Birth Weight and School-age Disabilities: A Population-based Study

Rachel Nonkin Avchen, Keith G. Scott and Craig A. Mason

From the Department of Psychology, University of Miami, Coral Gables, FL.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Mortality rates have declined for low birth weight and extremely low birth weight infants. Yet, the consequences of survival for these children may be adverse developmental outcomes. Few studies to date have examined school-age outcomes for these children. The participants in this study represented a population-based cohort of Florida children who were born between 1982 and 1984 and who were receiving a public school education in 1996–1997. Linkage methodology was used to establish a cohort of 267,213 children aged 12–15 years with both birth certificate and school records. Birth weights were stratified into 500-g increments beginning with <=999 g; 17% of the population had some school-identified disability. Risk ratios for specified school-identified disabilities increased as birth weight decreased for all birth weight strata of <=3,499 g. Narrow increments of birth weights may better portray a more accurate estimate of risk for infants born at extremes than the conventional definition of <2,500 g.

child; disabled children; infant; infant, low birth weight; morbidity

Abbreviations: CI, confidence interval; SD, standard deviation


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Advancements in medical technology allow many more infants born at extreme birth weights to survive today than in the recent past. Since 1949, the neonatal mortality rate has steadily declined (1Go). In Florida, the neonatal mortality rate decreased over the last two decades, from 9.93/1,000 in 1979 to 4.65/1,000 in 1997. The infant mortality rate was also reduced by about 48 percent during that time period (2Go). Reduction in infant mortality was associated with an increased survival of infants in the lowest tail of the birth weight distribution (1Go).

While mortality rates declined for low birth weight infants, the consequences of survival for these children may be associated with adverse developmental outcomes. Few studies to date examined school-age outcomes for these children. The most frequent age of follow-up was between 3 and 5 years (3GoGo–5Go). Yet, only 29 percent of children with special needs were identified before 5 years of age (6Go). Instead, identification of special education needs and placements tended to increase through middle childhood (7Go). Learning disability was not typically identified before third grade, and many other disabilities related to academic performance were not detected until a child was even older (8Go).

Inconsistency regarding diagnostic criteria of disabilities has made it difficult to operationalize study variables and generalize findings across the literature. In a meta-analysis of 80 low birth weight studies, Aylward et al. (5Go) reported inconsistent use of the terms "impairment," "disability," and "handicap." The utilization of Florida school records in the current study presented a unique opportunity to examine disabilities defined by standardized criteria. All identified exceptionalities, irrespective of Florida locale, conform to a detailed manual of standards that stipulates the standardized psychometric instruments allowed and cutoff scores used to determine primary exceptionality diagnoses.

Previous low birth weight studies also limited the generalizability of results because of inadequate samples. Aylward et al. (5Go) found that only 3 percent of the studies they reviewed were population based, whereas Escobar et al. (4Go) found that 13 percent of 111 reviewed studies reflected regional samples of low birth weight. The majority of low birth weight studies have consisted of small hospital-based samples.

Further, most studies to date examine low birth weight using the definition adopted by the World Health Organization in 1950 of less than 2,500 g (9Go). With the survival of infants at even smaller birth weights, conventional definitions of very low birth weight (<1,500 g) and extremely low birth weight (<1,000 g) are also common delineations within the literature. Yet, these cutpoints may misrepresent risk associated with varying degrees of birth weights.

The current paper addressed some of the common limitations enumerated in the low birth weight literature. The methodology used in this study allowed for a large, well-defined, population-based sample of children to be studied. A longitudinal assessment of the risk associated with varying birth weights and later special education placements was conducted from a population of Florida-born children who attended Florida public schools between the ages of 12 and15 years.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Study population and procedure
The participants in this study represented a population-based cohort of children who were born and educated in Florida. Two extant databases were utilized for this study. The Florida Department of Health furnished statewide birth certificate data for 449,606 deliveries from January 1, 1982, through December 31, 1984. The Florida Department of Education provided 2,527,338 public school records for the 1996–1997 academic year.

Unique records from each database were linked using deterministic matching techniques to create one logical record (10Go). Criteria for linkage were based on an exact match of last name, first name, date of birth, and gender. It was not possible to establish an exact match criterion for ethnicity because of differential coding between the databases. However, improbable discrepancies on ethnicity precluded a record from being linked. Infants with recorded death certificate records (n = 5,295) were removed from the birth certificate records prior to linkage.

