To account for the fact that nearly half the sample has moved since the three-year survey, we included an indicator for whether the family has moved in the last two years in all the models along with the poverty measure. Unfortunately, we do not have detailed, longitudinal residential information for each family. We do ask, at each wave, how many times the family has moved since the last interview. Using this information, we also created a variable which indicated how many times the family had moved in the last four years, and included it in our models.
This measure of residential instability was never significant in any of our models, so we instead used the simple measure of whether the family moved in the past two years. There were two types of questions. Items were coded with higher scores representing more neighborhood cohesion and summed to create the full scale.
The observations were a simplified version of the block physical disorder and physical decay measures created by Sampson and Raudenbush and included questions about the physical condition of the yard, street, and surrounding buildings. For the first part of the analysis, which validated the association between the activity measures and body mass index BMI percentile, we used ordinary least squares regression.
We tested several specifications of SES, and found that the income-to-needs ratio had a nonlinear association with BMI percentile, so we also included a squared income-to-needs ratio term. We also created categories for BMI percentile underweight, normal weight, overweight, and obese , and tested whether the associations between the activity measures and weight status varied depending upon the specification of the dependent variable, using ordered logit models. The associations between the activity measures and a four-category weight outcome were uniformly weaker than for the linear model, but the effects were in the same direction.
For the second part of the analysis, each of the three activity measures average hours per day spent playing outdoors; average hours per day spent watching television; and average times per week mother takes the child to a playground was a count measure and each was marked by over-dispersion, so OLS regression was not appropriate. Thus, negative binomial regression models were used. Table 1 presents descriptive statistics for the sample, consisting of the mean and standard deviation for each variable.
The mean BMI percentile in the sample was On average, children played outside about 2 h per day, and watched more than two and a half hours of television per day. Mothers took their children to the playground or the park nearly four times per week. The background characteristics show that the FFCWS sample was relatively disadvantaged reflecting the urban nature of the sample with more than one-third of mothers having not completed high school, and the mean income-to-needs ratio was 1.
As expected, hours of outdoor play were negatively associated with BMI, and hours of television were positively associated with BMI. For each hour of outdoor play, children, on average, scored about half a percentile point lower on BMI. The corresponding increase for each hour of television was similar, about half a percentile point. In fact, for each additional hour they play outside each day -over and above television watching- children scored 1.
Contrary to expectations, we found that the number of playground trips with the mother per week was not a statistically significant predictor of BMI at age five although the distribution of this variable was skewed toward the high end. We also found that the income-to-needs ratio was associated in a nonlinear way with BMI percentile, such that it was lowest for the poorest and wealthiest children.
Urban planning
Standard errors were adjusted for clustering at the city-level. Table 3 presents results of the negative binomial regression models for hours of outdoor play. Working mothers, and those families interviewed in the winter, reported less time outside. In Model 3, higher levels of collective efficacy were associated with more outdoor play time, even after accounting for differences between neighborhoods in poverty level and other residential context measures.
Children of mothers who worked full-time and children enrolled in kindergarten or a daycare program watched less television. We also see that maternal fear of the child playing outside is associated with more television time. Results for the number of times per week the mothers took the children to a park or playground were virtually identical to those for hours of outdoor play, so results are not presented here available upon request. Despite most recent research documenting a negative association between SES and the likelihood of overweight for children e.
In addition, we found that hours of outdoor play and television watching were both associated with BMI at age five, as was the ratio of outdoor play to television watching time. The magnitude of the associations was similar to those of earlier studies of older children e. A second surprising finding was that children living in public housing, and those living in the neighborhoods with higher levels of physical disorder, were playing outdoors more often than other children. These same characteristics were also associated with more television viewing, indicating that these activities were not substitutes for one another, at least in this study population.
Children in lower class households have much more unstructured time than do those in middle-class households, reflecting class differences not just in resources but also in child-raising philosophies Lareau, Thus, it seems likely that the poorest children in our sample who were less likely to be enrolled, especially full-time, in a preschool or daycare had more unstructured time to fill with outdoor play and sedentary activities, such as television watching.
