PEDIATRICS Vol. 118 No. 1 July 2006, pp. 217-223 (doi:10.1542/10.1542/peds.2005-2836)
Are Children of Moderately Low Birth Weight at Increased Risk for Poor Health? A New Look at an Old Question
Department of Pediatrics, Albert Einstein College of Medicine, Children’s Hospital at Montefiore, Bronx, New York
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONREFERENCES |
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OBJECTIVE. The goal was to examine whether moderately low birth weight children were at greater risk for health problems than normal birth weight children in a nationally representative sample of US children.
METHODS. Data were analyzed for 7817 children, 0 to 12 years of age, from the sample child file of the 2002 National Health Interview Survey. Logistic regressions were estimated to examine whether morbidity rates were higher among moderately low birth weight children than among normal birth weight children and to control for covariates. Health was measured as having a special health care need, having a chronic condition, being hospitalized in the past year, having a learning disability, attention-deficit disorder/attention-deficit/hyperactivity disorder, or other behavioral disorders, having minor health conditions, and having acute illnesses.
RESULTS. With control for other confounders, moderately low birth weight children were significantly more likely than normal birth weight children to be identified as having a special health care need, having a chronic condition, having a learning disability, and having attention-deficit disorder or attention-deficit/hyperactivity disorder. They were not more likely to have a hospitalization in the past year, other behavioral disorders, or minor health conditions or acute illnesses.
CONCLUSIONS. This population-based study of rates of current morbidity shows that moderately low birth weight children born since 1990 are vulnerable to a wide range of health, learning, and behavioral problems, compared with normal birth weight children. This suggests the need for continued focus on ways to reduce morbidity rates for moderately low birth weight children.
Key Words: moderately low birth weight • health status • chronic conditions • special health care needs • epidemiology
Abbreviations: MLBW—moderately low birth weight • VLBW—very low birth weight • LBW—low birth weight • NBW—normal birth weight • ADD—attention-deficit disorder • ADHD—attention-deficit/hyperactivity disorder • CSHCN—children with special health care needs • NHIS—National Health Interview Survey
It is well known that infants who are born prematurely or small for date are at increased risk for later physical and emotional health conditions and cognitive problems.1–3 In the past 2 decades, however, there have been dramatic improvements in neonatal care and in survival rates for low birth weight (LBW) infants. As smaller infants survive, more-recent studies have focused, with a few exceptions, on the outcomes for the smallest infants in the very low birth weight (VLBW) (<1500 g) or extremely low birth weight (<800 g) categories. This might have created the impression that, after early infancy, there are few reasons to pay special attention to children who weigh 1500 to 2499 g at the time of birth.
Although the early literature on LBW children focused on moderately low birth weight (MLBW) children (1500–2499 g), recent research on LBW infants generally does not include MLBW children. For example, a recent meta-analysis of 16 reports of cognitive and behavioral outcomes for school-aged children who were born preterm included only 2 studies with data on children of >1500 g.4 Of the studies that provide data on such children, a few suggest that MLBW children are not at significant risk after the newborn period. McCormick et al5 found that VLBW children, but not MLBW children, were at increased risk for a wide range of poor health outcomes. Huddy et al6 noted that these children generally are considered to be at low risk for later neurodevelopmental problems and usually do not receive special follow-up care but are at risk for school problems. Middle et al3 reported that MLBW children have rates of health service use, school performance, and educational support between those of VLBW children and children weighing 
2500 g at birth. Other reports of outcomes for MLBW infants noted increased risks for learning and behavioral problems,1,7 increased rates of learning problems,8 and, particularly among children of low socioeconomic status, increased rates of attention-deficit/hyperactivity disorder (ADHD).9 Higher neonatal and postneonatal mortality rates,10,11 higher hospital inpatient-related costs in both perinatal and subsequent periods,12,13 and higher asthma rates14 have also been reported.
The existing literature on LBW infants also is flawed because it focuses almost exclusively on children who were monitored in long-term cohort studies. Such studies are not generalizable because they enroll regional samples, usually from major medical centers, and have selective drop-out of members of the cohort.15 This is especially problematic for MLBW infants, because they are more likely to remain in community-based nurseries and thus are underrepresented in outcome studies at tertiary care units of major medical centers.16 Some of the existing studies also lack a normal birth weight (NBW) control group.
