In this study of a prospectively followed cohort, we found that persons lacking health insurance had higher rates of stroke and death than those who were insured. However, the rate of myocardial infarction was not significantly associated with insurance status. Aspects of personal health, such as awareness and control of cardiovascular risk factors, were also found to be related to insurance status. This study adds to the relatively small body of literature that prospectively examines the association of insurance status with clinical outcomes.
There has been only one randomized trial of insurance in the United States. The Rand Health Insurance Experiment was a multisite trial during which over 2,000 families were randomly assigned to an insurance plan that provided free care or a plan that required some cost sharing.8
No premiums were charged for any of the experimental plans and no family was assigned to be uninsured. Although participants randomized to free care had higher rates of health care utilization, the only significant benefit of free care on health measures in this trial was improved corrected far vision. The free care group was also found to have a lower diastolic blood pressure that approached statistical significance;8
and within the subgroup of hypertensives, free care participants had significantly lower blood pressures than their counterparts.9
Although participants randomized to free care did not realize significant improvement in many health status measures, such as physical and mental functioning and lipid control, better control of blood pressure significantly reduced the calculated risk of early death among a high risk subgroup.8
Other studies have examined “natural experiments” to examine the effects of loss of insurance in populations who were insured, but precipitously lose their coverage. These quasi-experimental studies have found that those losing insurance suffered substantial declines in health, including poorer blood pressure control, when compared to their insured peers.10–12
Cardiovascular risk assessment and risk factor management is widely acknowledged to be a cornerstone in the prevention of adverse cardiovascular events. Satisfactory control of risk conditions is predicated upon adequate access to medical care. We hypothesized that lack of stable insurance would result in reduced health care access, inadequate risk factor identification and management, and increased risk of cardiovascular events. In fact, we found that those without health insurance had a higher risk of forgoing routine physical examinations and a higher risk of being unaware of a personal diagnosis of hypertension, diabetes, or hyperlipidemia.
While we found that blood pressure was less likely to be controlled in those who were both hypertensive and uninsured, we did not find any differences by insurance status in the degree of lipid control in those who were told that they had hyperlipidemia. These results are similar to those of the Rand Health Insurance Experiment. One possible explanation may be that the data collection for both our study and the Rand study predated the widespread, aggressive control of lipids that constitutes current practice. As lipid management has become more intensive and lipid lowering therapy used more widely, subsequent studies may yield different results.
We found that lack of health insurance was associated with an increased rate of stroke and death in our study. A previous study concluded that uninsured white women, but not white men, were at an increased risk of cardiovascular death, compared to those with employer-based insurance, when adjusted for age and income.3
Interestingly, the authors of the study found that those with Medicaid and Medicare had the highest rates of cardiovascular and all-cause death; even higher than those without insurance. This earlier study did not control for participant health status or comorbidities, raising the possibility that unmeasured factors confounded the relationship between type of insurance and outcomes. Another study estimated that lack of health insurance was associated with an adjusted hazard ratio of 1.25 (95% CI 1.00–1.55) of death, when compared to private insurance.2
This estimate of the hazard of death associated with lack of insurance is similar to what was found in our study.
Although we found an elevated point estimate of the hazard of myocardial infarction associated with lack of insurance, this was not statistically significant. Although it is unclear why this is so, we postulate that this finding may point to the relative importance of hypertension as a risk factor for stroke compared to myocardial infarction. Hypertension is the most powerful risk factor for stroke.13
We observed that hypertension was significantly less likely to be well controlled in those lacking insurance. We believe that poorly controlled hypertension may be the link between lack of insurance and increased incidence of stroke. Although hypertension is an important risk factor for myocardial infarction, the relative contribution of other risk factors, such as inherited traits, lipid levels, smoking, and diabetes may be greater in the development of coronary heart disease. However, the interrelationships between multiple risk factors, demographic factors, insurance, and health outcomes are likely to be extremely complex. For example, we believe that poorer blood pressure control largely mediates the relationship between lack of insurance and increased risk of stroke. However, when we added systolic and diastolic blood pressure measurements to our model, we observed only modest attenuation of increased risk of stroke, suggesting that there are mediators, other than blood pressure, of the relationship between stroke and insurance. In addition, because we only have blood pressure levels at discrete time points, measurement issues may also affect our observations.
Our analysis has several important limitations. The estimation of the independent or distinct impact of insurance on health is very difficult, as health insurance is closely intertwined with other personal and community characteristics that are associated with health. Unlike randomized controlled trials, we could not equally distribute the other determinants of outcome to isolate a “pure” insurance exposure. Therefore, it is impossible to absolutely eliminate the possibility of residual confounding or bias in estimates derived from observational studies like this one. In our multivariable analyses, we statistically controlled for factors that we felt may be related to both insurance and the outcome, thus, reducing the potential for confounding bias and increasing the likelihood that the relationships we observed are truly causally related. In addition, elements of our study, namely, the association between lack of insurance and poorer blood pressure control, are mirrored in studies with different experimental designs, including the Rand randomized controlled trial of insurance.9
Yet, there still could be unknown, unmeasured, or poorly measured confounding factors that could influence our assessment of the relationship between insurance and our outcomes.
Our study analyzed data initially collected for purposes other than the objectives of our study. Consequently, insurance was not measured as completely as it could have been. Insurance was asked in such a manner that insurance history before the visits was not obtained. Also, the question querying insurance status changed at the fourth visit and this may have affected data ascertainment. In our analysis, “being insured” is a heterogeneous designation, including different types of plans and payers. Future investigations of the association of insurance with health, where type and duration of insurance can be quantified, will be extremely valuable. In addition, because of the constraints of the data, we were unable to assess the degree of diabetes control by insurance status, as hemoglobin A1C values for participants were unavailable. ARIC investigators informed participants of the results of their research medical evaluation in the form of a letter to the participants and their doctors after each visit. Therefore, although we recognize that in theory, risk factors that were present at visit 1 should have been known to participants thereafter, we decided to study the lack of awareness of cardiovascular risk factors at all 4 visits because participants may not have fully understood the communications from the investigators, may not have had a doctor, or may have developed a risk condition after visit 1. Structuring the analysis this way biases the measurement of the relationship between insurance status and awareness of cardiovascular risk factors toward the null.
In summary, we found a significant relationship between lack of health insurance and lower utilization of primary care resources, decreased awareness of personal cardiovascular risk factors, poorer control of hypertension, and finally, increased rate of stroke and death. This study, along with others that have associated lack of health insurance with adverse health outcomes, underscores the importance of developing policies that ensure that all can receive sufficient access to medical care.