Early initiatives included the Human Early-Life Exposure Project known as HELIX. This involved 32,000 “mother and new born child” pairs in six European Countries enrolled in 2014. Each had already been recruited to a birth cohort study. These cohort studies enrol people and then monitor them for the rest of their lives on a regular basis. Measures of the Exposome was added for the first three years of the study. The researchers measured indoor pollutants including food, consumer products, water and air. They also measured neighbourhood pollutants such as air and noise. A sample of mothers also gave blood samples. With it the researchers could look at biomarkers as a potential pre-cursor to illness.

The initial phase of the study concluded in 2017. I went to look for the results. Of course there were not any. The children were only three years old! Any impact of their early years Exposome might appear any time in the next ninety years of their lives. This is a long process! These studies are huge, complex and expensive. Given the definition of the Exposome, they must run for decades.

Repurposing Existing Studies

Researchers in health sciences have always tried to repurpose existing data sets. To help them regulators are harmonizing the measurement of the “environment” across Europe and the USA. With standard measures they will soon have better data. They can then unpick the complex interactions within the Exposome more easily.

A recent study of the USA shows such a repurposing. It uses the tax records and demonstrates the complexity of the task. Researchers collected over 1.4Bn US tax records from between 1999 and 2014. They combined these with social security records. They knew where people had lived. They could compute life expectancies based on the people known to have died. They could relate who died to their characteristics. Their results are surprisingly disappointing given the amount of data they collected.

Being Poor in Rich Cities

It is hardly surprising that life expectancy goes up with income. What is surprising is that the curve does not plateau at either end. More income will always buy you more life expectancy. Less always makes matters worse. What is disappointing is the 14.6 year life expectancy gap between the top 1% and the bottom 1%. That bottom group has the same life expectancy as the people of Somalia. Furthermore the gap seems to be widening over time not shrinking. In the last five years of the study, life expectancy in the top five percent of income increased by over two years. In the bottom five percent life expectancy hardly increased at all.

At the top of the income scale the life expectancies were in a narrow band. There was not much variation. In the bottom quartile there was a much wider range. Life expectancy varied by up to four years between different geographic areas. When studying the EXPOSOME this means that there will not be a set of rules that applies at all ages.

They used that variability within the bottom quartile to test various existing theories. The good news was that they could relate life expectancy to healthy behaviours. Lack of smoking, lower weights, exercise, all were associated with higher life expectancy. They looked at the availability of healthcare based on the Social Security records. The poor had less insurance coverage and less care than the wealthy. Within the “poor” however there was no significant relationship between life expectancy and care availability. They looked at the local labour market. Was a shortage of work increasing stress and hence reducing life expectancy? They looked at inequality within the geographic region. Was the range of salaries within a geography exacerbating income based social divisions? Neither had an effect.

The biggest variable was the city. For example, poor people in New York and San Francisco lived 5 years longer than those living in Detroit or Gary, Indiana. They had ruled out race and excluded deaths by "violent crime". It appeared that it was the environment of these cities that was more beneficial. The Exposome was working but they had not managed to capture it. They wondered about smoking restrictions within public spaces. They wondered about the quality of those public spaces. They speculated that people choosing to be “poor” in rich cities are somehow different. The only other explanation could be social. The rich cities may surround the “poor” with people demonstrating positive health behaviours.

Will the EXPOSOME deliver?

The EXPOSOME has a lot of value as a conceptual framework. It is especially useful for people working in the environmental health field. It is a good educational tool. Probably because of it researchers have learnt that cross- sectional studies are not going to deliver. More and more longitudinal studies are becoming available. Computing power is increasing to deal with complex inter-relationships. Medical researchers are producing point relationships. Like the “meat eating and lions” study in the previous Newsletter (See Newsletter #106 “The Genome and the Exposome”) . These relate specific environmental factors to specific diseases.

The bad news is the complexity of the task. Defining stress factors in the whole Exposome is difficult. The Exposome works at higher levels of abstraction. “Air pollution” is easy to understand. To operationalize it is more complex. We need to break it down. If we talk of particulates and gasses we multiply the complexity. If we split gasses into nitrogen dioxide and carbon monoxide we a are multiplying the number of variables. Defining the different "pressures" within the Exposome is not easy. .

How the different stressors interact with each other needs to be unpicked. Take air pollution again. Does outside air pollution exacerbated a tobacco smoke filled home environment? We need to measure the cumulative effect of multiple combinations over a whole life time. HELIX will only flag the potential factors in infancy. Finally the mechanisms that tie the EXPOSOME to the GENOME needs to be understood.

The impact of the EXPOSOME will never be negative. It stresses the importance of the environment in all its forms. Regulators will still ban smoking and vehicle emissions.