Demographic change and urban health: Towards a novel agenda for delivering sustainable and healthy cities for all.

The focus is on the demographic drivers and demographic implications of urban health and wellbeing in towns and cities across the globe. The aim is to identify key linkages between demographic change and urban health - subjects of two largely disparate fields of research and practice - with a view to informing arguments and advocacy for urban health while identifying research gaps and priorities. The core arguments are threefold. First, urban health advocates should express a globalized perspective on demographic processes, encompassing age-structural shifts in addition to population growth and decrease, and acknowledging their uneven spatial distributions within and between urban settings in different contexts. Second, advocates should recognize the dynamic and transformational effects that demographic forces will exert on economic and political systems in all urban settings. While demographic forces underpin the production of (intra)urban inequities in health, they also present opportunities to address those inequities. Third, a demographic perspective may help to extend urban health thinking and intervention beyond a biomedical model of disease, highlighting the need for a multi-generational view of the changing societal bases for urban health, and enjoining significant advances in how interested parties collect, manage, analyse, and use demographic data. Accordingly, opportunities are identified to increase the availability of granular and accurate data to enable evidence-informed action on the demographic/health nexus.

Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation.

The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models.Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites.In this paper we discuss the deficiencies of existing spatial population datasets and their limitations on epidemiological analyses. We review sources of detailed, contemporary, freely available and relevant spatial demographic data focusing on low income regions where such data are often sparse and highlight the value of incorporating these through a set of examples of their application in disease studies. Moreover, the importance of acknowledging, measuring, and accounting for uncertainty in spatial demographic datasets is outlined. Finally, a strategy for building an open-access database of spatial demographic data that is tailored to epidemiological applications is put forward.

Roundtable on Urban Living Environment Research (RULER).

For 18 months in 2009-2010, the Rockefeller Foundation provided support to establish the Roundtable on Urban Living Environment Research (RULER). Composed of leading experts in population health measurement from a variety of disciplines, sectors, and continents, RULER met for the purpose of reviewing existing methods of measurement for urban health in the context of recent reports from UN agencies on health inequities in urban settings. The audience for this report was identified as international, national, and local governing bodies; civil society; and donor agencies. The goal of the report was to identify gaps in measurement that must be filled in order to assess and evaluate population health in urban settings, especially in informal settlements (or slums) in low- and middle-income countries. Care must be taken to integrate recommendations with existing platforms (e.g., Health Metrics Network, the Institute for Health Metrics and Evaluation) that could incorporate, mature, and sustain efforts to address these gaps and promote effective data for healthy urban management. RULER noted that these existing platforms focus primarily on health outcomes and systems, mainly at the national level. Although substantial reviews of health outcomes and health service measures had been conducted elsewhere, such reviews covered these in an aggregate and perhaps misleading way. For example, some spatial aspects of health inequities, such as those pointed to in the 2008 report from the WHO's Commission on the Social Determinants of Health, received limited attention. If RULER were to focus on health inequities in the urban environment, access to disaggregated data was a priority. RULER observed that some urban health metrics were already available, if not always appreciated and utilized in ongoing efforts (e.g., census data with granular data on households, water, and sanitation but with little attention paid to the spatial dimensions of these data). Other less obvious elements had not exploited the gains realized in spatial measurement technology and techniques (e.g., defining geographic and social urban informal settlement boundaries, classification of population-based amenities and hazards, and innovative spatial measurement of local governance for health). In summary, the RULER team identified three major areas for enhancing measurement to motivate action for urban health-namely, disaggregation of geographic areas for intra-urban risk assessment and action, measures for both social environment and governance, and measures for a better understanding of the implications of the physical (e.g., climate) and built environment for health. The challenge of addressing these elements in resource-poor settings was acknowledged, as was the intensely political nature of urban health metrics. The RULER team went further to identify existing global health metrics structures that could serve as platforms for more granular metrics specific for urban settings.

Global Harmonization of Urbanization Measures: Proceed with Care.

By 2050, two-thirds of the world's population is expected to be living in cities and towns, a marked increase from today's level of 55 percent. If the general trend is unmistakable, efforts to measure it precisely have been beset with difficulties: the criteria defining urban areas, cities and towns differ from one country to the next and can also change over time for any given country. The past decade has seen great progress toward the long-awaited goal of scientifically comparable urbanization measures, thanks to the combined efforts of multiple disciplines. These efforts have been organized around what is termed the "statistical urbanization" concept, whereby urban areas are defined by population density, contiguity and total population size. Data derived from remote-sensing methods can now supply a variety of spatial proxies for urban areas defined in this way. However, it remains to be understood how such proxies complement, or depart from, meaningful country-specific alternatives. In this paper, we investigate finely resolved population census and satellite-derived data for the United States, Mexico and India, three countries with widely varying conceptions of urban places and long histories of debate and refinement of their national criteria. At the extremes of the urban-rural continuum, we find evidence of generally good agreement between the national and remote sensing-derived measures (albeit with variation by country), but identify significant disagreements in the middle ranges where today's urban policies are often focused.

Urban Family Planning in Low- and Middle-Income Countries: A Critical Scoping Review.

Health agendas for low- and middle-income countries (LMICs) should embrace and afford greater priority to urban family planning to help achieve a number of the global Sustainable Development Goals. The urgency of doing so is heightened by emerging evidence of urban fertility stalls and reversals in some sub-Saharan African contexts as well as the significance of natural increase over migration in driving rapid urban growth. Moreover, there is new evidence from evaluations of large programmatic interventions focused on urban family planning that suggest ways to inform future programmes and policies that are adapted to local contexts. We present the key dimensions and challenges of urban growth in LMICs, offer a critical scoping review of recent research findings on urban family planning and fertility dynamics, and highlight priorities for future research.

