Tag Archives: health

Breastfeeding promotion here and there

We have just concluded another annual World Breastfeeding Week, and the U.S. Centers for Disease Control has a new report on how well hospitals are promoting breastfeeding. The results show progress in the direction of public health objectives, but the distribution of services is very unequal. Here’s the background:

Childhood obesity is a national epidemic in the United States. Increasing the proportion of mothers who breastfeed is one important public health strategy for preventing childhood obesity. The World Health Organization and United Nations Children’s Fund (UNICEF) Baby-Friendly Hospital Initiative specifies Ten Steps to Successful Breastfeeding that delineate evidence-based hospital practices to improve breastfeeding initiation, duration, and exclusivity.

The CDC did a survey of obstetric hospitals and birth centers in 2007 and 2009, and found progress on some of the Ten Steps (click on the image to read the labels):

Just as compliance on the Ten Steps is uneven, so too is the percentage of births at the top-rated “Baby-Friendly facilities” by state:

The CDC estimates that 4.5% of all U.S. babies are born at “Baby-Friendly facilities.”

Finally, the CDC report is linked to a Report Card for states, which shows how well each state is doing in terms of breastfeeding outcomes, as well as “process indicators,” which measure some of the policy supports in place in each state, such as child care center regulations, state health department workers tasked with promoting breastfeeding, and the number of lactation consultants.

To look under the cultural hood a little, I loaded the national Maternity Practices in Infant Nutrition and Care (mPINC) scores for each state into Google Correlate to see what Google searches are most highly correlated with breastfeeding success and failure at the state level. The Google tool gives the 100 most correlated searches, and they are mostly cooking terms, including 8 references to Martha Stewart or Julia Child, Epicurious, and highbrow recipes like “pumpkin lasagna” and “asparagus prosciutto.” So, that’s kind of fun to know but not really useful.

Surprisingly relevant, however, was the high prevalence of searches for “Nutrition Action” and “Nutrition Action Healthletter,” which both were correlated at .84 or higher with the mPINC scores across states. That is a newsletter put out by the Center for Science in the Public Interest, which actively promotes — among other things – breastfeeding policies intended to improve health and nutrition. Here are the maps showing where mPINC scores are higher and more people Google the Nutrition Action Healthletter:

This does not mean the relationship is causal, of course. But it appears that the places were CSPI resonates are also those that do a better job of promoting breastfeeding. Hopefully, this will further motivate the social science of search behavior.

Anyway, as I noted last year, breastfeeding rates are strongly associated with the race/ethnicity and education level of mothers:

This may be because of working conditions or other demands on time, mothers’ health, or other factors — but it might also reflect the failure of public health and education programs to inform many mothers about the importance of breastfeeding and support their efforts to breastfeed. Public health promotion of breastfeeding can help extend its health benefits, but to do that will require sustained state-supported efforts.

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Do explicit, enforceable policies matter?

Yes.

The Supreme Court’s decision in the Dukes v. Wal-Mart case, Justice Scalia acknowledged that Wal-Mart’s many local managers had a lot of discretion in their personnel decisions, even though the company had a written policy against gender discrimination (who doesn’t?). But he gave the company credit for a vague policy and let it off the hook for a systematic pattern of disparity between men and women. So, when does a toothless, vague policy over wide discretion lead to a bad outcome, and is failing to prevent it the same as causing it?

A path-breaking sociological analysis of organizational affirmative action outcomes has shown that the companies that successfully diversify their management are most likely to have policies with teeth – where accountability is built into the diversity goal. In light of the Wal-Mart case, this led to a rollicking debate about how to think about “corporate culture” versus policies, and when to blame whom, legally or otherwise – which even divided sociologists.

