The effects of New Urbanism on public health

ABSTRACT

This paper investigates how the 10 New Urbanism principles produce outcomes that affect public health. The outcomes include: (1) higher usage of non-motorized and public transit modes, which results in more physical activity; (2) lower usage of private automobiles, which results in less air pollution; (3) safer streets, which results in fewer traffic accidents; and (4) complete community planning for residents, regardless of income, age or ideas, which results in better access to health resources. These results improve public health. This study also applies several walkability and connectivity indicators and suggests their use in cities to maximally accrue public-health benefits.

Introduction

Urban design factors can affect public health in several ways, including physical activity, traffic accident risk, pollution exposure, access to health resources, mental health and affordability, which affects households’ ability to afford other critical goods, such as healthy food and medical care. The US National Research Council and US Institute of Medicine (2013, 194) report:

The factors in the physical environment that are important to health include harmful substances, such as air pollution or proximity to toxic sites (the focus of classic environmental epidemiology); access to various health-related resources (e.g., healthy or unhealthy foods, recreational resources, medical care); and community design and the “built environment” (e.g., land use mix, street connectivity, transportation systems).

The aim of this study was to evaluate the potential impacts on the public health of several urban design features categorized under the New Urbanism principles. In 2018, the Congress for the New Urbanism (CNU) defines New Urbanism as ‘a planning and development approach based on the principles of how cities and towns had been built for the last several centuries: walkable blocks and streets, housing and shopping in close proximity, and accessible public spaces. In other words: New Urbanism focuses on human-scaled urban design’. The Michigan Land Use Institute (2006) identified 10 New Urbanism principles: walkability; connectivity; mixed use and diversity; mixed housing; quality architecture and urban design; traditional neighbourhood structure; increased density; smart transportation; sustainability; and quality of life. This paper examines the potential impact these interrelated principles have on public health and wellness.

The New Urbanism principles demonstrate multiple interrelated effects on certain health benefits, with the most important being physical activity, based on urban design elements that promote higher usage of non-motorized and public transit modes, therefore reducing the use of private automobiles, also resulting in less air and noise pollution. In addition, these principles also result in safer cities, resulting from the design of streets and communities. Moreover, New Urbanism provides complete community planning for all residents, regardless of income, culture, age or ideas, resulting in better access to health resources.

Physical inactivity is one of the leading causes of morbidity and mortality worldwide, placing a considerable burden on the health care system related to productivity losses and disability-adjusted life-years. Published research studies clearly suggest that physical inactivity is associated with a broad range of systemic, chronic diseases and health conditions. According to a 2013 estimate, the public health disease burden attributable to additional health care costs totalled $53.8 billion worldwide, of which $31.2 billion was paid by the public sector, $12.9 billion by the private sector and $9.7 billion by individual households (Ding et al. 2016).

The World Health Organization (WHO) has identified physical inactivity as the fourth leading risk factor for mortality, causing an estimated 3.2 million deaths globally. Some of the most routinely recommended forms of physical activity involve walking, cycling or participating in outdoor sports that are linked with significant health benefits (WHO 2018). In a recent longitudinal investigation covering four seasons over a three-year period, researchers designed a study to actively engage 317 participants in Saskatchewan, Canada, to report physical activity, sedentary behaviour, motivation, perception of outdoor and indoor environments and well-being. Various activities and social contexts, along with barriers and facilitators for physical activities, were captured. The study results revealed a complex interaction of intrinsic and extrinsic motivating factors, social context and outdoor and indoor environments, where favourable urban design and pet ownership served as predominant facilitators and work-related factors served as primary barriers (Katapally et al. 2018). Decades of scientific research have resulted in well-established data associating physical activity and behavioural patterns as key factors of health and wellness (Stephens 1988; Penedo and Dahn 2005; Hamer and Stamatakis 2010; Public Health Agency of Canada 2017; Laverly et al. 2018). Urban design has been suggested as one of the predominant facilitators of healthy behaviour (Katapally et al. 2018).

There are various urban-planning variables that can be identified to analyze their potential impact on health. Giles-Corti et al. (2016) identified three regional and five local urban and transportation planning and design interventions and features to create compact cities that enhance health and well-being. The regional planning tools included destination accessibility (such as services accessible by public transit), distribution of employment (such as an appropriate mix of employment across a region), and demand management (such as pricing policies to reduce the use of single-occupant vehicles [SOVs] and encourage alternative modes of transportation). The local urban design tools to enhance public health are by design (such as walkable areas around activity centres and accessible public space; interconnected street networks to minimize origins with destinations; safe non-motorized and public-transit networks; lot design to increase residential density and natural surveillance), density, distance to public transport, diversity (such as housing mixed with commercial, public and recreational facilities), and desirability (such as safe, accessible and attractive neighbourhoods that include convenient, affordable, frequent, safe and comfortable public transportation).

