ABSTRACT

OBJECTIVE

To investigate the effects of depressive symptoms in childhood on the intellectual development of young adults.

METHODS

Study conducted with a birth cohort of São Luís, Maranhão, Brazil, composed of 339 participants evaluated between 7 and 9 years and between 18 and 19 years. Structural equation modeling (young adult education, sex, race/color) and childhood variables (nutritional status, depressive symptoms, cognitive function, head of household’s and mother’s education, family income) were used. In addition, head of household’s occupation, mother’s age, and presence of partner were tested as determinants of adults’ intelligence quotient (IQ).

RESULTS

Presence of depressive symptoms in childhood triggered a reduction of 0.342 in standard deviation (SD) and -3.83 points in the average IQ of adults (p-value < 0.001). Cognitive function in childhood had a total and direct positive effect (standardized coefficient [SC] = 0.701; p-value < 0.001) on IQ, increasing 7.84 points with each increase in level. A positive indirect effect of child nutritional status (SC = 0.194; p-value = 0.045), head of household’s (SC = 0.162; p-value = 0.036), and mother’s education was identified, the latter mediated by cognitive function in childhood (SC = 0.215; p-value = 0.012) on the IQ of young people.

CONCLUSION

Presence of depressive symptoms in childhood triggered a long-term negative effect on intelligence, reducing the IQ score in adulthood.

Child; Adult; Depression; Intelligence

INTRODUCTION

The development of cognitive skills, mainly represented by intelligence and academic performance, has been widely studied due to its impact on socially relevant outcomes such as leadership ability, success at work, and social life¹1. Schelini PW, Almeida LS, Primi R. Aumento da inteligência ao longo do tempo: efeito Flynn e suas possíveis causas. Psico-USF. 2013;18(1):45-52. https://doi.org/10.1590/S1413-82712013000100006
https://doi.org/10.1590/S1413-8271201300... ,²2. Nakano TC, Moraes ID, Oliveira AW. Moraes IDT, Oliveira AW Relação entre inteligência e competências socioemocionais em crianças e adolescentes. Rev Psicol. 2019;37(2):407-24. https://doi.org/10.18800/psico.201902.002
https://doi.org/10.18800/psico.201902.00... .

Although intelligence is strongly influenced by heredity, parental stimulation, education, and nutritional and psychological status are known to also affect its development³3. Papalia DE, Feldman RD. Desenvolvimento humano. 12a ed. [place unknown]: McGraw Hill; 2013.. Among these variables, the mental health of children and adolescents has been the subject of many studies⁴4. Erskine HE, Baxter AJ, Patton G, Moffitt TE, Patel V, Whiteford HA. The global coverage of prevalence data for mental disorders in children and adolescents. Epidemiol Psychiatr Sci. Published online 2017;26(4):395-402. https://doi.org/10.1017/S2045796015001158
https://doi.org/10.1017/S204579601500115... due to the high worldwide prevalence of mental disorders in this age group in recent years, especially depression, which was identified in 6.2% of individuals aged 5 to 17 in 38 countries⁴4. Erskine HE, Baxter AJ, Patton G, Moffitt TE, Patel V, Whiteford HA. The global coverage of prevalence data for mental disorders in children and adolescents. Epidemiol Psychiatr Sci. Published online 2017;26(4):395-402. https://doi.org/10.1017/S2045796015001158
https://doi.org/10.1017/S204579601500115... . In Brazil, depressive disorders have been the most prevalent among the mental problems that affect children and adolescents⁵5. Thiengo DL, Cavalcante MT, Lovisi GM. Prevalência de transtornos mentais entre crianças e adolescentes e fatores associados: uma revisão sistemática. J Bras Psiquiatr. 2015;63(4):360-72. https://doi.org/10.1590/0047-2085000000046
https://doi.org/10.1590/0047-20850000000... ,⁸8. Silva AA, Barbieri MA, Cardoso VC, Batista RF, Simões VM, Vianna EO, et al. Prevalence of non-communicable diseases in Brazilian children: follow-up at school age of two Brazilian birth cohorts of the 1990’s. BMC Public Health. 2011 Jun;11(1):486. https://doi.org/10.1186/1471-2458-11-486
https://doi.org/10.1186/1471-2458-11-486... .

