Is anyone aware of any (commercial) data sets that divide the UK into urban and rural areas based on admin data (e.g. outcode postcodes) and/or physical data (e.g. eastings and northing or lats and longs).
Have a look at http://www.ons.gov.uk/ons/guide-method/geography/products/area-classifications/rural-urban-definition-and-la/rural-urban-definition--england-and-wales-/index.html for the official classification.
Clicking through on the links from the Rural definition pdf eventually gets you to here: http://www.ons.gov.uk/ons/guide-method/geography/products/index.html
Where you can download the 2001 and 2011 definitions at a variety of resolutions…
In response to Mapparz suggestion - I'd be tempted to use the OA level Rural-Urban geography in conjunction with the Open Names database and assign the postcode points with the OA classification:
Just had to track down the shapefile with this data in. Took a fair bit looking but eventually got this: http://geoportal.statistics.gov.uk/datasets/oa-ew-bgc-with-rucoa11
RUC classification at output area level (so pretty detailed) in a nice downloadable polygon shapefile.
The rural population is consistently less well-off than the urban population with respect to health. Differences between the two populations are not always substantial, however. The rural population is more likely to engage in risky health-related behaviors and to experience higher rates of chronic conditions and activity limitations. Rural residents are also more likely to be uninsured for longer periods of time, and are less likely than urban residents to receive some types of health care, including tests for various chronic conditions. Limited access to health care in rural areas is generally associated with the fact that there are fewer providers. This Profile compares people who live in a metro-politan statistical area (MSA) to those who do not (non-MSA). People who reside in a MSA are referred to as urban residents and those who live in a non-MSA are referred to as rural residents. About one-fifth of the U.S. population resides in a rural area. Larger differences between the rural and urban populations may be masked as a result of the way the data are reported. The use of broad “urban” and “rural” categories may mask some differences because of the substantial variations in population size and density. For example, a rural area may refer to a county with a city of 10,000 or more, or to a frontier area which has an extremely low population density, usually fewer than 6 people per square mile.
A larger proportion of the rural population than the urban population reports fair to poor physical and mental health. For example, the proportion of rural residents reporting fair to poor physical health is almost one and a half times the proportion of urban residents.
Rural areas face particular challenges related to accessing health care services. The question of how to provide high quality, affordable, sustainable health care to the 57 million Americans living in rural areas has become paramount.
Secretary Alex M. Azar II created a Rural Health Task Force at HHS, with key leaders and stakeholders from across the Department, to identify the needs of rural communities, how to meet those needs, and what HHS policy changes can address those needs. The intent is to determine not only how to deliver care in rural areas in a sustainable manner but also how rural health care may change in the future to ensure that it is accessible, high quality, value-based, and provided at the lowest cost possible.
As part of the Rural Health Task Force, HRSA is soliciting public input on how best to conceptualize and measure access to health care in rural communities. We encourage input from a broad range of stakeholders, including health care providers, researchers, community members, patients, consumers, families, caregivers, advocates, and other interested parties.
Chronic diseases are the leading causes of death and disability in America, and they affect some populations more than others. People who live in rural areas, for example, are more likely than urban residents to die prematurely from all of the five leading causes of death: heart disease, cancer, unintentional injury, chronic lower respiratory disease, and stroke. These rural health disparities have many causes:
- Health Behaviors: Rural residents often have limited access to healthy foods and fewer opportunities to be physically active compared to their urban counterparts, which can lead to conditions such as obesity and high blood pressure. Rural residents also have higher rates of smoking, which increases the risk of many chronic diseases.
- Health Care Access: Rural counties have fewer health care workers, specialists (such as cancer doctors), critical care units, emergency facilities, and transportation options. Residents are also more likely to be uninsured and to live farther away from health services.
- Healthy Food Access: National and local studies suggest that residents of low-income, minority, and rural neighborhoods often have less access to supermarkets and healthy foods.
- Demographic Characteristics: Residents of rural areas tend to be older, with lower incomes and less education than their urban counterparts. These factors are linked to poorer health.
About 46 million Americans&mdash15% of the US population&mdashlive in rural areas. CDC&rsquos National Center for Chronic Disease Prevention and Health Promotion works to improve health in these areas by:
- Measuring how many Americans have chronic diseases or chronic disease risk factors and reporting data down to the county level.
