The impact of the environment on health by country: a meta-synthesis

"What are the possible health gains due to environmental interventions?" and "How much disease burden could be averted by implementing them?". These are main questions for decision-making towards public health action. Quantifying the disease burden caused by the environment has however been difficult given the relative lack of evidence.

Nevertheless, thanks to the development of new tools in epidemiologic analysis and of methods to estimate population health impacts, several estimates of environmental burden of disease have been developed. While the health impacts from, for example, outdoor air pollution have been developed since about two decades, more recent comprehensive and comparative analyses and methods include: (a) a comparative risk assessment of 26 risk factors, six of which are environmental [1]; (b) estimates of the global impact of the environment on health [2, 3]; and (c) the Environmental Burden of Disease series [4] providing country guidance to estimate the burden from selected risks (based on the same methodology as (a) but covering additional risk factors). At national level, several similar analyses have been developed, highlighting an interest for such information [5–10]. Recently, the World Health Organization has developed country profiles of environmental burden of disease.

This article presents the methods and results of the recently published 192 country profiles of environmental burden of disease [11] and discusses their comparison across countries. These are the first country-by-country estimates of the impact of the total environment on health. These profiles can be used as input to a country process of developing a more refined estimate of their health impacts of the environment. They can also be used for intra-country comparisons or serve as preliminary orientation of national decision-makers to set priorities for preventive environmental health action.

The WHO country profiles on environmental burden of disease (Figure 1) are composed of three parts. Part 1 (a) provides "exposure-based" estimates for three risk factors, i.e. based on globally available country exposures, and for which quantitative methods for disease burden estimation have been published [4]. These three risk factors include 'unsafe water, sanitation and hygiene', 'indoor air pollution from solid fuel use' and 'outdoor air pollution'. Part 1 also includes main malaria and other vectors that are present in the country and cause certain health risks. Part 2 (b) is a preliminary estimate of the total environmental burden of disease for the country, based on a review of the evidence completed by expert opinion. Part 3 (c) presents a breakdown by disease group for the estimate provided in Part 2.

In addition, the country profiles list a number of socio-economic parameters such as the GNI (Gross National Income), population, population living in poverty, urbanization and others in order to better understand the country's situation. Also, selected environmental exposures are presented to provide additional information regarding prevention opportunities [11]. These additional exposures were selected because they are both globally available and relevant for quantification of various health outcomes: lead (e.g. associated with cognitive impairment), malnutrition (associated with most infectious diseases, and water, sanitation and hygiene) and crowding (e.g. associated with the transmission of tuberculosis). The impact of environment-related malnutrition has already been incorporated in the EBD estimates (see [12] for additional details relating to water, sanitation and hygiene in particular). No comprehensive database was, however, available for blood lead levels, and no methods for estimating the disease burden due to crowding had been developed at the time of estimation. Such country-level exposures can be used for refined estimates at country level.

Both exposure-based estimates (Part 1) and evidence reviews completed by expert opinion-based methods (Part 2 and 3) use population attributable fractions, but differ in its estimation method. To obtain the environmental burden of disease, these attributable fractions are then multiplied by the total burden of disease (in deaths or DALYs) of the relevant disease (see [13] or Volume 1 of [4] for additional information on the Global Burden of Disease concept). The population attributable fraction is defined as the proportional reduction in disease or death that would occur if exposure to the risk factor were reduced to zero (see Chapter 1 of [14] or Volume 1 of [4] for references and explanations).

Attributable disease burden as estimated here – based on attributable fractions – is in principle not equivalent to preventable burden. Rather, preventability also depends on the technical, social, economic, psychological and ethical dimensions of a situation [15]. This being said, such burden points to the impact of causes, and the potential for prevention under certain circumstances. To some extent, the preventability of the attributable burden is also influenced by its method of estimation (in particular the counterfactual, or reference value, against which the impact of current exposure burden was estimated, or in the case of expert evaluation the formulation of the question; see sections (a) and (b) below).

While the results are expressed in terms of total deaths or a summary measure of population health, more detailed information is sometimes available (such as by age group or region, provided the underlying epidemiological information was specific enough).

The following sections provide additional details on the methods underlying the Parts 1 to 3 of the country profiles.