Smoking in the movies

Here’s an interesting, at-least-vaguely related case. Positive depictions of smoking in the movies are widely understood to be harmful. Yet, smoking is also glamorous, artistic, and popular – representing both anti-adult rebellion and maturity. So, what to do? The Centers for Disease Control, in the always-riveting Morbidity and Mortality Weekly Report, has published a fascinating report on this topic. They report the number of tobacco incidents* in top-grossing, youth-rated (G, PG, PG-13) movies, and divide them between those that implemented an anti-tobacco policy and those that didn’t — helpfully cutting the movie industry roughly in half — and provide a simple before-and-after tabulation:

From 2005 to 2010, among the three major motion picture companies (half of the six members of the Motion Picture Association of America [MPAA]) with policies aimed at reducing tobacco use in their movies, the number of tobacco incidents per youth-rated movie decreased 95.8%, from an average of 23.1 incidents per movie to an average of 1.0 incident. For independent companies (which are not MPAA members) and the three MPAA members with no antitobacco policies, tobacco incidents decreased 41.7%, from an average of 17.9 incidents per youth-rated movie in 2005 to 10.4 in 2010, a 10-fold higher rate than the rate for the companies with policies. Among the three companies with antitobacco policies, 88.2% of their top-grossing movies had no tobacco incidents, compared with 57.4% of movies among companies without policies.

The difference is dramatic, as indicated by this image about the images. (Because I turned the columns into cigarettes, this is not just a graph, but an infographic):

The policies provide what may be an ideal mix of accountability and responsibility, short of a simplistic ban.

[The policies] provide for review of scripts, story boards, daily footage, rough cuts, and the final edited film by managers in each studio with the authority to implement the policies. However, although the three companies have eliminated depictions of tobacco use almost entirely from their G, PG, and PG-13 movies, as of June 2011 none of the three policies completely banned smoking or other tobacco imagery in the youth-rated films that they produced or distributed.

Maybe this formula is effective because there already has been a strong cultural shift against smoking — as strong, even, as the shift against excluding women from management positions?

Graphic addendum (disturbing image below)

Whether smoking in movies actually encourages young people to take up smoking is of course a not a settled issue — especially on websites sponsored by tobacco sellers, as seen in this ironic screen-shot from Smokers News:

One reason to have an explicit policy is that it’s easy to assume viewers will see through the glamour to the negative outcomes. “Surely no one will want to be like that character…” But people – maybe especially young people? – have an amazing capacity to celebrate selectively from the characters they see. I have learned from experience that, in children’s stories, even those who get their comeuppance in the end still manage to emerge as role models for their bad behavior. So maybe some people want to relive this from Pulp Fiction…

…and aren’t put off by this:

*”A new incident occurred each time 1) a tobacco product went off screen and then back on screen, 2) a different actor was shown with a tobacco product, or 3) a scene changed, and the new scene contained the use or implied off-screen use of a tobacco product.”

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Health paradox, illustrated

A nice illustration of immigrant advantages in infant mortality.

In almost every race/ethnic group, immigrants are healthier. Here’s the pattern for infant mortality.

Infant Mortality Rates, by Mother's Place of Birth and Race/Ethnicity: U.S., 2007

Immigrants are often healthier than the average people in the countries they came from, which explains some of this. Among Latinos in particular, researchers refer to the “epidemiological paradox,” by which Latinos’ health is surprisingly good given their economic conditions. Robert Hummer and colleagues, in a 2007 article, offered a succinct description:

…the relatively low levels of education, income, and health insurance coverage among Hispanics compared with non-Hispanic whites is thought to place the former at higher risk for negative health outcomes. However, it is well documented that some Hispanic groups exhibit similar observed death rates compared with the non-Hispanic white population and much lower death rates than the non-Hispanic black population, whom they closely resemble with respect to socioeconomic characteristics. The greatest enigma is exhibited by the Mexican-origin population of the United States. This Hispanic subgroup is characterized by low educational attainment; low health insurance coverage rates; mortality rates similar to non-Hispanic whites; and much more favorable mortality rates than those of non-Hispanic blacks across most of the life course.

The article has a lot of references to fill in the background and previous research on this paradox, which goes back at least to the 1980s. This is a fascinating and important research area, dealing with such questions as health behavior, intergenerational change, thorny puzzles about different immigrant groups, child development and lots more.

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Birthweight and infant mortality inequality

Birthweight drives the Black-White gap.

Here’s a look at birthweight patterns and their effects on the difference in infant mortality rates between Black and White children.