Instead, we demonstrated that in poor communities, specific social conditions may give rise to higher rates of physical activity. In public housing projects where parents especially mothers are likely to be home during the day, and thus potentially more available to supervise play, children may have higher rates of outdoor physical activity. Moreover, these children of mostly non-working mothers may be less likely to be enrolled in preschool or daycare programs, and thus may have more unstructured time at home in which to play outdoors. It also is likely that public housing projects provide relatively safe and accessible places to play e.
Although one strength of our study was the ability to control for maternal BMI in all our models, when we tested the physical activity models without this measure results were virtually identical. Our findings also dovetail with recent studies which find a positive effect of perceived collective efficacy on physical activity for adolescents and adults Cradock et al. The children of mothers who perceived higher levels of collective efficacy in their neighborhoods -net of neighborhood SES - were playing outside for longer periods each day, watching less television, and also visiting the park or playground more often each week.
Surprisingly, neighborhood poverty status was not significant in any of the models presented here, a finding at odds with other recent work which focused on child obesity rather than physical activity Lumeng et al. This may be because our sample was disproportionately poor and urban, which may reduce variability in neighborhood poverty and thus our ability to discern differences in the influence of this measure.
We also tested models including neighborhood poverty without our other residential context measures and this measure was only a significant predictor of hours of weekday television, such that children in low-poverty neighborhoods watched less television. Since this measure was from the three-year data, it is conceivable that, although we control for whether the family has moved between years three and five, we are not adequately capturing the socioeconomic environment; or that we are limited in explanatory power by utilizing Census tracts instead of smaller geographic areas.
Another limitation of our study was that all our outcome measures are mother-reported, and our findings may not be generalizable to younger preschool children in the U. We were also unable to disaggregate between time children may be spending outside alone vs. Ideally, future analyses of this sort would have more detailed measures of outdoor time and sedentary activities.
In addition, despite being well-suited for our research questions, our sample was limited, and thus our findings relate only to young, urban children in the U. For example, our findings point to the need for safe, open spaces near homes in urban areas for poor children who may not have access to preschool programs or to housing with its own play facilities. Rachel Tolbert Kimbro, Rice University. Jeanne Brooks-Gunn, Columbia University. Sara McLanahan, Princeton University. National Center for Biotechnology Information , U.
Author manuscript; available in PMC Sep 1. Author information Copyright and License information Disclaimer. Rachel Tolbert Kimbro, Rice University;. The publisher's final edited version of this article is available at Soc Sci Med. See other articles in PMC that cite the published article. Introduction Despite trends indicating a recent stabilizing in the upward obesity trend for children and adolescents in the U.
Residential context measures The first set of residential context measures include 1 whether the family lived in public housing, 2 number of residents in the household, and 3 type of housing: Statistical analysis For the first part of the analysis, which validated the association between the activity measures and body mass index BMI percentile, we used ordinary least squares regression.
Results Table 1 presents descriptive statistics for the sample, consisting of the mean and standard deviation for each variable. Open in a separate window. Model 1 Model 2 Model 3 Model 4 Coef. Family lives in public housing 0. Residential Context Family lives in public housing 0. Race differentials in obesity: Journal of Health and Social Behaviour. Neighborhood playgrounds, fast food restaurants, and crime: A national study of neighborhood safety, outdoor play, television viewing, and obesity in preschool children.
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Neighborhood social cohesion and youth participation in physical activity in Chicago. Parental overweight, socioeconomic status and high birth weight are the major determinants of overweight and obesity in 5e7 y-old children: International Journal of Obesity. A review of the literature. Television viewing and television in bedroom associated with overweight risk among low-income preschool children. Area characteristics and individual-level socioeconomic position indicators in three population-based epidemiologic studies.
Associations of neighborhood problems and neighborhood social cohesion with mental health and health behaviors: Media and risky behaviors. The difference in the NRI classification is that it includes rural development, which by definition cannot be considered to be "urban" sprawl.
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Currently, according to the Census , approximately 2. Nonetheless, some urban areas like Detroit have expanded geographically even while losing population. But it was not just urbanized areas in the U. According to data in "Cities and Automobile Dependence" by Kenworthy and Laube , urbanized area population losses occurred while there was an expansion of sprawl between and in Amsterdam, the Netherlands ; Brussels, Belgium ; Copenhagen, Denmark ; Frankfurt , Hamburg and Munich , Germany ; and Zurich , Switzerland , albeit without the dismantling of infrastructure that occurred in the United States.