- Studying and reporting on rural health disparities and innovative programs to reduce those disparities.
- Funding and guiding states, territories, and tribes to reach rural populations through proven interventions and innovative programs.
- Developing programs and promoting care through digital formats, such as online classes or &ldquotelehealth&rdquo approaches that reduce barriers to health care access for rural residents.
Compared to urban areas, rural areas have:
Higher rates of unhealthy behaviors
Less access to health care
Less access to healthy foods
These factors contribute to higher rates of premature death from the five leading causes of death.
See the National Center for Chronic Disease Prevention and Health Promotion infographic to find out more about the center&rsquos work to prevent chronic diseases.
Natural Environments, Obesity, and Physical Activity in Nonmetropolitan Areas of the United States
Funding:: This study was supported by National Research Initiative Grant 2008–35215-18814 from the USDA Cooperative State Research, Education and Extension Service. Disclosures: The authors declare that they have no competing interests. For further information, contact: Akihiko Michimi, Department of Public Health, Western Kentucky University, 1906 College Heights Blvd #11038, Bowling Green, KY 42101 e-mail: [email protected]
Purpose: To assess the associations of the natural environment with obesity and physical activity in nonmetropolitan areas of the United States among representative samples by using 2 indices of outdoor activity potential (OAP) at the county level.
Methods: We used the data from 457,820 and 473,296 noninstitutionalized adults aged over 18 years for obesity and physical activity, respectively, from the 2000-2006 Behavioral Risk Factor Surveillance System. The OAP indices were (1) a recreational opportunity index based on 24 variables related to outdoor physical activity, such as the number of facilities available for walking, biking, hiking, and swimming derived from the 1997 National Outdoor Recreation Supply Information System and (2) a natural amenities index which was based on physical and social environmental characteristics, such as climate, topographic relief, land cover, and tourism. We fitted logistic regression models using generalized estimating equations to control for county level intracorrelation and tested each index separately to assess its relationship with obesity and physical activity.
Findings: Recreational opportunities were higher in areas with greater natural amenities. After controlling for individual-level socioeconomic and demographic characteristics, the prevalence of obesity decreased and propensity for physical activity increased with increasing levels of both recreational opportunities and natural amenities.
Conclusions: Multiple indices of OAP based on characteristics of the built, natural and social environments were associated with decreased obesity and increased physical activity in nonmetropolitan areas. Public health interventions should consider the opportunities and limitations offered by the natural environment for promoting physical activity and reducing obesity in rural areas.
Barriers To Care Coordination In Rural Areas
Barriers to Care Coordination in Rural Areas. Rural communities may experience challenges implementing care coordination strategies and activities. Specific barriers may include: Difficulty working with small, independent healthcare providers. Financing to support program development and implementation, especially health information technology.
4 days ago / 95 People Used See more.
Although government programs such as E-rate provisions provide internet connection to schools and libraries under the U.S. federal government, more general internet access to a broader community has not been directly addressed in policy. The provision of "national" internet services tends to favor urban metropolitan regions.  The digital divide is even more prominent in developing countries, where physical access to internet services are at a much lower rate. While developed countries such as the U.S. face the challenge of providing universal service (ensuring that everyone has access to internet service in the home), developing countries face the challenge of providing universal access (ensuring that everyone has the opportunity to make use of the internet).  For example, in Egypt there are only about six phone lines per 100 people, with less than two lines per 100 people in rural areas, which makes it even more difficult for people to access the internet. 
The United States Department of Agriculture’s Economic Research Service has provided numerous studies and data on the Internet in rural America. One such article from the Agricultural Outlook magazine, Communications & the Internet in Rural America, summarizes internet uses in rural areas of the United States in 2002. It indicates, "Internet use by rural and urban households has also increased significantly during the 1990s, so significantly that it has one of the fastest rates of adoption for any household service." 
Another area for inclusion of the Internet is American farming. One study reviewed data from 2003 and found that "56 percent of farm operators used the Internet while 31 percent of rural workers used it at their place of work."  In later years challenges to economical rural telecommunications remain. People in inner city areas are closer together, so the access network to connect them is shorter and cheaper to build and maintain, while rural areas require more equipment per customer. However, even with this challenge the demand for services continues to grow. 
