The rich get richer, even in epidemiologic studies.

In a previous post, I indicated that I would eventually post epidemiologic analyses.

This is the first such post. Please refer back to the previous post, as needed, for a brief overview of epidemiologic methods and key concepts.

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My doctoral thesis in epidemiology focused on the health impacts of neighborhood walkability:

“Thus, more proximate destinations (e.g., shopping, work, recreation) and higher population density are thought to promote walking over driving, while walkable streets and proximate public transportation are thought to increase physical activity generally.” (pg. 1)

Specifically, I hypothesized that women who lived in less walkable neighborhoods at baseline would be more likely to be diagnosed with incident diabetes and/or have higher levels of depressive symptoms in the future than women living in more walkable neighborhoods. I used data from the Black Women’s Health Study (BWHS) as well as other data gathered by two members of my doctoral committee. Residential neighborhood walkability (most, 2nd most, 2nd least, least walkable) was assessed for BWHS residents of the New York City, Chicago and Los Angeles metropolitan areas in 1995. In the diabetes study (n=13,519), follow-up lasted 16 years, while in the depressive symptoms study (n=17,886), Center for Epidemiologic Studies-Depression (CES-D) scores were obtained in 1999 and 2005.

When I looked at the unadjusted association between neighborhood walkability and each outcome, however, I was surprised to find associations in the opposite direction than hypothesized. That is, women living in least walkable neighborhoods had 14% LOWER rates of incident diabetes over 16 years of follow-up than living in most walkable neighborhoods (which increased to 22% LOWER after adjusting for age[1]). The findings were similar (albeit even closer to the null) for depressive symptoms.

I was baffled…and more than a little nervous.

And then I started adjusting for other possible confounders (identified from the literature, confirmed using directed acyclic graphs).

The most obvious confounder was the socioeconomic status (SES)[2] of the woman’s neighborhood. First, it was strongly inversely associated with the exposure: the Pearson correlation[3] between continuous measures of neighborhood walkability and neighborhood SES was -0.31, and mean scaled neighborhood SES (mean=0, standard deviation [SD]=1) was 1.06 SD higher in least walkable neighborhoods than in most walkable neighborhoods.

In other words, less walkable neighborhoods tended to be much “better off” than more walkable neighborhoods.

Second, neighborhood SES was a risk factor for diabetes and for higher depressive symptoms in most walkable neighborhoods (my designated “unexposed” category). For example, every 1 SD decrease in neighborhood SES increased the risk of incident diabetes 29%. Results were similar for depressive symptoms[4]

Finally, neighborhood SES was not on the causal pathway between neighborhood walkability and either outcome.

And…huzzah!

After adjusting for SES (and city of residence), women living in any less walkable neighborhood had a 6% higher incidence of diabetes over 16 years of follow-up than women living a most walkable neighborhood.[5]

And…after adjusting for SES (and marital status), women living in a least walkable neighborhood had an 18% higher risk of having CES-D≥25[6] in 1999 and/or 2005 than women living in a most walkable neighborhood.[7]

In other words, adjusting for neighborhood SES turned living in a less walkable neighborhood from a protective factor to a risk factor.

Why would that be?

Because neighborhood walkability and neighborhood SES are inextricably tangled (at least within this primarily urban/suburban population of better-educated black women). The least walkable neighborhoods—hypothesized to yield more poor health outcomes—are much better off than the most walkable neighborhoods—hypothesized to yield better health outcomes.

Just bear with me while I put on my rarely-worn economic-populist hat to think through the policy implications of these findings.

The primary recommendation, of course, would be to find a way to increase the walkability of the less walkable neighborhoods, with the goal of improving health outcomes.

But those neighborhoods ALREADY have better health outcomes because of their higher SES.

And the most walkable neighborhoods?

Well, there is little you can do to improve their health outcomes via walkability, which is a pity because of the lower SES of these neighborhoods (and attendant less good health outcomes).

In other words: if you follow the policy recommendations suggested by my doctoral research, the rich (or, at least, the relatively better off) would get richer (improved neighborhood walkability), while the poor (relatively worse off) would get nothing.

Hmm…maybe it is a good thing I have not yet published my doctoral research.