To our knowledge, there are few data on the relationship of birth weight to child health in population-based samples in the United States. Notable exceptions are the report by Resnick et al,7 which focused primarily, but not exclusively, on educational outcomes in a statewide sample, and the report by Hediger et al,2 which used Third National Health and Nutrition Examination Survey data and found that LBW (<2500 g) was associated with delays in motor and social development.
From both epidemiologic and clinical perspectives, it is important to determine whether MLBW is associated with poorer health, compared with NBW (2500 g).17 Between 1984 and 2002, the percentage of births of <2500 g increased fairly steadily, from a low of 6.7% in 1984 to 8.1% in 2004, the highest level since 1970. Therefore, the percentage of births with weight of <2500 g increased almost 21% in the 2 decades from 1984 to 2004, whereas infant and neonatal mortality rates decreased 25% between 1990 and 2003 (the latest for which data are available). Although some increase in overall rates is attributable to infants of <1500 g, births with VLBW increased at a rate of only 15% in that time period.18 In 2004, when 8.1% of all children born in the United States were <2500 g at the time of delivery, only 1.5% of the total number of children born weighed <1500 g. Therefore, there were >5 times as many MLBW children as VLBW children. Among the 4.1 million births in 2004, this difference represented an at-risk population of >271000 MLBW children, compared with 61700 VLBW children.18 Elevated morbidity rates in this population could generate substantial illness burden and economic and social costs. The purposes of this study were to describe rates of chronic conditions, special health care needs, and other types of health problems among MLBW children, compared with NBW children, in a nationally representative sample of children in the United States and to assess the types of conditions for which such children are at increased risk, with adjustment for sociodemographic variables.
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METHODS |
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Sample
We used data on the sample child from the 2002 National Health Interview Survey (NHIS), a multipurpose health survey conducted by the National Center for Health Statistics, Centers for Disease Control and Prevention. The NHIS is the principal source of information on the health of the civilian, noninstitutionalized, household population in the United States.19 The basic module or core consists of 3 components, namely, the family core, the sample adult core, and the sample child core. The family core contains information on every person in the family and includes household composition, sociodemographic characteristics, basic indicators of health status, activity limitations, health insurance coverage, and access to and use of health care services. If children <18 years of age were present in the family, then 1 child was selected at random for the sample child core questionnaire, which includes additional questions on birth weight, health status, health care services, and behavior.
To reduce survey costs and to oversample specific population groups, the NHIS used methods of clustering and stratification. As a result, clusters of observations within the 2 primary sampling units in each of the 339 strata might not be completely independent; therefore, SE values were adjusted for stratification and clustering.19 Black and Hispanic populations were oversampled by the NHIS, to allow more-precise estimates of health status in these populations. Because the NHIS used a stratified sample with a multistage sample design, analyses were also weighted by the final annual sample child weight. These weights incorporated design and ratio adjustments, nonresponse rates, probability of selection and stratification, and adjustments to census totals for age, gender, and race/ethnicity (after stratification).19
There were data on 8860 children from birth to 12 years of age in the 2002 sample child file. Three children were missing information on whether they had a health limitation, 10 were missing information on whether they had been hospitalized in the past year, and 523 were missing information on birth weight. An additional 420 children were missing information on maternal education, and 69 were missing information on family type. Eighteen children were eliminated on a technicality; for this sample, there was only 1 primary sampling unit in their stratum. This resulted in a study sample of 7817 children.
An additional 1656 children (21% of the sample) were missing a measure of family poverty status. For the NHIS as a whole, nonresponse rates for total family income have been high. In the year 2002, the weighted percentage of families with unknown family income was 32% as an exact value and 29% as a detailed categorical value. Because there was a particular interest in the health of vulnerable populations, such as those with low income, the NHIS imputed income values.20 The NHIS created 5 sets of imputed values for each person. Use of these 5 files (1 for each set of imputed values) allowed us to adjust for the additional variability in the estimates resulting from the imputation.
Measures
Birth Weight
Birth weight was reported in pounds and ounces by the adult in the household who knew the child’s health best (almost always a parent) and was recoded in grams by the NHIS. A child was defined as VLBW if the weight at birth was reported to be <1500 g, as MLBW if the weight at birth was 1500 to 2499 g, and as NBW if the weight at birth was 2500 g.
