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Self-Reported Health Status and Health-Related Quality of Life of Teenagers Who Were Born Before 29 Weeks' Gestational Age

^a National Perinatal Epidemiology Unit
^b Department of Social Policy and Social Work, University of Oxford, Oxford, United Kingdom

	ABSTRACT

TOP ABSTRACT METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
OBJECTIVE. The objective of this study was to describe the self-reported health status and health-related quality of life of British teenagers who are in mainstream schooling and were born before 29 weeks' gestational age compared with British teenagers who were born at term.

METHODS. All surviving children who were born at <29 weeks' gestation in the former Northern Region of England in 1983 and in the former Oxford Region of England and in Scotland in 1984 were eligible. A comparison group of teenagers who were born at term were also recruited. Children's responses to the Health Utilities Index Mark III were compared.

RESULTS. A total of 218 of the original 535 children who were born in the 3 regions during the study period were alive at 15 to 16 years of age. A complete Health Utilities Index Mark III record was available for 140 children in mainstream schools and for 108 control subjects. In 7 of the 8 attributes (vision, hearing, speech, emotion, pain, ambulation, and dexterity), there were no statistically significant differences in any functional impairment between the comparator groups. However, the preterm group did report a higher level of functional impairment in the cognition attribute (40.7% vs 25.0%). Although there was no difference in the median Health Utilities Index Mark III utility score between the 2 groups (0.93), there was a broader range of utility scores for the preterm group (0.07–1.0 vs 0.45–1.0 for the control group).

CONCLUSIONS. Despite objective evidence that children and teenagers who were born preterm have poorer health on average than term-born control subjects, this is not reflected in their own ratings of their health status and health-related quality of life at 15 to 16 years of age. The reasons for these differences need to be further explored.

Key Words: infant • preterm • premature • follow-up • adolescents • health utility • quality of life

Abbreviations: HUI—Health Utilities Index • ELBW—extremely low birth weight • ELGA—extremely low gestational age

Children who are born very preterm are at increased risk for a range of adverse neonatal outcomes, including chronic lung disease,¹ severe brain injury,² retinopathy of prematurity,³ necrotizing enterocolitis,⁴ and neonatal sepsis.⁵ In later life, children who were born very preterm are at increased risk for motor and sensory impairment^6,7 learning difficulties,^8–12 and behavioral problems^13–16 Most studies that describe the long-term outcomes of children who are born very preterm use disease-specific instruments that fail to capture all neurodevelopmental, functional, and behavioral outcomes that might be of interest. In recent years, a number of investigators have recognized the importance of measuring the impact of preterm birth across multiple domains. Instruments that can be used to measure the multiple health impacts of preterm birth over the longer term include multidimensional health profiles, which measure different aspects of physical, mental, and social well-being, and multiattribute utility measures, which are health status classification systems with preexisting preference weights that can be attached to each permutation of responses. A particular advantage of the latter set of measures is that they generate composite utility scores that reflect population preferences for the overall health state that is being measured.

The multiattribute utility measures that have been developed include the Quality of Well-Being Scale,¹⁷ Rosser-Kind Classification of Illness States,¹⁸ Health Utilities Index (HUI),¹⁹ EuroQol 5-dimension,²⁰ 16D (a 16-dimensional measure of health-related quality of life),²¹ 17D (a 17-dimensional measure of health-related quality of life),²² Assessment of Quality of Life instrument,²³ and SF-6D (a short-form 6-dimensional measure of health-related quality of life).²⁴ The HUI is the most widely used of the multiattribute utility measures within the childhood context. It has been applied to patients with cancer,²⁵ liver transplant survivors,²⁶ chronic musculoskeletal disorders,²⁷ and cochlear implantation.²⁸ Of greater relevance to the study reported in this article, Saigal et al⁸ applied the Mark II classification of the HUI to 141 extremely low birth weight (ELBW) Canadian children during adolescence and a comparison group of 124 normal birth weight control subjects. They found that, as a group, ELBW teenagers rated their own health-related quality of life lower on average than the control group. However, the vast majority of ELBW teenagers rated their health-related quality of life as satisfactory and could not be distinguished from control subjects.⁸ A distinctive methodologic issue that arises in studies that measure the health status and health-related quality of life of children is identifying the appropriate respondent for the measurement task. In their study of Canadian adolescents who were born at ELBW, Saigal et al measured health status by direct personal interviews independently with the children and their parents using the HUI Mark II classification.²⁹ Differences between the child–parent dyads were observed mainly in the cognition dimension, in which children tended to describe themselves at a higher level of function than did their parents; and in the sensation dimension, in which children identified more problems compared with parent reports. These results are not entirely surprising, because the broader psychometric literature suggests that each child has a unique perspective on and valuation of his or her health status and may also learn to conceal his or her true emotions from parents and caregivers.^30,31