There is evidence that symptoms of internalization and cognitive ability are interrelated variables in child development until adolescence⁶6. Papachristou E, Flouri E. The codevelopment of internalizing symptoms, externalizing symptoms, and cognitive ability across childhood and adolescence. Dev Psychopathol. 2020 Oct;32(4):1375-89. https://doi.org/10.1017/S0954579419001330
https://doi.org/10.1017/S095457941900133... . However, a study conducted with Canadian children did not find significant evidence that the presence of internalization symptoms interfered with academic performance in adolescence, which is directly related to intellectual development. The only significant effect was a positive association of internalization with academic performance from 4 to 11 years of age⁹9. Weeks M, Ploubidis GB, Cairney J, Wild TC, Naicker K, Colman I. Developmental pathways linking childhood and adolescent internalizing, externalizing, academic competence, and adolescent depression. J Adolesc. 2016 Aug;51(1):30-40. https://doi.org/10.1016/j.adolescence.2016.05.009
https://doi.org/10.1016/j.adolescence.20... .

Changes caused by depressive symptoms usually cause significant damage to a child’s life, affecting their behavior at home, at school and with friends. The drop in school performance is one of the first indicators of depression in children, in addition to the development of dysphoria, isolation, and sadness¹⁰10. Cruvinel M, Boruchovitch E. Compreendendo a depressão infantil. Petrópolis: Vozes; 2014..

It remains unclear how depressive symptoms can interfere with intellectual development until adulthood, with the pathways of association between these variables, and how one variable influences another. It is also necessary to understand if the difficulties of one cause difficulties in another or if they relate only because they share causes.

Thus, the objective of this study is to answer the following questions: does the presence of depressive symptoms in childhood have a direct effect on the adult’s intelligence? Do parents’ socioeconomic variables during childhood have a greater effect on the adult’s intelligence than the presence of depressive symptoms in childhood? Is the association between childhood depressive symptoms and adult intelligence mediated by childhood cognition?

METHODS

Study Design

This is a cohort study conducted with individuals born in the city of São Luís, Maranhão, Brazil, involving two different periods: childhood and adulthood. This cohort is part of the research Determinantes ao longo do ciclo vital da obesidade, precursores de doenças crônicas, capital humano e saúde mental (Determinants throughout the life cycle of obesity, precursors of chronic diseases, human capital and mental health), developed by the Universidade Federal do Maranhão (UFMA), Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (FMRP/USP) and the Universidade Federal de Pelotas (UFPel)..

Study Population and Sample

The first phase of the cohort was initiated at birth in 10 public and private hospitals in the city, from March 1997 to February 1998, including 96.3% of births of the period through systematic sampling with proportional stratification according to the number of births in each maternity in one out of seven deliveries. Multiple births, stillbirths, and twin births were excluded. The final sample totaled 2,443 births¹¹11. Silva AA, Coimbra LC, Silva RA, Alves MT, Lamy Filho F, Lamy ZC, et al. Perinatal health and mother-child health care in the municipality of São Luís, Maranhão State, Brazil. Cad Saúde Pública. 2001;17(6):1413-23. https://doi.org/10.1590/S0102-311X2001000600012
https://doi.org/10.1590/S0102-311X200100... .

The second phase occurred when the children were 7 to 9 years old, in 2005 and 2006, through a complex sampling design, using the variable birth weight to define the sample necessary for evaluation at school age. The final sample totaled 805 children in this phase, 673 being followed since birth and 132 children born between 1997 and 1998 included in the retrospective cohort⁸8. Silva AA, Barbieri MA, Cardoso VC, Batista RF, Simões VM, Vianna EO, et al. Prevalence of non-communicable diseases in Brazilian children: follow-up at school age of two Brazilian birth cohorts of the 1990’s. BMC Public Health. 2011 Jun;11(1):486. https://doi.org/10.1186/1471-2458-11-486
https://doi.org/10.1186/1471-2458-11-486... .

The third phase occurred from January to November 2016, when the subjects were 18–19 years of age. Of the 805 participants from the previous stage, 339 participated in this follow-up. At this stage, we investigated socioeconomic and demographic status, income, lifestyle habits, cognitive skills, mental illness, among others¹²12. Simões VM, Batista RF, Alves MTSS, Ribeiro CCC, Thomaz EBAF, Carvalo CA et al. Health of adolescents in the 1997/1998 birth cohort in São Luís, Maranhão State, Brazil. Cad Saude Publica. 2020;36(7):e00164519. https://doi.org/10.1590/0102-311X00164519
https://doi.org/10.1590/0102-311X0016451... . The study included subjects who, at the time of evaluation, underwent tests of mental health, cognitive function in childhood and intellectual development in adulthood.

