Correlations Discovered Between Health Risks and Age, Income
Explore the graphic above to see the relationship between health risks, age and income. Select factors along
axis to see the interplay between these variables. At first glance, it seems that there are many important
relationships here. But are there?
Nothing is that easy and there are no short answers.
Let's take the simplest of the x-axis variables-- Age. Click through the y-axis values to explore the relationship
between a state's median age and the percentage of the population with various health risks.
- Percent Without Health Care. At first glance, there is not much correlation between median age
in a state and the percentage of the population without healthcare. But look closer and see that there is a cluster of
higher rates of non-insurance in states with younger populations. This is likely the result of Medicare being available
to those over 65. It's possible that states with large numbers of retirees are masking high rates of non-coverage among
younger people. There are notable outliers, for example Massachusetts, which mandates health care coverage for nearly
all residents.
- Percent Who Smoke. Here we see that smoking is less prevalent in states with a lower median age. While not a
strong correlation, this is consistent with public health efforts over the past several decades to prevent youth smoking.
- Percent Who are Obese. There does not appear to be any correlation between a state's median age and the
percent of the population who are obese.
Now consider median income. Select median income on the x-axis and click through the y-axis values to explore the relationship
between a state's median income and the percentage of the population with various health risks.
- Percent Without Health Care. Not surprisingly, there is a strong correlation between median income and the
percentage of the population without health care. Health care is expensive and most Americans are insured through their
employer. It makes sense that those with better employment would have more money and be more likely to have health insurance.
- Percent Who Smoke. There is a much stronger correlation between a state's median income and its smoking rate. Smoking
cessation can be an expensive, time-consuming venture. More money means more resources available for those who want to quit.
Over a large population, this makes a difference in the ability to sucessfully quit smoking.
- Percent Who are Obese. At first this relationship seems counter-intuitive. People with less money are far more likely
to be obese. One would think that having no money means having no food. However, the system of food supply in the United States is
one of extreme plenty for calories and extreme lack for nutrition. Healthy food is more expensive than cheap, calorie-dense junk
foods. Additionally, much like smoking cessation, weight loss programs are both costly and time-consuming. This puts it out of reach
of people without a certain income. Both of those factors together contribute to soaring obesity rates among the
nation's poor.
Finally, consider poverty rates. Select poverty on the x-axis and click through the y-axis values to explore the relationship
between a state's poverty rate and the percentage of the population with various health risks. The relationships and correlations
are nearly identical to those related to income. In fact, some of the relationships are more stark because poverty rates reflect
a family's income relative to the local economic conditions and is a stronger indication of a family's inability to afford basic needs.
- Percent Without Health Care. While we expect to see a similar relationship between poverty and health care access, it
is surprising to note that there are still very high percentages of the population without healthcare in some of the poorest states.
Theoretically Medicaid covers the poorest and sickest population in a state. Some states block access or simply do not have the
funds to enroll all of their poor.
- Percent Who Smoke. This relationship is nearly identical to the median income relationship to smoking rates. It's worth
noting that smoking can often be an outlet or emotional crutch for people living in desperate conditions.
- Percent Who are Obese. Again we see an even more stark relationship between poverty and obesity as we saw with income.
The real story here is that poverty kills. The health effects of living under the constant stress of poverty are well-documented. Poor
health further reduces a family's ability to earn money, perpetuating a cycle with no good outcomes. People with limited resources will
stick to a vice such as smoking as one of their only releases. Those with the desire to quit lack the resources to get help. Lack of
affordable, nutritious food leads cash-strapped families to purchase larger quantities of high-caloric food in order to feed everyone.
Decades of living this way takes a heavy toll on the body and spririt. Eventually, people live much sicker lives and die much sooner than
they should.
Now the question is what can we do to make things better? We need fact-driven research into interventions that reduce poverty. If we
can ensure that children have quality food available to them, that anyone who wants to quit will have access to proven cessation therapy,
and that people do not suffer unnecessarily or die from preventable, manageable conditions, then we would save the public an enormous
amount of money and live better lives. Too many politically-charged strategies have failed to make a difference. It's time we look at
this as a numbers problem rather than an emotional one. Try something. Measure its impact. Support measures that work. Repeat and improve.