OBJECTIVE. We evaluated the overall effect of Illinois’ school-entry mandate on hepatitis B vaccination coverage levels and racial/ethnic differences in vaccination coverage before and after the mandate.
METHODS. In 1997, the Illinois Department of Public Health mandated hepatitis B vaccination before entry into 5th grade. We conducted a retrospective cohort study of 6 consecutive Chicago public schools’ 12th-grade classes; 4 entered 5th grade before the mandate (premandate cohorts) and 2 afterward (postmandate cohorts). We used Chicago public schools’ vaccination database and calculated annual coverage levels for 2nd through 12th grades; the cohorts entered 12th grade during 2000–2005. We compared hepatitis B vaccination coverage levels according to race/ethnicity and coverage levels for the premandate and postmandate cohorts.
RESULTS. We evaluated 106 541 students. The postmandate cohort had significantly higher hepatitis B vaccination coverage levels than the premandate cohort at 5th-grade (38.2% vs 4.3%) and 9th-grade (85.0% vs 37.4%) entry. For 9th-grade students, compared with white students, black students were less likely to have received hepatitis B vaccination before the mandate; this disparity decreased for the first postmandate cohort. For Hispanic students, the disparity was less pronounced and also decreased after the mandate. By 9th grade in the postmandate cohorts, coverage levels for all racial/ethnic groups exceeded 80%.
CONCLUSIONS. There was a dramatic decrease in the disparity of hepatitis B vaccination coverage between white and black or Hispanic students. School-entry requirements effectively increased hepatitis B vaccination coverage levels regardless of race or ethnicity and should be considered for other recently recommended adolescent vaccines.
Comments
Deriving a measure of differences between rates that is unaffected by the prevalence of an outcome
In a March 27, 2008 comment [1] on the study by Morita et al.[2], I explained that standard measures of differences between rates at which demographic groups experience or fail to experience an outcome are problematic for determining whether a disparity has increased or decreased because such measures are affected by the overall prevalence of an outcome. In tables accompanying the comment,[3] I provided measures of differences between immunization rates of whites and blacks or whites and Hispanics according to an approach that is theoretically unaffected by the overall prevalence of an outcome. The approach, which yields a measure I termed “EES” for estimated effect size, involves deriving from a pair of rates the difference, in terms of percentage of a standard deviation, between means of hypothetical underlying (normal) distributions of factors associated with experiencing the outcome. Among many other places, the approach is discussed on the Solutions sub-page of the Measuring Health Disparities (MHD) page of jpscanlan.com,[4] and a downloadable Access database with which to implement the approach is made available on the Solutions Database sub-page of MHD.[5]
The Access database implementing the approach employs a table containing 100 pairs of standard published values for areas under the normal curve, where the values in the second part of the pair differs from the first part by from .01 to 1.00 standard deviations (in increments of .01 standard deviations), and the procedure carried out by the queries involves identifying the row that reflects the closest possible match for the subject combination of rates. It has recently come to my attention, however, that the same result can be achieved by a probit analysis, such as may be implemented from a downloadable Excel file made available by David B. Wilson of George Mason University.[6]
References:
1. Scanlan JP. Study illustrates ways in which the direction of a change in disparity turns on the measure chosen. Pediatrics Mar. 27, 2008: http://pediatrics.aappublications.org/cgi/eletters/121/3/e547 (Accessed on February 22, 2010.)
2. Morita JY, Ramirez E, Trick WE. Effect of school-entry vaccination requirements on racial and ethnic disparities in Hepatitis B immunization coverage among public high school students. Pediatrics 2008;121:e547-e552: http://pediatrics.aappublications.org/cgi/reprint/121/3/e547?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&fulltext=morita&andorexactfulltext=and&searchid=1&FIRSTINDEX=0&sortspec=relevance&resourcetype=HWCIT (Accessed on February 22, 2010.)
3. http://www.jpscanlan.com/images/Tables_A_and_B_to_Morita_Comment.pdf (Accessed on February 22, 2010.)
4. Solutions sub-page of Measuring Health Disparities page of jpscanlan.com: http://www.jpscanlan.com/measuringhealthdisp/solutions.html (Accessed on February 22, 2010.)
5. Solutions Database sub-page of Measuring Health Disparities page of jpscanlan.com: http://www.jpscanlan.com/measuringhealthdisp/solutionsdatabase.html (Accessed on February 22, 2010.)
6. http://mason.gmu.edu/~dwilsonb/ma.html (Accessed on February 22, 2010.)