The linked data set resulted in 267,277 cases of children aged 12–15 years. The linked cases represent a population-based sample of children who were both born in the state of Florida between 1982 and 1984 and receiving a public school education in the 1996–1997 academic year. Sixty-four of the linked cases did not have birth weight data and were excluded from this study. Fifty-one percent of the participants were male. Twenty-seven percent of the children had mothers with less than 12 years of education, 44 percent had mothers with exactly 12 years of education, and 29 percent had mothers with more than 12 years of education. Ethnicity is reported using the nomenclature from the birth certificate records. Approximately 70 percent of the children were White; 29 percent, Black; and 1 percent, other (i.e., Indian, Chinese, Japanese, Hawaiian, Filipino, other non-White, other Asian/Pacific Islander, unknown). Florida birth records do not enumerate a separate category for Hispanics. Previous studies suggest that this is a representative sample of this population with both a sensitivity and specificity of 0.97 (10Go).

The unlinked sample consisted of nonnative Floridians, privately schooled children, deceased children, and/or transient children. Given the extremely large sample size, analyses comparing unlinked children with linked children showed a number of small, yet statistically significant, differences. The birth records indicated that unlinked children had mothers with higher education levels (mean = 12.9 years for unlinked and mean = 12.2 years for linked, t test (460,346 cases) = 36.129, p < 0.001) and were more likely to be White (82.0 percent unlinked vs. 71.3 percent linked, {chi}21df = 6,585.574, p < 0.001). This probably reflects higher levels of out-of-state mobility and higher rates of private school placement among higher socioeconomic families.

In contrast, data from the school records suggested differences due to immigration patterns. Unlinked children were disproportionately Hispanic and Asian (22.7 percent and 3.1 percent, respectively, of the unlinked, 9.0 percent and 0.7 percent, respectively, of the linked, {chi}25df = 28,485, p < 0.001). In addition, unlinked children in the school records were less likely to have a school-identified exceptionality than were linked children (18.7 percent unlinked vs. 23.8 percent linked, {chi}21df = 2,182, p < 0.001). This probably reflects greater geographic stability for families with exceptional children, as well as lower rates of exceptionality placements among recent immigrants.

Statistical analyses
This study had a historical, prospective cohort design. Prospective cohort studies allow for the subject's history of exposure to be documented by utilizing relative risk ratios. These ratios allow the probability of school-identified disabilities to be measured when one rather than another birth weight stratum is attained. Primary school-identified disabilities were established in the exceptionality table of the Florida school records (table 1). The term "disability" was used to indicate the exclusion of normal achievers or children with an identified exceptionality of gifted in the risk group. Birth weights were stratified into 500-g increments beginning with <=999 g.


View this table:
[in this window]
[in a new window]
 
TABLE 1. Number of exceptionality cases within a birth weight stratum for children born in Florida from 1982 to 1984 who attended Florida public schools in 1996–1997

 
In the aggregated analyses, the risk ratios indicate the likelihood of developing a specified school-identified disability for a given birth weight stratum relative to those who are born with a birth weight between 3,500 and 3,999 g. The 3,500- to 3,999-g stratum represents the birth weight group with the smallest rate of disability per 1,000 cases (11Go).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Descriptive analyses
Descriptive analyses of the birth weight strata revealed an almost orderly relation between birth weight and special education categories. The disability rate declined as birth weight increased from 449/1,000 births for infants born at <=999 g compared with 146/1,000 births for children born at 3,500–3,999 g. The rate of disability increased slightly at the tail end of the birth weight strata, and infants born at >=5,000 g had a disability rate of 187/1,000 births.

The lightest born infants (<=999 g) accounted for only 0.2 percent of the population, but 44.9 percent of these children had some identified disability, unlike the heaviest born infants (>=5,000 g) who also made up about 0.2 percent of the population but accounted for only 18.7 percent of the children with disabilities. The greatest percentage of infants, 37.5 percent, weighed between 3,000 and 3,499 g, and 15.9 percent of these children subsequently had some disability. The smallest prevalence of disability, 14.6 percent, was seen in infants with birth weights between 3,500 and 3,999 g. On the other hand, when just children with disabilities were examined, infants born at less than 999 g accounted for only 0.6 percent; almost 90.0 percent of the children with disabilities had a birth weight of 2,500 g or more.

