Multiple outside factors affect cognitive performance of teenage girls: Local study 

  • Finds negative impact from poor socio-economic state, stress, stunting, and fatness

BY Ruwan Laknath Jayakody 

Poor socio-economic state, stress, stunting and fatness, a local study found, is negatively linked with the cognitive performance (CP) of female adolescents while the school type, family type and size, place of residence, the percentage of school attendance, the age group, the body mass index (BMI) for the age Z-score (BAZ) and the waist height ratio (WHtR) were not significantly associated with CP. 

These findings were made in an original article on “Poor socio-economic state, stress, stunting and fatness are negatively associated with the CP of female adolescents” which was authored by H.J.H. Madhushanthi (Ruhuna University’s Allied Health Sciences Faculty’s Nursing Department’s Senior Lecturer), S.W. Wimalasekera (Sri Jayewardenepura University’s Physiology Department’s Physiology Professor), C.S.E. Goonewardena (Sri Jayewardenepura University’s Medical Sciences Faculty’s Community Medicine Department’s Community Medicine Professor), A.A.T.D. Amarasekara (Sri Jayewardenepura University’s Allied Health Sciences Faculty’s Nursing and Midwifery Department’s Senior Lecturer) and J. Lenora (Ruhuna University’s Medical Faculty’s Physiology Department’s Physiology Professor) and published in the Sri Lanka Journal of Child Health 50 (4) in December 2021. 

Ages 11 to 14 years, considered early adolescence, is, as noted by the World Health Organisation’s “Nutrition in adolescence: Issues and challenges for the health sector: Issues in adolescent health and development”, characterised by significant physical, psychological, social and cognitive transformation. The prefrontal cortex of the brain, involved in high order cognitive outcomes, E. Sowell’s “Mapping continued brain growth and gray matter density reduction in dorsal frontal cortex: Inverse relationships during post-adolescent brain maturation” explained, undergoes a different development trajectory during adolescence. Since CP is influenced by nutritional, environmental and genetic factors, any issues with regard to nutrition and environmental factors during adolescence, B.T. Crookston, M.E. Penny, S.C. Alder, T.T. Dickerson, R.M. Merrill, J.B. Stanford, C.A. Porucznik and K.A. Dearden’s “Children who recover from early stunting and children who are not stunted demonstrate similar levels of cognition” noted, lead to the alteration of cognitive tasks governed by the frontal lobe. Hence, in the early years of life, as M. Bornstein and D. Putnick observed in “Cognitive and socio-emotional care giving in developing countries”, nutrition and socio-emotional factors play a major role in cognitive development. Studies (G. Fink and P.C. Rockers’s “Childhood growth, schooling and cognitive development: Further evidence from the Young Lives study”, N. Sokolovic, S. Selvam, K. Srinivasan, P. Thankachan, A. Kurpad and T. Thomas’s “Catch up growth does not associate with cognitive development in Indian school age children”, Sandjaja, B.K. Poh, N. Rojroonwasinkul, B.K.L. Nyugen, B. Budiman, L.O. Ng, K. Soonthorndhada, H.T. Xuyen, P. Deurenberg, P. Parikh and the South East Asian Nutrition Survey Study Group’s “Relationship between anthropometric indicators and CP in South East Asian school aged children”, K. Noble, M. Norman and M. Farah’s “Neuro-cognitive correlates of socio-economic status in kindergarten children” and D.A. Hackman, M.J. Farah and M.J. Meaney’s “Socio-economic status and the brain mechanistic insights from human and animal research”) reported that school aged children with protein energy malnutrition have poor performance on cognitive tasks like attention, memory, executive function, visuo-spatial ability, learning and intelligence quotient (IQ), while poor nonverbal intelligence scores of school aged children is associated with being underweight and stunting, and poor socio-economic status is associated with several cognitive deficits, language and executive function reading and school achievements. 

Therefore, Madhushanthi et al. sought to assess the nutritional and psycho-social factors affecting the CP of early female adolescent school children in the Galle educational zone. Hence, they conducted a descriptive, cross sectional study in randomly selected schools (including schools and classes representing all school categories) with 218 female adolescents between the ages of 11 to 14 years who were residing in the Galle City being recruited as participants. 

With regard to anthropometric measurements, the weight, height, waist circumference (WC) and the hip circumference (HC) were measured; the BMI, the fat mass percentage (FM%), the waist hip ratio (WHR) and the WHtR were calculated to assess the nutritional status; and the height for age Z-score (HAZ), the weight for age Z-score (WAZ) and the BAZ were calculated. Adolescents with HAZ, WAZ and BAZ reference values below the minus two standard deviation score were categorised as stunted, underweight and thin, respectively. 

