Published online January 4, 2006
PEDIATRICS Vol. 117 No. 1 January 2006, pp. e106-e112 (doi:10.1542/peds.2005-1286)
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow P3Rs: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when P3Rs are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow E-mail this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My File Cabinet
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Morse, S. B.
Right arrow Articles by Roth, J.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Morse, S. B.
Right arrow Articles by Roth, J.
Related Collections
Right arrow Premature & Newborn

Racial and Gender Differences in the Viability of Extremely Low Birth Weight Infants: A Population-Based Study

Steven B. Morse, MD, MPHa, Samuel S. Wu, PhDb, Changxing Ma, PhDb, Mario Ariet, PhDc, Michael Resnick, EdDa and Jeffrey Roth, PhDa

a Departments of Pediatrics
b Statistics
c Medicine, College of Medicine, University of Florida, Gainesville, Florida


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
OBJECTIVE. The purpose of this study is to provide a race- and gender-specific model for predicting 1-year survival rates for extremely low birth weight (ELBW) infants by using population-based data.

METHODS. Birth and death certificates were analyzed for all children (N = 5076) with birth weights between 300 g and 1000 g who were born in Florida between 1996 and 2000. Semiparametric, multivariate, logistic regression analysis was used to model 1-year survival probabilities as a function of birth weight, gestational age, mother's race, and infant's gender. Estimated survival rates among different race/gender groups were compared by using odds ratios (ORs).

RESULTS. One-year survival rates for 5076 ELBW infants born between 1996 and 2000 did not change during the 5-year period (60–62%). The survival rate at ≤500 g was ≤14% (n = 716). Survival rates at 501 to 600 g and 601 to 700 g were 36% and 62%, respectively. The survival rate reached >85% for infants of >800 g. Modeling indicated a survival advantage for female infants, compared with male infants (OR: 1.7; 95% confidence interval: 1.5–1.9), and for black infants, compared with white infants (OR: 1.3; 95% confidence interval: 1.1–1.5). Black female infants had 2.1 greater odds of survival than did white male infants.

CONCLUSIONS. This population-based study highlights the significant race and gender differences in 1-year survival rates for ELBW infants, as well as the interactions of these 2 factors. These findings can assist obstetricians and neonatologists not only in the care of ELBW infants but also in frank discussions with families.

Key Words: birth weight-specific mortality rate • low birth weight infant • infant death

Abbreviations: ELBW—extremely low birth weight • OR—odds ratio • CI—confidence interval • SGA—small for gestational age

There are ~4 million births annually in the United States.1, 2 Among these births, extremely low birth weight (ELBW) infants remain <1% of the total. Ever-improving medical care and technologies have continued to lower the threshold at which survival is possible. However, the highest mortality and morbidity rates remain within this ELBW cohort.1, 3–6

There are few population-based studies of the survival of ELBW infants.1 Most reports of ELBW survival rates are based on data for individual institutions or voluntary networks of hospitals, which limits the generalizability of the results to other populations.3–6 Studies are consistent with respect to ELBW infants having the highest mortality risk of all birth weight groups and exhibiting the greatest proportions of morbidities in a wide range of areas, including behavior, cognition, mobility, and sensation.7–11 It is for this high-risk population of infants that it is most difficult for health care providers to feel confident regarding their medical decision-making. It is known that caregivers' perceptions of the likelihood of survival affect their treatment of premature infants.12, 13 Often this perception of survival likelihood is based on limited data, personal experiences, and internal beliefs.12–14 In addition, parental attitudes often differ significantly from those of physicians and nurses regarding treatment of extremely premature infants.15, 16 Although the general population is aware that there is a lower long-term, health-related quality of life for ELBW infants, individuals support life-saving treatment for all ELBW infants, with a role for parents in the decision-making process.16, 17

Delineating risk factors for death among ELBW infants is difficult because of limited samples sizes and the number of factors that must be considered. Both race and gender have been shown to be related significantly to both overall survival and survival without major morbidity rates.4–6, 18–23