The overall prevalence of school-identified disabilities in this population was 16.6 percent (44,286 children; table 1). Of children with a disability, 56.3 percent were identified as having a specific learning disability, 15.1 percent as emotionally handicapped/severely emotionally disturbed, 10.8 percent as speech impaired/language impaired, 9.7 percent as educable mentally handicapped, 2.8 percent as trainable mentally handicapped/profoundly mentally handicapped, and 1.4 percent as orthopedically impaired. The other 4.0 percent of children were identified with less frequent disabilities, such as visual impairment and hard of hearing.

Regardless of birth weight, specific learning disability was the most commonly identified disability. For children born at <=2,499 g, the second most frequently identified disability was educable mentally handicapped, while emotionally handicapped/severely emotionally disturbed was the second most frequently identified disability for children born at >=2,500 g. There was much more variability for the third highest ranking disability by birth weight.

Risk ratio analyses
These analyses were conducted using Epi Info 6 (12Go). Ten mutually exclusive birth weight groups were defined. Risk ratios for children with a school-identified disability of orthopedically impaired, trainable mentally handicapped/profoundly mentally handicapped, educable mentally handicapped, speech impaired/language impaired, and other increased as birth weight decreased for all birth weight strata of <=3,499 g. Infants weighing <=999 g at birth were 22.05 (95 percent confidence interval (CI): 15.50, 31.37) times more likely than the referent group to be identified as trainable mentally handicapped/profoundly mentally handicapped. Table 2 contains risk ratios and 95 percent confidence intervals for each birth weight stratum and its associated school-identified disability.


View this table:
[in this window]
[in a new window]
 
TABLE 2. Risk ratios of identified school disabilities for a population of children born in Florida from 1982 to 1984 who attended Florida public schools in 1996–1997

 
Disability categories were combined into two groups based upon prevalence and further examined. One group included specific learning disability, emotionally handicapped/severely emotionally disturbed, and speech impaired/language impaired disabilities, and the other group combined educable, trainable, and profound mentally handicapped and orthopedically impaired disabilities. The latter group was at higher risk for disability than was the former group for all birth weight intervals except for infants born at 4,000–4,999 g. The pattern of risk for the latter group also showed that the lightest born infants had the greatest risk for an identified disability and, as birth weight increased, the risk of disability decreased (figure 1).



View larger version (18K):
[in this window]
[in a new window]
 
FIGURE 1. Risk ratios for disability categories by birth weight for children born in Florida from 1982 to 1984 who attended Florida public schools in 1996–1997. Disability categories are aggregated to reflect birth weight influence. EMH, educable mentally handicapped; TMH/PMH, trainable mentally handicapped/profoundly mentally handicapped; OI, orthopedically impaired; SI/LI, speech impaired/language impaired; EH/SED, emotionally handicapped/severely emotionally disturbed; SLD, specific learning disability.

 
Analyses by ethnicity
Overall, the mean birth weight was 3,331 (standard deviation (SD), 574) g. Black infants had a smaller mean birth weight of 3,155 (SD, 577) g than did White infants who averaged 3,404 (SD, 558) g at birth. Approximately 21.3 percent of the Black infants and 14.7 percent of the White infants had some school-identified disability.

An extremely large sample is necessary to evaluate individual disabilities by small birth weight increments and ethnicity. Cell sizes were inadequate when the current data were broken down in this manner. Thus, disabilities were collapsed into one category to estimate the rate and risk of disability within an ethnic group for a particular stratum of birth weight. Black children had higher rates of disability than did White children overall and within specific birth weight categories.

Results for the referent group were consistent with those of previous analyses for the White group but shifted to 4,500–4,999 g for Black infants. Regardless of ethnicity, there was a similar pattern of risk for disability by birth weight. As in the previous analyses, the lightest born infants were at the greatest risk of having a disability and, as birth weight increased, the risk of disability decreased. Black infants at <=999 g had a risk ratio of 2.83 (95 percent CI: 2.27, 3.52). White infants at <=999 g were 3.13 (95 percent CI: 2.7, 3.62) times as likely as the referent to have a school-identified disability. Again, there was a slight increase in risk at the heaviest birth weight stratum, >=5,000 g; Black infants had a risk ratio of 1.77 (95 percent CI: 1.22, 2.58) and White infants had a risk ratio of 1.22 (95 percent CI: 0.9, 1.51).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Smaller increments of birth weight strata better estimate risk for later developmental disabilities. To illustrate this point, risk ratios for the current study population were recalculated with the two classifications commonly used in birth weight research: 1) very low birth weight (<1,500 g), low birth weight (1,500–2,500 g), and normal/referent birth weight (>2,500 g) and 2) extremely low birth weight (<1,000 g), very low birth weight, low birth weight, and normal/referent birth weight (table 3). When the former classification is used, the risk of very low birth weight infants being identified as trainable mentally handicapped/profoundly mentally handicapped is 10.41 (95 percent CI: 8.40, 12.91) compared with a risk of 8.57 (95 percent CI: 6.53, 11.25) when the latter categories are used. The pattern of risk is more clear when calculations are based on 500-g increments; infants born at <999 g are 22.05 (95 percent CI: 15.50, 31.37) times more likely than the referent group (born at 3,500–3,999 g) to be identified as trainable mentally handicapped/profoundly mentally handicapped. Kiley and Paneth (13Go) even suggest that 250-g increments may best reflect developmental consequences.