Data Collection

In the school phase, a standardized questionnaire was applied to parents or guardians of children containing demographic questions. Weight and height were measured, with the children barefoot and in light clothing, using a periodically calibrated precision scale and an anthropometer⁸8. Silva AA, Barbieri MA, Cardoso VC, Batista RF, Simões VM, Vianna EO, et al. Prevalence of non-communicable diseases in Brazilian children: follow-up at school age of two Brazilian birth cohorts of the 1990’s. BMC Public Health. 2011 Jun;11(1):486. https://doi.org/10.1186/1471-2458-11-486
https://doi.org/10.1186/1471-2458-11-486... . To assess cognitive function in childhood, the Raven’s Colored Progressive Matrices (RCPM) was applied, which assesses general aspects of intelligence¹³13. Angelini AL, Alves ICB, Custódio EM, Duarte WF. Matrizes manuais progressivas coloridas de Raven (Escala Especial): padronização brasileira. São Paulo: Casa do Psicólogo; 1987.; and the Draw-a-Person test (DAP test), which assesses emotional maturity and psychomotor development¹⁴14. Wechsler SM. HFD III: o desenho da figura humana: avaliação do desenvolvimento cognitivo de crianças brasileiras. São Paulo: Editora da Pontifícia Universidade Católica de São Paulo; 2003.. To assess the presence of depressive symptoms in childhood, the Children’s Depression Inventory was used¹⁵15. Gouveia VV, Barbosa GA, Almeida HJ, Gaião AA. Children’s depression inventory - CDI: adaptation study with students of João Pessoa. J Bras Psiq. 1995;44(7):345-9. Portuguese..

Adult intelligence was assessed by the Wechsler Adult Intelligence Scale (WAIS III), which depicts a punctual measure of intelligence level. To verify the results, the raw data of the verbal and execution scales were initially analyzed. From the sum of scores of all subtests, the crude results were converted into weighted results and analyzed by the table corresponding to the WAIS III manual. The total intelligence quotient (IQ) was obtained by summing the raw values of the verbal and execution scales, and analyzing the values in the table by age, reflecting the participants’ intelligence levels¹⁶16. Wechsler D. WAIS-III: Escala de inteligência Wechsler para adultos. São Paulo: Casa do Psicólogo; 2004.. In cases where the participant had any condition that made it impossible to perform the test, it was not applied.

Variables

The dependent variable was the IQ of the young adult, obtained through the application of WAIS-III. For the theoretical model tested, the variable was treated as continuous numerical. For classification purposes, it can be categorized as: lower (≤ 89 points); medium (90 to 109 points); higher (≥ 110 points)¹⁶16. Wechsler D. WAIS-III: Escala de inteligência Wechsler para adultos. São Paulo: Casa do Psicólogo; 2004..

The explanatory variables observed in childhood were: sex (female; male), race/color (black; mixed/yellow/oriental; white); nutritional status: low weight (< 17 kg/m²) or adequate (> 17 kg/m²2. Nakano TC, Moraes ID, Oliveira AW. Moraes IDT, Oliveira AW Relação entre inteligência e competências socioemocionais em crianças e adolescentes. Rev Psicol. 2019;37(2):407-24. https://doi.org/10.18800/psico.201902.002
https://doi.org/10.18800/psico.201902.00... )⁸8. Silva AA, Barbieri MA, Cardoso VC, Batista RF, Simões VM, Vianna EO, et al. Prevalence of non-communicable diseases in Brazilian children: follow-up at school age of two Brazilian birth cohorts of the 1990’s. BMC Public Health. 2011 Jun;11(1):486. https://doi.org/10.1186/1471-2458-11-486
https://doi.org/10.1186/1471-2458-11-486... ; depressive symptoms: absent (≥ 17 points) or present (< 17 points)¹⁵15. Gouveia VV, Barbosa GA, Almeida HJ, Gaião AA. Children’s depression inventory - CDI: adaptation study with students of João Pessoa. J Bras Psiq. 1995;44(7):345-9. Portuguese.; education of the head of household and of the mother in full years (0–4 years; 5–8; 9 or more); family income in minimum wages (continuous numerical); occupation of the head of household (unskilled and unemployed manual; qualified and semi-skilled manual; non-manual); age of the mother (continuous numerical); presence of a partner (no; yes).

