R A C E A N D C E S A R E A N D E L I V E R Y IN F L O R I D A 1

Darren Grant

At a time when the Clinton Administration has set a goal of elimi- nating racial disparities in health by the year 2010, medical experts are struggling to understand one of the most glaring, and least talked about, disparities of all: death in childbirth.

In a study made public this spring, the Centers for Disease Control and Prevention in Atlanta reported that black women in the U.S. were nearly four times as likely to die during delivery, or shortly thereafter, as white women. The disparity, which has remained about the same for the last four decades, holds true even for women w h o . . , are middle class and have health insurance.

The findings. . , have renewed interest among scientists and legisla- tors in a problem that many people think no longer exis t s . . . Dr. David Satcher, the United States Surgeon General, (says) "the disparity is important. In this country, we have a certain standard of expectation about the risk of women dying in pregnancy, and black women are off the scale right now." (Sheryl Gay Stolberg, "Black Mothers' Mortality Rate Under Scrutiny," Front Page, 8 Aug. 1999 New York Times)

Persistent racial disparities in health and health ou tcomes are a grow- ing source of concern in the public health communi ty . For example , rates of infant mortal i ty between whites and nonwhites remain substantial , as

do rates of maternal mortal i ty, as il lustrated in the excerpt above . A fundamental question is how much these disparit ies s tem f rom racial differences in the underlying health of the individual , differences in "con- straints" that can limit the individual ' s range of action (such as l imited access to health care), and differences in t rea tment (due, perhaps , to discrimination). In this paper, we examine this quest ion for use o f the

cesarean section during childbirth. The cesarean section is one of the two most c o m m o n l y pe r fo rmed surgical procedures in the United States, and racial differences in cesarean rates are well documented . For example , in 1992, the year of the data in our study, 22.8 percent o f all birthing non- Hispanic white w o m e n in the United States received a cesarean section,

38 The Review of Black Political Economy/Summer 2000

compared to 22.2 percent of non-Hispanic black women and 21.2 percent of Hispanic women, according to the Centers for Disease Control and Prevention (1994). This paper uses regression analysis of a large admin- istrative claims database to break down differences in the cesarean rates of different racial groups into components attributable to differences in health, constraints, and treatment.

Previous studies on this topic are split. Several (Braveman et al., 1995; Gould et al., 1989; Williams and Hawes, 1979; Stafford et al., 1993) find whites to have higher risk-adjusted cesarean rates (adjusted for relevant medical factors and complications of childbirth), while some others (Wil- liams and Chen, 1983; Stafford, 1991) find the opposite. But there are limitations. All of these studies use data from the state of California, with the exception of Williams and Chen (1983), whose data is from Canada (Ontario). Only one (Williams and Chen, 1983) controls for the identity of the attending physician, which can substantially influence the prob- ability of receiving a cesarean section (see Goyert et al., 1989, or Grant, 2000). And none performs a decomposition of cesarean rates so that the contributions of different factors can be identified. This study conducts such a decomposition, using data from Florida that contains the identity of the attending physician, and so does not suffer from these limitations. Model. Consider a discrete choice model of physician j ' s decision of whether to perform a cesarean on mother i:

{ ctlNSi + [3MEDi + ~, Y k CNTYi.k'~

+ d~jPHYSij + pRACE i (1)

where CES is an indicator variable that equals one if a cesarean is per- formed and zero otherwise, INS is a vector of indicators for source of payment, MED is a vector of medical characteristics and diagnoses of childbirth, CNTY is a vector of indicator variables that equal one if mother i resides in county k and zero otherwise, PHYS is a vector of indicator variables that equal one if mother i is attended by physician j and zero otherwise, RACE is a vector of race identifiers, and ct, [3, ?, d~, and 9 are vectors of coefficients.

When this model is estimated using least squares, as a linear probabil- ity model, then differences in the cesarean rates of races A and B can be expressed as:

Grant 39

100(Cff_~S B - C E S A ) = 100~(INS B - I N S A )

�9 -I.-lO0~(Mff~O B - M f f ~ D A ) + 100~, k ( f N Z Y B , k - C N T Y A , k ) k

"1-100~ ~ J j ( P H Y S B , j - P H Y S A , j ) + 100(p B --PA) J

(2)

Cesarean rates are typically expressed as a percentage of all births, and we have adopted that definition here. We use this decomposition to de- termine how much of the difference in cesarean rates between two racial groups can be attributed to differences in health, constraints, and treat- ment.