Concerning the measurement of socio-economic and psycho-social adversities, it is noted that the socio-economic status (SES) is a composite index of parental education, occupation and income (the income to need ratio was calculated by dividing the total family income with the official poverty threshold published by the Census and Statistics Department for a family of that size). 

An interviewer administered psycho-social adversity scale was used to assess psycho-socially adverse factors. Adolescent stress was assessed using the interviewer administered adolescence stress questionnaire comprising 51 items measuring nine dimensions of adolescent stress including the stress of home life, school performance, school attendance, romantic relationships, peer pressure, teacher interaction, future uncertainty, school-leisure conflict and emerging adult responsibility, with each item rated as not at all stressful/irrelevant to me, a little stressful, moderately stressful, quite stressful and very stressful. 

When it came to the measurement of CP, three cognitive test batteries, intelligence tests (to measure various cognitive skills where eight subtests were used to assess four cognitive domains, namely, the verbal comprehension index on similarities and comprehension, the working memory index on the digit span and symbol search, the perceptual reasoning index on picture completion and matrix reasoning, and the processing speed index on cancellation and arithmetic), tests of non-verbal intelligence (examines cognitive function that do not require verbal or motor skills and used to measure abstract reasoning) and two computer based executive function tasks (inhibition control and visuo-spatial working memory) were used. 

The mean (average) age of the study participants was 12.31 years. 

On the psychological stress of adolescents, 158 (72.5%) belonged to the stressed group while 60 (27.5%) belonged to the non-stressed group. Stress was observed for school attendance (93.1%), future uncertainty (92.7%), school performance (84.9%), emerging responsibility (85.3%) and the conflict of school-leisure time (81.7%). Most adolescents considered the stress of future uncertainty and school attendance as the greatest stress inducing factors. 

On the association of the cognitive test scores and the adolescent stress questionnaire (ASQ) total score, the results indicated a significant effect of stress on the entire cognitive function test scores. 

On the association of the cognitive test scores and the demographic variables, the effects of the family type, the number of siblings, the place of residence, the percentage of school attendance and the school type on all cognitive test profiles were not statistically significant. 

On the association of the cognitive test scores and the socio-economic variables, the SES index was positively correlated with the verbal comprehension index (VCI), the working memory index (WMI), the estimated full scale intelligence quota (EFSIQ), the perceptual reasoning index (PRI), the processing speed index (PSI), and the visuo-spatial working memory. Poor inhibitory control (increased stop signal delay) was associated with a low SES index. Except for the visuo-spatial working memory, an inverse relationship was found between the future ready (PA) index (a collection of school progress measures related to school and student success) and the scores of the VCI, PSI, WMI, PRI, EFSIQ, the tests of non-verbal intelligence (TONI) and inhibitory control. 

On the association of the cognitive test scores and the nutritional parameters, the HAZ is significantly and positively associated with the PSI, WMI, PRI, EFSIQ and visuo-spatial working memory. Decreased HAZ is correlated with poor inhibitory control. WAZ was not correlated with most cognitive indices except the visuo-spatial working memory. No significant correlations were observed between the BAZ and WHtR with any cognitive test scores.

On the predictors of the CP of female adolescents, the school type, family type, place of residence, family size, the percentage of school attendance and age group, the BAZ and the WHtR were not significantly associated with CP. The anthropometric parameters (the HAZ, WAZ, FM%, WC, HC, and WHR) and the psychosocial variables (the SES index, the PA index score, and the ASQ total score) were significantly associated with the cognitive function test scores. The data showed multi co-linearity between the SES index and the PA index. The SES is a significant factor influencing child cognitive development. 

Regression analysis was conducted to determine the extent of the variance of the cognitive tests as explained by the anthropometric and socio-economic parameters, and the results showed that the regression model was statistically significant for the dependent variables (the VCI, PRI, WMI, PSI, EFSIQ, TONI score, visuo-spatial working memory and inhibitory control). 

A combination of the SES index, the ASQ total score and the HAZ significantly accounted for a 10.9% variance of the EFSIQ. The SES index was found to be positively and significantly associated with most cognitive variables including the VCI, PSI, WMI, PRI, EFSIQ, visuo-spatial working memory and inhibitory control. Increased HAZ was found to be positively associated with the PSI, EFSIQ, visuo-spatial working memory and inhibitory control scores. A single unit increase of FM% resulted in a unit reduction of the PSI score, the TONI score and the visuo-spatial working memory. 