Conflict of Interest:
None declared
Study illustrates ways in which the direction of a change in disparity turns on the measure chosen
Morita et al.[1] find that, in addition to increasing overall hepatitis B vaccination rates, a school-entry vaccination requirement led to a dramatic decrease in racial and ethnic disparities in vaccination rates.
Among 5th graders, before the requirement, the black rate was 63% lower than the white rate (3% versus 8%); immediately following implementation of the requirement, the black rate was only 28% lower than the black rate (33% versus 46%). Among 9th graders, before the requirement, the black rate was 30% lower than the white rate (32% versus 46%); following implementation, the black rate was only 6% lower than the white rate (84% versus 89%).
Among 5th graders, before the requirement, the Hispanic rate was 50% lower than the white rate (4% versus 8%); following implementation, the Hispanic rate was only 9% lower than the white rate (42% versus 46%). Among 9th graders, before the requirement the Hispanic rate was 13% lower than the white rate (40% versus 46%); following implementation the Hispanic rate was only 3% lower than the white rate (86% versus 89%). (Because, due to rounding, a 3.37% relative difference between 86% and 89% may look like the absolute difference between rates, which below I will term a “percentage point difference,” for clarity I note that the 3% figure is indeed the relative difference. The same holds for several similar situations below.)
But not everyone would agree with the authors’ conclusions about dramatic decreases in disparities. In particular, the National Center for Health Statistics (NCHS) would consider the program not to have caused dramatic decreases in disparities. Rather, NCHS would regard the disparities to have increased and in some cases dramatically so. For NCHS would view the matter in the following terms:
Among 5th graders, before the requirement, the black rate of failing to receive vaccination was only 5% higher than the white rate (97% versus 92%); after the program, the black rate was 24% higher than the white rate (67% versus 54%). Among 9th graders, before the requirement, the black rate of failing to receive vaccination was only 26% higher than the black rate (68% versus 54%); after implementation, the black rate was 45% higher than the white rate (16% versus 11%).
NCHS would also have regarded the program as leading to increases in disparities between Hispanics and whites. Among 5th graders, before the requirement, the Hispanic rate of failing to receive vaccination was only 4% higher than the white rate (96% versus 92%); after implementation, the Hispanic rate was 7% higher than the white rate (58% versus 54%). Among 9th graders, before the requirement, the Hispanic rate of failing to receive vaccination was only 11% higher than the white rate (60% versus 54%); after implementation, the Hispanic rate was 27% higher than the white rate (14% versus 11%).
The figures underlying the above statements and those that follow may be found in Tables A and B to this comment, which may be accessed by the following link: http://www.jpscanlan.com/images/Tables_A_and_B_to_Morita_Comment.pdf
At this point I add a bit of background. In 2000 I published an article called “Race and Mortality” in the social science magazine Society.[2] Race and Mortality described the statistical tendency whereby the rarer an outcome the greater tends to be the relative difference in experiencing it and the smaller tends to be the relative difference between rates of failing to experience it – a tendency I had since 1987 described in about a dozen articles on the interpretation of group differences in the law and the social and medical sciences. See Section A of this page: http://www.jpscanlan.com/homepage/measuringhlthdisp.html
Race and Mortality principally addressed the fact that during periods of declining mortality, increasing relative differences in mortality were being universally regarded as reflecting increases in health disparities without regard to the extent to which, solely for statistical reasons, increases in relative differences between mortality rates would typically accompany declining mortality and without regard to whether relative differences in survival rates were decreasing. But the article also pointed out that, solely as a matter of convention, disparities in things like beneficial healthcare procedures were typically measured in terms of relative differences in rates of receiving such procedures. Thus, it noted, since such procedures were becoming more widespread, racial disparities in those outcomes were perceived to be declining. A more succinct expression of these tendencies than found Race and Mortality, and one that addresses as well the implications of changes in overall prevalence with regard to absolute differences and odds ratios may be found in reference 3.)
Eventually, in a series of papers,[4-6] NCHS responded to Race and Mortality’s discussion of the way relative differences in favorable outcome and relative differences in adverse outcomes tend to give different impressions of the comparative size of disparities. It did so, however, not by addressing the implications of the fact that changes in overall prevalence tend to cause relative differences in adverse outcomes and relative differences in favorable outcomes to change systematically in opposite directions. Rather, it simply recommended that, for consistency, all health and healthcare disparities, including disparities in things like rates of mammography and immunization, should be measured in terms of relative differences in adverse outcomes (i.e., the failure to receive such procedures). As reflected by the Morita and other recent studies, that approach has not yet gained much following among researchers outside the government.
