Growth status, behavior and neuropsychological performance: a study of Brazilian school age children

Crescimento, comportamento e desempenho neuropsicológico: estudo de escolares brasileiros

Growth status, behavior and neuropsychological performance: a study of Brazilian school age children

Crescimento, comportamento e desempenho neuropsicológico: estudo de escolares brasileiros

Gilberto N.O. Brito^I; Mercedes de Onis^II

^IPesquisador Titular e Chefe, Laboratorio de Neuropsicologia Clínica, Setor de Neurociencias, Departamento de Pediatria, Instituto Fernandes Figueira, FIOCRUZ, Rio de Janeiro, RJ, e Professor Adjunto Doutor, Universidade Federal Fluminense, Niterói RJ, Brasil

^IIMedical Officer, Department of Nutrition for Health and Development, World Health Organization, Geneva, Switzerland

^{Correspondence}

ABSTRACT

AIM: To assess the association between child growth and teacher-reported behavior and academic standing, and neuropsychological performance.

METHOD: The heights of 344 public-school children were measured using standard procedures. Teachers were requested to complete two behavioral and one academic performance rating scales. Neuropsychological assessment consisted of the Edinburgh Handedness Inventory, the Steadiness Test and the Purdue Pegboard. Height-for-age z (HAZ) scores were calculated based on an international reference. Standard (z) scores for each factor of the first two behavioral rating scales and for each neuropsychological variable were computed for each child based on locally-derived norms.

RESULTS: HAZ scores were negatively correlated with factors related to hyperactivity, conduct problem, impulsivity and inattention of the behavioral rating scales. In addition, the lower the HAZ score the worse the academic performance.

CONCLUSION: These results add to the existing evidence indicating a strong association between growth status and child behavior and academic performance.

Key words: child growth, hyperactivity, inattention, conduct problem, neurobehavior.

RESUMO

OBJETIVO: Examinar a associação entre crescimento, comportamento na sala de aula, rendimento acadêmico e desempenho neuropsicológico em escolares.

MÉTODO: A estatura de 344 escolares da rede pública de Niterói foi medida através de procedimentos padronizados. Os professores preencheram duas escalas de avaliação comportamental e uma escala de avaliação do rendimento acadêmico. O exame neuropsicológico incluiu o Inventário da Preferência Manual de Edimburgo, o Teste do Equilíbrio da Haste e a Prancha de Purdue. Escores padronizados da estatura para a idade (HAZ) foram calculados com base em referência internacional. Escores padronizados (z) dos fatores das duas escalas de avaliação comportamental e das variáveis neuropsicológicas foram computados para cada criança com base em normas derivadas localmente.

RESULTADOS: Escores HAZ apresentaram correlação negativa com fatores relacionados à hiperatividade, problemas de conduta, impulsividade e inatenção das escalas de avaliação comportamental. Ademais, quanto mais baixo o escore HAZ, pior se mostrou o rendimento acadêmico.

CONCLUSÃO: Os resultados acrescentam à evidência de associação entre crescimento, comportamento na sala de aula e rendimento acadêmico.

Palavras-chave: crescimento, estado nutricional, hiperatividade, inatenção, conduta, neurocomportamento.

Growth retardation - as measured by low height-for-age - during infancy and early childhood has been found to have a strong adverse effect on cognitive function in late childhood^1-3. However, less is known about relationships between growth impairment and behavior and neuropsychological performance. In Brazil, to a large extent, research in child neuropsychology has been hindered by the lack of normative data for neurobehavioral assessment in children⁴. Earlier research of the first author has focused on the development of normative data for neuropsychological instruments used in the assessment of children in Brazil such as the Conners Abbreviated Teacher Rating Scale⁵, the Teacher Rating Scale-Brazil (TRS-B)⁶, the Edinburgh Handedness Inventory^7-8, the Attention Deficit/Hyperactivity Disorder Teacher Rating Scale-Brazil (ADHD-DSM-IIIR-B)⁹, the Steadiness Test and the Purdue Pegboard¹⁰. The clinical applications and relevance of these instruments for research in child neuropsychology in Brazil are described elsewhere¹¹.

The aim of our study is to build up on the earlier research described above and explore the association between child growth (i.e., height-for-age) and neurobehavioral performance in a sample of Brazilian school age children as assessed by the TRS-B, the ADHD-DSM-IIIR-B, the Academic Performance Teacher Rating Scale (AcPTRS-B), the Edinburgh Handedness Inventory, the Steadiness Test and the Purdue Pegboard.