The variable cognitive function in childhood was constructed from the variables cognitive function measured by the RCPM test, treated as categorical variable: below average (0–25); average (26–74); above average (75–100)¹³13. Angelini AL, Alves ICB, Custódio EM, Duarte WF. Matrizes manuais progressivas coloridas de Raven (Escala Especial): padronização brasileira. São Paulo: Casa do Psicólogo; 1987. and cognitive function measured by the DAP test, treated as categorical variable: below average (< 25^th percentile); average (25^th percentile); above average (> 25^th percentile)¹⁴14. Wechsler SM. HFD III: o desenho da figura humana: avaliação do desenvolvimento cognitivo de crianças brasileiras. São Paulo: Editora da Pontifícia Universidade Católica de São Paulo; 2003.. The education variable of the young adult was treated as categorical (0–4 years; 5–8; 9 or more).

Statistical Analysis

The descriptive analysis of the data was performed using version 14 of the Stata program (StataCorp., CollegeStation, United States of America). Categorical variables were presented through absolute and relative frequencies, numerical variables by mean and standard deviation.

Structural equation modeling was used¹⁷17. Kline RB. Principles and practice of structural equation modeling. [place unknown]: The Guilford Press; 2011. to investigate the association of depressive symptoms in childhood with covariates and their effects on intelligence in adulthood. A hybrid model was built, composed of confirmatory factor analysis used to construct the latent variable cognitive function in childhood and pathway analysis used to analyze the effects of depressive symptoms in childhood on the IQ in adulthood and estimate the linear relationships between the variables. For this, version 7 of the Mplus software was used.

According to the proposed theoretical model, the family socioeconomic variables observed during the participant’s childhood, occupied the most distal position and indicated the presence of depressive symptoms, nutritional status and cognitive function of the child, which determined the education of the young adult and their IQ (Figure).

The estimator used was the robust weighted least squares mean and variance adjusted (WLSMV), used for analysis of the observed categorical variables. Theta parameterization (θ) was used to control differences in residual variances.

The missing data were imputed to the variables by Mplus software, based on the variables prior to the parameterization in the theoretical model, using frequency and Bayesian analyses¹⁸18. Wang J, Wang X. Structural equation modeling: applications using mplus. [place unknown]: Thomson Digital; 2012. https://doi.org/10.1002/9781118356258
https://doi.org/10.1002/9781118356258... . With this imputation, the missing data did not hinder the result.

To evaluate the model fit, the following was considered as good: a) p-value > 0.05 for the Chi-square test (χ²); b) root mean square error of approximation (RMSEA) value < 0.05 and upper limit of the 90% confidence interval < 0.08; c) values greater than 0.95 for the comparative fit index (CFI) and the Tucker-Lewis index (TLI); and d) weighted root mean square residual (WRMR) values < 1¹⁷17. Kline RB. Principles and practice of structural equation modeling. [place unknown]: The Guilford Press; 2011..

In the analysis of the standardized estimates for the construction of the latent variable cognition in childhood, factor load > 0.5 was considered with a p-value < 0.05 as indicative that the correlation between the observed variable and the construct is moderately high in magnitude¹⁷17. Kline RB. Principles and practice of structural equation modeling. [place unknown]: The Guilford Press; 2011..

The modindices command was used to obtain suggestions for changes in the initial hypotheses¹⁸18. Wang J, Wang X. Structural equation modeling: applications using mplus. [place unknown]: Thomson Digital; 2012. https://doi.org/10.1002/9781118356258
https://doi.org/10.1002/9781118356258... , however, there were no plausible proposals from a theoretical point of view. In the final model, the total, direct, and indirect effects of the latent and observed variables were evaluated. An effect was considered when p-value was < 0.05.

To interpret the effects of the variables on the IQ of young adults, the value of the standardized coefficient of the total effect obtained in the structural model was multiplied by the standard deviation of the IQ.