A new report from the Centers for Disease Control, based on 2007 data, shows the distribution of birthweights and mortality outcomes by the race/ethnicity of mothers. Here is a story in three figures.

1. The infant mortality rate gap is large

In the figures below I focus on White (non-Hispanic), Black (non-Hispanic), and Hispanic. Since White and Hispanic infants have such similar rates, the issue I’m most concerned with is the Black-White gap.

2. Infant mortality rates are drastically affected by birthweight. But at each birthweight the race/ethnic gap is small.

The Black mortality rates are higher among the high-birthweight infants, but there are very few deaths out there (note the log scale, which is necessary to even see those gaps).

3. Black mothers are much more likely to have very-lowbirthweight infants.

Again, because of the log scale, you can see the gaps clearly even though there are very few births at the very low end. Still, 1.8% of Black women’s infants are born below 1,000 grams, where a large portion of infants don’t survive.

So what explains the higher infant mortality rates among Black women’s infants? The overwhelming issue is birthweight. If they had the same mortality rates at each birthweight, I calculate, the gap would close by 10%. But if they had the same birthweight distributions, the gap would close by 88%.

In previous posts, I reported that women who experienced childhood hardships are more likely to have low-birthweight babies. And I described the weathering hypothesis, which suggests delaying first births only improves outcomes for infants if their mothers’ health is not already deteriorating in their 20s, as it more often is with Black women. With this evidence, it is clear that the major problem driving the infant-mortality gap is not care of newborn infants itself, but rather the long-term health of Black women.

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Income gradient for children’s mental health

Lining them up (by income) and knocking them down.

I didn’t realize how strong the income gradient is for children’s emotional and behavioral problems. This new graph from the CDC combines data from 6 years of the National Health Interview Survey, and shows a steep relationship at all ages:

Percentage of Children with Serious Emotional or Behavioral Difficulties, by Age Group and Family: U.S., 2004-2009

The question asked was, “Overall, do you think that [child] has any difficulties in one or more of the following areas: emotions, concentration, behavior, or being able to get along with other people?” Children are included here if the parent said “yes, definite difficulties” or, “yes, severe difficulties.”

As background: I’ve posted before on the income gradient for asthma, overall health, diagnosis timing, mammographypregnancy, and women generally. That makes me curious, but not an expert. That is probably a good description for the authors of this recent review article, Janet Currie and Wanchuan Lin, who conclude:

Low-income children are in worse health than other children are. This paper explores the extent to which insults to health and activity limitations are responsible. In the most recent National Health Interview Survey (NHIS) data, low-income children are more likely than other children to have virtually every measured chronic or acute condition and are more likely to be limited by these conditions. Mental health conditions are particularly common and limiting. But the higher incidence of measured conditions and limits does not explain all of the relationships between income and overall health status, which suggests that unmeasured illnesses and injuries are also involved.

And finally, this reminds me of a good research tip. To get started on your subject, find a review article that’s a few years old or older, and then see which articles cite it — that should help bring you up to date. In this case, you could get these, which look highly relevant:

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Putting teen birth rates on the maps

The latest Morbidity and Mortality Weekly Report is out, with a report on teen birth rates in the U.S. The press release announces, “U.S. Teen Birth Rate Fell to Record Low in 2009.” (The report has information about birth control, virginity, and sex education as well.)

The CDC’s vital signs pamphlet still calls the rates “unacceptably high,” and notes they are “up to 9 times higher than in most other developed countries.”* Within the U.S. we have about a 4-to-1 ratio in teen birth rates between the states with highest and lowest rates, as you can see from this map:

Birth rates for teens aged 15-19 years in the US in 2009. Birth rates among those teens, by state, were lowest in the Northeast and upper Midwest, and highest across the southern states. Rates ranged from <20.0 per 1,000 population in three states to >60.0 in four states. The national rate was 39.1 in 2009.

Teen birth rates are the number of births per 1,000 women ages 15-19.

For comparison, using the U.N. Demographic Yearbook, I made a map of Europe using the same color scale as the CDC’s state map, though I had to add a few categories. (If you don’t know which countries are which, why not take a little time to learn them?)

Light blue, 31-39; White, 16-29; Pink, 10-16; Red, 0-10; Black, unavailable.

