This study utilised data from the National Income Dynamics Study, a longitudinal study with a sample of approximately 28 000 people, to investigate the cross-sectional and spatial distribution of multimorbidity and the association with socioeconomic disadvantage in South Africa for 2008 and 2012. Multimorbidity increased in prevalence from 2.73% to 2.84% in adults between 2008 and 2012 and was associated with age, socioeconomic deprivation, obesity and urban areas. Hypertension was found frequently coexisting with diabetes. Spatial analysis showed clusters (hot spots) of higher multimorbidity prevalence in parts of KwaZulu-Natal and the Eastern Cape, which compared with the socioeconomic disadvantage spatial pattern. Although these results were limited to a district level analysis, this study has provided a platform for future local level research and has provided insight into the socioeconomic determinants of disease multimorbidity within a developing country.

Though numbers alone may be insufficient to capture the nuances of population health, they provide a common language of appraisal and furnish clear evidence of disparities and inequalities. Over the past 30 years, facilitated by high speed computing and electronics, considerable investment has been made in the collection and analysis of urban health indicators, environmental indicators, and methods for their amalgamation. Much of this work has been characterized by a perceived need for a standard set of indicators. We used publication databases (e.g. Medline) and web searches to identify compilations of health indicators and health metrics. We found 14 long-term large-area compilations of health indicators and determinants and seven compilations of environmental health indicators, comprising hundreds of metrics. Despite the plethora of indicators, these compilations have striking similarities in the domains from which the indicators are drawn—an unappreciated concordance among the major collections. Research with these databases and other sources has produced a small number of composite indices, and a number of methods for the amalgamation of indicators and the demonstration of disparities. These indices have been primarily used for large-area (nation, region, state) comparisons, with both developing and developed countries, often for purposes of ranking. Small area indices have been less explored, in part perhaps because of the vagaries of data availability, and because idiosyncratic local conditions require flexible approaches as opposed to a fixed format. One result has been advances in the ability to compare large areas, but with a concomitant deficiency in tools for public health workers to assess the status of local health and health disparities. Large area assessments are important, but the need for small area action requires a greater focus on local information and analysis, emphasizing method over prespecified content.

We utilized a participatory mapping approach to collect point locations, photographs, and descriptive data about select built environment stressors identified and prioritized by community residents living in the Proctor Creek Watershed, a degraded, urban watershed in Northwest Atlanta, Georgia. Residents (watershed researchers) used an indicator identification framework to select three watershed stressors that influence urban livability: standing water, illegal dumping on land and in surface water, and faulty stormwater infrastructure. Through a community–university partnership and using Geographic Information Systems and digital mapping tools, watershed researchers and university students designed a mobile application (app) that enabled them to collect data associated with these stressors to create a spatial narrative, informed by local community knowledge, that offers visual documentation and representation of community conditions that negatively influence the environment, health, and quality of life in urban areas. By elevating the local knowledge and lived experience of community residents and codeveloping a relevant data collection tool, community residents generated fine-grained, street-level, actionable data. This process helped to fill gaps in publicly available datasets about environmental hazards in their watershed and helped residents initiate solution-oriented dialogue with government officials to address problem areas. We demonstrate that community-based knowledge can contribute to and extend scientific inquiry, as well as help communities to advance environmental justice and leverage opportunities for remediation and policy change.

The relative significance of indicators and determinants of health is important for local public health workers and planners. Of similar importance is a method for combining and evaluating such markers. We used a recently developed index, the Urban Health Index (UHI), to examine the impact of environmental variables on the overall health of cities. We used the UHI to rank 57 of the world’s largest cities (based on population size) in low- and middle-income countries. We examined nine variables in various combinations that were available from the Demographic and Health Surveys conducted in these countries. When arranged in ascending order, the distribution of UHIs follows the previously described pattern of gradual linear increase, with departures at each tail. The rank order of cities did not change materially with the omission of variables about women’s health knowledge or childhood vaccinations. Omission of environmental variables (a central water supply piped into homes, improved sanitation, and indoor solid fuel use) altered the rank order considerably. The data suggest that environmental indicators, measures of key household level risk to health, may play a vital role in the overall health of urban communities.