The heterogeneity and change in the urban structure of metropolitan areas in the United States, 1990-2010.

While the population of the United States has been predominantly urban for nearly 100 years, periodic transformations of the concepts and measures that define urban places and population have taken place, complicating over-time comparisons. We compare and combine data series of officially-designated urban areas, 1990-2010, at the census block-level within Metropolitan Statistical Areas (MSAs) with a satellite-derived consistent series on built-up area from the Global Human Settlement Layer to create urban classes that characterize urban structure and provide estimates of land and population. We find considerable heterogeneity in urban form across MSAs, even among those of similar population size, indicating the inherent difficulties in urban definitions. Over time, we observe slightly declining population densities and increasing land and population in areas captured only by census definitions or low built-up densities, constrained by the geography of place. Nevertheless, deriving urban proxies from satellite-derived built-up areas is promising for future efforts to create spatio-temporally consistent measures for urban land to guide urban demographic change analysis.

Urbanization in India: Population and Urban Classification Grids for 2011.

India is the world's most populous country, yet also one of the least urban. It has long been known that India's official estimates of urban percentages conflict with estimates derived from alternative conceptions of urbanization. To date, however, the detailed spatial and settlement boundary data needed to analyze and reconcile these differences have not been available. This paper presents gridded estimates of population at a resolution of 1 km along with two spatial renderings of urban areas-one based on the official tabulations of population and settlement types (i.e., statutory towns, outgrowths, and census towns) and the other on remotely-sensed measures of built-up land derived from the Global Human Settlement Layer. We also cross-classified the census data and the remotely-sensed data to construct a hybrid representation of the continuum of urban settlement. In their spatial detail, these materials go well beyond what has previously been available in the public domain, and thereby provide an empirical basis for comparison among competing conceptual models of urbanization.

Using sexually transmitted infection biomarkers to validate reporting of sexual behavior within a randomized, experimental evaluation of interviewing methods.

This paper examines the reporting of sexual and other risk behaviors within a randomized experiment using a computerized versus face-to-face interview mode. Biomarkers for sexually transmitted infection (STI) were used to validate self-reported behavior by interview mode. As part of a parent study evaluating home versus clinic screening and diagnosis for STIs, 818 women aged 18-40 years were recruited in 2004 at or near a primary care clinic in São Paulo, Brazil, and were randomized to a face-to-face interview or audio computer-assisted self-interviewing. Ninety-six percent of participants were tested for chlamydia, gonorrhea, and trichomoniasis. Reporting of STI risk behavior was consistently higher with the computerized mode of interview. Stronger associations between risk behaviors and STI were found with the computerized interview after controlling for sociodemographic factors. These results were obtained by using logistic regression approaches, as well as statistical methods that address potential residual confounding and covariate endogeneity. Furthermore, STI-positive participants were more likely than STI-negative participants to underreport risk behavior in the face-to-face interview. Results strongly suggest that computerized interviewing provides more accurate and reliable behavioral data. The analyses also confirm the benefits of using data on prevalent STIs for externally validating behavioral reporting.

Understanding urbanization: A study of census and satellite-derived urban classes in the United States, 1990-2010.

Most of future population growth will take place in the world's cities and towns. Yet, there is no well-established, consistent way to measure either urban land or people. Even census-based urban concepts and measures undergo frequent revision, impeding rigorous comparisons over time and place. This study presents a new spatial approach to derive consistent urban proxies for the US. It compares census-designated urban blocks with proxies for land-based classifications of built-up areas derived from time-series of the Global Human Settlement Layer (GHSL) for 1990-2010. This comparison provides a new way to understand urban structure and its changes: Most land that is more than 50% built-up, and people living on such land, are officially classified as urban. However, 30% of the census-designated urban population and land is located in less built-up areas that can be characterized as mainly suburban and peri-urban in nature. Such insights are important starting points for a new urban research program: creating globally and temporally consistent proxies to guide modelling of urban change.

The urban transformation of the developing world.

Sometime in the next 20 to 30 years, developing countries in Asia and Africa are likely to cross a historic threshold, joining Latin America in having a majority of urban residents. The urban demographic transformation is described here, with an emphasis on estimates and forecasts of urban population aggregates. To provide policy-makers with useful scientific guidance in the upcoming urban era, demographic researchers will need to refine their data sets to include spatial factors as well as urban vital rates and to make improvements to forecasting methods currently in use.

Urban poverty and health in developing countries: household and neighborhood effects.

In the United States and other high-income countries, there is intense scholarly and programmatic interest in the effects of household and neighborhood living standards on health. Yet few studies of developing-country cities have explored these issues. We investigated whether the health of urban women and children in poor countries is influenced by both household and neighborhood standards of living. Using data from the urban samples of 85 Demographic and Health Surveys and modeling living standards using factor-analytic MIMIC methods, we found that the neighborhoods of relatively poor households are more heterogeneous than is often asserted. Our results indicated that poor urban households do not tend to live in uniformly poor neighborhoods: about 1 in 10 of a poor household's neighbors is relatively affluent, belonging to the upper quartile of the urban distribution of living standards. Do household and neighborhood living standards influence health? Using multivariate models, we found that household living standards are closely associated with three health measures: unmet need for modern contraception, attendance of a trained health care provider at childbirth, and young children's height for age. Neighborhood living standards exert a significant additional influence in many of the surveys we examined, especially for birth attendance.