In 2011 the Federal Communications Commission (FCC) proposed to use the Universal Service Fund to subsidize rural broadband Internet services. In 2019, the FCC estimated that only 73.6% of the rural population had access to broadband services at 25 Mbps in 2017, compared to 98.3% of the population in urban areas.  However, many studies have contested FCC findings, claiming a greater number of Americans are without access to internet services at sufficient speeds.   For instance, in 2019 Pew Research Center found that only about two-thirds of rural Americans claimed to have a broadband internet connection at home, and although the gap in mobile technology ownership between rural and urban adults has narrowed, rural adults remain less likely to own these devices. 
One study in particular examined the ways in which inaccessibility for rural and "quasi-rural" residents affects their daily life, conceptualizing issues of accessibility as a form of socioeconomic inequity.  By using Illinois as a case study - a state with both urban and rural environments—the authors demonstrate how the rural-urban digital divide negatively impacts those that live in areas that fall between the two distinct categories of rural and urban. Interviews with residents from Illinois describe "missed pockets," or areas in which service installation is not available or far too expensive.  This inaccessibility leads many to experience sentiments of social isolation as residents feel disconnected from current events, cultural trends, and even close friends and family members.
Internet access inequalities are further deepened by public policy and commercial investment. In 2003, The Information Society published an article explaining how exchange areas and local access transport areas (LATAs) arrange citizens into markets for telecommunication companies, which centralizes access rather than encouraging businesses to cater to more remote communities.  These areas were created through regulatory measures intended to ensure greater access and are perpetuated by investment patterns as more disparate communities hold less potential for profits, thus creating "missed pockets."  
A membership association, NTCA - The Rural Broadband Association, comprising nearly 850 independent rural American telecommunications companies in forty-four states, was formed with the goal of improving communications services in rural America. 
In Canada, when pressed by Member of Parliament David de Burgh Graham, the Federation of Canadian Municipalities did not see access to the internet a right.  Telecommunications co-operatives like Antoine-Labelle provide an alternative to big Internet Service Providers.  
In Spain, the Guifi.net project has been for some people the only alternative to get access to the Internet. Usually, neighbors are the responsible to collect the necessary money to buy the network equipment that will do a Wireless link with another zone that already has internet access. There have also been cases in which the own city council has invested in the infrastructure.
In the UK, the government aimed to provide superfast broadband (speeds of 24Mbit/s or more) to 95% of the country by 2017.  In 2014, a study by the Oxford Internet Institute found that in areas less than 30 km (20 mi) from large cities, internet speed dropped below 2Mbit/s, the speed designated as "adequate" by the government. 
Frustrated by the slow progress being made by private telecoms companies, some rural communities have built their own broadband networks, such as the B4RN initiative. 
India has the second-biggest online market globally, yet a large portion of its populace – almost 700 million individuals – are detached. Indian internet network access AirJaldi has collaborated with Microsoft to give reasonable online access to rural areas. Dependable broadband associations are imperative for many youngsters who are being homeschooled during the pandemic for COVID-19. That may change as Indian web access provider, AirJaldi, is widening access through an imaginative undertaking with worldwide tech giant Microsoft. 
Due to poor telecommunication access in most rural areas, low-energy solutions such as those offered by Internet of Things networks are seen as a cost-effective solution well-adapted to agricultural environments.    Tasks such as controlling livestock conditions and numbers, the state of crops, and pests are progressively being taken over by m2m communications. Companies such as Sigfox, Cisco Systems and Fujitsu are delving into the agricultural market, offering innovative solutions to common problems in countries such as the U.S., Japan, Ireland and Uruguay.    
There is increasing conversation around the growing social necessity of being connected in today's world and moreover, growing social expectation that one is connected either with at home broadband, reliable cell-service, and at least email access. Currently, rural areas often depend on small, unreliable ISP providers and scrape by "siphoning from surplus data and bandwidth capacity, creating their own systems of redundancy, or (in some cases) launching community-based, local ISP when large incumbent providers fail to show an interest in the area." 
