MCHB/EPI Miami Conference — December 7 - 9, 2005

Child Development: The New Public Health Frontier — Transcript

RACHEL AVCHEN: Good morning, everyone. Today my talk is entitled "Younger, Lighter, and Weaker, Impact of Prematurity and Low Birth Weight on Developmental Outcomes." And I'd like to acknowledge my coauthors, Scott Gross, who is actually giving a presentation at this same moment in the economics session, and Marshaline Yergen Alsep, who unfortunately wasn't able to attend this conference. I should probably get the pointer in my hand. As everyone in this audience is well aware, medical and technological advances have allowed for the survival rates of younger and younger gestational ages and lower and lower birth weight infants. We have a fair bit of knowledge about the acute conditions associated with these younger survival rates, but less information about the long-term sequelae.

Unfortunately I'm following Sara, so it sounds a little bit silly to say that, but Florida is one of the areas that is able to do with studies like the one I will be discussing today. And my roots are in Florida , so I sort of come with that training and look for longitudinal data sets to do similar type studies. When I was in Florida at the University of Miami , I was able to do a study that linked the Florida special education and birth certificate data for the entire state, which yielded us a cohort about 260,000 children, 12 to 15 years of age.

Birth certificate data was from 1982 to '84, and the school data that we looked at at that point in time was '96 to '97. And what we found basically in a nutshell was, for unadjusted risk ratios, there was a dose response in that as babies were lower and lower birth weights, there was a higher and higher risk for any disability. And then, there were specific disabilities that stood out. For example, orthopedic impairment was, you know, 22 folds times the referent group for children less than 1,000 grams.

There's also been few studies on the cost associated with this long term sequelae. But recently, in 2004, Roth published a paper, again linking Florida data, and looked specifically at the increased cost associated with kindergarten special education, which is a pretty where group, because to be identified in kindergarten, as Sara just showed you, there's lots of general categories, the severely developmentally delayed--I'm sorry--SDD, Significantly Developmentally Delayed is where a lot of the infants get captured, and then as they move through the system, get older, they get more specific diagnosis. But, even so, using the Florida data, at kindergarten, Roth and his colleagues show that for infants born less than 1,000 grams, there was a 60 percent increase in cost associated with these children. And then for 1500 grams, there was a 31 percent incremental cost. The objective of this study that I'm going to share with you today was to determine to what extent children born premature or at a low birth weight are at an increased risk for developmental disabilities. And here again, I'm using special education data as a proxy for developmental disabilities. We're defining pre-term birth for this presentation as less than 37 weeks, and low birth weight as less than 2500 grams.

I've adjusted some of the analyses for observed maternal and infant characteristics, and I'll talk more specifically about what those are as we get through the presentation. And then the secondary objective, unfortunately, we were not able to get to this part of the study for this presentation, but it's a teaser, so look for the paper in the near future. But we'll be estimating incremental costs associated with the increased risk by the special education category. So similar to what we had done previously, or what I had done previously in Florida , I used data from Extempore certificate in special education databases for the five County metropolitan Atlanta area. The birth certificate data was for children born from 1989 to 1999, and we used school data from 1992 to 2002. We had a resulting population of close to a half a million children, three to 13 years of age. Fifty-one percent were male, 55 percent were white, 41 percent black, and about 4 percent were in another category. And about 7 percent of this cohort was receiving special education services. And I'd just like to note again, I think that number's a little bit lower because of the younger children being included in this cohort. The mean maternal age of the moms was 27 years. Sixty-six percent were married, which is I think a little bit higher than we might expect in a population study.

Maternal education, again, was a little bit higher than I think I would have expected. Fifty-four percent had more than 12 years of education. Twenty-nine percent had 12 years, as a marker for high school graduation. Seventeen percent had less than 12 years of education, and 2 percent of the data was missing on education for this population. About 10 percent of the sample was less 37 weeks, and about 9 percent was less than 2500 grams.

The exceptionalities that I'm specifically looking at--I don't think it advanced. Again, I mentioned about 7 percent of the sample had some exceptionality. And the major exceptionalities are, as the slide indicates, autism. I've grouped behavioral disorder and severely emotionally disturbed as a behavior exceptionality, learning disability, mental retardation, including mild, moderate, severe, and profound. Orthopedically impaired, which is a lot of times where the children with cerebral palsy end up. Other health impairments.

The other category represents a hodgepodge of small samples, small cell size, including children who were in the younger cohort in a community preschool program, who had been hospitalized for some period of time that required them out of school, and the significantly developmentally delayed group is here, and traumatic brain-injured children. And then I created a category called sensory impairment, which grouped the hearing and vision impairment and death and hard of hearing children.