METHOD

Subjects

A computer-generated unbiased sample of 346 children was the subject of this study. The children had a mean age of 9.4 years and were drawn from a large public school in the greater Rio de Janeiro area (Niteroi) with over 2000 registered children in preschool, elementary and junior high school classes. We selected this school not only due to its large number of children but also because it attracts children from all ethnic groups and social strata, albeit mostly from lower social classes, with place of residence in communities distributed throughout Niteroi, a city located across the Guanabara Bay from Rio de Janeiro. Children were screened for the presence of minor physical disabilities, motor and vocal tics, speech disorders, and other behavioral deviances (e.g., nail biting, streotypies) by the use of a physical handicap and behavior checklist described elsewhere¹¹ and those with impairment deemed capable to interfere with performance of the Steadiness Test and the Purdue Pegboard (e.g., visuomotor impairment or severe motor tics) were excluded from the study. Only two boys, one who refused to be tested and another boy who presented with a severe form of strabismus, were removed from the study. The final sample comprised 344 children (173 boys and 171 girls). The social class distribution of children in the present sample, according to Hollingshead and Redlich¹², was: I (N=2, 0.6%), II (N=9, 2.6%), III (N=34, 9.9%), IV (N=119, 34.6%) and V (N=176, 51.2%). Social classes I and II include university-educated executives, business managers in large concerns, and major and lesser professionals; social class III includes administrative personnel, owners of small independent businesses and minor professionals; and social classes IV and V include skilled, semi-skilled and unskilled laborers with lower educational levels. One hundred and forty eight children (43.0%) were Caucasian, 129 (37.5%) were of African ancestry and 67 (19.5%) were of a multiple-race group.

The study was approved by the Board of Directors of the Instituto de Educação Prof. Ismael Coutinho (IEPIC) and performed under the auspices of the agreement celebrated between IEPIC and the Instituto Fernandes Figueira of the Fundação Oswaldo Cruz (FIOCRUZ).

Anthropometric measurements

Height was measured following standard procedures¹³. Two trained individuals (the first author and a research associate) collected the data on height under the supervision of a nutritionist acquainted with anthropometric measurement procedures. Three measurements of height, each of which required to be within 0.5 cm of the others, were taken for each child and the mean height was used for data analysis. Age was determined through the child's birth certificate included in his/her school records. Height-for-age z scores (HAZ) were calculated based on the National Center for Health Statistics/World Health Organization (NCHS/WHO) reference using the age-specific regression equations¹⁴ and implemented in the ANTHRO software¹⁵. HAZ was then used as a continuous variable in data analysis.

Behavioral assessment

The teachers of the children were requested to complete the TRS-B⁶ and the ADHD-DSM-IIIR-B⁹. Both rating scales were scored from not at all (0) and just a little (1) to pretty much (2) and very much (3).

The TRS-B is comprised of 62 items distributed among five factorial dimensions (Hyperactivity-Conduct Problem; Independent Functioning-Positive Socialization; Inattention; Neuroticism/Anxiety; Negative Socialization). Standard (z) scores for each of these factors were computed for each child based on locally-derived norms⁶ and used as indices of behavioral functioning. Standard (z) scores were then entered as continuous variables in the statistical analysis of the data. Except for the behavioral dimension Independent Functioning-Positive Socialization, higher (and more positive) standard z scores signify that the child is having more difficulties along the behavioral dimensions derived from the TRS-B.

The ADHD-DSMIIIR-B includes the entirety of the diagnostic criteria for Attention Deficit/Hyperactivity Disorder (ADHD) according to DSM-IIIR¹⁶. Standard (z) scores for each of the factors extracted from this scale, Hyperactivity-Impulsivity and Inattention, were computed for each child based on locally-derived norms⁹ and also used as indices of behavioral functioning. Standard (z) scores were then used as continuous variables in the analysis. Higher (and more positive) standard z scores signify that the child is having more difficulties along the two behavioral dimensions derived from the ADHD-DSMIIIR-B.

Academic assessment

The teachers were also requested to complete the AcPTRS-B¹¹ for each child and instructed to rate his/her academic performance as much above average, above average, average, below average and much below average in comparison to their classmates. This measure of academic performance was included in the statistical analysis of the data as dummy-coded variables.

Neuropsychological assessment

The procedures for neuropsychological testing are described in detail elsewhere¹⁰. Briefly, the neuropsychological battery used in the present report was administered over two sessions (one session a day) by the first author and a research associate. Children were tested individually in a quiet and acclimatized room of the school.