Many of the difficulties faced by rural communities are "geo-policy barriers," defined as "chokepoints [or] mechanisms of control created through the interaction of geography, market forces, and public policies" that constrict not just access, but "also construct both communication and communities."  In the US, regulatory mandates have helped extend basic telecommunications to rural areas while mitigating market failure. However, despite efforts from the government, the telecommunications industry has stayed relatively monopolized therefore little competition has resulted in basic telecommunications without adequate connectivity for the developing needs of rural citizens. One state-based effort that has proved successful in adequately connecting Americans are EAS, or "expanded area service", programs, which "generally reduce intra-LATAS [local access transport areas] long-distance costs between specific exchanges or throughout a contiguous geographic area."  In regards to Internet access, one of the most important EAS programs creates "flat-rate calling zones that allow remote customers to reach an Internet service provider in a more populous area." 
Issues of rural connectivity have been exacerbated by the COVID-19 pandemic and reveal how "poor management of the Universal Service Fund, which subsidizes phone and internet access in rural areas, has meant some companies get the money without delivering on the promised numbers of households served or service quality."  Therefore, one immediate fix to rural connectivity would be accountability within U.S.F programs and arguably, more funding. While governments begin pondering questions such as, "is Internet access a right?", ideas on how to approach this issue fall along political party lines. Mainly, Democrats believe more government funding would help connect rural Americans while Republicans are backing new 5G mobile Internet technology to replace home Internet lines and solve access gaps.  These arguments are very similar to political arguments about "electricity and phone service in the early 1900s." 
The Federal Communications Commission (FCC) recently released an overview of initiatives based on "bridging the digital divide for all Americans,"  some of these include:
To review research published before and after the passage of the Patient Protection and Affordable Care Act (2010) examining barriers in seeking or accessing health care in rural populations in the USA.
This literature review was based on a comprehensive search for all literature researching rural health care provision and access in the USA.
Pubmed, Proquest Allied Nursing and Health Literature, National Rural Health Association (NRHA) Resource Center and Google Scholar databases were searched using the Medical Subject Headings (MeSH) ‘Rural Health Services’ and ‘Rural Health.’ MeSH subtitle headings used were ‘USA,’ ‘utilization,’ ‘trends’ and ‘supply and distribution.’ Keywords added to the search parameters were ‘access,’ ‘rural’ and ‘health care.’ Searches in Google Scholar employed the phrases ‘health care disparities in the USA,’ inequalities in ‘health care in the USA,’ ‘health care in rural USA’ and ‘access to health care in rural USA.’ After eliminating non-relevant articles, 34 articles were included.
Significant differences in health care access between rural and urban areas exist. Reluctance to seek health care in rural areas was based on cultural and financial constraints, often compounded by a scarcity of services, a lack of trained physicians, insufficient public transport, and poor availability of broadband internet services. Rural residents were found to have poorer health, with rural areas having difficulty in attracting and retaining physicians, and maintaining health services on a par with their urban counterparts.
Rural and urban health care disparities require an ongoing program of reform with the aim to improve the provision of services, promote recruitment, training and career development of rural health care professionals, increase comprehensive health insurance coverage and engage rural residents and healthcare providers in health promotion.
The Impact of Green Belts on Markets for Residential Land and Housing
A green belt or an urban growth boundary affects the markets for residential land and housing in several ways. A green belt reduces the supply of residential land by banning development inside it. This will then lead to a higher price of land and reduction of new housing supply. At the same time, housing supply becomes less elastic with respect to price. This happens because the price elasticity of new housing supply is influenced by the elasticity of developable land supply, and the latter is adversely affected by the regulation. The supply of housing becomes more elastic, the more elastic the supply of land is, given the share of land cost in total cost of housing production and the elasticity of substitution between land and nonland inputs (see article Supply Elasticity of Housing ).
A green belt policy also affects the types of housing constructed. Since such a policy raises the price of residential land, the cost of producing housing that uses land extensively (detached single family houses and detached houses) increases relative to the price of housing that uses land intensively (apartments and terrace houses). As a result, the construction of the former will fall relative to that of the latter, provided other residential density controls permit increased construction of the latter.
A green belt regulation also influences the location of development, by prohibiting development at the urban fringe and instead steering development towards locations beyond the outer edge of the green belt that are further from the city centre. Such changes may also accompany changes in the composition of housing types and building densities.
There could also be dynamic impacts on the timing and density of land development, as the threat posed by regulatory initiatives such as green belts can accelerate the pace of development in the rest of the metropolitan area.