You can see the high rates in the Eastern European countries of Russia, Ukraine, Romania and Bulgaria, with teen birth rates in the range of our l0w-middle states (like California). The high-middle European countries — including Britain, Ireland, the Baltics and some Central European countries — are comparable to our lowest-rates states (New England, etc.). Then the rest of Europe is off the U.S. chart, down to 4.3 in Switzerland.

Addendum: The UN has a longer list of country teen birth rates here. The US ranks 95th out of 207 countries for 2007 on that list.

*It’s a little strange that teen births are considered a problem by definition, even though some of these teens are married, which should make their births officially not a problem.

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Risks women share, more and less

What is the basis for women’s global unity?

The other day I discounted the idea — expressed in the myth of women owning less than one percent of all property in the world — that women share a universal propertylessness. “If global feminist unity is to be had,” I said. “It won’t be built on a shared poverty experience.” One person commenting on the Huffington Post retorted: “The shared experience of women is patriarchy.” And she challenged me to produce a “gift-wrapped statistic that might make people think twice about gender inequality.”

I don’t have it. But for discussion, consider maternal mortality. I have previously shared the worldwide trend (except in the U.S.) toward reducing maternal mortality — the deaths of women related to pregnancy and childbirth. For every 10,000 live births in the world, 260 mothers still die.

This isn’t a risk all women face, since many have no pregnancies or births, but it’s something that is unique to women (more so even than rape). It is at least a potential risk women have in common.

In reality, however, the risk is so unevenly distributed as to virtually undermine its universality. In Sub-Saharan Africa, among all women, one out of every 31 women is estimated to die from maternal causes; in Western Europe that number is one-in-8,800. That is partly because African women have more children, and partly because they are more likely to die during each pregnancy or birth.

Those numbers are from a new data sheet published by the Population Reference Bureau. They estimated the lifetime chance that a given woman would die from maternal causes (factoring in both birth rates and risks of death). I’ve converted those to deaths per 10,000 women, by world region:

As is the case with wealth, statistically anyway, the women of the richest countries have more in common with their male peers than they do with the women at the bottom of the scale. So this isn’t the gift-wrapped statistic for global feminist unity based on shared personal risks. But do people need to experience the same hardships in order to unite against them?

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Getting the story straight on working mothers and children’s risks

When the result is not the news. Or, woe is the status of most social science reporting.

The news release was titled, “Children Of Working Moms Face More Health Problems.”

The news headlines, repeated around the world on the Internet’s instant, editor-free news rebroadcasting systems, were predictable:

Corbis helpfully sold clip art of a working mother putting her child at risk (note the ancient computer monitor and elephant-sized phone, showing the venerability of this story…):

In fact, we had the whole panoply of clip art on display, helpfully collected by Google news:

A complicated story

The research, by North Carolina State University economist Melinda Morrill, is in press at the Journal of Health Economics (the abstract is here, and Morrill has an earlier version for free on her website here).

Her conclusion, reasonably justified by the analysis was this: “I identify the effects on overnight hospitalizations, asthma episodes, and injuries/poisonings for children ages 7–17. Maternal employment increases the probability of each adverse health event by nearly 200 percent.”

Wow. Sounds awful. But understand one thing. The risk of all these events is very low, whether the kids mothers are employed or not. Doubling or tripling these rates still means that the vast majority of children are unaffected (triple-emphasis added). Using her data, a few hundred thousand National Health Interview Survey respondents from 1985 to 2004, the overall rates of each outcome look like this:

At a glance, it doesn’t match the headlines. Children whose mothers worked are less likely to be hospitalized or have asthma attacks (but more likely to have injury or poisoning). That’s probably just because healthy, rich mothers are more likely to work and have healthy, rich, safer kids. (It’s OK, we can control for that.) More importantly, the rates are low and the differences are small. Nevertheless…

The real contribution of this article is a clever application of what Belinda Luscombe at Time helpfully (I mean that) called “difficult-to-explain statistical techniques.” Specifically, Morrill used — there is no way to sugar-coat this — an instrumental variable method with two-stage least-squares regression, otherwise known as IV-2SLS.