Until next time…

[1] It has become routine practice (foolish, in my opinion) always to adjust for age, gender and race/ethnicity in any epidemiologic study, regardless of whether they meet the three criteria for confounding or not. Given that this study only assessed black women, the only variable of these three left to adjust was age.

[2] SES combines income and education level into a general “status” measure. For my doctorate, we concatenated “median household income; median household value, percentage of houses receiving interest, dividends or net rental income; percentage of persons aged≥25 with college degrees; persons of employed persons aged≥16 in white collar occupations; percentage of families not headed by a single female.” (pg. 8)

[3] A measure of the linear association between two variables, ranging from -1.00 (as one increases, the other always decreases) to 1.00 (as one increases, the other always increases), with 0.00 a purely random association.

[4] I can’t seem to locate the actual analyses at this time.

[5] IRR=1.06, 95% confidence interval (CI)= 0.90 to 1.24.

[6] The scale runs from 0 to 60, with a higher score indicating higher depressive symptom levels. CES-D≥16 is the typical cut-point for an indication of clinical depression (though the CES-D is not an official diagnostic tool). The association between neighborhood walkability and CES-D score above/below 16 was essentially null. CES-D≥25 has also been cited as an indicator of clinical depression, so I tested both in my doctoral research.

[7] RR=1.18, 95% CI=1.02-1.37.

How film noir made me appreciate my daughter’s birthday celebration even more

My eldest daughter (let’s call her MyED) turned nine yesterday.

I know that MyED turned nine yesterday not only because I was at my wife’s side nine years ago yesterday when MyED was born, but because it is practically all anyone has heard from MyED, since…well, since her younger sister turned seven four months ago.

As a kid, back in the early 1970s, I anticipated each upcoming birthday with a similar fervor. What I don’t recall, however, was beginning to celebrate these birthdays as many as five days before the actual day.

When, exactly, did kid birthday celebrations become so elaborate and drawn out?

Hold on a minute, I hear you saying. Isn’t this blog supposed to be devoted to “data-driven storytelling?”

A fair question. As a general rule, I use data analysis to frame a story in these posts, be it about the “noirness” of Noir City, or where it all went wrong (and sometimes right) for Democrats in 2016, and how post-2005 Doctor Who episodes have been rated, and why Jamie Moyer ABSOLUTELY should be in the baseball Hall of Fame someday.

But I also reserve the right simply to tell a story…to make an interesting connection or two between various elements of my life.

And, by the way, I will sneak some data in here later. Just bear with me.

MyED’s birthday fell on a Tuesday in 2017. However, the first act of celebration was a sleepover (in our home) which began in the early afternoon on Thursday (Spring Break week) and lasted until late Friday afternoon. MyED planned the dinner menu for Thursday night, though my talented and patient wife cooked it. The first round of presents was opened Saturday morning during a special breakfast meal MyED had planned. This round consisted of a “birthday bucket”—analogous to a well-stuffed Christmas stocking (writes the Jewish-raised Agnostic), whose contents were selected by her younger sister and her dad.

Then the four of us trekked to my mother-in-law’s home for a lunch, a cake and the second round of presents. The lunch and cake were scrumptious (cooked and baked by my talented and patient wife), and based (well, not the asparagus) on MyED’s requests.

On the drive to and from “Grandee’s” home, we listened to a 22-track mix—the Birthday CD—I had prepared especially for MyED. Along with the “birthday bucket,” this has become a birthday tradition for both daughters.

And now I will present some data, because I am quite proud of these mixes!

I try to balance songs the relevant daughter would like with an appreciation of musical history. [Seriously, I want to sit both girls in front of School of Rock’s “rock flowchart” scene. I am not quite ready to subject them to all of Ken Burns’ Jazz yet, however.]

MyED’s current favorite musical artists are Katy Perry, Taylor Swift and Adele. She likes what she calls “girl singers” and leans toward highly melodic what used to be called “synthpop.”

No complaints there, given my own New Wave proclivities.