The objective of the study reported in this article was to describe the self-reported health status and health-related quality of life of British teenagers who are in mainstream schooling and were born at extremely low gestational age (ELGA) and a comparison group of teenagers who were born at term. The study is based on 3 rich geographically defined British cohorts that have been followed up since the mid-1980s. As such, it does not suffer from the selection biases that characterize many other studies of health status and health-related quality of life in childhood.

	METHODS

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Participants
The ELGA study is a multicenter collaborative study that pooled 3 geographically defined cohorts of children who were born at <29 weeks' gestation and followed them up at different ages.^14,32,33 Eligibility for each of these cohorts depended on the mother's residence at the time of birth in 1 of 3 geographic regions in the United Kingdom. All children who were born at <29 weeks' gestation in the former Northern region of England in 1983 and in the former Oxford Region of England and in Scotland in 1984 were included.^32–34 Gestational age at birth was estimated using a combination of date of last menstrual period and ultrasound examination when available. When there was a discrepancy of >14 days between these estimates, the ultrasound estimate was preferred.

For locating the children at age 15 to 16 years, a letter was sent to the address of the general practitioner who was identified from the child's most recent follow-up assessment. When the child was still registered, permission was requested from the general practitioner to reapproach the family. When the child was no longer registered with that general practitioner, the National Health Service Central Register was used to confirm that the child was still alive and, if so, the location of the child's current general practitioner. The child's current general practitioner was then approached and asked permission to reapproach the family.

Recruitment procedures varied among the 3 collaborating regions of the ELGA study, but essentially both the child and the parents were asked to give written permission for questionnaires to be sent to the child, parent, and general practitioner and for the child's school to be approached. The head teacher for each consenting child in mainstream schooling was asked to forward a questionnaire to the child's year tutor for completion and to help locate children who could act as study control subjects. The year tutor was asked to choose as control subjects the 3 children who were closest in date of birth to the ELGA child, in the same year group, and of the same gender. Control children and their parents were then written to and asked permission to participate in the study. Control subjects were not sought for children who were attending special schools. Full details on the tracing and recruitment procedures of the study participants are reported elsewhere.³⁴

Measurement of Health Status and Health-Related Quality of Life
The postal questionnaires that were sent to the children in 1999–2000 included questions on their school progress, health, mental health, behavior problems, and substance misuse. The children were asked to complete the postal questionnaires without assistance from their parents or other caregivers. Because the focus of the analysis was health status and health-related quality of life, we report in this article their responses to the HUI questionnaires. The HUI is a family of health status classification systems. The children were asked to complete the unedited 15-item questionnaire for self-administered, self-assessed usual health status assessment, which was obtained from the HUI developers and covers both Mark II and Mark III health status classification systems.³⁵ The Mark III classification system is now recommended by the developers because of its broad applicability in both clinical and general population health studies, improvements in a number of definitions, and an increased orthogonality of its attributes for structural independence.³⁶ The HUI Mark III health status classification system covers 8 attributes: cognition, vision, hearing, speech, ambulation, dexterity, emotion, and pain. Function within each attribute is graded on a 5- or 6-point scale that corresponds to level of severity, ranging from normal function to severe impairment. Responses to the HUI Mark III can be converted into a utility score by reference to a utility scoring algorithm that can be attached to each permutation of responses.³⁷ The utility scoring algorithm can be summarized as u* = 1.371 (b₁ x b₂ x b₃ x b₄ x b₅ x b₆ x b₇ x b₈) – 0.371, where u* is the utility of a chronic health state on the utility scale in which death has a utility of 0.00 and perfect health has a utility of 1.00. The b variables are substituted from a table of coefficients provided by the HUI developers for the appropriate attribute and level.³⁷ For development of the utility scoring algorithm, a random sample of 504 adults who were general population and living in the city of Hamilton, Canada, had previously been asked to value selected health states using both a visual analog scaling technique and a standard gamble instrument.³⁸ Additional details on the utility algorithm for the HUI Mark III are reported elsewhere.³⁶