Special Health Care Needs
We identified a child as having a chronic condition on the basis of results from the Children with Special Health Care Needs (CSHCN) Screener,21 which were available for each child in the sample child file. With the CSHCN Screener, a child was considered to have a special health care need if the parent responded affirmatively to 1 of the 5 questions assessing need or use of medication for a health condition; need or use of more medical, mental health, or educational services than is usual for most children of the same age; being limited or prevented in any way from doing the things that most children of the same age do; need or use of special therapy, such as physical, occupational, or speech therapy; or need or receipt of treatment or counseling for any kind of emotional, developmental, or behavioral problem. All questions applied a duration criterion of "lasted or is expected to last at least 12 months." We examined whether children in each birth weight category met the criteria for each of the 5 components of the CSHCN Screener, as well as the composite measure.
Chronic Conditions
We identified a child as having a chronic condition if a doctor or health professional told a parent that the child had 1 of the following conditions: mental retardation, a developmental delay, Down syndrome, cerebral palsy, autism, muscular dystrophy, cystic fibrosis, sickle cell anemia, diabetes mellitus, arthritis, congenital heart disease, asthma, or trouble seeing or hearing.
Hospitalization
Hospitalization was recorded if the child had been in the hospital for 1 night, other than when they were born, during the past year.
Mental or Cognitive Limitations
The NHIS did not collect information on mental or cognitive limitations among very young children but did record these measures for children 3 years of age.
Learning Disability
We identified a child as having a learning disability if a health professional or representative of the school ever told the caretaker that the child had a learning disability.
Attention-Deficit Disorder/ADHD
We identified a child as having attention-deficit disorder (ADD)/ADHD if a health professional or representative of the school ever told the caretaker that the child had ADD or ADHD.
Emotional or Behavioral Problem
We coded a child as having an emotional or behavioral problem if the respondent indicated that the child was 3 years of age and in the past 2 months had been unhappy or depressed or the child was 4 to 12 years of age and in the past 6 months had not been generally well behaved, had many worries or often seemed worried, was often unhappy, depressed, or tearful, or had difficulties with emotions, concentration, behavior, or the ability to get along with other people. The mental health indicators for children 3 years of age were based on items from the Child Behavior Checklist. For children 4 to 12 years of age, the questions were derived from the parent version of the Strengths and Difficulties Questionnaire.19
Minor Health Problems
We identified a child as having a minor health problem if, in the past 12 months, the child had 1 of the following conditions: hay fever, a respiratory allergy, a food or digestive allergy, eczema or another skin allergy, frequent diarrhea or colitis, anemia, >3 ear infections, seizures, frequent or severe headaches including migraines, or stuttering or stammering.
Acute Illnesses
We identified a child as having an acute illness if the child had experienced a chest or head cold in the past 2 weeks, a stomach or intestinal illness with vomiting or diarrhea in the past 2 weeks, or ever had chicken pox.
Analyses
We focused on the sample of children weighing 1500 g. With a 
2 test, we examined whether the proportion of children with each type of morbidity was significantly higher among children of MLBW (1500–2499 g) than children of NBW (2500 g). The low frequency of 1 indicator in the MLBW group (ie, need or use of special therapy, such as physical, occupational, or speech therapy) rendered estimates of its prevalence too imprecise to report (cell size: <20 observations).
Among VLBW children, small cell sizes caused estimates of the prevalence of most outcomes to be too imprecise to report. The exceptions were the composite CSHCN Screener results, results for 2 CSHCN Screener components (need or use of medication and high use of care or services), and the presence of a chronic condition, a minor health condition, or an acute illness.
We also examined whether findings of differences in morbidity rates among children in different birth weight categories reflected other correlates of LBW, such as low socioeconomic status. Logistic regression equations were estimated, modeling our morbidity measures as functions of birth weight group (ie, 2 dummies for MLBW and VLBW, with NBW as the reference group), first unadjusted and then adjusted for socioeconomic traits, including age, gender, race, mother’s education, poverty status, and family type (ie, both parents in the home versus other). Although we included VLBW children in the sample and therefore included a dummy variable for the VLBW group in the model, we do not report data for the VLBW group, compared with the NBW group, because of very small cell sizes, which resulted in unstable estimates. VLBW children were included in the analyses to avoid significant bias in the interpretation of data for the MLBW group.