An alternative to the linear probability model, that is conceptually preferable but computationally complicated, is a logit model. The data contain more than 1,000 physicians and, often, more than 100 births per physician. This cannot be accommodated by the fixed effect logit models available in standard econometrics packages, such as LIMDEP. Experi- ments using a subset of the data showed that the correlation between fixed effects estimated using the LP model and those using the logit exceeded 0.95. The primary conceptual advantage of the logit is that all probability estimates are bounded by zero and one. In the LP model we utilize, 13.6 percent of the predicted probabilities are negative (though often not by very much) and 4.0 percent are greater than one.

We discuss the effects of health, constraints, and treatment in reverse order, which is in order of increasing complexity, and also consider the "other factors" of physician and geographic heterogeneity. Expansive background material on the cesarean section, including discussions of the effect of many of the factors discussed forthwith, can be found in Marieskind (1980), Goldfarb (1984), Keeler and Brodie (1993), and Stafford (1990).

Differences in Treatment . This is the final term in equation (2), rep- resenting that part of cesarean rates that cannot be explained by all other factors. Some of these differences in treatment may be attributable to discrimination, but some of it may also be due to differences in health behaviors, consumer preferences, or personal characteristics that are re- lated to race and are not perfectly captured by the other explanatory variables.

Other Factors . The county dummies are used to proxy for individual heterogeneity, which is not measured (well) with this data set at the

40 The Review of Black Political Economy/Summer 2000

individual level. ZIP codes are available in the data described below, allowing a set of ZIP code fixed effects instead, but statistical tests con- sistently rejected the hypothesis these were jointly significant when added to the regression, and so they were omitted from the model. The physi- cian dummies primarily capture differences in physician selection. Since physicians differ in their inclinations to perform cesarean sections, differ- ences in the physicians attending women of different racial groups can have a genuine, causal effect on differences in the groups' overall cesar- ean rates.

Differences in Constraints. Since virtually all pregnant women have access to health care since the expansion of Medicaid prior to 1992 (the year of the data), the constraints facing the mother are not those of access per se. Instead, this term is composed of three parts, one due to differ- ences in source of payment, one due to differences in the attending physician, and one due to differences in health (discussed under the next heading).

Since Medicaid generally reimburses cesareans less generously than does private insurance, physicians may be less inclined to perform them. This may cause the cesarean rates of racial groups to differ if the groups have different percentages of mothers on Medicaid. A number of studies in the public health literature have concluded that source of payment influences the probability of receiving a cesarean section (for example, Gould, Davey, and Stafford, 1989, and Oleske et al., 1991). In a study of data similar to that employed here, Grant (2000) also finds a causal effect of source of payment, but it is much smaller than in the earlier literature. He finds that being on Medicaid lowers the probability of a cesarean by one percentage point, ceteris paribus. The primary reason for the smaller estimate is that Grant includes fixed effects to control for physician het- erogeneity, which is also done in this study. Thus, while we may expect source of payment to have some effect on racial differentials in cesarean rates, the effect need not be large.

The second constraint takes the form of access to particular physi- cians. As previously noted, the identity of the attending physician can have a causal effect on the probability that a mother will receive a cesar- ean. Differences in the physicians attending mothers of different racial groups may be partly because of consumer preferences, partly from geo- graphic constraints, and partly from insurance constraints (many physi- cians only accept a limited number of Medicaid patients). To determine how much racial disparities in cesarean rates are attributable to con- straint-based differences in the attending physician, we conduct a supple-

Grant 41

mentary regression in which the physician dummies are omitted as re- gressors (and the 13 and p coefficients are constrained to equal their values in the original regression), and re-calculate the decomposition. To the extent the identity of the physician is correlated with source of pay- ment and the county dummies, these components of the decomposition will increase accordingly (literally, from omitted variable bias), and we may interpret these differences as attributable to the source of payment and geographic constraints that restrict the mother's choice of physician.

