Key Points

We are all living during the time of the pandemic. The world waits in anticipation of the passing of this virus. We brace ourselves for a turbulent exit, with a glimmer of hope as vaccines are becoming available soon. During the past week, the United States has seen more than 150,000 cases on average each day. As we weather the storm of the third wave of COVID-19 cases, it looks like it is going to get worse before it gets better.

But although we share this time, our experience in it is diverse. Many people have jobs that require them to work outside of their homes. In Illinois, for example, a significant proportion (29%) of the recent COVID diagnoses have been attributable to exposure in factories and workplaces that are unable to accommodate physical distancing. Even the location of one’s house and the mean income of a neighborhood have been associated with an increased risk of COVID-19. While some families work in their comfortable homes, others live in small apartments with multiple residents working out of home at increased risk of exposure to COVID-19.

The Determinants of Health

A person’s health or disease state does not exist in a vacuum. In the clinic, addressing a condition without considering the entire microcosm of a person provides little more therapy than a band-aid. A clinician who understands the multi-factorial nature of health looks upstream at the “cause of the cause” when addressing a disease.

What is health? According to the World Health Organization (WHO), health is a “state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity.” Secondly in the WHO’s preamble to its constitution, it declares “the enjoyment of the highest attainable standard of health is one of the fundamental rights of every human being without distinction of race, religion, political belief, economic, or social condition (WHO).

Importantly, individual health is intimately tied to the environment in which a person lives. The Dahlgreen and Whitehead rainbow model (1991) provides a schema for viewing the microcosm of factors, or determinants, that contribute to one’s health. These include social and community networks, socio-economic factors, culture, and environmental conditions. The outer band of the model includes public health and social care services, access to healthcare, community infrastructure, agriculture and food production, level of education, water and sanitation, transport policies, and work environment.

If there is any question of the impact of these systems, consider that more than a quarter of the world’s population have no access to safe drinking water; and by 2025, an estimated half of the world’s population will be living in water-stressed areas. Unsafe drinking water contributes to the death of 829,000 people from diarrheal illness each year (WHO).

There is an important reason to look upstream for a cause to a health condition. When a patient comes to be seen for an asthma exacerbation and continues to smoke, it is easy to conclude that smoking exacerbates their asthma. But how is smoking addressed? Unfortunately, the clinic does not permit ample time to explore nicotine addiction. If we could approach behavior change, it is possible that the patient could experience improvements beyond asthma.

Often when we look deeper into the cause of behaviors, we find some startling associations. A study of risk factors of adolescent smoking in Brazil found an association with domestic violence, male gender, and early sex initiation, with odds ratios (OR) of 2.34, 2.11, and 6.56. (Viana et al, 2018). An odds ratio is a calculation of the association of risk of a variable with a known, in this case, smoking. The degree of religiosity of a person also appears to influence smoking behavior, with religion being protective (Martinez et al, 2015).

Socioeconomic Factors

It is well established that with better socio-economic status comes better health (Graham H, 2007). Significant changes in life expectancy were realized during the early part of the twentieth century, because of improvements in public health infrastructure, clean water, and sanitation advances.  By 1941, even before Ernst Chain and Howard Florey mass-produced penicillin, the mortality rate in the United States had already dropped from nearly 800 people per 100,000 population to 200 people per 100,000.  It now hovers at a rate of about 25 per 100,000.  A child born today can be expected to live for a lifespan of 79 years (2016 data) when it was about 30 years in the early 1900s.

The trend from high infant birth rates and high infant death rates to low birth rates and death rates is referred to as the demographic transition.  It is commonly seen when a country becomes more industrialized.  Unfortunately, even now, there are countries, such as the Central African Republic, where the life expectancy now (53 years in 2019) is like the US life expectancy was in the early 1900 (47 years in 1900).

One tool to assess the development of a country is to combine life expectancy, education, and per capita income, known as the Human Development Index.  It illustrates that life expectancy is higher in developed countries, such as the US, Canada, Europe, Australia, Japan, and New Zealand, while countries that have higher poverty such as Africa, Nepal, and East Asia have a lower life expectancy.  Life expectancy increases with a country’s wealth as it relates to better infrastructure, food availability, a cleaner environment, and better social services; where these systems are limited or incapacitated, such as in war-torn countries, life expectancy decreases.