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RESULTS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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For 4 of the 5 components of the CSHCN Screener and the composite, the proportion of CSHCN was significantly higher among MLBW children than NBW children. The one exception was that the number of children using physical therapy, occupational therapy, or speech therapy was too small to yield reliable estimates of therapy prevalence in the MLBW group (Table 1).
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Compared with NBW children, children of MLBW had a higher prevalence of most other aspects of poor health as well. For most of the included health measures, the proportion in poor health was significantly greater in the MLBW group than in the NBW group. The 2 exceptions were that MLBW children were not significantly more likely than NBW children to have more-minor health conditions or acute illnesses. Acute illnesses did not differ in prevalence among the 3 birth weight groups.
Because background characteristics such as low socioeconomic status may increase the risk of morbidity among children and are correlated with birth weight, we examined whether the health of MLBW children was worse than the health of NBW children once we controlled for the possible effects of these confounders. When we controlled for age, gender, race/ethnicity, mother’s education, family type, and poverty status, the odds of having a special health care need, as measured with the composite CSHCN Screener, was still significantly greater in the MLBW group than in the NBW group (Table 2).
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Table 3 presents findings regarding whether MLBW children were at increased risk for poor health, compared with NBW children, on the basis of the 5 components of the CSHCN Screener and the other measures of health status. For each health measure, we reported odds ratios indicating the odds of morbidity for MLBW children, compared with NBW children, first unadjusted and then controlling for the child’s age, gender, and race/ethnicity, mother’s education level, family type, and poverty status. MLBW children were significantly more likely to have special health care needs than were children of NBW, on the basis of 3 of the 5 components of the CSHCN Screener (need or use medication, use more health services than other children, and have an activity limitation). These findings confirm the results of the bivariate analyses. The exception was that the MLBW group was not significantly more likely than the NBW group to need or to use treatment or counseling for a mental health problem, even in the unadjusted model. This model differed from the bivariate model only in the inclusion of a dummy variable for VLBW children in the sample. For physical, occupational, or speech therapy, cell sizes were again too small to yield reliable estimates.
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On the basis of a list of specific chronic health conditions (mental retardation, a developmental delay, Down syndrome, cerebral palsy, autism, muscular dystrophy, cystic fibrosis, sickle cell anemia, diabetes mellitus, arthritis, congenital heart disease, asthma, or trouble seeing or hearing), we found that MLBW children were at greater risk for poor health, compared with NBW children, even after we controlled for sociodemographic traits. Once we adjusted for sociodemographic traits, however, MLBW children were no longer significantly more likely to have been hospitalized in the past year than were NBW children. When we controlled for sociodemographic characteristics, MLBW children were significantly more likely than NBW children to have a learning disability or ADD/ADHD, in accordance with the bivariate results. Once we adjusted for sociodemographic traits, however, MLBW children were no longer more likely to have other emotional/behavioral problems, compared with NBW children. Finally, MLBW children were not at increased risk for minor health conditions or acute illnesses, compared with their NBW peers, which mirrored the bivariate findings.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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We found that, compared with NBW children, MLBW children had higher rates of health problems, as measured in several ways. In the bivariate analyses, the morbidity rates of MLBW children were equal to those of NBW children in only 2 areas, namely, minor health conditions and acute illnesses. When we controlled for background characteristics that are known to be correlated with birth weight, morbidity rates among MLBW children remained higher than those among NBW children for several types of morbidity.
The higher morbidity rates are impressive, especially given the higher rates of death among LBW children in the postneonatal period, which have been shown even among MLBW infants.10,11,18 Death of children in the LBW categories would reduce the numbers of pathologic conditions detected among surviving children. Nevertheless, we found that rates of morbidity among surviving children were elevated even for those in the MLBW categories.
There are some important limitations to this research. First, this study was a secondary analysis of data obtained from respondents in a large-scale survey. In such surveys, answers to single questions are accepted without validation of the information. As a result, there might have been some error in our classification of birth weight or the different types of morbidity. However, the questions we used to operationalize health have extensive histories and are widely thought to be valid and reliable.
