SPECIAL ARTICLE

Why small black infants have a lower mortality rate .than small white infants: The case for-population-specific standards for birth weight

Al len Wi lcox, MD, PhD, a n d tan Russell, PhD

From the Epidemiology Branch, Division of Biometry and Risk Assessment, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, and the Health Services Research Unit, University of Aberdeen, Aberdeen, Scotland

Seventy years ago, Ylpp61 proposed a birth weight criterion of 2500 gm to identify small babies at high risk of perinatal death. Today this remains the standard definition of low birth weight. In 1939, Dunham et al. 2 questioned the uni- versal application Of 2500 gm. Shortly thereafter, Anderson et al. 3 Suggested different birth weight standards for black infants and white infants. Similar proposals have since been made by other researchers. 4-6 These suggestions have been ignored in practice.

In I980, RoOth 7 Carried the discussion further. He sug- gested that a separate criterion for LBW should be derived for each population from the particular birth weight distri- bution of that population. He noted that the frequency dis- tribution of birth weight is essentially gaussian and that there is a slight excess of small births in the lower tail. These two features characterize birth weight distributions from virtually all populations, including groups defined by race, social class, or other characteristics. 8 The distribution of birth weight has the same general shape for all groups, but it does not always have the same mean or the same spread. Rooth 7 proposed that LBW be defined for each population by a weight 2 SD less than the mean. He showed that this criterion for LBW could vary by as much as 350 gm among different populations.

Rooth 7 als0 showed that his criterion for LBW had a dis-

Supported in part by the Scottish Home and Health Department. Submitted for publication April 27, 1989; accepted Aug. 23, 1989. Reprin t requests: Allen Wilcox, MD, PhD, National Institute of Environmental Sciences, PO Box 12233, Research Triangle Park, NC 27709, o r Ian Russell, PhD, Health Services Regearch Unit, University of Aberdeen, Foresterhiil, Aberdeen AB9 2ZD, Scot- land. 9/19/16227

tinct advantage over the 2500 gm criterion: it is a much better predictor of perinatal death. Comparing data from several countries, Rooth found that perinatal death was more closely related to the proportion of births smaller than 2 SD below the mean than to the proportion of births <2500 gin. Despite this advantage, Rooth's proposal has received no wider acceptance than those of his predecessorS. We pre- sent a second argument in favor of Rooth's approach. There is a well-known paradox in pediatrics--that small black babies achieve better survival rates than small white babies, despite the worse survival rates of black babies in general. An extension of Rooth's method resolves this paradox.

�9 I LBW Low birth weight

See commentary, p. I01.

M E T H O D A N D R E S U L T S

Consider U.S. black infants and white infants 9, 10 (Table). Overall, the black stillbirth (or fetal mortality) rate is nearly double that for white infants~ 11.8 versus 6.4 per 1000. (Stillbirth rates are used in this example because Weight- specific perinatal mortality rates are not available for the United States as a whole; however, the same results are found with perinatal, neonatal, or infant mortality rates.l!) Even though the overall mortality rate for black babies is higher, black infants who weigh 2500 gm have a lower mortality rate than white infants of the same weight. 12 It appears that small black babies have an advantage over small white babies. However, when infants at 2 SD less than their own population mean are compared, the mortality rate

8 Wilcox and Russell The Journal of Pediatrics January 1990

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Black + -- + -- +

~..

5 0 -

~, 30-

g0-

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Birthweight (kg)

Fig. I. Birth weight distributions and weight-specific fetal mor- tality curves (United States 1982). (Data from Vital statistics of the United States 1982; vols 1 and 2. Hyattsville, Md.: National Center for Health Statistics, 1986; DDHS publication Nos. [PHS187-1100 and [PHS]86-1122.)

for black infants is higher than for white (18.3 vs 11.3 per 1000). Thus the apparent superiority of small black infants disappears when a population-specific standard for small- ness is used.

The Table presents a special case of a more general situation. 13 Fig. 1 shows birth weight distributions for black and white infants in the United States. 9,10 Both are

approximately gaussian, with the mean weight of black ba- bies about 250 gm lower than that of white babies. The weight-specific mortality curves shown in the upper part of the figure are typical of all populations: the mortality rate is highest for the smallest babies, falls steadily as birth weight increases, and rises again at the heaviest birth

weights: The mortality curves for black and white infants intersect at 3250 gm. Black infants have the higher risk of death at each weight >3250 gin; at each weight <3250 gm, black infants have the lower risk. This result has been fre- quently observed and discussed, 12' ~4,15 but it remains

unexplained. The intersection of mortality curves may be an artifact of

the way we 10ok at the data. An alternative is suggested by Rooth's approach. Rooth 7 used standard deviations from the mean to identify one specific point on the birth weight distribution. By extension, we can treat all points of the dis- tribution in this way. This method converts birth weight to a standardized scale (the z score), with a mean of zero and

Table. Weight-specific fetal mortality rates for black infants and white infants (United States, 1982)

Fetal mortality rate (per I000 births)

Black White infants infants

For all births 11.8 6.4 At 2500 gm 8.4 10.6 At 2 SD less than 18.3" t 1.3~

population mean

Data from Vital statistics of the United States 1982; vols 1 and 2. Hyatts- Vitle, Md.: National Center for Health Statistics, 1986; DHHS publication Nos. (PHS)87-1100 and (PHS)86-1122. *At 2220 gin. "~At 2480 gm.

standard deviation of one) 6 The effect is to shift the black and white birth weight distributions so that their gaussian portions are aligned (Fig. 2).