Differences in Health. These are captured by the medical variables, MED. Ideally, we would like to break this vector up into two compo- nents, one attributable to factors that cannot be influenced by the health behaviors of the mother, and the other attributable to factors under the control of the mother, such as diet or exercise. The former can also be considered a constraint. This is hard to do well with our data or the kinds of data typically available to analysts, but it is well-known that older mothers have more birth complications simply because of their age. There- fore, as a simple approximation, we have applied the 1~ coefficients to the levels of all medical diagnoses and the emergency admission variable that are predicted from maternal age and its square. Differences in these values across racial groups reflect racial disparities in the age at which mothers give birth (given in row 2 of Table 1), and give a crude approxi- mation of how much of the racial differences in medical characteristics cannot be attributed to health behaviors. The remainder is the maximum extent to which racial differences in cesarean rates might be closed by encouraging better health behaviors among groups currently in worse general health. Data. The data set is the 1992 Florida Hospital Patient Discharge Data, publicly available from Florida's Agency for Health Care Administra- tion. These data contain physician and hospital identifiers, demographic and payer information, source and type of admission, county of resi- dence, and up to 10 medical diagnoses for every patient discharge from a Florida hospital in 1992. We selected all birthing cases (182,273), and culled births to osteopathic physicians, births not paid for with medicaid, selfpay, commercia l insurance ( including H M O s and PPOs) , or CHAMPUS, and those with unidentifiable or uncertain: physician identi- fiers, source or type of admission, race, age, or county of residence. We are left with 145,920 observations. This sample size is large enough to allow physician fixed effects and geographic fixed effects- -more than 1,000 in total-- to be estimated with substantial accuracy. In addition, the author's extensive analysis of the data has uncovered very few data er-

42 The Review of Black Political Economy/Summer 2000

rors such as physicians with unreasonable numbers of births, unrealistic maternal ages, etc. The cesarean rate of our sample, 25.89 percent, is slightly higher than the overall cesarean rate in the complete data, 25.12 percent; and non-Hispanic whites are overrepresented (68.02 percent in our sample, 61.87 percent in the complete data), while the other racial groups are underrepresented, in roughly equal proportions. The primary reasons for omitting observations were unidentifiable physician identifi- ers and unknown source or type of admission .2

The medical variables are age and its square and indicator variables for: poor prenatal care, emergency admission, placenta previa, abruptio placentae, mild pre-eclampsia, severe pre-eclampsia, uterine hemorrhage, diabetes, hypertension, multiple fetus, face/brow presentation, breech, transverse or oblique presentation, premature, cervical incompetence, prior cesarean, herpes, uterine rupture, cord prolapse, low birthweight, high birthweight, dystocia, fetal distress, disproportion, and admission by per- sonal or HMO physician (as opposed to a staff or clinic physician). Generally, the diagnoses represent one of the following problems with the birth: physical difficulties birthing the baby vaginally, often because the baby is "presented" awkwardly in the uterus (breech, for example); problems involving the cord or placenta (for example, prolapse); prob- lems with the general health of the mother (such as hypertension); or a prior cesarean, which complicates the vaginal birth of successive chil- dren. For further detail, the reader is referred to Hausknecht and Heilman (1982), which describes these terms and the process of cesarean delivery in lay terms. The source of payment variables are indicators for: selfpay/ charity or Medicaid (with private insurance the omitted category). The data allow the private insurance category to be broken up into HMOs, PPOs, fee-for-service, and CHAMPUS, but statistical tests could not reject the hypothesis that they all had equivalent effects on cesarean rates and so they were combined into one category.

The race of the mother is identified as one of the following groups (number of observations in parentheses): White, Non-Hispanic (99,253); White Hispanic (10,997); Black Non-Hispanic (29,588); Black Hispanic (1,006); and other (5,076). As will be seen shortly, outcomes differ suffi- ciently for white and black Hispanics that one cannot justify, statistically, combining them into one group. We use the largest category--White , Non-Hispanic--as the reference group; it is always group A in equation (2). It is straightforward to algebraically manipulate the results to con- duct comparisons between any two racial groups. Results. Results are presented in Table 1. Rows 2-4 present means. The fifth row, the "no controls" regression, presents simple (unadjusted) dif-

Grant 43

T A B L E 1

Regression Results.