The country profile of environmental burden of disease for Brazil – overlaid by a reading guide – is provided in Figure 1 as an example. The profiles are available for 192 countries on the WHO web site [11]. They are structured in three parts, following the methods outlined above. In addition they provide some basic socio-economic and health indicators putting the data into context.

Additional file 1 provides a summary by country of the estimated number of deaths due to the three major risk factors unsafe 'water, sanitation & hygiene', 'indoor air pollution from solid fuel use' and 'outdoor air pollution', as well as basic exposure parameters. The last three columns of the Additional file 1 summarize estimates of the potentially preventable burden of the total environment, in premature deaths, DALYs per capita, and in percent of the country's total disease burden.

These results show that in 23 countries, the disease burden from the two risk factors 'unsafe water, sanitation & hygiene' and 'indoor air pollution from solid fuel use' alone accounts for more than one tenth of the country's total disease burden, amounting together to 3 million deaths globally. Outdoor air pollution adds another 860,000 deaths annually.

The disease prevention opportunities of environmental action per disease group differ generally by development status of a country. While contributions to infectious diseases, particularly diarrhoea and respiratory infections, are highest in the least developed countries, non-communicable diseases such as cancers and cardiovascular diseases are more affected in higher income countries.

The "environmental DALYs" per capita provide an overall measure of the environmental disease burden rate by country. They vary widely across countries, similar to the total burden of disease (Figure 2). Globally, 24% of the total disease burden, or 13 million premature deaths, could potentially be prevented through environmental improvements (or shifted to other causes of premature death or disability).

In 2007, WHO released the first ever country-by-country estimates of the impact environmental factors have on health for 192 Member states (WHO counts 193 Member states since 2006, but the latest health data available is from 2002, when only 192 countries were members of the organization) [11]. These country estimates are a first step to assisting national decision-makers in the sectors of health and environment to set priorities for preventive action. They can form an initial basis for orienting action to prevent disease by environmental improvements. Taken in a relative context, they can also be used as intra-national comparisons of broad environmental categories.

Strictly speaking, the disease burden that could be prevented through environmental action does not ensure that the concerned population would live a healthy life until standard life expectancy or beyond. It is likely that part of that population, in particular as life expectancy increases, is shifted to other causes of disease instead.

The number of environmental DALYs is an indication of the burden per capita that could be prevented by environmental improvement, and is a value that lends itself to inter-country comparison. This value is also the most meaningful one for capturing the disease burden attributable to the environment (next to last column in the Additional file 1), or the increase in healthy life years of a population when reducing environmental risks. The percentage of the total country's burden of disease that could be prevented by environmental improvements provides an indication of the total disease prevention that could be achieved within a country through environmental action.

Comparing the country rates of DALYs per capita by disease group with the world's lowest and highest country rates (comparison within the same line of the profile) provide an indication on the performance of the country with other countries. Values on the left ("lowest country rate") and on the right ("highest country rate") give an idea of the extreme values that were found within the 192 countries for which the exercise was done. Comparing however the country's DALYs per capita across disease groups (comparison across the "country rate" column of the profile) provides an indication of which diseases are the most affected by the environment in the country and points to the greatest prevention opportunities.

Plotting the environmental DALYs per capita versus the GNI (Figure 3) shows a strong decrease in environmental burden as GNI increases, before stabilizing around 15 DALYs/1 000 capita. A closer look at the values below 75 DALYs per 1 000 capita (Figure 4) shows that countries may perform rather differently in terms of environmental health impacts for a similar GNI. For example, with a GNI between 5 000 and 10 000 US$ per capita, the environmental burden of disease can range between around 20 and 55 DALYs per capita, which is more than a 2.5-fold difference. Such differences seem to support that affordable environmental management options may significantly impact on population health.

For countries with GNI values below 5 000 US$, the environmental burden can even differ by a factor of five. In many of these low-income countries, the disease burden is characterized by a high child mortality which is often linked to insufficient health care (the case-fatality rates are high) and/or malnutrition. Recurrent infections of diarrhoea and pneumonia, and malaria caused by poor sanitary conditions, solid fuel use and poor vector management therefore put children at particular risk and impact heavily on a country's disease burden.

Low income countries suffer the most from environmental health factors, losing up to 20 times more healthy years of life per person per year than high income countries. However, the data show that even in countries with better environmental conditions almost one sixth of the disease burden could be prevented.