Ethical Approval
The ELGA study was approved by the Oxford Multi-Centre Ethics Committee and by local ethics committees in the former Northern Region and in Scotland.

Statistical Analyses
In this analysis, we used the self-reports of the teenagers only. Comparisons were made between the ELGA teenagers in mainstream schools and their term-born control subjects. Differences in baseline characteristics between the ELGA children and their control subjects were tested using the Pearson ² test. For each of the 8 attributes of the HUI Mark III, we compared the proportion of children with (1) any level of functional limitation and (2) severe functional impairment using Fisher's exact test for equality of proportions. Severe functional impairment for each of the 8 attributes of the HUI Mark III had previously been defined by the HUI developers to facilitate comparisons among patient groups and over time.³⁵ Severe functional impairment was defined as levels 5 and 6 in the cognition, vision, and hearing attributes; level 5 in the speech attribute; levels 4, 5, and 6 in the ambulation and dexterity attributes; and levels 4 and 5 in the emotion and pain attributes. Descriptive statistics were calculated for the derived utility scores. Differences in utility scores were tested using 2-sample t tests for unequal variance. Because many comparisons were made, we used a conservative P value threshold of <.01. Statistical analyses were conducted using Stata 8.0 (Stata Corp, College Station, TX).

	RESULTS

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Of the 535 children in the original ELGA cohorts, 218 were alive at 15 to 16 years of age and approached to participate in the study. This rate of mortality was not uncommon in the presurfactant era of neonatology. The postal questionnaires were returned by 175 (80.3%) ELGA children, 147 of whom were in mainstream schools at the time of the study and 28 of whom were in special needs schools. In the United Kingdom, the majority of children with special needs are educated in mainstream schools. However, there are a few children whose needs are so complex that they require education outside mainstream education in special schools. A complete HUI Mark III record was available for 140 of the 147 ELGA children in mainstream schools, as well as for all 108 control subjects approached. These children formed the basis of our analyses. Nonresponders in the ELGA group were comparable to responders in terms of birth weight and gestational age but were of lower social status (data available on request). The demographic and socioeconomic characteristics of the 140 participating ELGA children in mainstream schools and the 108 control subjects were broadly similar (Table 1).

	DISCUSSION

TOP ABSTRACT METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

The results of this study are broadly in line with what has been reported elsewhere in the published literature. However, it is worth noting that most of these studies are based on preterm samples with higher gestational age than this sample. A recently conducted comprehensive review of studies of health-related quality of life of preterm children concluded that the majority of these children do not rate their health-related quality of life as significantly different from that of term-born control subjects despite objective evidence that they have poorer health on average.³⁹ Furthermore, this finding has been replicated, in large part, by a number of empirical studies. Danish researchers assessed the health-related quality of life of 85 young adults (18–20 years of age), born in 1971–1974 with birth weights <1500 g, and made comparisons with 85 young adults who were born at >2500 g during the same period.⁴⁰ Health-related quality of life was assessed by telephone interview using an instrument that covered elementary biological needs, warm human relationships, meaningful occupation, and diverse and exciting experiences. Young adults who had birth weights of <1500 g and reported no impairments did not differ from control subjects on scores of health-related quality of life, but those who reported physical or mental impairment had scores of health-related quality of life that were significantly lower than those in the control group.⁴⁰ These researchers repeated their study on a cohort born in 1980–1982. The results were essentially identical, although those with birth weights of <1500 g reported significant impairment on objective as opposed to subjective assessment of health-related quality of life.⁴¹ A Swedish study compared the health-related quality of life of 39 young adults (age 19) who were born before 35 weeks' gestation and 23 term-born control subjects. Self-rated health-related quality of life was assessed using the visual analog scaling technique. The investigators found no significant differences between the 2 groups.⁴²

