The Use of Ecologic Data in Pharmacoepidemiology: A Focus on the Relationship Between Suicide and Depression Among Youths
The field of pharmacoepidemiology make use of different types of data to study the effects of medications on health outcomes. One type of data that is used in this field is ecologic data. Ecologic data are defined as “aggregate data describing the distribution of a health outcome or exposure within a population at a given point in time” (1). In this essay, we will discuss the use of ecologic data in pharmacoepidemiology, with a focus on a study conducted by Olfson and his team that looks at the relationship between suicide and the use of anti-depressants among youths.
2. Ecologic Data in Pharmacoepidemiology:
Ecologic data have been used in pharmacoepidemiology for a variety of purposes. For example, ecologic studies have been used to study the geographic variation in drug prescribing patterns (2) and to examine the relationship between region-specific characteristics and health outcomes (3).
Ecologic studies have several advantages over individual-level studies. First, ecologic studies can be conducted with readily available data, such as administrative claims data or census data. Second, ecologic studies can be conducted quickly and at a lower cost than individual-level studies. Third, ecologic studies can be used to study relationships between exposures and outcomes that would be difficult or impossible to study at the individual level, such as the relationship between regional characteristics and health outcomes.
However, ecologic studies also have several limitations. First, ecologic studies cannot directly assess causality. Second, ecologic studies may be subject to confounding by factors that are not measured in the data. Third,ecologic studies may be subject to selection bias if the population being studied is not representative of the general population.
3. Olfson and his team’s use of ecologic data:
In a study published in 2003, Olfson and his team used ecologic data to examine the relationship between suicide and the use of anti-depressants among youths (4). The authors used data from the National Center for Health Statistics’ National Vital Statistics System to identify all suicides among individuals aged 15-19 years from 1979 to 1998. The authors then used Census data to identify the number of people in each county who were living below the poverty line. Finally, the authors used claims data from Medicaid to identify the number of prescriptions for anti-depressants filled in each county.
The authors found that counties with higher rates of poverty were associated with higher rates of suicide, after controlling for other factors such as race/ethnicity and urbanicity. The authors also found that counties with higher rates of anti-depressant prescriptions were associated with lower rates of suicide. The authors concluded that there may be a relationship between poverty and suicide that is mediated by depression.
4. The relationship between suicide and depression among youths:
Depression is a major risk factor for suicide (5). In fact, it has been estimated that 90% of individuals who die by suicide have some form of mental illness (6). Suicide is preventable, but it is important to understand the factors that contribute to suicide risk so that prevention efforts can be targeted appropriately.
One factor that has been identified as a risk factor for suicide is poverty (7). Poverty has been associated with increased rates of mental illness, including depression (8). Poverty has also been associated with other risk factors for suicide, such as social isolation and access to means of self-harm (9).
5. Region-specific ecologic data:
As discussed above, ecologic data can be used to examine relationships between regional characteristics and health outcomes. In the Olfson et al. study, the authors used Census data to identify the number of people in each county who were living below the poverty line. However, there are other types of region-specific data that could be used in ecologic studies of suicide.
For example, data on the availability of mental health services in different regions could be used to examine the relationship between access to care and suicide risk. Data on firearms ownership could be used to examine the relationship between gun availability and suicide risk. And data on social cohesion could be used to examine the relationship between social isolation and suicide risk.
In conclusion, ecologic data can be a useful tool in pharmacoepidemiology. Ecologic studies have several advantages over individual-level studies, but they also have several limitations. Olfson and his team’s use of ecologic data showed that there may be a relationship between poverty and suicide that is mediated by depression. Future studies should use region-specific ecologic data to examine the relationship between regional characteristics and suicide risk.