Can this be explained to a non-expert audience? As a non-practitioner who has read a bunch of these papers, let’s see if I can do it.

  • Whereas, for many questions in social science, we would like to investigate a causal relationship, but the complexity of such relationships makes that difficult to establish; and,
  • Whereas, from a scientific point of view, the ideal study design is a true experiment, in which we randomly assign people to different conditions and trace their effects, thereby removing contaminating factors such as past experience, personal decisions and preferences, strengths and weaknesses, etc.; and,
  • Whereas, social scientists often can’t do true experiments because of ethics (and other reasons), and when we do experiments (like laboratory simulations), they differ substantially from real-life situations;
  • Therefore, some social scientists (usually called “economists”) use instrumental variable (IV) analysis, in which the trick is to find something (an “instrument”) that acts like an experiment, (more or less) randomly assigning people to different conditions, so that their true effects can be identified.

That’s the gist of it: has something (more or less) random occurred which (a) causes the independent variable to change (e.g., driving mothers into the labor force) while (b) neither causing, nor resulting from, the dependent variable (hospitalization, injury or asthma attack).

In this case, Morrill cleverly split children into two groups: those who had younger siblings who were just old enough to start kindergarten, and those who had younger siblings that were just too young to start kindergarten. Because mothers have a tendency to start work when the younger child goes off to kindergarten, but children reaching kindergarten age is neither cause nor effect of older children’s health outcomes, this acts like an experiment — some moms are assigned to the go-to-work group and some aren’t, and membership in the two groups is more or less random.

The method is called 2SLS because, using a complex prediction model, the economist first identifies those mothers whose employment was likely the result of the the younger child reaching kindergarten age, and then (in the second stage) uses a complex prediction model to determine whether those mothers’ older children were more likely to end up sick or injured than the children of those who did not start work.

Bottom lines

This method creates something close to an experiment, close enough that it is sometimes called a “natural experiment,” since the scientist didn’t engineer it. However, it also analyzes events that are extremely narrowly construed. It really is only a test of what happens when American mothers of two or more children started work after the younger child reached kindergarten age (over a 20-year period) — holding constant a wide array of social and demographic variables. Since the randomness of the school-age “instrument” can, in a practical sense, be confirmed statistically, the effect is reasonably called “causal,” but caution in the interpretation is wise.

And Morrill was cautious. Although she found that older children of mothers who went off to work in these conditions were indeed more likely to suffer these ill effects, she did a number of other checks to make sure things were as they appeared.

In fact, one of the mostly-overlooked aspects of the paper was a section on “heterogeneous effects.” Here, she tested whether the overall effect she found actually resulted from some subset of the families experiencing large effects while others experienced none. In my interpretation, this is where the real story is.

The effect of mothers going off to work on children’s hospitalization was three-times greater for Blacks than for Whites (and non-existent for Hispanics). The effect was only significant for mothers who had no more than high school education (unlike most or all of the women in the clip art above!). And the effect was three-times larger for single mothers than married mothers.

With no measures of child care availability or any details about the care arrangements of the families’ children, I’m left to conclude that the results probably reflect the simple fact that poorer women have fewer good options for childcare, so that when they enter the labor force, their children experience some increased risk of accident or illness.

Stop the presses

I see this result as a confirmation of common sense, not shocking or disturbing, or in any substantive way altering my understanding of the work-family-children situation: mothers working for pay increases the risks of illness or injury associated with non-supervision, or supervision by others. That this seems obvious does not detract from the value of the study, just from the breathlessness of its news coverage.

What are the implications of this? I can think of two. First, mothers (or, obviously, any caretakers) who are considering entering the labor force need to consider the availability and quality of alternative care arrangements for the children they will no longer be caring for during their working hours. Hopefully, they already knew this. Second, for public policy, we need to consider the availability and affordability of care arrangements for children whose parents are employed.