Second, information about gestational age and multiple births was not available in the data set. Therefore, we were unable to distinguish gestational age from birth weight and multiple births from singletons, 2 distinctions that have implications for later morbidity.17,18,22
Third, the source of information about birth weight and morbidity was the same person. There are potential problems with recall bias, particularly if parents of MLBW children were more alert to morbidity than parents of NBW children. We think it is unlikely that response bias is the cause of these findings, because morbidity indicators that are considered most sensitive to "vulnerable child syndrome,"23,24 such as frequency of minor and acute illnesses, did not differ across birth weight categories. Although we cannot rule out recall bias or misclassification bias, there is no inherent reason to think that selective answers should be biased systematically, especially because the questions were embedded in a far-larger data-collecting effort.
Finally, we were unable to test a causal relationship with this cross-sectional data set. Although it is likely that in some instances MLBW is a manifestation of immaturity secondary to short gestation, which leads to later morbidity, in other instances it may serve as a marker of a genetic condition or prenatal risk (such as intrauterine growth failure) that is associated with the outcomes we examined. In either case, MLBW should alert clinicians to the higher risk and possibility of later morbidity, which may be amenable to preventive interventions. The extent to which earlier identification and provision of appropriate services can improve outcomes remains to be determined.
The physical and emotional health conditions and cognitive problems faced by extremely low birth weight and VLBW children have been the appropriate focus of a great deal of research attention. Clearly their morbidity remains a key issue, as reflected in the much higher odds ratio for special health care needs. In the past several decades, changes in neonatal care have reduced mortality rates dramatically, which has resulted in a major focus on the outcomes for infants in lower birth weight categories, where it is well known that serious long-term problems continue to be a major concern. Because the recent literature concentrated on VLBW and ELBW infants, it was unclear whether MLBW children also experience ongoing vulnerability to poor health or whether their rates of morbidity are comparable to the rates for the general population. It is especially important to examine this question with a nationally representative sample of children because many of these children may remain outside highly specialized NICUs and therefore may be excluded from regional follow-up studies conducted by tertiary care centers. To our knowledge, other than the study by Hediger et al2 on the effects of birth weight and gestational age on motor and social development, this is the first national population-based study of rates of morbidity among MLBW children since more-recent improvements in neonatal care were implemented. The children in this sample were born between 1990 and 2002; this was a time when regional perinatal centers and surfactant were already in widespread use.
As improvements in the care of newborns in the NICU result in lower mortality rates, we must continue to study the long-term health of these at-risk children. These data suggest a need to refocus attention on the increased longer-term health morbidity of MLBW children and to improve our understanding of the mechanisms through which the increased morbidity occurs. This population is 5 times larger than that of smaller infants, is at elevated risk for poor health, compared with NBW infants, and is vulnerable to a wide range of health, behavioral, and learning problems.
Because the problems of VLBW children are so much more profound and because most recent research in this area focused on these children, clinicians may minimize the risk that MLBW infants face regarding longer-term outcomes. We recommend that pediatricians have a higher index of suspicion, monitor these infants more closely, and act promptly to provide necessary services. It is hoped that heightened vigilance in monitoring and intervening with these children will improve their outcomes. We also think that more research is needed to understand which subgroups of MLBW children have the most risk, when different kinds of health problems can be recognized among MLBW children, and whether there are additional kinds of treatment these infants should undergo in the newborn period or as early intervention that could reduce their longer-term problems. At present, however, we suggest that heightened appreciation of risk should result in earlier recognition of concerns and earlier intervention that might reduce the longer-term vulnerability of these infants to poor health.
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ACKNOWLEDGMENTS |
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This research was supported, in part, by a Robert Wood Johnson Investigator Award in Health Policy Research (grant 38655, to R.E.K.S. and L.J.B.).
We thank Deborah Campbell for her advice and comments.
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FOOTNOTES |
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Accepted Feb 6, 2006.
Address correspondence to Ruth E. K. Stein, MD, Albert Einstein College of Medicine, VE6B27, 1300 Morris Park Ave, Bronx, NY 10461. E-mail: rstein{at}aecom.yu.edu
An earlier version of this work was presented at the annual meeting of the Pediatric Academic Society; May 17, 2005; Washington, DC.
The authors have indicated they have no financial relationships relevant to this article to disclose.
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