When weight-specific mortality rates are plotted on this same scale, the mortality curves no longer intersect (Fig. 2). Black infants have a higher mortality rate at every rescaled birth weight. In effect, a black infant is consistently at higher risk than a white infant if the two have birth weights that deviate equally from the mean weight for their own race.

The principles discussed here are not specific to compar- isons of race. A standardized birth weight scale will sepa- rate intersecting mortality curves in many other compari- sons. For example, small infants of smokers have lower mortality rates than the small infants of nonsmokers, even though the infants of smokers have higher overall perinatal rates. 17 The introduction of a standardized birth weight scale resolves this paradox.

C O M M E N T

Rooth 7 proposed that LBW be defined by reference to the relevant distribution of birth weight. We have proposed a more general approach to the analysis of birth weight, based on the underlying gaussian distribution of birth weight.8, 11, 13 By using this approach, one can divide the

excess perinatal mortality rate of black infants (or any other group) into two parts. One part comes from the higher mortality rate at each birth weight; this may become apparent only after adjustment of birth weight in the way suggested above. The uniformly higher weight-specific mortality curve of black infants shown in Fig. 2 represents an increased risk that affects every black baby, regardless of weight.

The second part of the excess black mortality rate comes from the slight excess of small babies in the lower tail of the birth weight distribution. In all populations, there is a "re-

Volume 116 Population-specific standards for birth weight 9 Number 1

sidual distribution" of very small babies that remains when the "predominant" gaussian distribution is subtracted from

the whole distribution. 8 Virtually all of these small babies are preterm, and their haphazard distribution outside the gaussian distribution suggests that disorganized, perhaps pathologic, processes are at work. These residual births contribute a disproportionately large number of perinatal deaths, even though they make up only 2% to 7% of all births. In the previous example, 2.7% of white births were in the residual distribution, compared with 4.8% of black births. In our experience, the population with more residual births has the higher perinatal mortality rate.

Researchers have used both the proportion of births <2500 gm and the proportion <1500 gm (very low birth weight) (<1500 gin) as indicators of a population's peri- natal risk. The success with which such indicators predict a population's perinatal mortality rate depends on the de- gree to which residual births are identified. As Rooth 7 has shown, the proportion of birth weights <2500 gm is an er- ratic predictor of perinatal mortality rate; the reason is that the 2500 gm criterion mixes a varying portion of the gaus- sian distribution with the residual. Very low birth weight is a better criterion because it excludes virtually all births in the gaussian distribution; however, it misses a varying pro- portion of residual births of infants weighing >1500 gin.

Rooth's criterion 7 of 2 SD less than the mean is even bet- ter because it seeks to capture all residual births and a uni- form proportion of the gaussian distribution. Any difference between populations should then reflect a difference in their proportions of residual births. Although Rooth's approach is sound in principle, he estimates the standard deviation from the entire birth weight distribution. Such estimates are biased upward by the presence of the residual births. As a result, the proportion of the gaussian distribution captured by Rooth's criterion is still not uniform. More accurate methods for estimating the parameters of the underlying gaussian distribution are now available.* 18

We have shown that differences between populations in the gaussian portion of their birth weight distributions do not affect perinatal mortality rates. 13 This may be surpris-

ing because lower birth weight within a population is so strongly related to mortality rates. However, what is true within populations is not necessarily true between populations.a9 Girls have better perinatal survival rates de- spite the fact that they are smaller at birth than boys. In- fants of Asian descent born in the United States have lower perinatal mortality rates than white infants do, although the mean birth weight of Asian infants is less than that for white infants, z~ Black infants born in 1986 ha~t a lower mortality

*A FORTRAN computer software program for deriving popula- tion-specific standards from birth weight distributions is available from either author.