Such approach, however, underlies the measurement of progress towards the health and healthcare disparities reduction goals in Health People 2010.[7] Measurement of disparities by the Agency for Healthcare Research and Quality (AHRQ), which issues the yearly National Healthcare Disparities Report, may be slightly different. As of the 2006 report,[8] AHRQ was measuring disparities in terms of the larger of the relative difference in the favorable or the adverse outcome. Since the latter relative difference is almost always larger than the former for the things that AHRQ examines, its approach is usually consistent with that of NCHS. But that is not always the case, and, as shown in Tables A and B, at least for certain periods, it would not be so with respect to some issues addressed in the Morita study. For example, despite the dramatic decline in the relative difference between vaccination rates of black and white 5th graders immediately after the requirement was implemented, the relative difference in vaccination rates remained larger than the relative difference in rates of failing to be vaccinated. Thus, AHRQ might agree with the authors of the instant study as to certain periods and agree with NCHS for other periods. And, with respect to situations where one relative difference is larger in one period and the other in another period, AHRQ would probably have some difficulty deciding what to do (as discussed with regard to the Morita study and some other matters in the Addendum to reference 9).
There remains the issue of whether the vaccination requirement affected the comparative situation of blacks and white with respect to vaccination in some meaningful sense – that is, in ways other than those that would tend naturally to occur due to the overall increases in vaccination rates.
Some researchers rely on absolute differences between rates to measure healthcare disparities. Among 5th graders, the absolute difference between vaccination rates increased immediately after the implementation of the requirement (from 5 percentage points to 13 percentage points), while among 9th graders the absolute difference declined (from 14 percentage points to 5). Thus, some researchers would consider the disparity to have increased among 5th graders but have declined among 9th graders. For reasons explained in several places, however, these changes are simply what would be expected usually to occur given the range of initial and final rates at issue.[3,9-11] Those and other works address implications of various patterns of changes in absolute differences as the overall prevalence of an outcome changes – roughly, when rare outcomes increase, absolute differences between rates tend to increase; when common outcomes increase, absolute differences tend to decline – at sufficient length that there is little value in belaboring such matter here. (The same holds for differences measured in odds ratios, which tend to change in the opposite direction of absolute differences.)
I will note, however, that many researcher who favor absolute differences as measures of disparities do so both because the absolute difference is unaffected by whether one examines the favorable or the adverse outcome and because absolute differences better reflect the burden on the disadvantaged group of its disadvantaged position relative to the outcome at issue. NCHS, while principally relying on relative differences in adverse outcomes to measure disparities, also emphasizes the importance of absolute differences between rates as indicators of the excess burden on the disadvantaged group. And in this regard the absolute difference seems to have some appeal as a measure of disparity even when it changes solely because of a change in overall prevalence. But we see in Tables A and B that after implementation of the requirement, among fifth graders, the absolute difference increased for both blacks and Hispanic, substantially in the former case. And in fact one will tend to observe such pattern generally when relatively uncommon outcomes become more widespread (as discussed in references 9-11). In such circumstances, the absolute difference as a meaningful measure of disparity loses much of its appeal.
In references 11 and 12, and a few other places, I have described an approach to measuring disparities between rates that ought to be unaffected by changes in overall prevalence. Specifically, based on the rates at each point in time, the approach derives a difference between means of hypothetical underlying normal distributions of factors associated with an outcome. The approach is somewhat speculative given that we cannot observe the actual nature of the underlying distributions. But to my mind the approach is superior to anything else so far developed and is certainly superior to the simple reliance on the standard measures of differences between rates without regard to the way the measures tend usually to change solely because of a change in the overall prevalence of an outcome. In any case, the results of that approach as applied to the Morita data are included in Tables A and B. And they seem to indicate that for blacks, among 5th graders the disparity declined immediately after implementation of the requirement (a decline that occurred, to return to the point in the preceding paragraph, while absolute differences between rates increased substantially), and continued to decline in the following year; among 9th graders, the disparity initially declined, but increased slightly in the following year.
For Hispanics, among 5th graders, the disparity declined immediately following the implementation of the requirement and continued to decline in the following year. Among 9th graders, however, there was no change in the Hispanic-white disparity immediately following implementation of the requirement, but a substantial decrease in the following year.