Because medical decisions regarding treatment have major effects on both ELBW infants and their families, it is imperative that obstetricians and neonatologists consider the most recent and specific data regarding survival rates. The purpose of this study is to provide a race- and gender-specific model for predicting survival rates for ELBW infants.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study Sample
By using the Florida birth vital statistics database, all singleton live births between 1996 and 2000 were identified. From these 976824 records, 5663 infants were identified as having a birth weight between 300 g and 1000 g and a gestational age between 20 weeks and 35 weeks. Gestational age was determined from the date of the last menstrual period, as indicated on the birth certificate. If the last menstrual period was not available, then the clinical estimate of gestational age recorded on the birth certificate was used. Race was based on the maternal race designation on the birth certificate, and all records with either a white or black designation were included (N = 5532). Records were excluded if any of the following values necessary for analysis were missing: gestational age, birth weight, race, or gender. In addition, records with inconsistent birth weights and gestational ages were excluded. Inconsistent birth weight was defined as a birth weight that fell outside range of the gestational age-specific median weight ± 3 SDs. After exclusion of these 456 outliers, the final sample consisted of 5076 ELBW singleton infants. The sample was then stratified according to weekly gestational age and 100-g increments between 300 g and 1000 g (Table 1).


View this table:
[in this window]
[in a new window]
  		TABLE 1 Number of Florida Singleton Live-Born Infants Between 300 and 1000 g (1996–2000)

 
Among these 5076 ELBW infants, death certificate information was merged to identify any death occurring at ≤1 year. ELBW infant survival rates were calculated according to weekly gestational age and birth weight, in 100-g increments (Table 2).


View this table:
[in this window]
[in a new window]
  		TABLE 2 Gestational Age- and Birth Weight-Specific Survival Rates Among Florida Singleton Live-Born Infants (1996–2000)

 
Statistical Analyses
Semiparametric, multivariate, logistic regression analysis was used to model survival probability as a function of birth weight, gestational age, mother's race, and infant's gender.24, 25 This model eliminated the need for precise specification of the functional form of the model. Because the relationship between gestational age and birth weight is nonlinear, this model was a better choice than logistic or linear regression analysis.

Race- and gender-specific survival curves at designated gestational ages of 24, 26, and 28 weeks and birth weights of 500, 750, and 1000 g were created by using this model (Figs 1 and 2). Race- and gender-specific isomortality curves were also generated, allowing a continuum of birth weights and gestational ages to be viewed simultaneously (Fig 3). Odds ratios (ORs) and confidence intervals (CIs) were calculated to compare survival rates among different race and gender combinations (Table 3).


Figure 1
View larger version (18K):
[in this window]
[in a new window]
  		FIGURE 1 Infant survival probability according to gestational age at specific birth weights of 500 g (A), 750 g (B), and 1000 g (C). Survival probability is plotted for specific race and gender combinations. Declines in survival probabilities with advancing gestational age represent SGA effects (B and C).

 

Figure 2
View larger version (23K):
[in this window]
[in a new window]
  		FIGURE 2 Infant survival probability according to birth weight at specific gestational ages of 24 weeks (A), 26 weeks (B), and 28 weeks (C). Survival probability is plotted for specific race and gender combinations.

 

Figure 3
View larger version (20K):
[in this window]
[in a new window]
  		FIGURE 3 Isomortality contour plots of survival probability, in 10% increments, for specific race and gender combinations (A, black female; B, black male; C, white female; D, white male).

 

View this table:
[in this window]
[in a new window]
  		TABLE 3 Influence of Race and Gender on Survival Rates Among ELBW Infants (<1000 g)

 

   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Across the 5 years studied, each year contributed between 18% and 21% of the sample. Within the entire cohort of 5076 infants, 51% percent were male and 47% were black. Fifty-nine percent (n = 3011) of the ELBW cohort (500–1000 g) remained alive at 1 year of age. Survival rates did not vary significantly across the 5-year study period, ranging from 60% to 62%. Gestational ages in the specified weight range of 300 to 1000 g were between 20 weeks and 35 weeks (Table 1). The median birth weights at the earliest gestational ages of 22, 23, and 24 weeks were 482, 567, and 624 g, respectively, which is consistent with current fetal growth curves.26, 27 Among infants of <1000 g, the most frequent gestational ages were 24 to 27 weeks (Table 1).

