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.

A majority of urban residents in sub-Saharan Africa (SSA) and other developing regions live in informal settlements, or slums. Much of the discourse on slum health centres on younger generations, while an intensifying agenda on healthy ageing as yet lacks a systematic focus on slums. Similarly, the global age-friendly cities (AFC) movement does not, thus far, extend to slums. This paper examines the particular challenges that a slum-focused age-friendly initiative in SSA may need to address, and the relevance of present AFC indicators and domains for initiatives to advance the health and well-being of older slum dwellers. The analysis builds on the case of two slum communities in Nairobi, Kenya. It analyzes two bodies of relevant evidence from these settlements, namely on the health and social circumstances of older residents, and on the local application and measurement of AFC indicators. The findings point to a set of unsurprising, but also less obvious, core health and social adversities that an age-friendly initiative in such settlements would need to consider. The findings show, further, that the current AFC domains and indicators framework only partly capture these adversities, but that there is potential for adapting the framework to be meaningful for slum settings. The paper concludes by underscoring the need for, and opportunities inherent in, the pursuit of an “age-friendly slums” initiative going forward.

This study evaluated the process by which core indicators of Age-friendly Cities were measured in diverse contexts worldwide. The indicators were developed through research and international expert consultation, and piloted in 15 communities from 12 countries in 2014–2015. Pilot sites attempted to measure all indicators, covering the physical and social environment, quality of life and equity, using locally available data. As a result, the majority of pilot sites reported data for each indicator using one of two possible operational definitions, though data availability varied. Often the indicators were measured using a modified or an alternative definition. Fidelity of measurement was generally higher for the physical environment indicators than for the social environment indicators. Assessing equity was seen as essential but challenging in practice. The core indicators provide an adaptable method for measuring the physical accessibility and social inclusiveness of communities and their impact on wellbeing and equity, especially for older adults. It provides a tool for closing the gap in locally derived data on age-friendliness and improving accountability. Selecting, measuring and reflecting on the indicators through an inclusive process helps to ensure the relevance and validity of the data and to raise awareness and promote collaboration. These, in turn, can become drivers of change for communities at any stage of progress in becoming age-friendly.

The research community has shown increasing interest in developing and using metrics to determine the relationships between urban living and health. In particular, we have seen a recent exponential increase in efforts aiming to investigate and apply metrics for urban health, especially the health impacts of the social and built environments as well as air pollution. A greater recognition of the need to investigate the impacts and trends of health inequities is also evident through more recent literature. Data availability and accuracy have improved through new affordable technologies for mapping, geographic information systems (GIS), and remote sensing. However, less research has been conducted in low- and middle-income countries where quality data are not always available, and capacity for analyzing available data may be limited. For this increased interest in research and development of metrics to be meaningful, the best available evidence must be accessible to decision makers to improve health impacts through urban policies.

Current measures for monitoring progress towards universal health coverage (UHC) do not adequately account for populations that do not have the same level of access to quality care services and/or financial protection to cover health expenses for when care is accessed. This gap in accounting for unmet health care needs may contribute to underutilization of needed services or widening inequalities. Asking people whether or not their needs for health care have been met, as part of a household survey, is a pragmatic way of capturing this information. This analysis examined responses to self-reported questions about unmet need asked as part of 17 health, social and economic surveys conducted between 2001 and 2019, representing 83 low-, middle- and high-income countries. Noting the large variation in questions and response categories, the results point to low levels (less than 2%) of unmet need reported in adults aged 60+ years in countries like Andorra, Qatar, Republic of Korea, Slovenia, Thailand and Viet Nam to rates of over 50% in Georgia, Haiti, Morocco, Rwanda, and Zimbabwe. While unique, these estimates are likely underestimates, and do not begin to address issues of poor quality of care as a barrier or contributing to unmet need in those who were able to access care. Monitoring progress towards UHC will need to incorporate estimates of unmet need if we are to reach universality and reduce health inequalities in older populations.