Materials and methods

Data source, guiding rationale for selection of study parameters

For the purposes of this study, the public-health data for counties across the United States was obtained from the County Health Rankings and Roadmaps (CHR&R) programme, a collaboration of the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Initiative (CHR&R 2017). The multiyear public-health data accumulated through this programme is a reliable source of multiyear data at the county level for a wide range of health and wellness indicators, providing an annual snapshot of how health- and wellness-related factors are influenced by where people live, learn, work and play.

This study identified data linked to health and wellness at the county level for selected geographical regions in the United States that consist of uniquely large urban centres, as well as mixed rural, mixed suburban and rural counties. Among the selected geographical regions are three counties that include designated smart cities in the United States for comparative data analysis. Los Angeles County, California (Los Angeles); Harris County, Texas (Houston); and El Paso County, Colorado, were included as large urban centres. Clay County, Mississippi, and Allen County, Kansas, were included as mixed locations for socio-economic factors. Cedar County, Iowa, was included as a typical rural county. The final three regions – San Francisco County, California (San Francisco); Washington, DC; and Multnomah County, Oregon (Portland) – contain cities ranked among the smartest cities in North America, based on a key set of assessment factors linked to sustainability, technology-enabled innovation and citizen participation (Cohen 2013).

Analysis approach

The following two approaches were applied to explore the relationship between New Urbanism principles and public health.

1. A statistical analysis based on the data obtained from selected counties in the United States to test the effect of the first two principles of New Urbanism (walkability and connectivity) on public health. Several measures of effectiveness (MOEs) were used to represent connectivity, walkability and health. A correlation analysis was conducted to explore the relationship between walkability, connectivity and health.

2. A literature review to examine the effect of the other eight New Urbanism principles on health, including: mixed use and diversity; mixed housing; quality architecture and urban design; traditional neighbourhood structure; increased density; smart transportation; sustainability; and quality of life.

Principles 1 and 2: effect of connectivity and walkability on health

Health condition score (dependent variables)

The study identified data for a two-year period (2016 and 2017), broadly categorized according to the US Centers for Disease Control and Prevention (CDC) to represent (a) length and quality of life; (b) health behaviours; (c) clinical care; (d) socio-economic factors; and (e) physical environment. A subset of relevant data was selected for the analysis. Table 1 is a subset of health- and wellness-related data for the nine counties, with lower values being more desirable. The data, which were reported in various units of measure, were converted into per capita and percentages for comparative analysis.

Table 1. Health and wellness data for the nine study counties scaled as percentage, per capita, to eliminate multiple formats and improve consistency for data analysis.

Health outcomes	Premature age-adjusted mortality per capita	Frequent physical distress (%)	Frequent mental distress (%)	Diabetes prevalence (%)	Premature death per capita	Poor physical health days	Adult obesity (%)	SUM	Motor vehicle crash death rate
San Francisco, CA	0.00028	9	9	8	0.00543	3.2	16	45.2	4
Washington, DC	0.00060	10	10	8	0.01145	3.2	22	53.2	6
Multnomah, OR, (Portland)	0.00041	11	12	8	0.00981	3.9	21	55.9	6
Harris, TX, (Houston)	0.00007	11	11	9	0.00143	3.5	27	61.5	10
Los Angeles, CA	0.00003	11	11	9	0.00048	3.6	21	55.6	7
El Paso, CO	0.00044	10	10	7	0.00919	3.5	22	52.5	10
Allen, KS	0.03774	10	10	11	0.81780	3.4	34	69.3	21
Cedar, IA	0.01200	9	9	11	0.21810	3.0	32	64.2	9
Clay, MS	0.02644	15	15	15	0.55367	5.0	35	85.6	18

The values in Table 1 were normalized between 0 and 1. The outcome presented in Table 2 represents health condition scores (HCSs) sorted by the US counties included in this analysis, with the minimum value set to zero and the higher value indicating a better HCS for the health-outcome criteria. The following formula was applied to normalize and make HCS dimensionless.

Table 2. Health and wellness data scores for the study counties with values normalized between 0 and 1^*.