In contrast to the findings above, a series of studies by Saigal et al^43,44 of ELBW children did find significant differences in health status and health-related quality of life compared with control subjects. In an early study by these investigators, the health-related quality of life of ELBW children and a reference group of children at 8 years of age was retrospectively classified using the HUI Mark II classification on the basis of assessments that were provided by health professionals. The utility scores for each child were estimated indirectly using a formula that was derived from preference measurements that were obtained from parents in the general population.^43,44 Mean utility scores were lower for the ELBW children than for the reference group. A later study by Saigal et al⁴⁵ compared the health status and health-related quality of life of 141 children who born weighing <1000 g and 145 normal birth weight control subjects. Children completed the HUI Mark II classification between ages 12 and 16. The children who born weighing <1000 g were significantly more limited in cognition, sensation, self-care, and pain compared with the control subjects. Furthermore, they had a significantly lower mean utility score. However, the vast majority of the ELBW group viewed their health-related quality of life as satisfactory, and it was difficult to distinguish their scores from those of the term-born control subjects.⁴⁵ It should be noted that there were differences between the methods used by the latter study and those used by our study. Notably, the research instruments in the study by Saigal et al⁴⁵ were interviewer administered, and the utility scores that were attached to the HUI Mark II responses were obtained directly from the children themselves using the visual analog and standard gamble techniques. In contrast, the children in our study completed postal questionnaires and the utility scores that were attached to the HUI Mark III responses were derived from a general population of Canadian adults. Recent research suggests that our approach of indirectly estimating utility scores by attaching population-derived utility scores to HUI health states may be a poor substitute for directly measured utility scores.⁴⁶ Nevertheless, there is no evidence to suggest that this systematically biases group differences in utility scores.⁴⁶

There seem to be 3 main explanations as to why many studies of health status and health-related quality of life, including this one with an extremely preterm cohort, fail to find major differences between preterm-born teenagers and term-born control subjects. First, it is possible that the measures of health status and health-related quality of life that are applied in these studies are poor. The limited evidence that is available presents a mixed picture of the psychometric properties of the alternative measures of health status and health-related quality of life applied in a childhood context.³⁰ It is evident that additional research is required to establish the practicality, reliability, and validity of these measures when applied to pediatric populations. In particular, it may be that the reading level that is required for the HUI and other measures is somewhat high for pediatric samples in which a number of children may have mild learning difficulties. A second explanation for the nonsignificant differences between our study groups is that preterm-born teenagers who attend mainstream schooling are likely to be healthier and have less disability than those who require special schooling. In particular, the ability to cope in a mainstream school usually precludes those with severe cognitive or behavioral problems. Therefore, it may not be surprising that this group of preterm children are little different from their peers. However, in a previous report on these teens, parents of ELGA teenagers in mainstream school reported a higher incidence of problems than did parents of control subjects in physical functioning, mental health, and family life.^16,34 Furthermore, their teachers rated their ability lower than that of the control group.³⁴ A final consideration when interpreting our results is that it may be possible that teenagers' perceptions of their health status and health-related quality of life may be different from that of their families, caregivers, or health professionals. In a companion article that examined emotional and behavioral problems in the same population, group differences in conduct and emotional problems were less pronounced when teens self-reported on their own well-being, compared with when these reports came from teachers and parents, suggesting that young people might rate their problems differently from adults who know them well.¹⁶ However, youth perceptions would not seem to account for the lack of group differences in these data, because the HUI responses that were reported by the ELGA preterm and control group parents were almost identical (data available from authors).

The only significant difference in health status between the ELGA teenagers and control subjects was on the cognition attribute. This attribute is tested using 2 questions: 1 on memory and 1 on thinking and problem-solving. Previous studies have established that very low birth weight infants are more likely to develop visual perceptual and visual-motor impairments, delay in some language functions, and working memory deficit, and, at school age, they may have learning problems and attention deficit,^15,47 although few have focused on specific abilities of the cognitive spectrum during late childhood. The mechanisms by which prematurity might cause cognitive deficits in adolescence require additional research.

