|Issue: Vol. 79, No. 1
By Ted Schettler, M.D., MPH, Science and Environmental Health Network.
Complex relationships among genetic, biologic, toxicologic, nutritional, geologic, economic, political, social, cultural, and historical phenomena are major determinants of health or disease. The dominant scientific approach to understanding this complexity involves taking it apart in order to examine more manageable pieces. That approach emphasizes the role of parts and de-emphasizes relationships. Then, in an attempt to understand some larger whole, scientists often construct models built of selected individual variables from the ground up, referring to “independent” variables that combine to determine the “dependent” outcome of interest.
Clinical medicine, and to a large degree public health practice, favor examination of individual risk factors when trying to understand the causes and distribution of disease. In many instances that approach has been enormously fruitful and has led to important medical and technological achievements. However, models built of individual risk factors have explanatory limits. They are necessarily impoverished representations of profound multidimensional system complexity—in the individual, community, and ecosystem.
Multiple interactions among variables, positive and negative feedback loops, and non-linear system dynamics determine the health and behavior of individuals, populations, and entire ecosystems. System behavior depends on specific circumstances and often fluctuates around a mean. However, exaggerated oscillations or near-threshold conditions can create vulnerability to small perturbations that can propel the entire system into new dynamic operating conditions. Studies that ignore details of system conditions will miss important real-world determinants of health in complex interactive systems.
In humans, homeostatic mechanisms work to maintain favorable physiologic conditions, but sufficient external stress can exceed the buffering capacity of the system or cause adaptive responses with their own adverse impacts. In individuals, the result may be illness or premature death. In populations of people, changes in system conditions can cause the emergence of new patterns of disease or behavior. Ecosystem changes may favor certain populations, and some species may find new system dynamics inhospitable. These are the driving forces of evolutionary biology.
Most medical conditions do not have single “causes” or single necessary antecedents. Typically, a number of factors are linked together in complex causal webs, in a context of susceptibility. At best, we can say that some collection of factors increases the risk of a disease but their relative contributions may vary considerably from one circumstance to another.
The strength of association between an exposure and disease is fundamentally affected by the prevalence of other component causes in a given context. What is unimportant in one set of circumstances may be very important in another. Commonly used statistical models intended to describe relationships among multiple risk factors, including multiple regression analyses, are often unable to capture the complex heterogeneity of real world circumstances.
The combined and independent impacts of dietary iron deficiency, lead exposure, and social conditions on brain development of children illustrate some of these points. These three variables are, of course, not the only determinants of childhood brain development, but they are important. Awareness of their interactive, combined effects is essential for designing effective public health interventions.
Iron deficiency, lead exposure, social circumstances and brain development in children:
Many studies show that developmental low-level lead exposures are associated with persistent cognitive impacts and behavioral changes. (Needleman, Bellinger, 1987; Lanphear) Blood lead levels around 2 or 3 years of age are particularly important for their impacts on cognitive development. (Bellinger, 1991; Bellinger, 1992)
Iron deficiency is probably the world’s most common single nutrient deficiency. About 10% of toddlers in the US are iron deficient, and the prevalence is substantially higher in non-Hispanic blacks, Mexican-American females, and Alaskan natives. (CDC, 2002). Children who are iron deficient are at risk for cognitive deficits, even if they do not have iron deficiency anemia. (NAS, 2000; Grantham-McGregor & Ani, 2001) Studies of the impact of treatment are inconsistent though most conclude that children continue to exhibit lower academic performance, even after iron deficiency anemia is corrected. (Martins, 2001; Hurtado, 1999; Halterman, 2001)
A number of studies have documented a correlation between iron deficiency and elevated lead levels, particularly in younger children. (Yip and Dallman, 1984; Yip, 1981; Wright, 1999; Bradman, 2001) Iron deficiency may amplify the effect of environmental lead contamination by increasing absorption and retention and/or by increasing hand-to-mouth behavior and lead ingestion.
Despite their correlation, iron deficiency is not essential in the pathway between lead exposure and cognitive impacts. Lead also has effects on cognition that are independent of iron status. (Kordas, 2004) Iron is required for neurotransmitter synthesis and myelination. (NAS, 2000) Lead can disrupt cell proliferation, differentiation, synapse formation, myelination, and programmed cell death, as well as altering neurotransmitter levels. (Silbergeld, 1992)
Studies of the impact of interventions that reduce blood lead levels have variable results. (Ruff, 1993) The children who benefit most from lead level reduction appear to be those whose iron status is sufficient. (Ruff, 1996) Lead level reduction in children who are iron deficient does not seem to improve cognitive performance.