View this table:
[in this window]
[in a new window]
 
TABLE 3. Comparison of risk ratios of identified school disabilities using different birth weight cutpoints for a population of children born in Florida from 1982 to 1984 who attended Florida public schools in 1996–1997

 
In multiethnic samples, it may also be inappropriate to accept a standard based upon a population of European origin (1Go). The idea that arbitrary cutpoints accurately reflect homogenous groups of infants is probably misleading. Fundamental differences between cultures exist. Numerous studies indicate that Black infants are twice as likely as White infants to be born at low birth weight (14GoGo–16Go). In this study, Black infants were approximately three times more likely than White infants to be <=999 g at birth and two times more likely to be 2,000–2,499 g at birth. Yet, even though the rate of disability is higher among the Black children, the pattern of risk was similar for both ethnic groups, suggesting that birth weight may be an independent predictor of later developmental disabilities. Further research is needed to investigate the influence of other measures of socioeconomic status, such as maternal age and education.

From a policy perspective, analyses based upon broad birth weight groups are best utilized as crude indicators of outcomes. Narrow increments of birth weight portray a more accurate estimate of risk, and when possible, further delineation by ethnicity and perhaps other socioeconomic factors will reflect the most precise approximation of outcome for a given child. Irrespective of the actual estimate of risk, it is clear that the pattern of weight-specific infant morbidity is similar to documented trends in weight-specific infant mortality. Lighter born infants are at a greater risk of dying than are heavier born infants, and if they do survive, they are at a greater risk of later developmental disabilities than are heavier born infants. Further, the risk of mental and motor disabilities appears to be greater than the risk of learning, speech, and behavior disabilities. Although birth weight is a good indicator in general of developmental delays, small birth weight (and possible neonatal complications that often result from low birth weight) may best predict the risk of delays in cognitive and motor development. It is also interesting to note, however, that extremely heavy birth weight infants, those born at >=5,000 g, may also be at an increased risk of orthopedic delays.

There is no conventional age at which assessment of disabilities is evaluated. Yet, the very nature of long-term assessment requires time to elapse. By linking extant databases that represent cross-sectional points in time, an almost instantaneous sample is available while avoiding drawbacks associated with traditional longitudinal studies such as subject attrition, time delay, and cost. Linking large data sets also typically yields a large sample or population that can be easily, specifically, and accurately defined. The initial linkage also facilitates continued surveillance.

This study represents results from a population of Florida-born children who attended Florida public schools between the ages of 12 and 15 years. It excludes nonnative Floridians, privately schooled children, deceased children, and transient children. The subset of children with disabilities in this study population is similar to the New York City special education population studied by Andrews et al. (8Go). Andrews et al. implemented a similar methodology to study special education risk, and the main categories of disability (learning disability, 51.9 percent; emotional disorder, 14.4 percent; and mental retardation, 3.1 percent) are comparable with the current special education population (specific learning disability, emotionally handicapped/severely emotionally disturbed, trainable mentally handicapped/profoundly mentally handicapped). Likewise, the two populations are similar on the child-related factors enumerated by Andrews et al. Within the special education group, Andrews et al. found that 67.1 percent of the children were male, 13.1 percent had birth weights of <2,501 g, and 3.9 percent had an Apgar score of less than eight compared with the Florida special education population that had 69.1 percent, 10.5 percent, and 4.6 percent, respectively.

Establishing a clear definition of the population/sample allows study results to be scrupulously generalized. Although the populations are similar in the previously mentioned studies, the analyses are very different. The results from Andrews et al. (8Go) suggest that risk profiles and cumulative hazard curves best predict special education placement. The current study suggests that the birth weight risk of identified school disabilities is more accurately analyzed in smaller increments, and that low birth weight infants are at a greater risk of disability than are heavier born infants. Together, studies utilizing similar samples can be collectively interpreted to make a greater contribution to the field as a whole.