But now, kid, let’s meet (or re-meet) some other excellent women in music. Chrissie Hynde. Suzanne Vega. Pat Benatar. Donna Summer. Aretha Franklin. Barbra Streisand (forget the diva nonsense; Streisand can SING). Christine McVie and Stevie Nicks. Gwen Stefani. Terri Nunn. Debbie Harry. Bjork. Dale Bozzio. Alison Moyet. Carol Decker (the lead singer of T’Pau).

My friend from Noir City, the excellent jazz singer Laura Kelly Ellis.

And…before Perry and Swift…there was the great Debbie Gibson.

Overall, 16 of 22 tracks (and 16 of 19 featuring vocals) have a female lead singer.

Being a musical child of the 1980’s, 11 of the CD’s 22 tracks come from that decade. The oldest track was “Symphony #9 In D Minor, Op. 125, “Choral” – 4. Allegro Assai” (i.e., Ode to Joy) by Ludwig von Beethoven, while the second oldest was Henry Mancini’s “Baby Elephant Walk.” The most recent tracks were Murray Gold’s “Doctor Who XI theme” (2010) and Ellis’ rendition of “Laura” (2011).

Thus, while the average release data was 1977.6 (1984.9 without Mr. Beethoven), the median was 1983.5. Yeah, that sounds like a mix I would put together.

Did I mention the CD closes with The Beatles’ “Hey Jude” (1968)? All 7 minutes and 11 seconds of it. Recorded from vinyl.

All of which brings me back to the ongoing birthday celebration.

Sunday and Monday were relatively quiet on that front.

But yesterday MyED got to celebrate her ACTUAL birthday by…getting a cast put on her left wrist! She had fallen hard off her scooter nine days earlier, and today the orthopedist decided to switch from a heavy splint to a full cast, making MyED deliriously happy.

Seriously, she can’t wait for everyone at school to sign it. [For those keeping score at home, I was the third signer, after MyED’s mother and sister].

Once she returned home from Boston Children’s Hospital, however, there was a third (but not final—we anticipate more arriving in the mail) round of presents to open. And then the four of us went out to a delicious feast at MyED’s favorite Mexican restaurant, bringing these five days of celebration to a close.

While I might sound like I am being a curmudgeon, kvetching about “these darned kids today” with their iPads and their Kids YouTube…and while my wife and I spent a lot of time shaking our heads about contemporary birthday culture…and observing that there might be just a bit of overkill here…and dreading the post-birthday emotional hangover (from BOTH daughters)…that is neither my intention nor my point.

Here is the point.

Readers of this blog know that as a rabid fan of film noir, I am constructing a massive database of published film noir lists https://justbearwithme.blog/2017/02/06/noir-city-15/. Besides providing fodder for ongoing data analysis, this database provides a checklist of titles I have not yet seen (I have only seen 550 [11.5%] of the 4,803 films in the database).

This is how I came to watch Nora Prentiss (1947; 20 LISTS, 22 POINTS) over the weekend.

I will spare you a full plot synopsis, but there is one scene of particular relevance to discuss.

In the film, Dr. Talbot, a respected doctor held to a rigid schedule by his wife (who clearly has Daddy issues), happens to go off schedule one night. As a result, he is on the scene to treat the titular Nora Prentiss after she is hit by a car across from the building housing his practice. The two ultimately have an affair, inexorably leading Dr. Talbot to lose track of his wife and two children—and his well-regulated life.

One child is his daughter “Bunny,” who turns 16 about halfway through the film. It is clear from their morning interaction that her father has completely forgotten it is his daughter’s birthday. A rather opulent birthday celebration takes place that evening, except that her father neglects to attend much of the party. But for the fact that he and Nora have a fight, he would not have appeared at all. Luckily, his wife intercepts him as he is entering the house to slip him a wrapped present (“exactly what I wanted, Daddy, thank you!”), somewhat redeeming her churlish and distant behavior toward him for much of the first half of the movie.

The ending of Nora Prentiss is one of the bleakest and most intriguing in the classic film noir canon, but it is this scene—a father completely forgetting his own daughter’s birthday party—that continues to haunt me.

And it is exactly why, for all of my mumbled grumbling about “these endless birthdays,” I secretly loved every minute of it.

Now, let me just get some rest before my youngest daughter’s birthday in eight months!

Until next time…