Health Inequities in Manitoba: Is the Socioeconomic Gap

Types of program or policy interventions to decrease the
socioeconomic gap
xxvi University of Manitoba
There is debate as to whether programs should be universal or aimed at specific “at risk” groups.
According to Geoffry Rose’s Theorem (1992), a large number of people at small risk may give rise to
more cases of disease than a small number who are at high risk. In other words, a small change over a
large population gives a greater overall benefit than a large change over a small at–risk group within
that population. If each person changes positively, even by a small amount, the population distribution
will be profoundly affected. By shifting the population curve (normal distribution curve) by only a
small amount, say one–half of a standard deviation, the percentage of the population below the mean
changes from 50% to 31%—a substantial decrease in those considered ‘below’ the original average
(mean) cut–off.
If everyone experiences a similar improvement, resulting in a true population shift, the overall mean
shows improvement. However, the gap between the healthiest and the least healthy remains the same
in absolute difference terms. So planners and policy–makers need to strive towards improving the
overall health of the entire population, but also simultaneously reducing the gap between the most
and least healthy by differentially improving the health of the least healthy. In other words, we need to
focus on shifting the entire population to improved health while “squishing” the distribution, i.e., giving
targeted interventions to the least healthy so they will ‘catch up’ to attain the health status of the most
healthy. Targeted programs are also needed when the least healthy group is not improving as rapidly
as the rest of the population, thus increasing the gap and necessitating rapid catch up to even maintain
the gap that existed previously. Once again, a targeted intervention for this at–risk group, along with
the universal intervention, must be considered both to catch up the group which lags behind and, once
caught up, to shrink the gap.
Given the results of this research report, the Gini coefficients and the Lorenz curves may give decision–
makers evidence upon which to base either the universal population approach or simultaneous
universal and targeted approaches. If the Gini coefficient is 0, i.e., the Lorenz curve approximates the
line of equality, then the health risk is equally distributed throughout the socioeconomic groups. The
more the bend (i.e., the greater the Gini coefficient), the more inequality exists, and the more a targeted
policy or program (in addition to a universal program) is needed to increase the overall health of the
population. An effective targeted program needs to be designed to increase the health of the least
healthy group along with the rest of the population and even increase health at a more rapid pace
(thereby shrinking the gap and reducing the absolute difference in inequality).
Looking at our measures of inequity, when do we continue to stick with a more universal approach only;
and when do we approach programs and policies from both the universal and the targeted directions?
This may give a hint to planners and policy–makers as to the continuum of universal versus targeted
+ universal programs, since as the Gini coefficient increases, the larger the inequality, and the more
necessity for targeted programs to affect lowest neighbourhood income groups differentially. See
Tables E.4 and E.5 for the degree of inequality and the increasing need for targeted programs on top of
universal programs.