Health outcomes	Premature age-adjusted mortality	Frequent physical distress	Frequent mental distress	Diabetes prevalence	Premature death	Poor physical health	Adult obesity	Overall	Motor vehicle crash death
San Francisco, CA	0.99	0.40	0.40	0.47	0.99	0.36	0.54	0.47	0.81
Washington, DC	0.98	0.33	0.33	0.47	0.99	0.36	0.37	0.38	0.71
Multnomah, OR, (Portland)	0.99	0.27	0.20	0.47	0.99	0.22	0.40	0.35	0.71
Harris, TX, (Houston)	1.00	0.27	0.27	0.40	1.00	0.30	0.23	0.28	0.52
Los Angeles, CA	1.00	0.27	0.27	0.40	1.00	0.28	0.40	0.35	0.67
El Paso, CO	0.99	0.33	0.33	0.53	0.99	0.30	0.37	0.39	0.52
Allen, KS	0.00	0.33	0.33	0.27	0.00	0.32	0.03	0.19	0.00
Cedar, IA	0.68	0.40	0.40	0.27	0.73	0.40	0.09	0.25	0.57
Clay, MS	0.30	0.00	0.00	0.00	0.32	0.00	0.00	0.00	0.14

*Legend: higher values equate to better health conditions for that criteria. Green indicates better health conditions, and red indicates worse health conditions. Readers of the print copy can view the tables in colour in the online publication.

Assuming:

$z_{ij}=$Value of criterion j for county i

Then:

$r_{ij}=1-\frac{z_{ij}}{Max{z}_{ij}}$

The result will be (0 ≤ r_ij ≤1), with higher r_ij values being more desirable.

Connectivity and walkability scores (independent variables)

The evaluation criteria and MOE for level of connectivity, which represents the urban form, and intersection density, indicative of the walkability of each area, were analyzed. TransCAD, a GIS-capable transportation planning software, was used for this analysis (Caliper Corporation 2018). The transportation network geographical files for the US counties that were provided as part of the software package were used for this analysis.

Connectivity

Table 3 is a summary of the connectivity indicators (CIs) for the selected counties in this study. These measures represent the urban form. Grid networks have a higher level of connectivity. The following CI variables were estimated:

Table 3. Connectivity indicators as urban form and intersection density as walkability measures of effectiveness (MOE) for the selected study counties.

	Connectivity indicators					Walkability indicator
Urban form and walkability MOE	Link-node ratio	Gamma index	Alpha index	Connected-node ratio	Overall connectivity	Average number of intersections per square mile
San Francisco, CA	1.61	0.54	0.31	0.88	4.36	154
Washington, DC	1.53	0.51	0.26	0.89	4.22	107
Multnomah, OR, (Portland)	1.35	0.45	0.17	0.79	3.81	56
Harris, TX, (Houston)	1.31	0.44	0.16	0.77	3.73	53
Los Angeles, CA	1.30	0.43	0.15	0.78	3.72	30
El Paso, CO	1.24	0.41	0.12	0.72	3.58	13
Allen, KS	1.26	0.42	0.13	0.76	3.61	6
Cedar, IA	1.19	0.40	0.09	0.68	3.40	4
Clay, MS	1.11	0.37	0.05	0.60	3.20	6

Link-Node Ratio: An index of connectivity equal to the number of links divided by the number of nodes.

Gamma Index: Ratio of the number of links in the network to the maximum possible number of links between nodes.

Alpha Index: Ratio of the number of actual circuits to the maximum number of circuits.

Connected-Node Ratio: Number of street intersections divided by the number of intersections plus cul-de-sacs.

Walkability

Allan Jacobs’s monumental study on city street design, supported by data and drawings of more than 40 world cities, each 1-mile square, indicated that cities with smaller blocks and thus more intersections are the most walkable (Jacobs 1995). In addition, in a recent study, the walkability indicator known as intersection density was measured to find its relationship with physical activity based on data collected in 14 cities worldwide. The result indicated a positive significant and linear relationship between physical activity and intersection density, net residential density, public transport density and number of parks (Sallis et al. 2016).

Intersection density: This indicator was used for the walkability criteria. Table 3 shows the density of street intersections in the selected counties based on the number of intersections per square mile and giving a weight of 1 to four-way intersections, which are more attractive to walking, and a weight of 0.5 to three-way tee intersections. As shown in Table 3, in terms of the average number of intersections per square mile, San Francisco, California, and Washington, DC ranked at the top, with 154 and 107 intersections, respectively, followed by Multnomah County (Portland).

Table 4 summarizes the result of transportation-network connectivity and walkability using normalized values between 0 and 1. The higher scores for the variables applied indicate a better interconnected and walkable roadway network. The following formula was applied to normalize and make connectivity and walkability values dimensionless.

Table 4. Urban form and walkability scores for the selected study counties where values are normalized between 0 and 1.