There are a number of strengths to the study reported in this article. First, it is based on an extremely preterm population-based cohort that was drawn from defined geographic areas rather than a clinic-based population; consequently, selection biases are unlikely to represent a major problem. Second, children were recruited from 3 regions of the United Kingdom that reflect its socioeconomic and ethnic diversity; therefore, the study is likely to have high external validity. Third, the study used a validated and reliable measure of health status and health-related quality of life, HUI. Fourth, the analysis used school-age control subjects that were specifically recruited for this study rather than data from siblings, which are prone to biases as a result of continuously changing developmental situations, or comparisons with British population norms, for which limited data are available.

The study does have a number of caveats, which should be borne in mind by readers. First, it was not possible to identify an appropriate comparison group for the 28 index children in special needs schools, because classes in special needs schools are organized according to ability to participate in particular activities rather than age. Therefore, these children were not included in this analysis. Separate comparisons between the entire ELGA cohort, including the children who were attending special needs schools, and the 108 term-born control subjects revealed that the ELGA children as a totality did report a statistically significant higher level of functional impairment in 4 of the 8 HUI Mark III attributes (cognition, hearing, ambulation, and dexterity). Furthermore, the mean utility score was significantly lower for the entire ELGA cohort when compared with the term-born control subjects (0.82 vs 0.89; P = .003). Nevertheless, given the absence of control subjects for the 28 index children in special needs schools, we believe that the appropriate comparisons are those that we report in the main section of the article. Second, although the response rates to our questionnaires were relatively high, there is a concern that the outcome of the children who were not seen or assessed differs from those who were seen. Additional analyses revealed that the nonresponders to our study included a higher proportion of children without previous assessments and a higher proportion of children of lower social status. This obviously needs to be borne in mind when interpreting the group findings. Third, although the HUI is the most widely used of the multiattribute utility measures within the childhood context, the underlying preference weights that were provided by the developers were derived from a survey of Canadian adults. Additional research that elucidates the underlying valuations of preterm children with the necessary cognitive capacities for the health states that they experience during adolescence and later into adulthood is required. Fourth, although it is possible that bias was introduced though the year tutor's choice of control subjects, this is unlikely, because they were requested to choose the children who were closest in date of birth to the ELGA child.

	CONCLUSIONS

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Follow-up studies of very preterm infants into adolescence and adulthood have benefited tremendously from the examination of a broader set of outcomes than simply morbidity and mortality.⁴⁸ In particular, measures of health-related quality of life and health utilities have enabled the translation of neurologic and other sequelae into outcomes that are arguably more meaningful to patients, health service providers, and policy makers. These comprehensive accounts of individual patient experience provide a more detailed account on which to base service provision and to evaluate outcome of interventions. They also permit comparison with other chronic conditions of childhood, which can help with prioritization and funding of services. Their use in follow-up studies, however, is not yet routine, and more methodologic work is required, particularly with regard to eliciting underlying preferences for the health states that are experienced from the children themselves and in understanding the meaning of young peoples' self-perceptions of their health.

	ACKNOWLEDGMENTS

 
This study was supported by core funding for the National Perinatal Epidemiology Unit from the Department of Health in England.

We acknowledge the contribution of the participants in this project, the researchers who invested a great deal of time and effort in setting up this study and following up the children, and the ELGA principal investigators for giving permission for this analysis. The original ELGA group of principal investigators consisted of Frances Gardner, Edmund Hey, Ann Johnson, Lesley Mutch, Unni Wariyar, and Patricia Yudkin. The ELGA steering group consisted of the investigators plus Sarah Arkle, Ursula Bowler (project coordinator), Christine Hockley, Michael Jones, Barbara Maughan, and Anne Stewart.

	FOOTNOTES

 
Address correspondence to Ron Gray, MBChB, MPH, National Perinatal Epidemiology Unit, University of Oxford, Old Road Campus, Headington, Oxford OX3 7LF, United Kingdom. E-mail: ron.gray{at}npeu.ox.ac.uk

The authors have indicated they have no financial relationships relevant to this article to disclose.

The views presented here are those of the authors and not necessarily those of the Department of Health.

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