Ethical Aspects

The study met the criteria of Resolution¹⁹19. Ministério da Saúde (BR). Conselho Nacional de Saúde. Resolução nº 466, de 12 de dezembro de 2012. Brasília, DF: Ministério da Saúde; 2012. 466/2012of the National Health Council of Brazil. The subjects’ guardians signed an informed consent form (ICF). Withdrawal was allowed without any prejudice to the interviewee at any stage of the research. The projects and the ICFs of both phases of the research were approved by the Research Ethics Committee of the Hospital Universitário da Universidade Federal do Maranhão: Consolidated Opinion No. 60, of April 18, 2005, and Consolidated Opinion No. 1,302,489, of October 29, 2015.

RESULTS

In the sample of 339 young adults, 55.16% were female, 67.85% were mixed/yellow/oriental and 83.78% had 5 to 8 years of study (Table 1). The mean IQ of the participants was 99.45 (11.19) points. The majority (60.47%) achieved results classified as average, with the lowest performance being 70 and the highest 137 points.

During childhood, 92.31% of the study participants had adequate nutritional status and 18.29% had depressive symptoms. According to the RCPM test, 44.25% presented average cognitive function in this phase and, according to the DAP, 56.64%. The mean age of the participants’ mothers in this phase was 23.15 (5,22) years. Most of them lived with a partner (79.29%) and had 9 or more years of study (58.41%). Regarding the heads of households, 56.64% were unemployed or engaged in unskilled manual occupation and 42.18% had 9 or more years of education. The income of 67.85% of families was between one and less than four minimum wages (Table 1).

The model proposed to investigate the pathways of the association between the presence of depressive symptoms in childhood and intelligence in adulthood presented a good fit for the indicators RMSEA, CFI, TLI, and WRMR (Table 2) and there were no plausible suggestions for modification.

The factor analysis for the construction of cognitive function in childhood showed that the indicator variables correlated with the construct, presenting a factor load > 0.5 and p values < 0.001 (Table 3).

The presence of depressive symptoms in childhood had a total negative effect of -0.342 SD on the average IQ in adulthood (Table 4), which corresponds to -3.83 points (p-value < 0.001). Cognitive development in childhood had a total and direct positive effect on IQ (Table 4), revealing an increase of 0.701 SD in its average (p-value < 0.001), corresponding to an increase of 7.84 points at each elevation in the level of child cognitive development.

The nutritional status of the participant in childhood (SC = 0.240; p-value = 0.002) and the levels of education of the head of household (SC = 0.227; p-value < 0.001) and of the mother of the participant in this phase (SC = 0.163; p-value = 0.004) showed a total positive effect, predominantly indirect, on IQ in adulthood (Table 4). The positive indirect effect of maternal education on IQ was mediated by childhood cognition (SC = 0.215; p-value = 0.012) (Table 4).

DISCUSSION

In this study, the presence of depressive symptoms in children had negative long-term results in the development of intelligence, reducing the IQ score in adulthood. This effect was not mediated by cognitive function in childhood, whose impact on IQ was direct. Positive indirect effects of the participant’s nutritional status in childhood, levels of education of the mother and of the head of household on the adult IQ score were observed. Additionally, we observed that cognition in childhood seems to mediate the positive effect of maternal education on the IQ score in adulthood.

It is possible that the reduction in IQ observed in young adults who had depressive symptoms in childhood is explained by the impaired ability to think, concentrate, or make decisions that accompany these symptoms in children. In this age group, the drop in school performance is one of the first signs of depression and can be a manifestation of attention deficit¹⁰10. Cruvinel M, Boruchovitch E. Compreendendo a depressão infantil. Petrópolis: Vozes; 2014.. In this study, depressive symptoms in childhood had a direct negative effect on the education of young adults. Another possible explanation is that depressive symptoms detected in childhood can persist and be intensified into adulthood, thus generating lifelong impacts²⁰20. Veldman K, Reijneveld SA, Verhulst FC, Ortiz JA, Bültmann U. A life course perspective on mental health problems, employment, and work outcomes. Scand J Work Environ Health. 2017 Jul;43(4):316-25. https://doi.org/10.5271/sjweh.3651
https://doi.org/10.5271/sjweh.3651... . Previous studies have shown that changes in mental health in childhood and adolescence can compromise academic performance and the level of education achieved, and the latter, in turn, can impact the job opportunities and careers of these individuals²¹21. Groot S, Veldman K, Amick III, BC, Oldehinkel TAJ, Arends I, Bültmann U. Does the timing and duration of mental health problems during childhood and adolescence matter for labour market participation of young adults ? J Epidemiol Community Heal. 75(9):896-902. https://doi.org/10.1136/jech-2020-215994
https://doi.org/10.1136/jech-2020-215994... ,²²22. Minh A, Bültmann U, Reijneveld SA, Zon SKR Van, Mcleod CB. Depressive symptom trajectories and early adult education and employment: comparing longitudinal cohorts in Canada and the United States. Int J Environ Res Public Heal. 2021 Apr;18(8)\;4279. https://doi.org/10.3390/ijerph18084279
https://doi.org/10.3390/ijerph18084279... .