The first session included the following tests:

Edinburgh Handedness Inventory. This instrument was used to assess the manual preference of the participants. The procedures for the administration of the Edinburgh Handedness Inventory in children were as described before⁸. Each child was requested to perform the ten tasks included in the inventory and the hand used to perform each activity was recorded. Laterality quotients (LQs) could range from -100 (consistent left-handedness) to +100 (consistent right-handedness)⁸.

Steadiness Test. This test was used to assess motor persistence, motor coordination and attention¹⁷. The procedures for this test were as reported by Brito and Santos-Morales¹⁰ and Gardner¹⁷. Three trials of 60 sec were administered with the hand the child preferred to use in the test as well as with the non-preferred hand. Trials for each hand were administered alternately. Standard (z) scores for total number of contacts and total touch time across the three trials were derived for each child based on Brazilian norms¹⁰.

The second session consisted of the following test:

Purdue Pegboard. This instrument provides an excellent test of fine motor coordination in children with neurodevelopmental disabilities¹⁷. Procedures for this test were as described in Brito and Santos-Morales¹⁰ and Tiffin¹⁸. Standard (z) scores for number of pegs placed with the preferred and non-preferred hands, number of pegs placed with both hands, total time to place 10 pegs across three trials with the preferred and non-preferred hands, total time to transfer 10 pegs across three trials with the preferred and non-preferred hands and total number of items assembled in the "assembly" modality were obtained for each child based on normative data gathered in Brazil¹⁰.

Statistical analysis

The data were analyzed using PC-SAS¹⁹. Proc CORR was used to determine whether growth status correlated with neurobehavioral variables. Additionally, we used the Spearman's rank-order correlations as the assumptions for the use of parametric procedures could not be met by the neurobehavioral data. Furthermore, the individual correlation was used as the conceptual unit of error rate due to the exploratory nature of our study.

RESULTS

Table 1 shows mean (and SD) z scores, and minimum and maximum z scores for height-for-age and the behavioral and neuropsychological variables. Only nine children (2.6%) had HAZ scores equal or below -2.0. The distribution of scores on the AcPTRS-B was the following: (1) much higher than average - N = 9 (2.6%); (2) higher than average - N = 64 (18.6%); (3) average - N = 209 (60.8%); (4) below average - N = 44 (12.8%); (5) much below average - N = 18 (5.2%). Laterality quotients (LQs) were distributed as follows: (1) -100< LQ<-50, N = 30 (8.7%); (2) -50<LQ<0, N = 5 (1.5%); (3) 0<LQ<+50, N = 0; (4) +50<LQ<+100, N = 309 (89.8%).

Table 2 shows the Spearman's rank order correlation coefficients between HAZ and the z-scores for the behavioral and neuropsychological variables. The data presented in the table demonstrate that HAZ is significantly and negatively correlated with two specific behavioral domains derived from the TRS-B: Hyperactivity/Conduct Problem and Inattention. The lower the HAZ of the child the higher his/her z-score in these two behavioral domains.

The significant negative correlation coefficients also found between HAZ and the z-scores of the behavioral domains extracted from the ADHD-DSM-IIIR-B, i.e., Hyperactivity/Impulsivity and Inattention, provide further confirmation of the specificity of the relationship between height-for-age and Hyperactivity and Inattention.

Teacher ratings of academic performance according to the AcPTRS were also found to be significantly and negatively correlated with HAZ, i.e., the lower the latter scores the higher (and worse) the rating of academic performance.

None of the other behavioral and neuropsychological variables had a significant correlation with HAZ.

DISCUSSION

The results show that HAZ is negatively and specifically correlated with the behavioral domains of Hyperactivity/Conduct Problem and Inattention derived from the TRS-B. The significant negative correlations also found between HAZ and the two behavioral domains of Hyperactivity/Impulsivity and Inattention extracted from the ADHD-DSM-IIIR-B confirm the specificity of the relationship between growth status and Hyperactivity and Inattention. These significant negative correlations indicate that lower HAZs are associated with higher degrees of neuropsychopathology along those two behavioral domains. The results also show a significant association between HAZ and teacher's ratings of academic performance; the lower the HAZ the worse the rating of academic performance. No associations were found between HAZ and neuropsychological variables derived from the Edinburgh Inventory, the Steadiness Test and the Purdue Pegboard.

The association of HAZ and teacher ratings of children's behavior in the domains Hyperactivity/Impulsivity and Inattention reported in the present study is consistent with the finding that the birth weight of children with generalized hyperkinesis is significantly lower than that of normal children²⁰. Furthermore, a study performed in Brazil demonstrated that growth status represents a factor associated with attention deficit-hyperactivity disorder²¹. Moreover, a recent study showed that children stunted in early childhood had more conduct problems at home, regardless of their social backgrounds, and fewer prosocial behaviors at school than non-stunted children²².