	Connectivity indicators					Walkability indicator
Urban form and walkability MOE	Link-node ratio	Gamma index	Alpha index	Connected-node ratio	Overall connectivity	Average number of intersections per square mile
San Francisco, CA	1.00	1.00	1.00	0.99	1.00	1.00
Washington, DC	0.95	0.95	0.86	1.00	0.97	0.70
Multnomah, OR, (Portland)	0.84	0.84	0.57	0.88	0.87	0.37
Harris, TX, (Houston)	0.82	0.82	0.51	0.86	0.86	0.34
Los Angeles, CA	0.81	0.81	0.50	0.87	0.85	0.20
El Paso, CO	0.77	0.77	0.39	0.81	0.82	0.08
Allen, KS	0.78	0.78	0.42	0.85	0.83	0.04
Cedar, IA	0.74	0.74	0.31	0.76	0.78	0.03
Clay, MS	0.69	0.69	0.18	0.67	0.73	0.04

*Legend: higher values equate to better connectivity and walkability. Green indicates better connectivity and walkability, and red indicates worse connectivity and walkability. Readers of the print copy can view the tables in colour in the online publication.

Assuming:

$z_{ij}=$Value of criterion j for county i

Then:

$r_{ij}=\frac{z_{ij}}{Max{z}_{ij}}$

The result will be (0 ≤ r_ij ≤1), with higher r_ij values being more desirable.

The results indicate that San Francisco has the highest level of connectivity and walkability, followed by Washington, DC and Multnomah County, Oregon (Portland). Harris County, Texas (Houston), Los Angeles County, California, and El Paso County, Colorado, are rated as lower, and Allen County, Kansas, Cedar County, Iowa, and Clay County, Mississippi, are rated the lowest in terms of roadway interconnectedness and walkability. These latter three counties are classified as rural counties.

Analysis revealed that the study regions with the highest intersection density were also among the 10 smart cities in North America that focus on optimizing existing infrastructure to create better land-use decisions and leverage citizen participation (Cohen 2013). Rural counties and those with lower standings in socio-economic demographics, such as Allen County, Kansas, Cedar County, Iowa, and Clay County, Mississippi, received the lowest ratings in terms of roadway interconnectedness and walkability.

Connectivity and walkability linkage with health condition

A correlation analysis was conducted to measure the association between the selected health and wellness data (dependent variable) and the urban connectivity and walkability measures (independent variables). The result is shown in Table 5. The strength and direction of linear relationship ranging from +0.5 to +0.7 are considered strong and indicate a positive relationship, and values above +0.7 are regarded as very strong correlations.

Results and discussion

The results of the correlation analysis clearly indicate a very strong relationship between (a) connectivity and health and (b) walkability and health. In addition, the counties that have a higher value of walkability and connectivity (San Francisco, Portland and Washington, DC) consistently rank higher across the health and wellness measures. This indicates that urban forms manifesting gridded networks and smaller blocks, allowing for more intersections and enabling pedestrians to walk a variety of routes from their points of origin and destinations, have a promotive effect on health and wellness and embody a key design characteristic of smart cities. Study counties reporting a higher incidence of obesity and greater prevalence of type 2 diabetes have much lower CI values, requiring automobiles for transportation. This result complements a study conducted in Ontario, Canada, which revealed a correlation between a higher level of neighbourhood walkability with a decreased prevalence of obesity and a decreased incidence of diabetes. Nevertheless, the same study recommended further investigations to evaluate causality in the reported correlations (Creatore et al. 2016).

By design, a dense grid network, whether the grid is regular or irregular, with smaller block size and intersection spacing, provides multiple choices and more freedom for pedestrians to walk any origin-destination pairs. Pedestrians have choices of different routes and can discover more at each junction, while their routes will be shorter because they can avoid out-of-direction traffic. Smaller blocks provide more places where automobiles can stop to allow pedestrians to cross streets. Furthermore, smaller blocks that have reduced distances between two consecutive intersections will distribute car traffic among the roads more evenly as opposed to funnelling all car traffic onto a few major roads, which is typical of a low-CI city design. Studies have shown that small block size and a dense grid roadway network offer a different experience, encourage the use of other means of transportation, and promote health and wellness (Katapally et al. 2018). Smaller blocks reduce distances between origin-destination pairs, a key shortcoming of conventional expressway design.

Primary constraints on the data analysis and evaluation are the probable roles of socio-economic and demographic variables. Furthermore, there are relatively few walkable cities in the United States, which limited the sample size for this study. Hence, the data analysis approach should be used as a guide for the purpose of comparative analysis, not for developing a comprehensive mathematical model. However, this study also referred to Allan Jacobs’s data analysis of city street design as a secondary resource, which is supported by data and drawings representing more than 40 world cities, revealing that higher intersection density promotes a higher level of walking, which aligns with this study’s conclusion.

