 0 EU , regardless of baseline weight.
The inverse association between walking and weight gain was evident across all baseline weight categories for women and men. Values may appear inconsistent because of rounding.
Bars for 0 exercise units EU are identical across sex and baseline weight because of regression parameterization. The likelihood of y weight loss and weight maintenance compared with weight gain by longitudinal walking level, with control for key covariates with no need for interaction terms, is shown in Table 3.
The likelihood of weight loss and maintenance was relatively higher at higher walking levels. We also found associations between smoking negative , marriage positive , and weight gain. Coefficients presented as adjusted odds ratios weight loss vs weight gain; weight maintenance vs weight gain. These models, conditioned on the subject, do not estimate parameters for variables that are constant within subject ie, race, sex, baseline weight, and study center.
Ref, referent category; EU, exercise units calculated on the basis of frequency and intensity of activity. We found a statistically robust relation between temporal change in walking and long-term weight change. Furthermore, an increase in walking over the early to middle adult years was associated with less weight gain over time and an increased likelihood of weight loss and maintenance compared with weight gain.
The strongest association was found in heavier women with baseline weight at the 75th percentile or It was our aim to explore the association between walking and weight change, holding other forms of physical activity constant. Thus, in this study, we were explicitly not interested in the physiologic effects of walking compared with other forms of physical activity. Nonetheless, using an interaction between walking and nonwalking physical activity data not shown , we found that the negative association between walking and annual weight change was stronger for participants with low than for women with high nonwalking physical activity.
Furthermore, we were most interested in determining policy and intervention practicality of consistent as opposed to inconsistent walking over time. Our findings are in line with research on other forms of physical activity spanning shorter time frames For example, others found evidence suggesting that physical activity may attenuate weight gain 29 — However, these findings are based on shorter time periods of follow-up and fewer repeated measures generally just 2 repeated visits.
Other research shows a negative association between walking and adiposity 14 , However, additional research suggests that the relation between adiposity and vigorous activity depends on BMI. For example, among women, for each mile of running per week, the decrease in BMI was 9-fold greater at the 95th than at the 5th percentile of BMI 33 , A cross-sectional analysis on walking suggests that associations of walking with adiposity may also be greatest among heavy women Our findings also contribute to the literature on small changes in physical activity and the prevention of weight gain 36 , Whereas our findings on the role of walking on weight gain attenuation indicate modest associations, they can have a substantial impact on both the individual and population levels, especially over long periods.
Furthermore, adding between 2 and 4 h of walking per week are clearly achievable targets from a public health perspective. Of particular relevance is our finding of a greater association in heavier women at baseline, because heavier weight is often a barrier to physical activity Walking is a particularly good form of activity to target. Furthermore, walking can be integrated beyond leisure into active transportation or commuting 41 — 44 and overall lifestyle or utilitarian activity 1 , 6 — 8.
The strengths of this study include its use of complete, detailed, longitudinal data over a y time span and standardized repeated measures of physical activity, including estimates of a variety of types of activities made with an instrument with known reliability and validity. We examined the independent associations of walking, controlling for other forms of self-reported physical activity as well as total calorie intake, to assess the independent associations of walking with long-term weight change.
Furthermore, longitudinal, repeated-measures conditional regression modeling is the most powerful statistical technique for exploring average associations of walking with average weight gain over time. Despite these strengths, this study had some limitations.
Background: Although walking is the most popular leisure-time activity for adults, few long-term, longitudinal studies have examined the association between walking, an affordable and accessible form of physical activity, and weight gain. Objective: The objective was to evaluate the association between changes in leisure-time walking and weight gain over a y period. After accounting for nonwalking physical activity, calorie intake, and other covariates, we found a substantial association between walking and annualized weight change; the greatest association was for those with a larger baseline weight. For example, for women at the 75th percentile of baseline weight, 0. Conclusion: Walking throughout adulthood may attenuate the long-term weight gain that occurs in most adults.
No other d Continue Reading. Metabolic syndrome is a complex disorder characterized by a cluster of metabolic abnormalities including hypertension, obesity, type 2 diabetes, and dyslipidemia. Here is the latest research on metabolic syndrome and type 2 diabetes mellitus. This feed focuses on the application of CRISPR-Cas system in high-throughput genome-wide screens to identify genes that affect virus-host interactions. Here is the latest research. Cryogenic electron microscopy Cryo-EM allows the determination of biological macromolecules and their assemblies at a near-atomic resolution.
Pedometers and other types of step-counting devices are growing in popularity with both researchers and practitioners. The focus of this article is on describing the most recent pedometer-related advances in terms of cardiovascular health. The emergent body of evidence suggests that pedometer-determined physical activity is related to a number of cardiovascular health outcomes and that intervention participants can realize modest changes in body mass index and blood pressure. Additional health benefits accrue with greater increases. Of course, even more benefits are possible from engaging in vigorous physical activity, but this seems less appealing for most people.
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Levine and S. McCrady and L.
Я могу вам помочь. - Спасибо, не. Мне нужен консьерж. На лице привратника появилась обиженная гримаса, словно Беккер чем-то его оскорбил. - Рог aqui, senor.
- Он просто расстроен. Но он получит то, что ему причитается. - Она встряхнула волосами и подмигнула. - Может быть, все-таки скажете что-нибудь. Что помогло бы мне? - сказал Беккер.
- Это Servicio Social de Sevilla.
Возвращение домой оказалось долгим и слишком утомительным. Последний месяц был для Лиланда Фонтейна временем больших ожиданий: в агентстве происходило нечто такое, что могло изменить ход истории, и, как это ни странно директор Фонтейн узнал об этом лишь случайно. Три месяца назад до Фонтейна дошли слухи о том, что от Стратмора уходит жена. Он узнал также и о том, что его заместитель просиживает на службе до глубокой ночи и может не выдержать такого напряжения.
Забудьте о ней! - Он отключил телефон и запихнул за ремень. Больше ему никто не помешает. В двенадцати тысячах миль от этого места Токуген Нуматака в полной растерянности застыл у окна своего кабинета.
Ему все время казалось, что Беккер совсем рядом, за углом. Одним глазом он следил за тенью, другим - за ступенями под ногами. Вдруг Халохоту показалось, что тень Беккера как бы споткнулась.
Он смотрел в ее глаза, надеясь увидеть в них насмешливые искорки. Но их там не. - Сью… зан, - заикаясь, начал .
Клушар кивнул: - Со спутницей. Роскошной рыжеволосой девицей. Мой Бог. Это была настоящая красотка. - Спутница? - бессмысленно повторил Беккер.
- Туда и обратно. Он был настолько погружен в свои мысли, что не заметил человека в очках в тонкой металлической оправе, который следил за ним с другой стороны улицы. ГЛАВА 18 Стоя у громадного окна во всю стену своего кабинета в токийском небоскребе, Нуматака с наслаждением дымил сигарой и улыбался.
Это его прерогатива. Я плачу вам за то, чтобы вы следили за отчетностью и обслуживали сотрудников, а не шпионили за моим заместителем. Если бы не он, мы бы до сих пор взламывали шифры с помощью карандаша и бумаги.
Сьюзан слушала молча. - Как ты могла догадаться, - продолжал он, - вскоре я собираюсь выйти в отставку. Но я хотел уйти с высоко поднятой головой.
Your email address will not be published. Required fields are marked *