The significant association found in our study between HAZ and teacher's ratings of children's academic performance adds to the evidence from a number of studies demonstrating a relationship between growth status and academic performance and cognitive functioning^22-26. Although our study could not ascertain the effects of stunting in early childhood on later school achievement due to the small number of children who were stunted in our sample, the direction of the association between height-for-age and academic performance is in agreement with these earlier findings. Furthermore, an association between body-size measures and mental test scores in a population of well-nourished children has also been reported by other investigators²⁷.

The precise mechanism linking physical growth and poor neurobehavioral development is not known. There has been a long standing interest in whether general or specific nutritional deficiencies at a sensitive or critical period of brain growth or maturation could have a long lasting or permanent "programming" influence on later cognitive performance. One noteworthy example of a nutritional influence on cognitive function is maternal iodine deficiency, which may result in reduced cognitive function or even cretinism^28,29. Furthermore, prenatal nutritional deprivation changes sleep/wake mechanisms³⁰ and interferes with benzodiazepine-induced spatial learning deficits³¹ in rats as adults. However, it is difficult to extrapolate from such studies in rats to human behavior. In humans, there are at least two commonly suggested explanatory hypotheses. One of these hypotheses is that malnutrition impairs brain growth and neural development and hence future behavior, while the other states that the association between nutritional status and cognitive development is mediated by motor maturation, activity level and exploratory behavior³. The association between growth status and cognitive development cannot be regarded as a simple causal relationship because of the complex (proximal and distal) environmental factors that affect both growth and development. It is possible that more than one mechanism act in concert to impair neurobehavioral functioning. It might also be hypothesized that low height-for-age interferes with school achievement by its effect on the behavioral domains related to hyperactivity/impulsivity and inattention as indicated by the present findings.

The fact that we did not find a significant correlation between height-for-age and the neuropsychological variables derived from the Edinburg Handedness Inventory, the Steadiness Test and the Purdue Pegboard is possibly due to the small number of children with severe height-for-age deficits in our sample.

In conclusion, we found significant associations between height-for-age, externalizing behaviors and teacher ratings of academic performance in a large sample of Brazilian school-age children. Externalizing behaviors can interfere with academic performance and are considered to predict future psychosocial adjustment²². However, the mechanism of the developmental deficits in academic performance induced by growth retardationdeficits has not yet been elucidated. The use of instruments that assess academic performance directly rather than teacher ratings of academic performance might offer a more precise view of the relationship between growth status and achievement. Such research is now underway in our laboratory.

Acknowledgments

The authors are grateful to Vania M. Fonseca, MSc, for assistance in the standardization of the anthropometric procedures, Tanna Santos-Morales, MSc, for assistance in the collection of the data, Angela Guedes (NPD-UFF) for assistance in the use of the SAS package, Rubem Goulart (NPD-UFF) for the maintenance of computer systems and Tatianna R. Santos for assistance in the preparation of the manuscript. The authors also wish to thank the children who participated in the study, their teachers and the staff of IEPIC (Instituto de Educação Prof. Ismael Coutinho).

Received 2 February 2004, received in final form 13 May 2004. Accepted 13 July 2004.