One thing that is clear is that this was a remarkably successful program. But as with other remarkably successful programs,[13] appraising the impact of the program on racial and ethnic disparities is much more complicated than it may seem at first sight.
References:
1. Morita JY, Ramirez E, Trick WE. Effect of school-entry vaccination requirements on racial and ethnic disparities in Hepatitis B immunization coverage among public high school students. Pediatrics 2008;121:e547-e552: http://pediatrics.aappublications.org/cgi/reprint/121/3/e547?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&fulltext=morita&andorexactfulltext=and&searchid=1&FIRSTINDEX=0&sortspec=relevance&resourcetype=HWCIT
2. Scanlan JP. Race and mortality. Society 2000;37(2):19-35 (reprinted in Current 2000 (Feb)): http://www.jpscanlan.com/images/Race_and_Mortality.pdf.
3. Scanlan JP. Can we actually measure health disparities? Chance 2006:19(2):47-51: http://www.jpscanlan.com/images/Can_We_Actually_Measure_Health_Disparities.pdf
4. Keppel KG, Pearcy JN, Klein RJ. Measuring progress in Healthy People 2010. Healthy People statistical notes. No. 25. Hyattsville, Md.: National Center for Health Statistics: http://www.cdc.gov/nchs/data/statnt/statnt25.pdf
5. Keppel KG, Pamuk E, Lynch J, et al. Methodological issues in measuring health disparities. Vital and health statistics. Series 2. No. 141. Washington, D.C.: Government Printing Office, 2005.(DHHS publication no. (PHS) 2005-1341.): http://www.cdc.gov/nchs/data/series/sr_02/sr02_141.pdf.
6. Keppel, KG, Pearcy JN. Measuring health disparities in terms of adverse outcomes. J Public Health Management Practice. 2005:11(6): 479-83
7. Keppel KG, Bilheimer L, Gurley L. Improving population health and reducing health disparities. Health Affairs 2007;26(5):1281-1292.
8. Agency for Healthcare Research and Quality, 2006 National Healthcare Disparities Report: http://www.ahrq.gov/QUAL/nhqr06/nhqr06.htm
9. Scanlan JP. Measurement Problems in the National Healthcare Disparities Report, presented at American Public Health Association 135th Annual Meeting & Exposition, Washington, DC, Nov. 3-7, 2007. PowerPoint Presentation: http://www.jpscanlan.com/images/APHA_2007_Presentation.ppt Oral Presentation: http://www.jpscanlan.com/images/ORAL_ANNOTATED.pdf Addendum (March 11, 2008): http://www.jpscanlan.com/images/Addendum.pdf
10. Scanlan JP. Effects of choice measure on determination of whether health care disparities are increasing or decreasing. Journal Review May 1, 2007, responding to Vaccarino V, Rathore SS, Wenger NK, et al. Sex and racial differences in the management of acute myocardial infarction, 1994 through 2002. N Engl J Med 2005;353:671-682 (and several other articles in the same issue): http://www.journalreview.org/view_pubmed_article.php?pmid=16107620&webenv=00P_2r_lHBKZPkExnEkCR_j5 -u8waNcJ- 87aLnoSJWxvN_ljFKstOR3CAx%402B600907661FF950_0034SID&qkey=1&rescnt=2&retstart=0&q=%22vaccarino+v%22+%22rathore+ss%22
11. Scanlan JP. Can We Actually Measure Health Disparities, presented at the 7th International Conference on Health Policy Statistics, Philadelphia, PA, Jan. 17-18, 2008 (invited session).
PowerPoint Presentation: http://www.jpscanlan.com/images/2008_ICHPS.ppt Oral Presentation: http://www.jpscanlan.com/images/2008_ICHPS_Oral.pdf
12. Scanlan JP. Comparing the size of inequalities in dichotomous measures in light of the standard correlations between such measures and the prevalence of an outcome. Journal Review Jan. 14, 2008, responding to Boström G, Rosén M. Measuring social inequalities in health – politics or science? Scan J Public Health 2003;31:211-215: http://www.journalreview.org/view_pubmed_article.php?pmid=12850975&specialty_id
13. Scanlan JP. Changing social inequalities in SIDS. Am J Public Health Dec. 11, 2005, responding to Pickett et al. Widening social inequalities in risk for sudden infant death syndrome. Am J Public Health 2005;95:97-81: http://www.ajph.org/cgi/eletters/95/11/1976
Conflict of Interest:
None declared