One of the major environmental problems associated with sprawl is land loss , habitat loss and subsequent reduction in biodiversity. A review by Czech and colleagues [38] finds that urbanization endangers more species and is more geographically ubiquitous in the mainland United States than any other human activity.
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Regions with high birth rates and immigration are therefore faced with environmental problems due to unplanned urban growth and emerging megacities such as Kolkata. At the same time, the urban cores of these and nearly all other major cities in the United States , Western Europe , and Japan that did not annex new territory experienced the related phenomena of falling household size and, particularly in the U. Due to the larger area consumed by sprawling suburbs compared to urban neighborhoods, more farmland and wildlife habitats are displaced per resident.
As forest cover is cleared and covered with impervious surfaces concrete and asphalt in the suburbs, rainfall is less effectively absorbed into the groundwater aquifers. Sprawl increases water pollution as rain water picks up gasoline , motor oil , heavy metals , and other pollutants in runoff from parking lots and roads. Sprawl leads to increased driving, and increased driving leads to vehicle emissions that contribute to air pollution and its attendant negative impacts on human health.
In addition, the reduced physical activity implied by increased automobile use has negative health consequences. Sprawl significantly predicts chronic medical conditions and health-related quality of life, but not mental health disorders. In the years following World War II, when vehicle ownership was becoming widespread, public health officials recommended the health benefits of suburbs due to soot and industrial fumes in the city center. However, air in modern suburbs is not necessarily cleaner than air in urban neighborhoods.
On average, suburban residents generate more per capita pollution and carbon emissions than their urban counterparts because of their increased driving. A heavy reliance on automobiles increases traffic throughout the city as well as automobile crashes, pedestrian injuries, and air pollution. Research covered in the Journal of Economic Issues and State and Local Government Review shows a link between sprawl and emergency medical services response and fire department response delays. Living in larger, more spread out spaces generally makes public services more expensive. Since car usage becomes endemic and public transport often becomes significantly more expensive, city planners are forced to build highway and parking infrastructure , which in turn decreases taxable land and revenue, and decreases the desirability of the area adjacent to such structures.
Introduction
Residents of low-density areas spend a higher proportion of their income on transportation than residents of high density areas. Urban sprawl may be partly responsible for the decline in social capital in the United States. Compact neighborhoods can foster casual social interactions among neighbors, while sprawl creates barriers.
Sprawl tends to replace public spaces with private spaces such as fenced-in backyards. Critics of sprawl maintain that sprawl erodes quality of life. Duany and Plater-Zyberk believe that in traditional neighborhoods the nearness of the workplace to retail and restaurant space that provides cafes and convenience stores with daytime customers is an essential component to the successful balance of urban life. Furthermore, they state that the closeness of the workplace to homes also gives people the option of walking or riding a bicycle to work or school and that without this kind of interaction between the different components of life the urban pattern quickly falls apart.
Urban sprawl has class and racial implications in many parts of the world; the relative homogeneity of many sprawl developments may reinforce class and racial divides through residential segregation. Numerous studies link increased population density with increased aggression. It is argued that human beings, while social animals, need significant amounts of social space or they become agitated and aggressive. According to Nancy Chin, a large number of effects of sprawl have been discussed in the academic literature in some detail; however, the most contentious issues can be reduced "to an older set of arguments, between those advocating a planning approach and those advocating the efficiency of the market.
Arguments opposing urban sprawl include concrete effects such as health and environmental issues as well as abstract consequences including neighborhood vitality. American public policy analyst Randal O'Toole of the Cato Institute , a libertarian think tank , has argued that sprawl, thanks to the automobile, gave rise to affordable suburban neighborhoods for middle class and lower class individuals, including non-whites. He notes that efforts to combat sprawl often result in subsidizing development in wealthier and whiter neighborhoods while condemning and demolishing poorer minority neighborhoods.
The American Institute of Architects and the American Planning Association recommend against sprawl and instead endorses smart , mixed-use development , including buildings in close proximity to one another that cut down on automobile use, save energy, and promote walkable, healthy, well-designed neighborhoods. One of the primary debates around suburban sprawl is the extent to which sprawl is the result of consumer preference. Some, such as Peter Gordon, a professor of planning and economics at the University of Southern California's School of Urban Planning and Development, argue that most households have shown a clear preference for low-density living and that this is a fact that should not be ignored by planners.
