Jobs and repeals

Couldn’t resist this:

Sources: Current Employment Statistics (seasonally adjusted); Washington Post 2 Chambers blog.

Note: The blog is nonpartisan.

Health inequality recap

On SCOTUS’s ACA D-Day, here is a quick recap of some health inequality posts.

Percentage of Adults Aged 18-64 Who Did Not Get Needed Prescription Drugs Because of Cost, by Poverty Status: National Health Interview Survey, 1999-2010

From 1,000 women diagnosed with breast cancer over 11 years in Washington, D.C.: The number of days between the discovery of an anomaly and the diagnosis, by race/ethnicity and insurance status.

 

Children with asthma are almost twice as likely as all children to be below the poverty line, and less than half as likely to live at 4-times the poverty line or higher.

 

All groups of countries are showing improvement in maternal mortality rates except the U.S.

The U.S. lags seriously behind almost all European countries on infant mortality (most of which is caused by preterm births, the result of women’s poor health).

Estimated Percentage of Persons Who Delayed Seeking or Did Not Receive Medical Care During the Preceding Year Because of Cost, by Respondent-Assessed Health Status

OK, that’s enough! You can see all the health care related posts here.

Prescriptions for poverty

Poverty is usually described as a status, as there are people below and above the poverty line. We need to do more to capture and represent the experience of poverty.

There are ways this can be done even in a single survey question, such as this one: ”During the past 12 months, was there any time when you needed prescription medicine but didn’t get it because you couldn’t afford it?” Here are the percentages answering affirmatively, by official poverty-line status:

Percentage of Adults Aged 18-64 Who Did Not Get Needed Prescription Drugs Because of Cost, by Poverty Status: National Health Interview Survey, 1999-2010

This is not the same as not having any of the prescription drugs you need. What it indicates is economic insecurity rather than deprivation per se.

Care vacuums

Which came first, the closed nursing home or the doubled-up household?

The recession-driven spikes in multigenerational households and cohabiting couples are making families feel the love a little more proximately. These are spikes in longer-term trends; another one is the race and class disparity in reliance on nursing home care.

And in the last 10 years the people who use nursing homes more have disproportionately experienced the closure of local facilities, according to a new analysis in the Archives of Internal Medicine.

The authors analyzed the closure of almost 3,000 nursing facilities – a little more than half of them free-standing nursing homes – between 1999 and 2008, for a loss of about 5% of all nursing care beds.

They conclude:

The relative risk of closure was significantly higher in zip code areas with a higher proportion of blacks or Hispanics or a higher poverty rate. … Closures tended to be spatially clustered in minority-concentrated zip codes around the urban core, often in pockets of concentrated poverty.

The findings are nicely illustrated in this figure from Chicago, showing closures (red triangles), remaining facilities (black dots), and racial composition (darker blue = higher minority composition):

In practical terms, this means poor people, Blacks and Latinos in urban areas are more likely to live further from the nearest nursing care facility:

…in zip codes in which at least 1 nursing home closed from 1999 through 2008, the nearest distance to an operating facility increased from 2.73 miles in 1999 to 3.81 miles in 2008… In contrast, this distance was shortened slightly in zip codes without any nursing home closure… Similarly, in the poorest quartile of zip codes (ranked by poverty rate), this nearest distance increased by 10.4%, from 3.45 to 3.81 miles.

Most people doubling up or moving in together because of economic constraints probably aren’t responding to a lack of nursing home care. But both trends are indicative of the intermingling (geographic, economic and otherwise) of care needs, housing needs, economic insecurity and family relationships.

Race, insurance, and diagnosis delay

It’s not just access to insurance that privileges White women in breast cancer treatment.

New research shows that, even with the same kind of insurance, White women’s breast cancer is diagnosed more efficiently than that of Black and Latina women.

The research involved almost 1,000 women diagnosed with breast cancer over 11 years in Washington, D.C. They recorded the number of days between the discovery of an anomaly and the diagnosis:

Source: My graph from data in the news release.

The cause of the delays was not revealed in the study, but potential culprits include behavior by patients, doctors, and hospital actors — the subject of new research the authors hope to inspire.

Mammography’s income gradient

Rich women get more regular cancer screening.

Women with more money are healthier, generally, and new data from the CDC shows a strong relationship between income and regular mammography for women over age 49. (The pattern for education is about the same.)

Because Black women have more breast cancer — with worse outcomes on average — than White women, I was expecting a stronger race/ethnicity pattern. Instead, the data show that Black, White, and Asian/Pacific Islander women all have rates over 80%. The exception is American Indian women, only 70% of whom have had the recommended screening.

The big difference is in having health insurance, not surprisingly. Among those with health insurance, screening is 84%; among those without it’s just 56%. And to make matters more rational — and less humane — being married helps, too.

The report concludes:

Health-care reform is likely to increase access by increasing insurance coverage and by reducing out-of-pocket costs for mammography screening. Widespread implementation of evidence-based interventions also will be needed to increase screening rates. These include patient and provider reminders to schedule a mammogram, use of small media (e.g., videos, letters, brochures, and flyers), one-on-one education of women, and reduction of structural barriers (e.g., more convenient hours and attention to language, health literacy, and cultural factors).

Healthcare’s race of place

Who sees a nephrologist before their failing kidneys require chronic dialysis?

This seems like a technical subject for me, but I think I get the point of this new paper from the Journal of the American Society of Nephrology (always a good source for material). They knew that Black kidney patients were less likely to see a specialist before their kidneys fail than White patients — that is, before they reach ESRD, or end-stage renal disease. And failure to receive specialized care can have negative effects on the course of their disease.