Most studies on the impact of urban containment policies like green belts analyse effects on the prices of land and housing. The finding that such policies are associated with higher prices can be due to a decrease in housing supply, but also an increase in demand caused by the positive effect of regulations on amenities. If the green belt generates amenities such as clean air, scenic beauty, and recreational space, the benefits will be capitalised into land values. This makes it difficult to interpret the results of empirical studies.
Analysts including Monk and Whitehead (1999) argue that the typical econometric analysis of the price of land or housing is incapable of explaining the impact of regulation, because the planning system is nationwide and this therefore prevents comparisons between areas where policy applies and areas that are free of intervention. For this reason, they take a behavioural approach and analyse the trend of planning permissions granted, the price of residential land, new housing completions, house prices, as well as house types and densities for two adjoining local authority districts in the southeast of England during the period 1981–91. These two districts were within the same county structure plan but the application of planning controls differed in terms of their tightness. Their analysis confirmed that constraint in one area pushes up prices in all areas, the differences in the extent of constraints are reflected in relative land prices, and so tight constraints on land supply in the face of demand increases resulted in rising prices of land and housing, but minimal responses in housing output.
There are relatively few studies that directly analyse the impact of growth controls or green belts on the supply of urban residential land or new housing. Son and Kim (1998) analysed data on 171 cities in Korea and found that green belts contribute to urban land shortages. They first estimated the land price gradients for urban and surrounding rural areas, and then calculated the shortage or surplus of urban land as the difference between the equilibrium size of urban land area and the actual land in urban use. Finally, they investigated the factors determining the shortage or surplus of urban land by estimating a regression equation relating the calculated shortage or surplus to a set of demand side variables (e.g., population and local government revenue), infrastructure, and measures of natural and regulatory constraints on land use. Estimation results suggest that the size of green belt as a percentage of total urban area is a significant factor in determining the shortage of urban land, but natural constraints were not significant. Bramley (1993) estimated a system of five equations representing UK housing markets and used the model to analyse the impact of planning policies on the supply of residential land and housing. Bramley constructed indices of natural constraints and those measuring strictness of planning constraints. The green belt variable is included as a natural constraint considering its permanence. He found that the green belt and other natural constraints decrease housing output.
Urban containment policies are believed to have made housing supply less elastic in the United Kingdom. Pryce (1999) used the data compiled by Bramley to estimate a housing supply function. He derived estimates of the price elasticity of new housing supply as well as the elasticity of housing price with respect to land availability. He found that a 75% increase in the stock of land with outstanding permissions for housing would lead to a fall in housing price of 32.4% assuming that the price elasticity of housing demand equals −0.7.
Planning controls could also affect the type of new housing produced. Evans and Hatwich (2005) report that the share of single-storey houses in private dwelling construction fell from 12% to 5% between 1990 and 2004. Moreover, virtually no single-storey houses were built in southern England where demand for such housing is greater but the land supply constraint was more severe. Monk and Whitehead (1999) also point out that the regulatory system has limited the range of choices of housing types and densities.
Finally, Cunningham (2007) investigates the dynamic impact planning policy risk on land development. Using the data on Cooke County of the State of Washington, USA, he estimated the impact of the urban growth boundary on the timing of development. He found that the introduction of the urban growth boundary would have reduced land development by between 42% and 48% in the absence of real-option considerations, but the impact drops to between 28% and 39% once the role of real option is considered.
In sum, the literature provides some evidence for the negative impact of planning controls in general and green belts or urban growth boundaries in particular on the availability of land for housing and the supply of housing.
Understanding Geographic and Neighborhood Variations in Overdose Death Rates
The current opioid epidemic continues to challenge us in new and potentially troubling ways. For example, research today finds more overdose deaths occurring in rural, rather than urban, geographic areas. Yet, studies have often ignored heterogeneities within these spaces and the neighborhood variations therein. Using geodemographic classification, we investigate neighborhood differences in overdose death rates by geographical areas to further understand where and among what groups the problem might be most concentrated. For deaths between 2013 and 2016, we find significant variation in rates among neighborhoods, defined by their socio-economic and demographic characteristics. For example, overdose death rates vary up to 13-fold among neighborhoods within geographic areas. Our results overall show that while the rural or urban classification of a geographic area is important in understanding the current overdose problem, a more segmented analysis by neighborhood’s socio-economic and demographic makeup is also necessary.
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