Principle 3: effect of mixed use and diversity on public health

Mixed-use developments bring origin-destination pairs closer, enhancing urban vibrancy, increasing physical activity and promoting the use of active transportation, resulting in improved health outcomes and reduced travel distance, minimizing the need for private automobiles. Frank, Andresen, and Schmid (2004) revealed an association between land use and physical fitness in a study involving the 13 counties of the metropolitan Atlanta region, and concluded that the likelihood of being obese reduces as the mix of land use increases. The study estimated that each additional hour spent in an automobile per day was associated with a 6% increase in the likelihood of obesity. Conversely, each additional kilometre walked per day was associated with a 4.8% reduction in the likelihood of obesity.

The health benefits accrued with mixed-use developments are attributable to people walking and riding bicycles more than in typical suburban environments with segregated land use. Saelens, Sallis, and Frank (2003) presented evidence indicating that residents in communities that have higher-density developments, greater connectivity and more mixed-use land walk and/or cycle more for utilitarian purposes as opposed to low-density developments with lower levels of connectivity and with widely separated single land uses.

Principle 4: effect of mixed housing on public health

Mixed housing aims to meet the basic needs of all residents to live, work and play, regardless of income level, age, socio-economic standing or culture. Complete communities is an urban-planning concept that respects the needs of all residents – regardless of their income, culture, age or ideas. Considering that the focus of the health quality of residents is more on prevention, a range of housing choices that enables older adults to age in place is vital. Affordable housing, safe outdoor spaces, places that encourage active living with inexpensive and convenient transportation options, opportunities for social participation and community leadership, and accessible health and wellness services are among the important criteria to promote for developing age-friendly communities (Jeste et al. 2016). Residential areas in communities should include affordable housing for low-income populations and the elderly, so they can spend more income on their health and well-being. As stated by the co-founder of the CNU, Peter Calthorpe (1999, 179),

We should no longer isolate the poor in the inner city and segregate the middle class in the suburbs. It implies limiting additional public housing in low-income neighbourhoods, and instead scattering public housing throughout the region and fostering inclusionary zoning in the suburbs.

Principle 5: effect of quality architecture and urban design on public health

Indoor environments, as designed and operated, are linked to adverse effects on public health (Guenther and Vittori 2008). As it relates to outdoor environments, the transportation network is the framework upon which cities are built and shapes the growth and evolution of cities. Conventional road design relies on wide roads and highways segmenting cities into parts and promotes automobile traffic while offering no support for non-motorized transportation. This results in traffic congestion and pollution and minimizes walking, thereby resulting in negative impacts on public health. An interactive public realm offers opportunities for people to meet, move, relax and observe through a network of well-connected, narrower streets and appropriately arranged streetscapes that encompass a series of open spaces and nodes of activity. The health-promotive urban design should not lay out streets only as conduits to move traffic but rather as enablers for residents to walk, socialize and play. Wide roads, by design, break connectivity within the city. It is known that roads have diseconomy of scale as opposed to other services (Kulash, Anglin, and Marks 1990). In other words, four two-lane roads function better than one eight-lane road for pedestrians and automobiles, because there will be more choices for turning and because traffic distributes more evenly on multiple streets rather than being funnelled onto a few wide roads, making it easier for pedestrians to walk, navigate and cross streets.

Principle 6: effect of traditional neighbourhood structure on public health

New Urbanism should not be framed merely as a conservative approach to recapture outdated traditions while ignoring the issues of our time. However, replacing cul-de-sacs and auto-oriented shopping malls with traditional urban design, along with instituting diversity and the principles of regionalism, will take cities back from cars and return them to people (Calthorpe et al. 1999). Traditional urban design, while considering the needs of modern life, attempts to resurrect the sense of place and community in neighbourhoods with its attendant mental- and physical-health-quality improvements.

The Michigan Land Use Institute (2006) describes the traditional neighbourhood structure principle of New Urbanism as neighbourhoods with definite centres and edges, including public spaces near the centre. Each neighbourhood contains a range of uses and densities within a 10-minute walk. Traditional neighbourhood design promotes compact housing, a grid street network with short blocks and mixed use. Zuniga-Teran et al. (2017) performed a comparative analysis of four different neighbourhood designs in Tucson, Arizona – (a) traditional development; (b) suburban development; (c) cluster housing development; and (d) enclosed community – and evaluated the level of walkability and its effects on physical activity and well-being. The study concluded that traditional development strongly correlated with the highest value for walkability, whether for recreation or transportation. Suburban development indicated significant association and the highest mean values for mental health and well-being. Cluster housing was ranked the highest for social interactions with neighbours and for perceived safety from crime. Enclosed community did not obtain the highest mean value for any well-being benefit in any of these categories.