Even when corrected, iron deficiency in infancy appears to have long term consequences, with reduced mental and motor functioning and increased behavioral problems in children when evaluated at 10 years of age. (Lozoff, 2000) Children living in poor social circumstances seem to be particularly affected, whereas more enriched social circumstances tend to blunt the impacts of early iron deficiency on mental functioning.
This example points to a deeply rooted problem: Focusing on individual risk factors often does not honor the complexity of systems of interest. Other examples from animal and human studies also illustrate the interpenetration of nutritional status, exposure to toxic chemicals, and mammalian biology:
- Nutritional status can modify the carcinogenic risk of exposure to carcinogens
- Nutritional status can modify the teratogenic risk of exposure to teratogens
- Dietary selenium reduces the toxic impacts of mercury
- Maternal social and economic deprivation increase the neurodevelopmental impact of prenatal exposure to chlorpyrifos in their children. (Rauh, Whyatt, et al)
- Omega 3 fatty acids in fish reduce the cardiovascular toxicity of mercury (Clarkson, 2003)
- Mercury decreases the beneficial effects of omega 3 fatty acids on brain development.
- Omega 6 fatty acids increase atherosclerosis caused by PCB exposure while plant derived anti-oxidants protect against this effect (Hennig, 2002)
The prevailing paradigm resists framing cognitive impairment, cancer, or birth defects as ecological outcomes—outcomes inherent in a particular ecosystem—and favors conceptualizing these as problems in individuals to be explained by individual risk factors and understood using primitive models.
Identifying individual risk factors has been very helpful for understanding major determinants of certain diseases like lung cancer and heart disease. Perhaps, however, we should be thinking about diseases that are resistant to a risk-factor approach, such as breast and prostate cancer, many birth defects, or neurodevelopmental disorders as ecological manifestations of multiple changes in the dynamic system in which people are conceived, develop, live, and grow old.
It seems unlikely that we will truly understand the origins and prevalence of these conditions and be able to design preventive strategies by looking just at individual risk factors. These are conditions that emerge from complex systems, and we do not understand their ecology well enough. Effective prevention is more likely to be realized when top-down systems analyses are added to a bottom-up individual risk factor approach. Biologists, epidemiologists, clinicians, and the general public must be willing to expand their horizons, learning from ecologists and other integrative disciplines.
New approaches may be fruitful in three areas:
- how we imagine the world,
- how we study the world, and
- how we respond.
Many different social and cultural institutions could address these three approaches, including education, research, medical care, public health, governmental agencies, businesses, religious organizations, the non-profit sector, and philanthropy.
Ecology and evolutionary biology should be introduced early into primary, secondary, college, and graduate education to supplement a reductionist, bottom-up approach with a top-down systems perspective.
Efforts at cross disciplinary research and collaboration are likely to offer new insights. New epidemiologic and statistical techniques should be employed to deal with system interactions, feedback loops, and non-linear system dynamics. Methods used in the ecological and social sciences may have much to offer the biological sciences to aid in understanding.
Traditional clinical medical care tends to focus primarily on individual risk factors and therapies directed at modifying them individually. A more integrative approach that simultaneously addresses a number of relevant factors may hold promise for enhancing the systemic health of individuals and populations, as well as addressing the health of entire ecosystems.
Businesses, health care facilities, local and regional governments, farmers, agricultural institutions, religious organizations, among others, could be encouraged through a variety of incentives to modify or expand their spheres of concern to entire ecological systems in which they operate. New economic analyses that are better indicators of ecological health, rather than simply monetary growth, are needed. As it is, “silos” of specialization encourage a focus on single risk factors or metrics, with little attention to entire systems in which those factors operate.
How might we address malnutrition, food production systems, soil and water quality, exposure to carcinogens and other toxicants, and socioeconomic stress collectively? How would this change the structure and approach of educational, scientific, medical, and civic institutions? Can we continue to hope that a haphazard collection of interests, ideologies, and civic and governmental institutions developed long ago will contribute to ecosystem resilience that will remain favorable to continued human survival on a finite planet over time?
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