It may be especially useful to have a clearly defined population/sample when studying outcomes related to birth weight. A clearly defined population/sample eliminates generalization of results between cohorts that may have experienced differences in medical treatments. By the time long-term consequences of one cohort can be meaningfully evaluated, changes in medical care may influence later developmental outcomes (17Go).

Few population-based, epidemiologic studies on the developmental outcomes of infants of various birth weight strata are currently available. Utilization of existing databases, like those in this study, allows researchers to plan, develop, manage, and/or evaluate risk factors that can contribute to the prevention, intervention, and/or control of adverse health events. Birth weight is one of the first indicators of later developmental risk, and it is a primary variable documented on all birth certificate records. Screening infants at birth could be a viable option for early identification of infants at risk for special education. For these reasons, subsequent population-based surveillance of developmental outcomes is needed.


    ACKNOWLEDGMENTS
 
This research was supported by the Florida Diagnostic & Learning Resources System (FDLRS), Florida Department of Health, and the Florida Department of Education, Bureau of Instructional Support and Community Services.


    NOTES
 
Reprint requests to Dr. Keith G. Scott, Department of Psychology, University of Miami, P.O. Box 249229, Coral Gables, FL 33124-0721 (e-mail: kscott{at}child.psy.miami.edu).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Paneth NS. The problem of low birth weight. Future Child 1995;5:19–34.[ISI][Medline]
  2. CDC WONDER. Centers for Disease Control and Prevention (Atlanta, GA), 2000. (http://wonder.cdc.gov/).
  3. Lee K, Kim B, Khoshnood B, et al. Outcome of very low birth weight infants in industrialized countries: 1947–1987. Am J Epidemiol 1995;141:1188–93.[Abstract]
  4. Escobar GJ, Littenberg B, Petitti DB. Outcome among surviving very low birthweight infants: a meta-analysis. Arch Dis Child 1991;66:204–11.[Abstract]
  5. Aylward GP, Pfeiffer SI, Wright A, et al. Outcome studies of low birth weight infants published in the last decade: a metaanalysis. J Pediatr 1989;115:515–20.[ISI][Medline]
  6. Palfrey JS, Singer JD, Walker DK, et al. Early identification of children's special needs: a study in five metropolitan communities. J Pediatr 1987;111:651–9.[ISI][Medline]
  7. Scott KG, Carran DT. Identification and referral of handicapped infants. In: Wang MC, Reynolds MC, Walberg HJ, eds. Handbook of special education research and practice: low incidence conditions. Oxford, England: Pergamon Press, 1989:227–41.
  8. Andrews H, Goldberg D, Wellen N. Prediction of special education placement from birth certificate data. Am J Prev Med 1995;11:55–60.[ISI][Medline]
  9. World Health Organization. Expert group on prematurity: final report. Geneva, Switzerland: World Health Organization, 1950.
  10. Boussy CA, Scott KG. Use of data base linkage methodology in epidemiological studies of mental retardation. Int Rev Res Ment Retard 1993;19:135–61.[ISI]
  11. Scott KG, Mason CA, Chapman DA. The use of epidemiology methodology as a means of influencing public policy. Child Dev 1999;70:1263–72.[ISI]
  12. Epi Info 6. Centers for Disease Control and Prevention (Atlanta, GA) and World Health Organization (Geneva, Switzerland), 1997. (http://www.cdc.gov/epo/epi/software.htm/).
  13. Kiley JL, Paneth N. Follow-up studies of low-birthweight infants: suggestions for design, analysis, and reporting. Dev Med Child Neurol 1981;23:96–100.[ISI][Medline]
  14. Abel M. Low birth weight and interactions between traditional birth risk factors. J Genet Psychol 1997;158:443–56.[ISI][Medline]
  15. Chomitz VR, Cheung LWY, Lieberman E. The role of lifestyle in preventing low birth weight. Future Child 1995;5:121–38.[ISI][Medline]
  16. Starfield B, Shapiro S, Weiss J, et al. Race, family income, and low birth weight. Am J Epidemiol 1991;134:1167–74.[Abstract]
  17. Hack M, Klein N, Taylor HG. Long-term developmental outcomes of low birth weight infants. Future Child 1995;5:176–96.[ISI][Medline]
Received for publication April 3, 2000. Accepted for publication June 8, 2001.