The direct effect of childhood cognition on adult intelligence observed in this study is in line with previous studies, which reveal high cognitive stability throughout life²³23. Yu H, Mccoach DB, Gottfried AW, Eskeles A. Stability of intelligence from infancy through adolescence: an autoregressive latent variable model. Intelligence. 2017 Sep;2018(69):8-15. https://doi.org/10.1016/j.intell.2018.03.011
https://doi.org/10.1016/j.intell.2018.03... ,²⁴24. Karama S, Bastin ME, Murray C, Royle NA, Penke L, Muñoz Maniega S, et al. Childhood cognitive ability accounts for associations between cognitive ability and brain cortical thickness in old age. Mol Psychiatry. 2014 May;19(5):555-9. https://doi.org/10.1038/mp.2013.64
https://doi.org/10.1038/mp.2013.64... . Yu et al.²³23. Yu H, Mccoach DB, Gottfried AW, Eskeles A. Stability of intelligence from infancy through adolescence: an autoregressive latent variable model. Intelligence. 2017 Sep;2018(69):8-15. https://doi.org/10.1016/j.intell.2018.03.011
https://doi.org/10.1016/j.intell.2018.03... observed, using a latent construct of intelligence, that there was considerable stability in intelligence over the four periods investigated: childhood, preschool, school, and adolescence. In addition, the longitudinal progression of intelligence from childhood to adolescence was completely mediated by the intelligence of the previous period. Additionally, data from 588 individuals in the Lothian Birth Cohort 1936 revealed that cognitive ability at age 11 was a predictor of cortical thickness approximately 60 years later and was responsible for more than two-thirds of the cross-sectional association between intelligence and cortical thickness in old age²⁴24. Karama S, Bastin ME, Murray C, Royle NA, Penke L, Muñoz Maniega S, et al. Childhood cognitive ability accounts for associations between cognitive ability and brain cortical thickness in old age. Mol Psychiatry. 2014 May;19(5):555-9. https://doi.org/10.1038/mp.2013.64
https://doi.org/10.1038/mp.2013.64... .

Several studies have already shown the importance of the family’s socioeconomic situation in development and cognition in childhood and throughout life²⁵25. Cave SN, Wright M, Stumm S. Change and stability in the association of parents ’ education with children’s intelligence. Intelligence. 2022;90(Jan-Feb 2021):101597. https://doi.org/10.1016/j.intell.2021.101597
https://doi.org/10.1016/j.intell.2021.10... ,²⁶26. Rindermann H, Ceci SJ. Parents’ education is more important than their wealth in shaping their children’s intelligence: results of 19 samples in seven countries at different developmental levels. J Educ Gift. 2018;41(4):298-326. https://doi.org/10.1177/0162353218799481
https://doi.org/10.1177/0162353218799481... . In this context, education has been used as one of the main indicators of socioeconomic status²⁵25. Cave SN, Wright M, Stumm S. Change and stability in the association of parents ’ education with children’s intelligence. Intelligence. 2022;90(Jan-Feb 2021):101597. https://doi.org/10.1016/j.intell.2021.101597
https://doi.org/10.1016/j.intell.2021.10... . A study conducted with data from seven countries (n = 15.297), including Brazil, revealed that the education of parents could be more important than family wealth in shaping the intelligence of their children (4–22 years)²⁶26. Rindermann H, Ceci SJ. Parents’ education is more important than their wealth in shaping their children’s intelligence: results of 19 samples in seven countries at different developmental levels. J Educ Gift. 2018;41(4):298-326. https://doi.org/10.1177/0162353218799481
https://doi.org/10.1177/0162353218799481... .