Madhushanthi et al. showed that anthropometric nutritional indicators (the HAZ, FM% and WC), stress, the SES index and ASQ total score were significant predictors of CP amongst early female adolescents. As shown by Poh et al. and A. Eilander, S. Muthayya, H.V.D. Knaap, K. Srinivasan, T. Thomas, F.J. Kok, A.V. Kurpad and S.J.M. Osendarp’s “Under-nutrition, fatty acid and micronutrient status in relation to CP in Indian school children: A cross sectional study”, the chosen cognitive abilities are vulnerable for macronutrient deficiencies. Stunting (low HAZ) is negatively associated with cognitive outcomes, Madhushanthi et al. explained. Per Sokolovic et al. and B. Kar, S. Rao and B. Chandramouli’s “Cognitive development in children with chronic protein energy malnutrition”, the decreased availability of energy and micronutrients during the adolescent growth period resulted in decreased linear growth, reduced neurodevelopment of the brain and changes in behaviour and cognition. J. Bryan, S. Osendarp, D. Hughes, E. Calvaresi, K. Baghurst and J.V. Klinken’s “Nutrients for cognitive development in school aged children” noted that long-term protein energy malnutrition leads to altered brain architecture and neuronal functions while per D. Benton, P. Winichagoon, T. Ng, E. Tee and M. Isabelle’s “Symposium on nutrition and cognition towards research and application for different life stages” observed the retardation of growth in the hippocampus (complex brain structure embedded deep into the temporal lobe and has a major role in learning and memory), frontal lobe and temporal lobes which are involved in higher order cognitive tasks. According to the social isolation theory (S. Grantham-McGregor and H. Baker-Henningham’s “Review of the evidence linking protein and energy to mental development”), under-nutrition has a role in deficit cognitive outcomes as undernourished children are less explorative and apathetic with reduced activity which contributes to poor environmental stimulation and in turn to poor cognitive development. Impaired cognitive function in adolescence is more likely to continue into adult life and may hinder development of the full intelligence potential as an adult (K. Hanscombe, M. Trzaskowski, C. Haworth, O. Davis, P. Dale and R. Plomin’s “Socio-economic status and children’s intelligence: In a United Kingdom representative sample: SES moderates the environmental, not genetic effect on IQ”).

Madhushanthi et al. found that the family SES index is a robust indicator of most cognitive indices of female adolescents. This shows a strong positive association of higher parental SES with higher scores on cognitive measures and academic tests from early childhood through adolescence (V. McLoyd’s “Socio-economic disadvantage and child development” and Hanscombe et al.). Evidence (Hackman et al.) suggested that the SES-related difference in neural development begins in utero. Madhushanthi et al. found that the SES index significantly predicts verbal comprehension and executive functions (inhibitory control and visuo-spatial working memory). Hackman et al. elaborated on the role of the underlying SES associated differences in neuro-cognitive abilities as being attributed to multiple factors including pre-natal influences, post-natal care and cognitive stimulation. On the other hand, M. Wadsworth, T. Raviv, B. Compas and J. Connor-Smith’s “Parent and adolescent responses to poverty-related stress: Tests of mediated and moderated coping models” observed that inappropriate parenting practices are correlated with emotional and behavioural problems in children that even contribute to problems in later life. 

Compared to adolescents from higher SES backgrounds, adolescents from low SES backgrounds show more psychopathologies like internalised behaviours (depression and schizophrenia [symptoms can include delusions, hallucinations, disorganised speech, trouble with thinking, and the lack of motivation]) and externalised behaviours (S. Qin, E. Hermans, H.V. Marle, J. Luo and G. Fernandez’s “Acute psychological stress reduces working memory-related activity in the dorso-lateral prefrontal cortex”). Persistent stress, according to A. Arnsten and B. Li’s “Neurobiology of executive functions: Catecholamine (hormones made by the adrenal glands which are released into the body in response to physical or emotional stress) influences on prefrontal cortical (relating to the outer layer of the cerebrum) functions”, activates the hypothalamic-pituitary-adrenal axis and elevates stress hormones which adversely affect brain neurodevelopment and compromise cognitive and academic achievements. For R. Romeo, as noted in “The impact of stress on the structure of the adolescent brain: Implications for adolescent mental health”, continued maturation of the cortico-limbic regions in adolescence makes the adolescent brain more vulnerable to stress. Studies (S.P. Walker, T.D. Wachs, J.M. Gardner, B. Lozoff, G.A. Wasserman, E. Pollitt, J.A. Carter and the International Child Development Steering Group’s “Child development: Risk factors for adverse outcomes in developing countries”) suggest that stress exerted structural changes in the prefrontal cortex during adolescence would cause long lasting psychopathologies compared to stress experienced during adult life. There is evidence (H. Saint Clair-Thompson, R. Stevens, A. Hunt and E. Bolder’s “Educational psychology: An International Journal of Experimental Educational Psychology”) that school-based working memory training boosts the performance in mathematics, IQ and the classroom performance of children and adolescents. 

In conclusion, Madhushanthi et al. found that SES plays a crucial role in the neuro-cognitive profile of female adolescents with the study highlighting the influence of low HAZ, SES, psychological stress and increased fatness as indicators that contribute to the poor CP of female adolescents.