THE RELATIONSHIP BETWEEN DEGREE OF BLOOD PRESSURE REDUCTION AND MORTALITY AMONG HYPERTENSIVES IN THE HYPERTENSION DETECTION AND FOLLOW-UP PROGRAM

The relationship between degree of diastolic blood pressure (DBP) reduction and mortality was examined among hypertensives, ages 30-69, in the Hypertension Detection and Follow-up Program (HDFP). The HDFP was a multi-center community-based trial, which followed 10,940 hypertensive participants for five years. One-year survival was required for inclusion in this investigation since the one-year annual visit was the first occasion where change in blood pressure could be measured on all participants. During the subsequent four years of follow-up on 10,052 participants, 568 deaths occurred. For levels of change in DBP and for categories of variables related to mortality, the crude mortality rate was calculated. Time-dependent life tables were also calculated so as to utilize available blood pressure data over time. In addition, the Cox life table regression model, extended to take into account both time-constant and time-dependent covariates, was used to examine the relationship change in blood pressure over time and mortality.^ The results of the time-dependent life table and time-dependent Cox life table regression analyses supported the existence of a quadratic function which modeled the relationship between DBP reduction and mortality, even after adjusting for other risk factors. The minimum mortality hazard ratio, based on a particular model, occurred at a DBP reduction of 22.6 mm Hg (standard error = 10.6) in the whole population and 8.5 mm Hg (standard error = 4.6) in the baseline DBP stratum 90-104. After this reduction, there was a small increase in the risk of death. There was not evidence of the quadratic function after fitting the same model using systolic blood pressure. Methodologic issues involved in studying a particular degree of blood pressure reduction were considered. The confidence interval around the change corresponding to the minimum hazard ratio was wide and the obtained blood pressure level should not be interpreted as a goal for treatment. Blood pressure reduction was attributed, not only to pharmacologic therapy, but also to regression to the mean, and to other unknown factors unrelated to treatment. Therefore, the surprising results of this study do not provide direct implications for treatment, but strongly suggest replication in other populations. ^

A model of factors determining levels of public support for health care policy in the United States

Public preferences for policy are formed in a little-understood process that is not adequately described by traditional economic theory of choice. In this paper I suggest that U.S. aggregate support for health reform can be modeled as tradeoffs among a small number of behavioral values and the stage of policy development. The theory underlying the model is based on Samuelson, et al.'s (1986) work and Wilke's (1991) elaboration of it as the Greed/Efficiency/Fairness (GEF) hypothesis of motivation in the management of resource dilemmas, and behavioral economics informed by Kahneman and Thaler's prospect theory. ^ The model developed in this paper employs ordered probit econometric techniques applied to data derived from U.S. polls taken from 1990 to mid-2003 that measured support for health reform proposals. Outcome data are four-tiered Likert counts; independent variables are dummies representing the presence or absence of operationalizations of each behavioral variable, along with an integer representing policy process stage. Marginal effects of each independent variable predict how support levels change on triggering that variable. Model estimation results indicate a vanishingly small likelihood that all coefficients are zero and all variables have signs expected from model theory. ^ Three hypotheses were tested: support will drain from health reform policy as it becomes increasingly well-articulated and approaches enactment; reforms appealing to fairness through universal health coverage will enjoy a higher degree of support than those targeted more narrowly; health reforms calling for government operation of the health finance system will achieve lower support than those that do not. Model results support the first and last hypotheses. Contrary to expectations, universal health care proposals did not provide incremental support beyond those targeted to “deserving” populations—children, elderly, working families. In addition, loss of autonomy (e.g. restrictions on choice of care giver) is found to be the “third rail” of health reform with significantly-reduced support. When applied to a hypothetical health reform in which an employer-mandated Medical Savings Account policy is the centerpiece, the model predicts support that may be insufficient to enactment. These results indicate that the method developed in the paper may prove valuable to health policy designers. ^

The effect of immigration status on racial differences in health insurance coverage, access to care, and utilization in the United States

Background. Lack of coverage, lack of access, and failure to utilize health care services have all been linked to dismal health outcomes in the US. Such consequences have been a longstanding challenge that US minorities are faced with, in the context of a health care system believed to be lacking efficiency and equity. National population surveys in the US suggest that the number of uninsured approaches 50 millions, while some concerns and suspicions are raised by opponents to the growing number of foreign born US residents, many of whom are Hispanic. Research shows that race is a significant predictor of lack of coverage, access, and utilization, while age, gender, education, and income are also linked to these outcomes. We investigated the potential effect of immigration status or duration in the US on the association between coverage, access, use, and race. Methods. Using National Health Interview Survey (NHIS) data of 2006, we selected 22, 667 individuals of Non-Hispanic Black, Hispanic, and Non-Hispanic White descent, at least 18 years of age, US-born and foreign-born who reported their duration of residence in the US. Through complex sample survey logistic regression analysis, we computed odds ratios, beta coefficients, and 95% confidence intervals using models which excluded then included immigration status. Results. Although a significant predictor of the outcomes, immigration status did not change the relationship between each of the dependent variables (coverage, access, utilization), and the factor race, while adjusting for age, gender, education, and income. Our results show that Hispanics were least likely to have coverage (OR=.58; 95% CI[.49, .68]), access (OR=.62; 95% CI[.50, .76]), and to utilize services (OR=.60; 95% CI[.46, .79]) followed by Non-Hispanic Blacks, and Non-Hispanic Whites. These results were not changed by stratification, or the inclusion of interaction terms to eliminate the potential effect of relationships between independent variables. Recent immigrants (<5 years in US) were 0.12 times less likely to be insured, but also 0.26 times less likely to utilize services (p<0.001), and in addition they represented only 7.3% of the uninsured and 1.9% of the US population in 2006. Furthermore, 12% of the Non-Hispanic White population in the US was not covered, and 65% of the uninsured individuals were US-Born Citizens. Other predictors of lack of coverage, access and use were age below 45, male gender, education at high school or below, and income of less than $20,000. Conclusion. This investigation shows that the high percentage of uninsured was not directly caused by Hispanics, and immigration status alone could not explain racial differences in coverage, access, and utilization. An immigration reform may not be the solution to the healthcare crisis, and more specifically, will not stop the increase in the number of uninsured in the US, nor reduce the cost of health care. As a better alternative, universal health insu rance coverage should be considered, when aiming to eliminate racial disparities, and to solve the health care crisis. ^ Keywords. health insurance, coverage, access, utilization, race, immigration, disparities.^