Principle 7: effect of increased density on public health

High-density developments within the context of a compact city that promote vertical growth and mixed use and that create limits to urban expansion bring origins closer to destinations and therefore make places more walkable, leading to many economic, social, environmental and health benefits. In contrast, urban sprawl tends to create resident dependency on private automobiles, an increase in vehicle miles travelled (VMT). Adverse impacts on health result from the air pollution associated with more automobile traffic in an urban sprawl environment.

Evidence exists that residents in more compact areas have more active travel and therefore lower body mass indexes (BMIs) and lower probabilities of obesity and chronic diseases (Ewing and Cervero 2010). In a study, Ewing et al. (2014) concluded that urban and suburban areas with more compact areas are linked with ameliorative effects on obesity and chronic diseases. The study indicated that sprawl is associated with obesity, high blood pressure or other health conditions, but did not elaborate on the type of sprawl associated with adverse health effects, recommending additional epidemiologic research using longitudinal cohorts for the study.

In a study prepared by Giles-Corti et al. (2014) for the National Heart Foundation of Australia, the potential impact of low-density developments on physical activity and health was investigated. Extensive literature review and meta data analysis concluded that those who lived in lower-density neighbourhoods, or who were perceived as living in lower-density areas, walked less than those in the higher-density areas. The same study also revealed associative evidence between living in lower-density areas and increased overweight and obese adults and adolescents, although such a relationship with younger children was inconclusive. Moreover, the study revealed a greater positive association between behavioural changes geared towards walking and cycling among individuals living in higher densities compared to those living in low-density developments that are more dependent on automobiles for transportation. This study also obtained population and land area data for the studied counties from the database provided by Caliper as part of TransCAD software (Caliper Corporation 2018) and explored a strong positive relationship between population density and walkability based on the scores reported in Table 4. The result is illustrated in Figure 1, which was generated by the same software. It is noteworthy to mention that activity centres in Portland, Oregon, are highly walkable. The reason that Portland’s walkability score is not as high as expected, is because the analysis considered the entirety of Multnomah County, where Portland is located, and the low-density character of the county’s suburbs brought its overall average walkability score to a lower value.

Principle 8: effect of smart transportation on public health

Figure 1. Population density per square mile (numbers on top) and walkability scores (numbers on bottom) for selected study counties. Each symbol represents 20 people per square mile. Maps are not to scale.

City planners and public-health experts are beginning to evaluate the potential of smart technologies to directly address health- and wellness-related benefits as part of a foundational architecture concept for smart cities. However, it is important to note that technology is merely an enabler and effective only when applied with best-practice transportation planning and urban design. Smart transportation is about moving people as opposed to cars. This research and other published evidence indicate that smart cities enabling smart transportation by providing multimodal transportation with an emphasis on non-motorized and public transit modes have a promotive and positive impact on health and wellness. Smart city design considerations should address health- and wellness-related priorities and require establishing health-related public policies at the local levels by the city administrators to create healthy environments and surroundings and to establish service offerings aimed at promoting citizen empowerment and participation at the community level (Andrade et al. 2017).

Multimodal transportation system

Cities planned for multimodal transportation as opposed to automobile-centric constructs tend to alleviate traffic congestion, reduce energy consumption and lower emissions. Notably, multimodal transportation system measures to reduce SOVs can have a significant positive effect on public health. Policy measures, such as congestion pricing, limiting parking supply and promoting other modes of transportation, will discourage the use of the automobile, resulting in a strategic shift towards non-motorized and public transit modes

A recent study by Frederick, Riggs, and Gilderbloom (2017) examined 148 US counties and their metropolitan statistical areas by measuring 12 public-health and quality-of-life indicators against commute mode diversity (CMD). It found a positive relationship between metropolitan areas that have fewer workers commuting by SOV with (a) better health conditions and healthier behaviours evaluated on the Gallup/Healthway’s Well-Being Index; (b) more leisure quality reported by Sperling’s Cities Ranked and Rated; (c) more access to exercise reported by the Environmental Systems Research Institute; (d) less sedentary living and obesity reported in the CDC Diabetes Interactive Atlas; and (e) more years of potential life lost (an indicator of longevity and overall health) and higher birth weights (an indicator of infant health), as reported by the National Center for Health Statistics. The finding revealed powerful statistical evidence of cities offering multimodal travel environments having a positive impact on public health as well as many other sociological, geographical and economic concerns, including race, density, latitude, education and income. The main components of a multimodal system are walking, cycling and public transportation. Researchers have evaluated the positive impact of public transportation on health and wellness and assessed ways to incorporate these public health-related considerations as part of formulating transportation policy (Litman 2016). These and other similar studies have evaluated the significant behavioural changes, such as walking, cycling, the use of public transit and lower ownership of automobiles, associated with a qualitative improvement in health and wellness (Bailey, Mokhtarian, and Little 2008; Ohland and Poticha 2009).