As much of the mortality from diarrhoea and respiratory infections concerns children under the age of five years in the lower income countries, it also becomes apparent that addressing unsafe water, sanitation & hygiene and indoor air pollution from solid fuel use can significantly reduce child mortality in many countries, for example by more than 25% in about 20 countries. Adding the malaria deaths in children that could be prevented through environmental management would increase this share even further.

In higher income countries, the environmental component of the disease burden operates mainly through non-communicable diseases, including cancers and cardiovascular diseases. These deaths occur at a relatively late stage in life, displaying relatively high premature death rates, but relatively low DALY rates (based on the years of life lost rather than the number of deaths).

Although we have not assessed the health impacts of social determinants (such as levels of poverty, education, employment conditions [31]), investments in these will also have a positive impact on health. These determinants act as modifiers of the environmental determinants. Wealthier people can often better protect themselves against environmental risks. For example, people with higher income can possibly afford bottled water, while the poor may not; poorer people often have more dangerous jobs, or live closer to contaminated environments. On the other hand, everyone is exposed to outdoor air pollution and other ubiquitous determinants.

The presented estimates of total disease burden caused by the environment provide an approximate estimate of burden that could potentially be prevented, given the availability and successful implementation of effective intervention. Due to the estimation by disease rather than by risk factor, issues such as interactions between risk factors or multicausality have not been addressed specifically.

The estimates may have the following main sources of uncertainty: (1) relevant exposure databases available for the majority of countries are limited; while survey data for access to safe water, basic sanitation and use of solid fuels are now available for most countries, the missing data have been modelled; (2) given the lack of exposure data, the number of risks for which disease burden could be estimated with exposure-based methods was limited; the health impacts specific to other environmental risks could not be estimated on a country-by-country basis; (3) comprehensive health statistics are lacking for many countries; WHO estimates rely on modelling when data are incomplete; they however constitute the only comprehensive and consistent database of this type; (4) applying regional attributable fractions to country health statistics may not fully reflect the country-specific environmental exposures, in particular if these differ significantly from the regional mean; for example, if the risks for respiratory infections (e.g. solid fuel use, outdoor air pollutions, second-hand smoke) in a specific country differ significantly from the regional mean, then the presented estimates will carry larger uncertainties; provided however that the country's environmental situation is relatively similar to the one prevailing in the region (e.g. similar environmental policies, proportion of urban population, industrial activities), then the presented estimates may provide useful indications; (5) within-country variations in health status and exposure: if vulnerable populations are more likely to be exposed (which often applies with environmental exposures), the method may lead to an underestimation of effects.

The magnitude of uncertainties is difficult to evaluate. While in principle it would be possible to estimate uncertainties of the different components of the estimate, i.e. uncertainties in health data, the attributable fractions and the exposure data, it is more difficult to estimate the error generated by the use of regional attributable fractions as opposed to national estimates. In the absence of quantified information on uncertainties around these components of the estimate, a quantitative estimate of a "confidence interval" is not appropriate. For improving accuracy and reducing uncertainties, a more refined estimate based on national data may be carried out.

The comparative estimates of the proportion of disease burden attributable to the environment vary between 13 and 37% according to the country. These estimates show that the potential for improving health through a healthier environment is substantial in literally every country around the world. Environmental modifications could particularly reduce child mortality in many of the lowest income countries, but also play an important role in preventing non-communicable diseases in the higher income countries.

We acknowledge that the estimates proposed in this publication carry quite large uncertainties, and should primarily serve as preliminary estimates to refine at country level with additional input data. They do however, for the first time, provide an overview of the disease prevention opportunities by disease group (which have already been grossly linked to intervention area [2], and on which additional work is in preparation) through environmental action for 192 countries. Additional exposure-based methods for environmental risks are currently being developed, and exposures assessed, which could improve the accuracy of future estimates. Ideally, such estimates could also be extended to cover risk factors from other areas (such as physical inactivity, malnutrition, smoking, poverty etc.). Such a "health determinants picture" would then provide a more complete picture of a country's prevention opportunities. Basic methods for the assessment of health impacts from many of such risks are already available [1, 14].

The authors are staff members of the World Health Organization. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions or the stated policy of the World Health Organization.