It is a giant step backward to interfere with this effective process unless the benefits of intervention substantially exceed its cost.
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Jackson [70] have argued that since low-density housing is often notably in the U. Whether urban sprawl does increase problems of automobile dependency and whether conversely, policies of smart growth can reduce them have been fiercely contested issues over several decades. Within cities, studies from across many countries mainly in the developed world have shown that denser urban areas with greater mixture of land use and better public transport tend to have lower car use than less dense suburban and ex-urban residential areas.
This usually holds true even after controlling for socio-economic factors such as differences in household composition and income. One confounding factor, which has been the subject of many studies, is residential self-selection: Some studies have found that, when self-selection is controlled for, the built environment has no significant effect on travel behaviour. Those not opposed to low density development argue that traffic intensities tend to be less, traffic speeds faster and, as a result, ambient air pollution is lower.
Kansas City, Missouri is often cited as an example of ideal low-density development, with congestion below the mean and home prices below comparable Midwestern cities. Wendell Cox and Randal O'Toole are leading figures supporting lower density development. Longitudinal time-lapse studies of commute times in major metropolitan areas in the United States have shown that commute times decreased for the period to even though the geographic size of the city increased.
Reviewing the evidence on urban intensification, smart growth and their effects on travel behaviour Melia et al. Planning policies that increase population densities in urban areas do tend to reduce car use, but the effect is a weak one, so doubling the population density of a particular area will not halve the frequency or distance of car use.
There is also some concern that anti-sprawl policies will increase housing prices. Some research suggests Oregon has had the largest housing affordability loss in the nation, [82] but other research shows that Portland's price increases are comparable to other Western cities. In Australia, it is claimed by some that housing affordability has hit "crisis levels" due to "urban consolidation" policies implemented by state governments.
Many critics concede that sprawl produces some negative externalities; however there is some dispute about the most effective way to reduce these negative effects. The term 'smart growth' has been particularly used in North America. The terms 'compact city' or 'urban intensification' are often used to describe similar concepts in Europe and particularly the UK where it has influenced government policy and planning practice in recent years.
The state of Oregon enacted a law in limiting the area urban areas could occupy, through urban growth boundaries. As a result, Portland , the state's largest urban area, has become a leader in smart growth policies that seek to make urban areas more compact they are called urban consolidation policies.
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While the growth boundary has not been tight enough to vastly increase density, the consensus is that the growth boundaries have protected great amounts of wild areas and farmland around the metro area. Many parts of the San Francisco Bay Area have also adopted urban growth boundaries; 25 of its cities and 5 of its counties have urban growth boundaries. Many of these were adopted with the support and advocacy of Greenbelt Alliance , a non-profit land conservation and urban planning organization.
In other areas, the design principles of District Regionalism and New Urbanism have been employed to combat urban sprawl. The concept of Circular flow land use management has been developed in Europe to reduce land take by urban sprawl through promoting inner-city and brownfield development. While cities such as Los Angeles are well known for sprawling suburbs, policies and public opinion are changing.
Transit-oriented development, in which higher-density mixed-use areas are permitted or encouraged near transit stops is encouraging more compact development in certain areas-particularly those with light and heavy rail transit systems. Bicycles are the preferred means of travel in many countries. Businesses in areas of some towns where bicycle use is high are thriving. Bicycles and transit are contributing in two important ways toward the success of businesses: Walkability is a measure of how friendly an area is to walking.
Walkability has many health, environmental, and economic benefits. However, evaluating walkability is challenging because it requires the consideration of many subjective factors. From Wikipedia, the free encyclopedia. Examples of urban sprawl in developing countries. From top, left to right: Rural neighborhoods in Morrisville, North Carolina are rapidly developing into affluent, urbanized neighborhoods and subdivisions.
Urban Studies Research
The two images above are on opposite sides of the same street. Ceteris paribus , urban intensification which increases population density will reduce per capita car use, with benefits to the global environment, but will also increase concentrations of motor traffic, worsening the local environment in those locations where it occurs. Smart growth , Compact City , Transit-oriented development , and New urbanism.
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