So here's just an overview slide of the results that we found for gestational age less than 37 weeks, prematurity, and exceptionality outcome. The referent here is all children who were greater than or equal to 37 weeks, who did not have an exceptionality or were considered gifted. And then, I just kind of arbitrarily created these groups. Oh, I didn't mean to advance. Did I advance? Sorry. Can you back up one? I meant to use the pointer. My grouping is just for the sake of this presentation, and you'll see on the next slide why I did this. But basically I have learning disability and behavioral disorder as having little to no excess risk. And the reason I say this is because I'm used to seeing sort of high above two risks associated with some of these DD's. Of course, they're still at risk here. I mean, you're 1.23 times as likely, if you're born less than 37 weeks, to end up with a behavioral disorder. That's still significant, but compared to what you'll see with some of the others, it's not as severe. And then the mild group, we're seeing any disability, so grouping all of these together, autism, other health impairment, the moderate risks, I'm sorry, I'm getting somebody's head, sorry. Sensory impairment, mental retardation, and the other group. And then the severe risk, again, is this orthopedic impairment group with a risk ratio of seven.

Okay. And here a similar way of presenting sort of a summary data to you, but here it's for birth weight of, again, the referent group here would be 2500 grams, equal to or greater than 2500 grams, again, not having any exceptionality or being gifted. And the data falls out in a similar way, except that the behavioral group now becomes part of the mild risk ratio group. This is a really hard angle to see the slides, so bear with me and my pointing abilities.

So the next few slides I just wanted to sort of point out to you mild, moderate, and severe examples. And, you'll see here for any exceptionality, being premature puts you at an increased risk for having any exceptionality. One point three two times with an adjusted odds ratio, and I felt, Craig, don't go up in arms that I'm mixing risk ratios and odds ratios. But I felt given that the prevalence of these conditions is rare enough that the odds ratios is approximating the risk ratio close enough. I adjusted for maternal race, age, education, marital status, and child's sex. And it's fairly consistent.

So I don't think we see any confounders. And then likewise, when you just look at birth weight, I didn't adjust on birth weight, you see a similar risk with a mild increase in the disability likelihood. For sensory impairment--again, this is the hearing and vision loss children. Less than 37 weeks, you're seeing a 2.35 unadjusted risk ratio and an adjusted risk ratio of 2.2, suggesting again a weak positive correlation of risk factors for pre-term birth, and a receipt of sensory impairment services. Likewise, again, an increased risk of 2.6 if you just look at it by birth weight. I think I'm giving up on the pointer. A moderate increase when we get to mental retardation. For prematurity, you see a risk of about 2.65 unadjusted, with an adjusted risk ratio of 2.28, suggesting there is some confounding going on here with these risk factors of maternal race, age, education, marital status, and child's sex. And then likewise, there's probably confounding I would imagine when we run those analyses for birth rate, because you're seeing a much more significant, if you will, risk associated with birth weight at a 3.5 times. And then the orthopedic impairment group, what I consider the severe risk group. For premature children less than 37 weeks, you're seeing seven time folds for unadjusted risk ratios, and that increases when we adjust. So there is a negative correlation suggesting something's really going on with children born at these low gestational age and likewise at these low birth weights in terms of ending up with an orthopedic impairment exceptionality category.

So, nothing profound here, but I would conclude that children who are born premature or low birth weight have a moderately elevated risk for developmental disabilities when we use special education as a proxy for measuring disability. And the primary exceptionalities in terms of risk that these children are likely to end up receiving services for are orthopedic impairment, mental retardation, sensory impairment. And interestingly, this was similar to the study I discussed very early on that I did in Florida , that these were sort of the high-risk groups.

So it was nice to see in another data set using different children that we're seeing similar trends. In terms of public health implications, I think it's really important to think about the longtime lifetime morbidity associated with a survival rate of children born premature or low birth weight and what the health burden on the community really is for these children. They are at an increased risk for developmental disabilities and a lifetime of medical, educational, and special service needs. The care that each child is going to require is not only a burden to their individual family, but to the community. And this burden is exasperated by circumstances such as poverty or communities with fragile health-care systems.

So in terms of next steps, we have a lot of work to do, but I'm actually really excited to get back to the office and sort of have some downtime over December to do some of these analyses. I'd like to look at this data set taking out sort of the younger children, because I have a sense that when we look at just the school-age children, six to 13 years of age, we're going to have truer estimates of the risk associated with the outcome. I'm going to refine the analysis looking at different gestational age cut-offs. If anyone was in the plenary session yesterday, there's really some urgency to understand what the impact is on children sort of born near-term, late, late premature children.

So, looking at it not just by the very premature children, which is less than or equal to 32 weeks, but the 35 to 36-week group. And then, as my study showed with the Florida data, the finer that we can look at birth weight, I think the closer we are to really understanding the risk associated with those outcomes--so to look at this group in 500 gram increments.

And then finally, once we settle on the best iteration of how to really approximate the risk, we are going to, with Scott Gross's help and unfortunately you're not hearing his talk today, but he is a health economist estimate the incremental cost associated with each of these especially to categories.

And finally I acknowledged my co-authors in the beginning of this slide, but I'd also like to acknowledge Ellen Devine, who is a statistician with the National Center on Birth Defects and Developmental Disabilities, and is always someone whose ear I like to bend when I'm doing analyses. So thank you and I'll look forward to your questions at the end of the discussion.