1000

' ~ IO0

o ~ 1o.

l Whit.e o .... o---- o I Black . . . . . [

0 - . k ~ _ _ �9

5 0 -

. 4-0- $

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0 _q

C - " a ~ - - I i - -"=2=- "l " ~ ): - 6 - 5 - 4 - 3 - 2 - - t 0 1 2 3 4-

Birthweight (standardized "z" score)

Fig. 2. Birth weight distributions and weight-specific fetal mor- tality curves, after conversion of birth weight to standardized z score (mean = 0; SD = 1) (United States, 1982). (Data from Vi- tal statistics of the United States 1982; vols 1 and 2. Hyattsville, Md.: National Center for Health Statistics, 1986; DHHS publica- tion Nos. [PHS]87-1100 and [PHS]86-1122).

rate than did white infants born 20 years earlier, 2~ even though the mean birth weight of black infants in 1986 was still much lower than that of white infants in 1966.

Population differences in the gaussian distribution of birth weight do not affect mortality rates; however, they do need to be taken into account in any analysis of the rela- tionship between birth weight and risk. We previously pro- posed a method of analysis that considers birth weight in relation to its underlying gaussian distribution.13 In this ar-

ticle, we have shown that population-specific standards for LBW, based on the gaussian distribution, resolve the well- known paradox that small black infants have a lower mor- tality rate than white infants of the same absolute weight. This finding provides further support for the use of popula- tion-specific birth weight standards when babies from dif- ferent populations are compared.

The JOURNAL reviewers provided useful suggestions for revision. The illustrations were generated by Dr. David R. McConnaughey.

R E F E R E N C E S

1. Ylpp5 A. Das Wachstum der Frfihgeborenen yon der Geburt bis zum Schulalter. Z Kinderhielkd 1919;24:111-78.

2. Dunham EC, Jenss RM, Christie AU. A consideration of race and sex in relation to the growthand development of infants. J PEDIATR 1939;14:156-60.

1 0 Wilcox and Russell The Journal of Pediatrics January 1990

3. Anderson NA, Brown EW, Lyon RA. Causes of prematurity. III. Influence of race and sex on duration of gestation and weight at birth. Am J Dis Child 1943;65:523-34.

4. Brown EW, Lyon RA, Anderson NA. Causes of prematurity. IV. Influence of maternal illness on the incidence of prematu- rity: employment of a new criterion of prematurity for the Ne- gro race. Am J Dis Child 1945;70:314-7.

5. Erhardt CL, Joshi GB, Nelson FG, et al. Influence of weight and gestation on perinatal and neonatal mortality by ethnic group. Am J Public Health 1964;54:1841-55.

6. Davies DP, Senior N, Cole G, et al. Size at birth of Asian and white Caucasian babies born in Leicester: implications for ob- stetric and pediatric practices. Early Hum Dev 1982;6:257-63.

7. Rooth G. Low birthweight revised. Lancet 1980;1:639-41. 8. Wilcox A J, Russell IT. Birthweight and perinatal mortality. I.

On the frequency distribution of birth weight, lnt J Epidemiol 1983;12:314-8.

9. Vital statistics of the United States 1982; vol 1. Hyattsville, Md.: National Center for Health Statistics, 1986; DHHS publication No. (PHS) 87-1100.

10. Vital statistics of the United States 1982; vol 2, part A. Hyattsville, Md.: National Center for Health Statistics, 1986; DHHS publication No. (PHS) 86-1122.

11. Wilcox A J, Russell IT. Birthweight and perinatal mortality. II. On weight-specific mortality. Int J Epidemiol 1983;12:319-25.

12. North AF Jr, MacDonald HM. Why are neonatal mortality rates lower in small black infants than in white infants in sim- ilar birth weight. J P~DIATR 1977;90:809-10.

13. Wilcox A J, Russell IT. Birthweight and perinatal mortality. III. Towards a new method of analysis. Int J Epidemiol 1986;15:188-96.

14. Binkin N J, Williams RL, Hogue C JR, Chen PM. Reducing black neonatal mortality: will improvement in birth weight be enough? JAMA 1985;235:373-5.

15. Alexander GR, Tompkins ME, Altekruse JM, Hornung CA. Racial differences in the relation of birth weight and gesta- tional age to neonatal mortality. Public Health Rep 1985;100;539-47.

16. Fryer JG, Hunt RG. Modeling the distribution of birthweight. WHO Report on Social and Biological Effects on Perinatal Mortality; vol 3. Bristol, England: University of Bristol Press (in press).

17. Meyer MB, Comstock GW. Maternal cigarette smoking and perinatal mortality. Am J Epidemiol 1972;96:1-10.

18. Russell D, Russell IT, Wilcox A J. A computer program to es- timate parameters of the birth weight distribution. Occasional Paper No. 4. Aberdeen, Scotland: Health Services Research Unit, 1989.

19. Susser M. Causal thinking in the health sciences: Concepts and strategies of epidemiology. New York: Oxford University Press, 1973:60-1.

20. Taffel S. Characteristics of Asian births: United States, 1980. Monthly Vital Statistics Report 1984;32(suppl.):l-16.

21. National Center for Health Statistics. Advance data of final mortality statistics, 1986. Monthly Vital Statistics Report 1988;37(suppl.):l-56.

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