Need for traffic level-of-service standards to encourage multimodal transportation system

One of the problems associated with implementing best-practice urban design relates to the tools being applied in conventional traffic engineering to evaluate development and traffic conditions. An important aspect of this research is the tools applied to measure connectivity and walkability to evaluate the transportation systems. Traffic engineers, in many cases, have used other tools, such as link volume-to-capacity (V/C) ratio, intersection level of service or related measurements, to ease mobility for cars. However, the focus remains on increasing the roadway and intersection capacity to solve congestion instead of implementing a well-connected network to accommodate all modes of transportation. Transportation design has segregated people and cars under the guise of safety, with an emphasis on wider and larger roadways, which are fundamentally anti-pedestrian. As a result, wider roads and expressways limit accessibility, and large metropolitan centres become increasingly dependent on automobile transportation (Jacobs 1995).

Need for roadway design standards to encourage compact cities

The road hierarchy system known as roadway functional classification, based on conventional roadway design standards, distorts a land-use system and exacerbates the problem by locating residential pods around local roads and commercial areas around expressways. As a result, conventional road systems increase distances between origin and destination points, thus contributing to increasing traffic and causing a sprawl effect and the segregation of uses. In contrast, the interconnected grid roadway system, with denser, smaller blocks and narrower roads, promotes compact and mixed land use, decreasing distances between origins and destinations and offering attendant public-health benefits.

Design models to promote accessibility as opposed to mobility

Conventional traffic engineering has focused mostly on mobility rather than accessibility. The underlying logic is that less accessibility provides better mobility, and, as expressways have less access to ingress and egress, they can move traffic without any delay. Such a concept could work only if no traveller needed to get on or off of expressways, which is not the case. Consequently, the conventional system of roadway hierarchy promotes expressways and interchanges, causing out-of-direction and clogged traffic. Expressways, by design, have access and exit points only at certain distances, causing longer commute distances. Moreover, expressways encourage residents to live far from work, causing longer trip distances, more energy consumption, environmental pollution and adverse health impacts for the public.

Non-motorized transportation network

Smart transportation, which is health-promotive, should provide a continuous and human-scaled sidewalk and cycling network that includes features such as trees, lighting, street furniture and public art to enliven a city. Sidewalks and cycle tracks should have reasonable widths for pedestrians and be connected by frequent safe street crossings. Although sidewalks are an important element of the public realm, it takes more than just a sidewalk to be conducive to walking and cycling. This requires pedestrian networks that are seamless and well connected to other modes of transportation. Furthermore, right-of-way (ROW) design should consider the bicycle plan and allow for the inclusion of bike tracks as part of the ROW. A smaller kerb radius at intersections will minimize crosswalk lengths and make cities more walkable. Alternatively, a large radius and free right-turn slip lanes encourage speeding by motorists and are not considered a pedestrian-friendly design.

Transit-friendly road network

A robust public-transit route system that is optimized for all travellers to reach stops within walking distance, with frequent service, is the key to the success of public transportation. Smart city public transit design should allow for bus kerbs or bulbs that allow buses to stop on the main traffic lane while other automobiles wait until all passengers are on board and the bus can continue travel without delay. Conventional auto-friendly transit systems use bays for public transportation systems, where the bus must stop to allow cars to pass on the main lane, and once the bus finds a gap after delay, it can get out of the bay and merge into traffic. A transit-oriented design, in contrast, uses kerbs or bulbs so buses stop on main traffic lanes while automobiles must wait.

Traffic safety

Given the importance of traffic safety and its relationship to public health, this study examined the motor-vehicle crash death rate by each county studied as an additional measure and analyzed its relationship with roadway connectivity and walkability in the correlation analysis. The results, summarized in Table 5, indicate another corollary benefit of the interconnected roadway networks and walkable places in the study counties, demonstrating better traffic safety and reporting fewer fatal accidents.

Table 5. Coefficient of correlation values indicating strength of the relationship between urban form and walkability indicators and health and wellness and motor vehicle accident fatalities.