The birth weight (in 100-g increments)- and gestational age-specific survival rates are shown in Table 2. As expected, the lowest survival rates were noted for the earliest gestational ages, with survival rates among infants of ≤22 weeks (n = 716) being at best 11%. At 23 weeks, the survival rate was 27%. Survival rates reached ≥85% once gestational ages reached 28 weeks. Because of the truncation of data at 1000 g, the survival rates at the later gestational ages of 30 to 35 weeks represent survival rates among small-for-gestational age (SGA) infants. Within all gestational age groups, survival rates increased as weight increased.

With the use of semiparametric logistic regression models, survival rates at designated birth weights of 500, 750, and 1000 g were generated for all 4 gender and race combinations (Fig 1). At any given birth weight, black female infants had the greatest survival advantage and white male infants had the lowest survival rate. Across all gestational ages for a given birth weight, female infants survived at a higher rate than did male infants, and black infants survived at a higher rate than did white infants. The largest survival differences were observed at the lowest gestational ages.

To isolate the effect of birth weight on survival rates, gestational age-specific predicted survival curves were generated for all race and gender combinations at 24, 26, and 28 weeks (Fig 2). Predicted survival rates improved for all race/gender groups as birth weight increased. As gestational age increased, the range of predicted survival rates narrowed. As in previously published reports, the deleterious effect of birth weights in the SGA range was demonstrated in all 3 curves.28 As birth weights declined below commonly accepted SGA weights for all 3 gestational age-specific curves, survival rates decreased.26, 27

In addition to the SGA effect on survival rates, the effects of race and gender were apparent in these curves. Female survival rates were higher than male survival rates in all 3 gestational age curves and across the entire range of birth weights. Black survival rates were always higher than white survival rates. In addition, the effect of female gender on survival rates seemed larger than the effect of black race. Both race and gender effects became more distinct at lower weights and gestational ages.

To illustrate more clearly the effects of race and gender across a continuum of gestational ages and birth weights, isomortality contour plots were constructed (Fig 3). These plots provided survival estimates in 10% increments for all plausible birth weight and gestational age combinations. As expected, as weight and gestational age increased, survival rates also increased. The effects on survival rates of additional maturity and weight were greater at gestational ages of <27 weeks and birth weights of <700 g for all 4 plots. Survival rates were higher for female and black infants at all gestational age and birth weight combinations.

To quantify the differences in survival rates among the various race/gender groups shown graphically in Figs 1 and 2, ORs with 95% CIs were computed on the basis of predicted survival rates, with the semiparametric model (Table 3). Overall, the odds of survival for black ELBW infants were 1.3 times (95% CI: 1.1–1.5) those for white ELBW infants. The odds of survival for female infants were 1.7 times (95% CI: 1.5–1.9) those for male infants. Combining race and gender, the largest advantage was seen among black female infants, compared with white male infants, with a 2.1 (95% CI: 1.7–2.6) increased odds of survival. Although white infants in general had lower survival rates than did black infants, black male survival rates were lower than white female rates, with an OR of 0.8 (95% CI: 0.6–0.9).


   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
There are several published reports of survival rates among ELBW infants.3–5 However, those reports did not distinguish survival rates according to both race and gender. In addition, small sample sizes and single-institution data limited the utility of those reports. We present easy-to-use, up-to-date, race- and gender-specific, survival estimates for infants born at <1000 g. These survival probabilities are based on a large, population-based sample of >5000 infants in a recent period (1996–2000).

With >1500 infants at <24 weeks of gestation, we were able to provide survival estimates at the extreme limit of prematurity. The survival rate remained quite poor among infants at ≤22 weeks (survival rate: 11%). Even at 23 weeks, the survival rate was only 27%. With an extremely high risk of severe morbidities, resuscitation of these infants remains highly controversial.29, 30 However, survival rates did show improvement even at these early gestational ages as birth weights increased above the median birth weight for the gestational age, which should be considered in decisions regarding treatment.