I’m always looking for concrete ways of illustrating the point that “race” is not (just) an individual trait, that it’s a structural feature of society. Going back to my dissertation project, and more recently, one way to show that has been to look at the “race” of larger social groupings, like labor markets, workplaces or jobs.

So the kidney treatment analysis caught my attention because they examined the pattern of care according to the racial composition of patients’ zip codes. Sure enough, the Black-White individual disparity in early access to a specialist was pronounced, but it was exacerbated by a Black-White zip-code disparity as well.

The Black-White gap is apparent at all levels of Black concentration by zip code — but everyone in higher-percent-Black zip codes has a higher risk of delayed care. In the detailed analysis, they find the relationship still holds even when individual socioeconomic status, and local-area socioeconomic status, are controlled. So it’s not just a poverty effect.

In the healthcare-access sweepstakes, in which racial inequality is a pronounced feature, places have a race, too.

Health insurance v. asthma

Having health insurance doesn’t eliminate Black-White disparities in asthma and its effects, according to a new study, which studied only children in the extensive Military Health System, who all have access to the same government-run healthcare in an HMO-style service. The press release says:

Black and Hispanic children were more likely to be diagnosed with asthma at all ages. Black children of all ages and Hispanic children age 5 to 10 were more likely to have potentially avoidable hospitalizations or emergency department visits related to asthma.

Whites were also more likely to see a specialist while Blacks were more likely to go to emergency rooms.

So, some of the asthma gap persists even when everyone has health insurance coverage. But access to insurance coverage per se isn’t the only thing that generates health inequality. Everything from health behavior and education to environmental conditions to racism in the medical system can contribute.

We shouldn’t be surprised that a gap persists even when people have access to medical care. However, when you compare the asthma prevalence rates in the Military Health System to those in the general population of children, in this report, which I covered previously, it appears asthma rates are lower among children in the military system, and the Black-White gap is lower as well.

Note: Includes children only. Total population rates from p. 21 of this report, military rates from this paper in the Archives of Pediatrics and Adolescent Medicine.

Universal health coverage can’t be counted on to eliminate race-ethnic gaps in health and health care, but it probably wouldn’t hurt.

Paid for disability care

One thing you can say about the Community Living Assistance Services and Supports Act: It sure is a CLASS Act.

It’s part of Obamacare:

It is a self-funded and voluntary long-term care insurance choice. Workers will pay in premiums in order to receive a daily cash benefit if they develop a disability. … The benefit is flexible: it could be used for a range of community support services, from respite care to home care. No taxpayer funds will be used to pay benefits under this provision. The program will actually reduce Medicaid spending, as people are able to continue working and living in their homes and not enter nursing homes.

I guess it’s like Social Security: conjured as self-insurance, but really paying as you (we) go. And what of the “flexible” benefits? Marketplace Money reports:

The government basically gives you a check, which then you spend. And you can even actually hire a family member, which could be great for family members who don’t have to then choose between going to work and caring for a parent. Of course, at the same there’s a big potential for fraud. I should mention though that you can’t hire your spouse, because apparently the pledge to be there in sickness and health extends to long-term care.

Correction to the Marketplace story. I’m now told by several correspondents that this is not true, that the CLASS benefit is a cash payment, supposed to be about $50/day depending on the extent of disability, to be spent as you like. That’s good to hear. I had thought this was a case of: “it’s really wives’ who absolutely, positively, always must work for free.”

This makes most of this post unnecessary. So instead I’ll just give you a reference to some basic info on the act, and a recent article in Health Affairs on policy issues with long-term care coverage in general. I hope it’s helpful. And thanks to those who wrote correcting the story.

U.S. bucks the trend on maternal mortality

Worldwide, the news is good. The U.S. is the exception.

The big news from The Lancet is that maternal mortality — the number of women who die in pregnancy and childbirth, per 100,000 live births — has fallen worldwide, from 422 in 1980, to 320 in 1990, and all the way down to 251 by 2008.

Unmentioned in much of the news coverage was the trend reported for the United States, which shows up on the map of rates of change in maternal mortality for each country:

Yearly rate of decline in maternal mortality ratio, 1990–2008

The red states, so to speak, are those with increases in maternal mortality rates from 1990 to 2008. The U.S. is joined by a cluster of sub-Saharan countries in Africa, Afghanistan, and a few other small ones. Big improvements were concentrated in Asia, North Africa and Latin America.

Maybe the U.S. maternal mortality rate was already so good in 1980 that it had nowhere to go but up? Not so. Among countries that already had low rates — below 50 per 100,000 in 1980 — all groups showed continuing improvement except the U.S.

Maternal mortality ratio per 100, 000 live births, low MMR regions

That light blue line for “North America, High Income,” is for the U.S. and Canada. The upward part of the trend is driven entirely by the U.S. (Numbers for each country are in supplemental materials behind the Lancet‘s pay wall.)

This reversal in the U.S. was recently seen in California, where maternal deaths tripled in the last decade. Explanations for that are not clear. Obesity, fertility treatments and older birth mothers all contribute, but can’t explain the whole pattern. Increased C-sections and induced pre-term births are suspected culprits.

Given that the rest of the already-well-off world found ways to improve over the last three decades, I can’t think of a good excuse for the U.S.’s poor showing.

I’m not an expert on this issue in general, but this is what I learned today, FYI: In poor countries, maternal mortality has been shown to fall with increases in women’s overall empowerment and education, access to health care and clean water, and trained delivery personnel — factors that help differentiate sub-Saharan countries that have seen progress from those that haven’t. Overall higher consumption levels help, too, naturally — and within poor countries, the poorest mothers face much higher risks for the same reasons whole countries have it worse (education, sanitation and health care). Finally, economic dependence among poor countries, especially multinational corporate investment, is associated with higher levels of maternal mortality.