White Hispanic

Black Non- Hispanic

Black Hispanic

Non-White Non- Hispanic

1. Number of Births 10,997 29,588 1,006 5,076

2. Average Maternal Age 26.6 24.2 27.7 27 5

3. % Medicaid 39.7 62.9 32.8 32 8

4. % Charity/Selfpay 13.6 5.6 6.1 15.5

NO CONTROLS 5, Unadjusted Differential in 4.80 *** -2.91 *** -3.13 ** -1,42 ** Cesarean Rates

FULL CONTROLS 6. Source of Payment Effects -0.23 -0.34 0.01 -0]9

7. Medical Effects 1.42 -2.53 -0.21 -1+90

8. Geographic Effects 0.45 0.22 1.27 0.39

9. Physician Effects 1.98 -0.45 -3.03 1 1 L

10, Treatment Effects 1.L2 *** 0.17 -1.14 -0.86 *

m

11 TOTAL DIFFERENTIAL 0.26 -3.17 -0.59 -0 19 DUE TO CONSTRAINTS

12. Directly Attributable to -0.23 -0.34 0.01 -0 19 Source of Payment (same as row 6)

13 Medical Effects Attributable -0.61 -2.44 0.24 0.11 to Maternal Age

14. Physician Effects 1.05 -0.23 -0.84 0 7l Attributable to Geography

15 Physician Effects 0.05 -0,16 0.00 -0.02 Attributable to Source of Payment

Note: All numbers in rows 3-15 are in percentage points. Data source given in text. Significance levels on no controls regression and "treatment effects" of the full controls regression: *** = 1%; ** = 5%; * = 10% in a two-tailed test. The reference group, White non-Hispanic, contained 99,253 births; overall cesarean rate = 26.19%; average maternal age = 27.14 years; 31.6% covered by Medicaid, 7.1% by Charity/Selfpay. (The remainder are covered by commercial insurance/HMO/PPO or CHAMPUS.) Decompositions don ' t quite add up to the raw effects given in the "no controls" regression because of rounding and rounding error in the calculation of the components of the decomposition.

44 The Review of Black Political Economy/Summer 2000

ferences in cesarean rates. There are substantial differences in the cesar- ean rates of the five groups, all statistically significant, except for black Hispanics and black non-Hispanics, who have similar rates. There is a substantial difference in the cesarean rates of white Hispanics and white non-Hispanics. Statistically, we cannot support lumping together black and white Hispanics, nor an additive "Hispanic effect" which is the same for blacks and whites. This is also true in the regressions with the full set of controls.

The middle of the table presents the decompositions given in equation (2), with white non-Hispanics as the reference group. Rows 6-10 give the five components of the decomposition as itemized in equation (2). The treatment effects, in row i0, are simply regression coefficients, and significance levels on tests of the hypothesis that they differ from zero (implicitly, the coefficient for white, non-Hispanics) are presented. The bottom third of the table shows how much these differentials can be attributed to constraints; this is also broken down into components.

The first column of the table breaks down the large, positive difference in the cesarean rates of white Hispanics and non-Hispanics. This differ- ence is spread out across medical effects (about one-third), physician effects (over one-third), and treatment effects (almost one-third). Since white Hispanic mothers are younger than their non-Hispanic counter- parts, we would expect them to have less medical complications of birth (in the thirteenth row of the table) but instead they have many more (in the seventh row). This indicates that health behaviors related to child- birth may be increasing cesarean rates among this group. About half of the physician effects are attributable to geographic constraints--in part, the high concentration of Hispanics in Dade and Broward counties, which traditionally have high cesarean rates--but half are not, and may reflect consumer preferences or other influences. (Compare rows 9 and 14.) Treatment effects are substantial and positive, counter to what we might expect if minorities are being denied care due to discrimination.