The issue of black race conferring a survival advantage among premature infants has been debated. Some studies showed a distinct advantage,5, 21 whereas other studies found no significant difference.20, 31, 32 We found that black race conferred a significant survival advantage at 1 year of age across all gestational ages among ELBW infants. The steepest part of the survival curves in Figs 2 and 3 occurred among the lower birth weights and gestational ages, indicating increasing advantage of black race as the degree of prematurity increases. In addition, the OR for black versus white survival was 1.3 (95% CI: 1.1–1.5), favoring black race. Our results suggest that race plays an important role in estimates of survival rates and therefore may affect treatment decisions.

Female gender increased the odds of survival regardless of race (OR: 1.7; 95% CI: 1.5–2.0), with both black and white female infants having higher survival rates than black and white male infants. This result is consistent with other studies that demonstrated a female survival advantage.4–6, 19, 23 In a study by La Pine et al,6 the female survival rate was 20% higher than the male survival rate among infants born at <800 g. Using our isomortality contour graphs and comparing within-race survival rates between male and female infants, we also found survival advantages of 10% to 20% for female infants.

With similarity to other studies, we found that the greatest weekly improvements in survival rates occurred between 25 and 28 weeks of gestation and between 600 and 800 g.5, 33 After 28 weeks, survival rates approached 90% and less difference in survival rates among race/gender groups was seen. In addition, we found little change in survival rates for ELBW infants during the latter half of the 1990s.34

Limitations of this study centered on the use of merged birth and death certificate data. On the basis of matched birth and death certificates, it is not possible to distinguish the type of treatment received at the earliest gestational ages. Some infants at ≤24 weeks might have received comfort care alone, whereas others might have been treated more aggressively. If infants who received comfort care only could have been excluded, then the estimates of survival rates at ≤24 weeks and ≤500 g would have been higher than those reported here. Admittedly, survival data alone do not provide enough information for caregivers to decide on initiation or continuation of treatment. We intend to extend this research to include the significant morbidities associated with delivery at <1000 g.

This study does provide survival estimates from population-based data. This allows for a large sample size for rare events such as delivery at ≤24 weeks of gestation. In addition, the sample represents a heterogeneous group of ELBW infants delivered in multiple settings, which allows the results to be more generalizable than results based on data from individual institutions.

This study highlights the significant differences in survival rates between male and female infants and between black and white infants, as well as the interactions of these 2 factors. Obstetricians will continue to face difficult decisions regarding the care of mothers in preterm labor at very early gestational ages, and neonatologists will continue to struggle with decisions regarding the initiation and withdrawal of care for extremely premature infants. The data presented here are intended to assist both groups not only in management but also in frank discussions with families.


   ACKNOWLEDGMENTS
 
This work was supported by Children's Medical Services, Florida Department of Health, and Maternal Child Health and Education Research and Data Center, University of Florida.

We thank the following professionals whose cooperation and expertise facilitated completion of this study: Meade Grigg, Florida Department of Health; Randy Carter, University at Buffalo, State University of New York; and Waldemar Carlo, University of Alabama, Birmingham.


   FOOTNOTES
 
Accepted Jul 19, 2005.

Address correspondence to Steven B. Morse, MD, MPH, Department of Pediatrics, University of Florida, PO Box 100296, Gainesville, FL 32610-0296. E-mail: morsesb{at}peds.ufl.edu