Coefficient of correlation	Premature age-adjusted mortality per capita	Frequent physical distress (%)	Frequent mental distress (%)	Diabetes prevalence (%)	Premature death per capita	Poor physical health days	Adult obesity	Overall health	Motor vehicle crash death rate
Link-node ratio	0.53	0.54	0.51	0.65	0.51	0.52	0.78	0.78	0.67
Gamma index	0.53	0.54	0.51	0.65	0.51	0.52	0.78	0.78	0.67
Alpha index	0.53	0.54	0.51	0.65	0.51	0.52	0.78	0.78	0.67
Connected-node ratio	0.52	0.61	0.58	0.74	0.50	0.62	0.75	0.81	0.63
SUM	0.55	0.55	0.53	0.70	0.53	0.54	0.80	0.81	0.67
Number of intersections	0.54	0.37	0.35	0.51	0.52	0.35	0.74	0.67	0.66

Principles 9 and 10: effect of sustainability and quality of life on public health

Numerous research studies have defined smart cities not only by use of technology but also a focus on sustainability and as the crucibles for promoting health and wellness as part of the broader people-centric design and use of technologies. What determines a smart city should be not only how all the artefacts in the city, including buildings, automobiles, trees, parking and trash cans, are interconnected by technology, but also how they functionally better integrate how places and people are well connected as communities by urban design. Environmentally friendly smart cities aim not only at the proximate goals of energy efficiency and pollution prevention but also at the ultimate goal of sustainable cities and communities, which, according to United Nation Development Programme (UNDP), means ‘ensuring access to safe and affordable housing, and upgrading slum settlements. It also involves investment in public transport, creating green public spaces, and improving urban planning and management in a way that is both participatory and inclusive’ (United Nation Development Programme 2018).

Smart health is a requirement of smart and sustainable cities. Researchers have proposed the concept of smart health (s-health) as an extension of electronic health (e-health), which is the context-aware complement of mobile health within smart cities, and they have approached this concept as an opportunity to exploit the power of mobile technologies for the more efficient and effective delivery of health care services (Solanas et al. 2014).

Conclusion

The study undertook a systematic investigation of the role of 10 New Urbanism principles on public health and wellness. The impact of the first two principles of New Urbanism, walkability and connectivity, were evaluated by comparing selected US counties. Health condition scores for the selected health and wellness measures for the study regions that included Washington, DC, San Francisco, California, and Portland, Oregon, were consistently higher than other regions included in the study. These regions also scored high on various connectivity indicators that were measured and scored high for intersection density, which is a key design measure indicative of walkability. Higher intersection density and roadway connectivity with narrower roads result in an urban form that induces behavioural changes that promote the use of non-motorized modes of transportation and a higher level of physical activity, bringing with them the attendant health and wellness benefits.

Literature reviews were also conducted to analyze the impact of the other eight New Urbanism principles on public health. Available evidence indicates that residents in mixed-use areas walk and/or cycle more frequently and have better health. Studies point to a complete community planning concept with mixed housing for all residents, regardless of income level, age or culture, yields a positive effect on health and well-being. This paper referred to a study comparing four types of urban fabric, including traditional development, suburban development and cluster housing development, and concluded that traditional development is distinctively the most walkable. This study showed that higher density areas can bring origin and destination pairs closer, and therefore positively affect active transportation use, bringing attendant public health and wellness benefits. Smart transportation is defined not only as a technology related improvement, but also a multimodal transportation systems which provides different choices for people to move and discourages the use of SOVs, enabling health-promotive behaviours. Policy measures to revise the auto-centric level-of-service tools applied by conventional roadway and traffic engineering standards will make cities more pedestrian- and transit-friendly, resulting in positive impacts on health and wellness. Figure 2 summarizes how New Urbanism principles improve public health.

The MOEs applied in this study to analyze the connectivity and walkability of developments are recommended as tools to establish roadway level of service. Traffic safety goals are better attained when cities are more walkable and have higher levels of roadway connectivity. Hence, the principles of New Urbanism improve the design and functionalities of the cities as well as public health and wellness and should be a guide for policy makers and practitioners for smart city-development projects. Further research is warranted to apply the influence of socio-economic and demographic variables, particularly income, and compare them with the physical environment’s effects on public health. Moreover, given that New Urbanism principles result in communities that provide people with the opportunity for more social interaction, effects on mental health, including stress, anxiety and depression, are other important topics of research.

Figure 2. New Urbanism principles, outcomes and results leading to public health improvement.

Disclosure statement

No potential conflict of interest was reported by the authors.