As for the bigger question, the one about mothers’ guilt and hard choices, Belinda Luscomb was good enough to link to a recent meta-analysis — a study of studies — that analyzed 69 different studies of the effect of mothers’ early employment on their children’s school achievement and psychological health, published by the American Psychological Association. That study concluded:

The small effect size and primarily nonsignificant results for main effects of early maternal employment should allay concerns about mothers working when children are young. However, negative findings associated with employment during the child’s first year are compatible with calls for more generous maternal leave policies. Results highlight the importance of social context for identifying under which conditions and for which subgroups early maternal employment is associated with positive or negative child outcomes.

Now we can confirm that another risk — small and manageable in the vast majority of cases — is illness or injury associated with loss of parental supervision. Something to watch out for. But didn’t we already know that?

There, I said it. Sorry it took so long.

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If we could teach kids one thing

Is “self control” that thing?

The parenting advice pile in my blog reader is brimming over again. It’s a frustrating pile, which includes everything from marketing hucksters to well-intentioned ignorance and naive extension of reasonable ideas to unsupported generalizations. One recent article, however — which didn’t come through the parenting channels — offers a model of scientific method. It also reinforces some basic facts about inequality, and shows the limits of what we know.

Researchers Terrie Moffitt and colleagues, writing in the Proceedings of the National Academy of Sciences, traced a sample of children born in New Zealand in the early 1970s through age 32. Their study used a measure of “self control” from the first 10 years of life to see whether it was associated with health, wealth, and criminality by age 32.

By “self control” — the key concept in the study — they mean:

nine measures of childhood self-control [including] observational ratings of children’s lack of control, parent and teacher reports of impulsive aggression, and parent, teacher, and self reports of hyperactivity, lack of persistence, inattention, and impulsivity.

The study is observational, rather than experimental, in that they didn’t assign children to a self-control condition, but rather just observed how they turned out in relation to the self control they displayed. That means we can’t conclude the relationship is causal. There are lots of things about these kids and their lives that we don’t know, which could be hiding behind that self-control “effect.” (If we could get this idea alone to catch on with the parenting-advice-reading public, the social world would be a more relaxed place.)

Anyway, to me, three things stand out in their results:

  1. Self control does successfully predict health, wealth and criminality in the ways they expect. Kids with higher levels of self control do better on these measures later in life. And that holds with simple statistical controls for family socioeconomic status (low versus not low), and childhood IQ score (low versus not low).
  2. Family socioeconomic status (SES) is even more important. We already knew that, but it’s nice to be able to see that, even controlling for IQ and self control, SES is a key determinant of well being later in life.
  3. IQ scores in childhood are the least important, compared with SES and self control.

The authors are focused on self control, and their correlational evidence is quite strong, as seen in this key figure:

One more empirical point to reinforce: even though the science news was headlined “Don’t Take that Cookie!“, this article does not show that efforts to change children’s self control have beneficial effects. Although they do find that children whose self control improves over time are headed in a good direction, that improvement is not from the result of a measured intervention. So we really can’t say that working to improve self control makes a difference. Not that there’s anything wrong with it.

Finally, let me add one point on the philosophy of social science regarding studies like this. Neither this nor any other study of what makes children “turn out” a certain way speaks to absolute principles of well being — they are all socially situated in space and time. That is, there may be social contexts in which self control matters more, or less, than it did among New Zealanders born in 1972-73; the same holds for IQ scores and socioeconomic status.

As we should expect, today’s parents are concerned with what they can do to help their kids in the social here and now sweepstakes. But from a social point of view, we might just as concerned with how to reduce the well-being gaps between those with more versus less self control, IQ points and socioeconomic status as we are with how to get some kids more of these assets in order to help them get ahead. That’s our choice.

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Health inequality compendium

The CDC releases a slew of inequality trends.

Many people will find the new report from the Centers from Disease Control very helpful. It’s called CDC Health Disparities and Inequalities Report — United States, 2011, and it covers everything from inadequate and unhealthy housing to preterm birth by race/ethnicity:

I previously reported national comparisons showing the U.S. bringing up the rear on this health indicator, and discussed the evidence for the role of obesity. This table was nice because it broke out the Latino groups, which we often don’t get (next step, Asians).

Anyway, very nice to see CDC putting resources into the collection and dissemination of inequality indicators. This report should be especially useful to teachers who want to include health in their discussion of inequality, but aren’t specialists in health outcomes (like me).

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