Research supported by FUNPENE

References

• 1. Berkman DS, Lescano AG, Gilman RH, Lopez SL, Black MM. Effects of stunting, diarrhoeal disease, and parasitic infection during infancy on cognition in late childhood: a follow-up study. Lancet 2002;359:564-571.
• 2. Grantham-McGregor SM. A review of studies of the effect of severe malnutrition on mental development. J Nutr 1995;125:S2233-2238S.
• 3. Gorman KS. Malnutrition and cognitive development: evidence from experimental/quasi-experimental studies among the mild-to-moderate malnourished. J Nutr 1995;125:S2239-S2244.
• 4. Brito GNO, Alfradique GMN, Pereira CCS, Porto CMB, Santos TR. Developmental norms for eight instruments used in the neuropsychological assessment of children: studies in Brazil. Braz J Med Biol Res 1998;31:399-412.
• 5. Brito GNO. The Conners Abbreviated Teacher Rating Scale: development of norms in Brazil. J Abn Child Psychol 1987;15:511-518.
• 6. Brito GNO, Pinto RCA. A Composite Teacher Rating Scale: analysis in a sample of Brazilian children. J Clin Exp Neuropsychol 1991;13:417-418.
• 7. Brito GNO, Lins MFC, Paumgartten FJR, Brito LSO. Hand preference in 4- to 7-year-old children: An analysis with the Edinburgh Inventory in Brazil. Dev Neuropsychol 1992; 8:59-68.
• 8. Brito GNO, Santos-Morales TR. Lateral preferences in 8- to 15-year-old Brazilian children assessed with the Edinburgh Inventory: different measures of handedness and comparison with younger children and adults. Dev Neuropsychol 1999;16:433-453.
• 9. Brito GNO, Lins MFC, Pinto RCA. A behavioral assessment scale for Attention Deficit Disorder in Brazilian children based on DSM-III-R criteria. J Abn Child Psychol 1995;23:509-520.
• 10. Brito GNO, Santos-Morales TR. Developmental norms for the Gardner Steadiness Test and the Purdue Pegboard: a study with children of a metropolitan school in Brazil. Braz J Med Biol Res 2002;35:931-949.
• 11. Brito GNO, Pereira CCS, Santos-Morales TR. Behavioral and neuropsychological correlates of hyperactivity and inattention in Brazilian school children. Dev Med Child Neurol 1999;41:732-739.
• 12. Hollingshead AB, Redlich FC. Social class and mental illness. New York: Wiley; 1958.
• 13. World Health Organization. Physical status: the use and interpretation of anthropometry: report of a WHO Expert Committee. WHO Tech Rep Series 1995;854:424-434.
• 14. Dibley MJ, Goldsby JB, Staehling NW, Trowbridge FL. Development of normalized curves for the international growth reference: historical and technical considerations. Am J Clin Nutr 1987;46:736-748.
• 15. World Health Organization and US Centers for Disease Control. ANTHRO software. Version 2000. Geneva: WHO; 2002.
• ¹⁶ American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 3rd ed-revised (DSM-III-R). Washington, DC: American Psychiatric Association, 1987.
• 17. Gardner RA. The objective diagnosis of minimal brain dysfunction. Cresskill, NJ: Creative Therapeutics, 1979.
• 18. Tiffin J. Purdue pegboard: examiner manual. Chicago, IL: Science Research Associates, 1968.
• 19. SAS Institute. SAS/STAT user's guide. Vol 2, 4^th Ed. Cary, NC: SAS Institute; 1990.
• 20. Gillberg C, Carlström G, Rasmussen P. Hyperkinetic disorders in seven-year-old children with perceptual, motor and attentional deficits. J Child Psychol Psychiatry 1983;24: 233-246.
• 21. Guardiola A, Fuchs FD, Terra AR, et al. Importância dos aspectos nutricionais como fator associado à síndrome de hiperatividade com déficit de atenção. Arq Neuropsiquiatr 1997;55:598-605.
• 22. Chang SM, Walker SP, Grantham-McGregor S, Powell CA. Early childhood stunting and later behaviour and school achievement. J Child Psychol Psychiatry 2002;43:775-783.
• 23. Clarke NMA, Grantham-McGregor SM, Powell C. Nutrition and health predictors of school failure in Jamaican children. Ecol Food Nutr 1991;55:955-958.
• 24. Moock P, Leslie J. Childhood malnutrition and schooling in the Terai region of Nepal. J Dev Economics 1986;20:33-52.
• 25. Martorell R, Rivera J, Kaplowitz H, Pollit E. Long-term consequences of growth retardation during early childhood. In Hernandez M, Argente J, (eds). Human growth: basic and clinical aspects. Amsterdam: Elsevier, 1992:143-149.
• 26. PAHO. Nutrition, health and child development. Scientific Publication No. 566. Washington, DC: PAHO; 1998.
• 27. Pollitt E, Mueller W. The relation of growth to cognition in a well-nourished preschool population. Child Development 1982;53:1157-1163.
• 28. Morley R, Lucas A. Nutrition and cognitive development. Br Med Bull 1997;53:123-134.
• 29. Susser M. The challenge of causality: human nutrition, brain development and mental performance. Bull NY Acad Med 1989;65:1032-1049.
• 30. Datta S, Patterson EH, Vincitore M, Tonkiss J, Morgane PJ, Galler JR. Prenatal protein-malnourished rats show changes in sleep/wake behavior as adults. J Sleep Res 2000;9:71-79.
• 31. Tonkiss J, Shultz PL, Shumsky JS, et al. Chlordiazepoxide-induced spatial learning deficits: dose-dependent differences following prenatal malnutrition. Pharmacol Biochem Behav 2000;65:105-116.

Publication Dates

• Publication in this collection
  25 Apr 2006
• Date of issue
  Dec 2004

History

• Accepted
  13 July 2004
• Received
  02 Feb 2004
• Reviewed
  13 May 2004