Unfortunately, these estimates on a country’s development often do not consider the patchwork of socioeconomic disparities within it. There are huge income gaps within some countries, from which emerge differences in chronic disease risk and longevity. Poverty correlates, and perhaps contributes, directly to unhealthy behaviors, such as poor diet and decreased physical activity. These behaviors lead to chronic diseases, such as obesity, diabetes, and hypertension. There are also higher rates of mental health problems and tobacco consumption in lower-income areas. Consequently, there is a reduced lifespan and healthspan (Stringhini et al).

Whether a county is poor or affluent may predict the prevalence of chronic diseases, such as obesity, hypertension, arthritis – with higher rates in poor counties (Shaw et al.) The disparity cuts through multiple factors. There are also differences in education levels between the poor and affluent communities, less in the poor counties. Higher education level has been associated with a lower risk of chronic disease.

Aside from income differences, within poor counties, there is often greater access to fast-food restaurants and convenient stores (“food swamps”), less access to healthy food options, like natural foods (“food deserts”), and a relative lack of green space (Shaw, K et al).

These findings have important health policy implications for these counties, many of which are neighboring more affluent areas that may have significant differences in the rates of chronic diseases and cancer (O’Connor et al).

Some of the areas of greatest chronic disease burden are also those with the greatest poverty.

More and more, we are realizing that a person’s physical health is deeply linked to their socio-economic context. Some unexpected factors include environmental, such as access to green space or living density, others include those that occur in childhood such as trauma.

According to the World Health Organization, and the National Institute of Health, the presence of urban green spaces has a direct relationship with physical health. Green spaces are essentially areas of wooded or mixed vegetation and can show up as natural areas or parks.

Green spaces enrich the mental and physical health of a person. The presence of nature can improve mood and can help alleviate depressive symptoms, especially when combined with exercise.

Trees and vegetation produce oxygen and filter pollutants while water bodies can cool and moderate extreme temperatures. They are pleasant places for exercise, social interaction, and recreation. They positively affect the health of those living around it, having an even greater impact and benefit to lower socioeconomic groups. Green spaces also provide safe routes for runners, walkers, and cyclists — decreasing the number of traffic-related deaths around it.

However, given that green spaces are so vital to a population’s physical and mental health, there is a clear class divide in access to these green spaces. According to a study that looked at ten major metropolitan areas (ie: New York, Los Angeles, Phoenix, etc.), higher income and education level is significantly associated with greater access to green space. Those from lower-income and education levels — the groups who benefit from green space the most — have less access to it, possibly contributing to greater health issues.

We must consider not only the current context of an individual but their history as well. Trauma that occurs to someone as a child can impact physical health across their life span and potentially generations after them. In 1998, an important study on the determinants of health was published by Dr. Vincent Felitti et al: The Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experience (ACE) Study.

The researchers used a questionnaire to follow a standardized medical evaluation of 9,508 adult health plan members to determine factors described as “ACEs.” Even though questionnaires cannot discern the degree of recall bias; i.e. how does someone look back at their childhood and decide on “frequency of abuse,” someone’s impressions are still important. More than half had experienced at least one hardship, while a quarter experienced two or more.

The experience of an adverse childhood event, such as physical, verbal, sexual abuse, death of a parent, or a divorce, led to increased risk of conditions such as alcoholism, drug abuse, depression, suicide attempt, increased sexual partners, sexually transmitted infection, cancer, ischemic heart disease, chronic lung or liver disease, and severe obesity. Although the risk for severe obesity (1.4 to 1.6-fold) in those with four or more categories of adverse experiences was less than conditions such as alcoholism, drug abuse, depression, or suicide attempt (4-12-fold increased risk), the association of adverse events and disease is significant (Felitti et al, 1998).

The study also showed a correlation between smoking and a higher ACE score, as well as the association with Chronic obstructive pulmonary disease (COPD). Arguably, this study suggested that a person’s state of physical health and disease may be a barometer of past experiences, and even their adjustment to them (adaptive versus maladaptive behavior). This has important implications on how we may better approach the health and disease model (Felitti, 2002).

How does poverty interact with ACEs? Do ACEs cause poverty, or does poverty contribute to ACEs? A recent study examining supplemental information on ACE questionnaires confirmed that poverty experienced in childhood can result in negative physical and mental health outcomes in adulthood. Trauma and poverty appear to be cyclical and inter-related, contributing to adverse health outcomes.

Trauma and Adverse Childhood Events (ACEs) are associated with decreased health and increased risk of mortality

Click to access aces-fact-sheet.pdf