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Martin JA, Kochanek KD, Strobino DM, Guyer B, MacDorman MF. Annual summary of vital statistics: 2003. Pediatrics. 2005;115 :619 –634[Abstract/Free Full Text]
  2. MacDorman MF, Minino AM, Strobino DM, Guyer B. Annual summary of vital statistics: 2001. Pediatrics. 2002;110 :1037 –1052[Abstract/Free Full Text]
  3. Lemons JA, Bauer CR, Oh W, et al. Very low birth weight outcomes of the National Institute of Child Health and Human Development Neonatal Research Network, January 1995 through December 1996. Pediatrics. 2001;107 (1). Available at: www.pediatrics.org/cgi/content/full/107/1/e1
  4. Allen MC, Donohue PK, Dusman AE. The limit of viability: neonatal outcome of infants born at 22 to 25 weeks' gestation. N Engl J Med. 1993;329 :1597 –1601[Abstract/Free Full Text]
  5. Copper RL, Goldenberg RL, Creasy RK, et al. A multicenter study of preterm birth weight and gestational age-specific neonatal mortality. Am J Obstet Gynecol. 1993;168 :78 –84[ISI][Medline]
  6. La Pine TR, Jackson JC, Bennet FC. Outcome of infants weighing less than 800 grams at birth: 15 years' experience. Pediatrics. 1995;96 :479 –483[Abstract/Free Full Text]
  7. Schmidt B, Asztalos EV, Roberts RS, Robertson CM, Suave RS, Whitfield MF. Impact of bronchopulmonary dysplasia, brain injury, and severe retinopathy on the outcome of extremely low-birth-weight infants at 18 months: results from the trial of indomethacin prophylaxis in preterms. JAMA. 2003;289 :1124 –1129[Abstract/Free Full Text]
  8. Hille ET, den Ouden AL, Saigal S, et al. Behavioral problems in children who weigh 1000 g or less at birth in four countries. Lancet. 2001;357 :1641 –1643[CrossRef][ISI][Medline]
  9. Piecuch RE, Leonard CH, Cooper BA, Sehring SA. Outcome of extremely low birth weight infants (500 to 999 grams) over a 12-year period. Pediatrics. 1997;100 :633 –639[Abstract/Free Full Text]
  10. Saigal S, Rosenbaum P, Stoskopf B, et al. Comprehensive assessment of the health status of extremely low birth weight children at eight years of age: comparison with a reference group. J Pediatr. 1994;125 :411 –417[CrossRef][ISI][Medline]
  11. Whitfield MF, Grunau RV, Holsti L. Extremely premature (≤800 g) schoolchildren: multiple areas of hidden disability. Arch Dis Child. 1997;77 :F85 –F90
  12. Morse SB, Haywood JL, Goldenberg RL, Bronstein J, Nelson KG, Carlo WA. Estimation of neonatal outcome and perinatal therapy. Pediatrics. 2000;105 :1046 –1050[Abstract/Free Full Text]
  13. Haywood JL, Morse SB, Goldenberg RL, Bronstein J, Nelson KG, Carlo WA. Estimation of outcome and restriction of interventions in neonates. Pediatrics. 1998;102 (2). Available at: www.pediatrics.org/cgi/content/full/102/2/e20
  14. Haywood JL, Goldenberg RL, Bronstein J, Nelson KG, Carlo WA. Comparison of perceived and actual rates of survival and freedom from handicap in premature infants. Am J Obstet Gynecol. 1994;171 :432 –439[ISI][Medline]
  15. Streiner DL, Saigal S, Burrows E, Stoskopf B, Rosenbaum P. Attitudes of parents and health care professionals toward active treatment of extremely premature infants. Pediatrics. 2001;108 :152 –157[Abstract/Free Full Text]
  16. Saigal S, Burrows E, Stoskopf BL, Rosenbaum PL, Streiner D. Impact of extreme prematurity on families of adolescent children. J Pediatr. 2000;137 :701 –706[CrossRef][ISI][Medline]
  17. Saigal S, Feeny D, Furlong W, Rosenbaum P, Burrows E, Torrance G. Comparison of the health-related quality of life of extremely low birth weight children and a reference group of children at age eight years. J Pediatr. 1994;125 :418 –425[CrossRef][ISI][Medline]
  18. Bacak SJ, Baptiste-Roberts K, Amon E, Ireland B, Leet T. Risk factors for neonatal mortality among extremely-low-birth-weight infants. Am J Obstet Gynecol. 2005;192 :862 –867[CrossRef][ISI][Medline]