The second column breaks down the large, negative difference in the cesarean rates of (non-Hispanic) whites and blacks. Virtually all of it is attributable to medical effects, nearly all of which are attributable to lower maternal age. Simply put, non-Hispanic black mothers are younger, and therefore have less medical complications and lower cesarean rates. There is no evidence of discrimination in the treatment effects; the point estimate is actually positive and is insignificant. The raw cesarean rates, and the medical, physician, and treatment effects for white Hispanics and black non-Hispanics are substantially different, so it is not appropriate to

Grant 45

treat all minorities alike, or to presume that cesarean rates are subject to the same influences in both groups.

The third and fourth columns consider the remaining two categories. The large negative differential in cesarean rates between white and black Hispanics is primarily due to "flip-flops" in the physician effects (large and positive for the former, large and negative for the latter) and the treatment effects (also). The lower cesarean rates in the "other" racial category, relative to white non-Hispanics, is due to a variety of causes and offsetting effects without any obvious pattern. There is evidence of negative treatment effects for both groups; they are statistically signifi- cant for the "other" category.

Some of the physician effects identified in the various entries in row 9 reflect differences in practice volume, but not much. Practice volume-- the number of births performed during the year--varies considerably in our sample (mean=152.89, standard deviation=148.37), and is related to race, with physicians treating non-Hispanic whites having notably lower volume than those treating Hispanics, who in turn have notably lower volume than those treating non-Hispanic blacks. But the effect of volume on the probability of receiving a cesarean is small. When we re-estimated our basic model, replacing the physician fixed effects with a variable for practice volume, the coefficient was negative and significant, but small: a one-standard deviation increase in practice volume (a large increase) lowered the probability of cesarean section by 0.4 percentage points.

Row 11 presents estimates of the extent to which the differential in cesarean rates can be attributed to constraints: source of payment, in row 12, medical effects attributable to age, in row 13, and physician effects attributable to geography and source of payment, in rows 14 and 15. The overall effect of constraints is small for three groups and large for one: non-Hispanic black mothers, who, as noted before, receive fewer cesar- eans primarily because they give birth at lower ages. For the remaining groups, most notably Hispanic whites, constraints explain very little of the differential in cesarean rates. In these groups a large fraction of this differential might be closed by a combination of better health behaviors, changes in the choice of physician, and the elimination of differences in treatment (treatment effects). Of especial note, the source of payment effects--both direct, and indirect, through their effect on the identity of the attending physician--are small for all racial groups. Thus financial con- straints cannot be blamed very much for racial differences in cesarean rates. Conclusion. This study has used a simple statistical decomposition meth- odology to break down differences in cesarean rates of different racial

46 The Review of Black Political Economy/Summer 2000

groups in Florida into different component parts. Our most striking find- ings are as follows. First, most of the racial difference in cesarean rates between non-Hispanic whites and non-Hispanic blacks can be attributed to fewer medical complications among the latter, primarily because they give birth at younger ages. In contrast, little o f the sizable racial differ- ence in cesarean rates between Hispanic and non-Hispanic whites is at- tributable to factors mostly or wholly beyond the control o f the mother , such as source o f payment. Finally, there is little evidence o f systematic discrimination against all minorities in the decision to per form cesarean sections during delivery, though there is some evidence of negative "treat- ment effects" for some racial groups.

N O T E S

1. I thank Santanu Datta and Amanda Twiss of Healthcare Business Services International, Inc. for providing the data used here; and Kristin Ellis, Mike Roberts, and Michelle Weiner for research assistance. This research was supported by a Faculty Research Stipend from Georgia Southern University.

2. In these data physicians are sometimes identified by their state license number and sometimes by their UPIN number. These were matched using a proprietary data set supplied by Healthcare Business Services International, Inc. Unidentifiable phy- sicians had unmatched UPIN numbers, unreported license numbers, or, in just a few cases, license numbers of 0 or 99999.

R E F E R E N C E S

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Goldfarb, Marsha G. Who Receives Cesareans: Patient and Hospital Characteris- tics. National Center for Health Services Research, Rockville, MD (1984).

Gould, J.B., Becky Davey, and Randall Stafford. "Socioeconomic Differences in Cesarean Sections," New England Journal of Medicine, 321:233-239 (1989).

Goyert, G., S. Bottoms, M. Treadwell, and P. Nehra. "The Physician Factor in Cesarean Birth Rates," New England Journal of Medicine, 320:706-709 (1989).

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