From theory to action: Implementing the WSSD Global Initiative on children's environmental health indicators
The MEME model: A framework for Children's Environmental Health Indicators
Embedding indicators for children’s environmental health within an appropriate framework has several advantages: A framework represents a simplified version of our underlying concept of reality and makes this view of the world explicit to the target audience. A framework also helps us to be more systematic in defining the issues that confront us, and in analyzing and interpreting them.
WHO, through a participatory process, has developed a framework for children’s environmental health indicators to help (i) assess the impact of the environment on children’s health, (ii) facilitate inter-country and inter-regional comparisons of the status of children’s environmental health, and (iii) monitor the effects of interventions to improve children’s health in relation to the environment9. This Multiple Exposures Multiple Effects (MEME) model (Figure 2) provides the conceptual and theoretical basis for the development, collection and use of children’s environmental health indicators under the umbrella of CEHI.
As its name implies, the MEME model emphasizes the complex relationships between environmental exposures and child health outcomes. Individual exposures can lead to many different health outcomes; specific health outcomes can be attributed to many different exposures. Both exposures and health outcomes – as well as the associations between them - are affected by contextual conditions, such as social, economic or demographic factors. Beyond identifying these underlying driving forces for children’s environmental health problems, information on socioeconomic status is important for disaggregating exposure and health information to investigate environmental justice concerns and to identify vulnerable groups. Actions can be targeted at reducing exposures or at reducing the severity of health outcomes.
The MEME model thus describes the four ingredients required for the monitoring of children’s environmental health: exposure indicators, health outcome indicators, contextual indicators, and action indicators. Table 1 applies the MEME model to the example of indicators related to childhood respiratory diseases.
Table 1: Indicators for childhood respiratory diseases
| Contexts | Exposures | Health outcomes | Actions |
| Children aged 0-14 years* living in poverty | Children aged 0-14 years* living in unsafe, unhealthy or hazardous housing | Intrauterine growth retardation in newborn children | Annual rate of change in tobacco consumption |
| Overcrowding | Mortality rate for children aged 0-4 years due to acute respiratory illness | Annual rate of change in atmospheric pollutant concentrations | |
| Children aged 0-14 years* living in proximity to heavily trafficked roads | Morbidity rate for children aged 0-4 years due to acute respiratory illness | Annual rate of change in numbers of households relying on biomass fuels or coal as the main source of heating or cooking | |
| Mean annual exposure of children aged 0-4 years to atmospheric particulate pollution | Prevalence of chronic respiratory illnesses in children aged 0-14 years* | ||
| Children aged 0-4 years living in households using biomass fuels or coal as the main source of heating or cooking | |||
| Children aged 0-14 years * living in households in which at least one adult smokes on a regular basis |
Where possible, we recommend to disaggregate age groups further into 0-4 years, 10-14 years.
Issues of indicator design
Indicators are visualizations of underlying data that aim to adequately reflect reality. Their design and reporting involves the manipulation, integration, processing and appropriate representation of existing data. Therefore, any indicator is only as good as the data on which it is based10. Consequently, the most important problem to be overcome in relation to children’s environmental health indicators is the scarcity of suitable data at the national or district level.
In principle, there are two solutions: The first uses whichever data are available and makes the most of them. For example, where direct measures of exposures to environmental pollutants are unavailable, these exposures could either be estimated by modelling techniques or represented by a proxy. Even partial information represents a starting point and can help highlight gaps in the existing data and motivate essential monitoring. The second solution involves new data collection and a much bigger investment in terms of financial and technical resources. However, where national surveys are not feasible, smaller sample surveys may be conducted and the results extrapolated to a wider geographic area or population. The CEH indicators pilot in the Eastern Mediterranean region is pursuing the latter approach by collecting detailed environmental health information among a smaller population group through a harmonized assessment tool.
Hence developing children’s environmental health indicators represents a compromise between feasibility and cost on the one hand, and data quality on the other hand. We propose to get started with the best available data, with the goal of collecting and compiling comparable, high quality data in the long term. It is also important to keep in mind that indicators are unable to identify new, unexpected problems – indicators can only answer those questions that are explicitly asked.