  19. Shankaran S, Fanaroff AA, Wright LL, et al. Risk factors for early death among extremely low-birth-weight infants. Am J Obstet Gynecol. 2002;186 :796 –802[CrossRef][ISI][Medline]
  20. Allen MC, Alexander GR, Tompkins ME, Hulsey TC. Racial differences in temporal changes in newborn viability and survival by gestational age. Paediatr Perinat Epidemiol. 2000;14 :152 –158[CrossRef][ISI][Medline]
  21. Alexander GR, Kogan M, Bader D, Carlo W, Allen M, Mor J. US birth weight/gestational age-specific neonatal mortality: 1995–1997 rates for whites, Hispanics, and blacks. Pediatrics. 2003;111(1) . Available at: www.pediatrics.org/cgi/content/full/111/1/e61
  22. Demissie K, Rhoads GG, Ananth CV, et al. Trends in preterm birth and neonatal mortality among blacks and whites in the United States from 1989 to 1997. Am J Epidemiol. 2001;154 :307 –315[Abstract/Free Full Text]
  23. Stevenson DK, Verter J, Fanaroff AA, et al. Sex differences in outcomes of very low birthweight infants: the newborn male disadvantage. Arch Dis Child Fetal Neonatal Ed. 2000;83 :F182–F185
  24. Herman AA, Hastie TJ. An analysis of gestational age, neonatal size and neonatal death using nonparamentric logistic regression. J Clin Epidemiol. 1990;45 :1179 –1190
  25. Hastie TJ, Tibshirani RJ. Generalized Additive Models. London, United Kingdom: Chapman & Hall; 1990
  26. Alexander GR, Himes JH, Kaufman RB, Mor J, Kogan M. A United States national reference for fetal growth. Obstet Gynecol. 1996;87 :163 –168[Abstract]
  27. Fenton TR. A new growth chart for preterm babies: Babson and Benda's chart updated with recent data and a new format. BMC Pediatr. 2003;3 :13 –23[CrossRef][Medline]
  28. Regev RH, Lusky A, Dolfin T, Litmanovitz I, Arnon S, Reichman B. Excess mortality and morbidity among small-for-gestational-age premature infants: a population-based study. J Pediatr. 2003;143 :186 –191[CrossRef][ISI][Medline]
  29. Hernandez JA, Offutt J, Butterfield LJ. The cost of care of the less-than-1000-gram infant. Clin Perinatol. 1986;13 :461 –476[ISI][Medline]
  30. Catlin AJ. Physicians' neonatal resuscitation of extremely low-birth-weight preterm infants. Neonatal Netw. 2000;19 :25 –32[Medline]
  31. Petrova A, Mehta R, Anwar M, Hiatt M, Heygi T. Impact of race and ethnicity on the outcome of preterm infants below 32 weeks gestation. J Perinatol. 2003;23 :404 –408[CrossRef][Medline]
  32. Greenberg DN, Yoder BA, Clark RH, Butzin CA, Null DM. Effect of maternal race on outcome of preterm infants in the military. Pediatrics. 1993;91 :572 –577[Abstract/Free Full Text]
  33. Goldenberg RL, Nelson KG, Davis RO, Koski J. Delay in delivery: influence of gestational age and the duration of delay on perinatal outcome. Obstet Gynecol. 1984;64 :480 –484[Abstract/Free Full Text]
  34. Horbar JD, Badger GJ, Carpenter JH, et al. Trends in mortality and morbidity for very low birth weight infants, 1991–1999. Pediatrics. 2002;110 :143 –151[Abstract/Free Full Text]
PEDIATRICS (ISSN 1098-4275). ©2006 by the American Academy of Pediatrics



This article has been cited by other articles:


Home page
 Am. J. Physiol. Regul. Integr. Comp. Physiol.Home page
L. Bennet, L. C. Booth, N. Ahmed-Nasef, J. M. Dean, J. Davidson, J. S. Quaedackers, and A. J. Gunn
Male disadvantage? Fetal sex and cardiovascular responses to asphyxia in preterm fetal sheep
Am J Physiol Regulatory Integrative Comp Physiol, September 1, 2007; 293(3): R1280 - R1286.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow P3Rs: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when P3Rs are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow E-mail this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My File Cabinet
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Morse, S. B.
Right arrow Articles by Roth, J.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Morse, S. B.
Right arrow Articles by Roth, J.
Related Collections
Right arrow Premature & Newborn