The relationship between parenting and child intelligence can be explained by both genetic and environmental factors²⁵25. Cave SN, Wright M, Stumm S. Change and stability in the association of parents ’ education with children’s intelligence. Intelligence. 2022;90(Jan-Feb 2021):101597. https://doi.org/10.1016/j.intell.2021.101597
https://doi.org/10.1016/j.intell.2021.10... ,²⁷27. Stumm S, Ziada ES, Mcmillan A, Rimfeld K, Dale PS, Plomin R. Predicting educational achievement from genomic measures and socioeconomic status. Dev Sci. 2020 May;23(3):e12925: https://doi.org/10.1111/desc.12925
https://doi.org/10.1111/desc.12925... . Parents with a higher level of education seem to invest more money and time in their children, resulting in better health and education conditions²⁸28. Prickett KC, Augustine JM. Maternal education and investments in children’s health. J Marriage Fam. 2016 Feb;78(1):7-25. https://doi.org/10.1111/jomf.12253
https://doi.org/10.1111/jomf.12253... , as well as offering an intellectually more stimulating environment, which could result in superior performance on some tests²⁹29. Jeong J, McCoy DC, Fink G. Paternal and maternal education, caregivers’ support for learning, and early child development in 44 low- and middle-income countries. Early Child Res Q. 2017;41(June):136-48. https://doi.org/10.1016/j.ecresq.2017.07.001
https://doi.org/10.1016/j.ecresq.2017.07... . Evidence from low- and middle-income countries indicates that maternal level of education would be an important protective factor for the child well-being and development³⁰30. Walker SP, Wachs TD, Grantham-McGregor S, Black MM, Nelson CA, Huffman SL, et al. Inequality in early childhood: risk and protective factors for early child development. Lancet. 2011 Oct;378(9799):1325-38. https://doi.org/10.1016/S0140-6736 (11)60555-2
https://doi.org/10.1016/S0140-6736 (11)6... , with an effect apparently superior to that of paternal level of education³¹31. Jeong J, Obradović J, Rasheed M, Charles D, Fink G. Maternal and paternal stimulation: mediators of parenting intervention effects on preschoolers ’ development. J Appl Dev Psychol. 2018 Nov;2019(60):105-18. https://doi.org/10.1016/j.appdev.2018.12.001
https://doi.org/10.1016/j.appdev.2018.12... . Mothers with higher levels of education seem to provide their children with greater learning opportunities, higher quality interaction and less experience of parental stress³²32. Shin JY, Nhan NV. Predictors of parenting stress among Vietnamese mothers of young children with and without cognitive delay. J Intellect Dev Disabil. 2009 Mar;34(1):17-26. https://doi.org/10.1080/13668250802690914
https://doi.org/10.1080/1366825080269091... . In addition to these facts, maternal stimulation is among the main mechanisms that explain the relationship between maternal education and child development³¹31. Jeong J, Obradović J, Rasheed M, Charles D, Fink G. Maternal and paternal stimulation: mediators of parenting intervention effects on preschoolers ’ development. J Appl Dev Psychol. 2018 Nov;2019(60):105-18. https://doi.org/10.1016/j.appdev.2018.12.001
https://doi.org/10.1016/j.appdev.2018.12... ,³³33. Magnuson KA, Sexton HR, Davis-Kean PE, Huston AC. Increases in maternal education and young children’s language skills. Merrill-Palmer Q. 2022;55(3):319-50. https://doi.org/10.1353/mpq.0.0024
https://doi.org/10.1353/mpq.0.0024... .

In agreement with our findings, recent studies show that child development can also be affected by the child’s nutritional conditions³⁴34. Burneo-Garcés C, Cruz-Quintana F, Pérez-García M, Fernández-Alcántara M, Fasfous A, Pérez-Marfil MN. Interaction between socioeconomic status and cognitive development in children aged 7, 9, and 11 years: a cross-sectional study. Dev Neuropsychol. 2019;44(1):1-16. https://doi.org/10.1080/87565641.2018.1554662
https://doi.org/10.1080/87565641.2018.15... ,³⁵35. Galler JR, Bringas-Vega ML, Tang Q, Rabinowitz AG, Musa KI, Chai WJ, et al. Neurodevelopmental effects of childhood malnutrition: a neuroimaging perspective. Neuroimage. 2021 May;231(January):117828. https://doi.org/10.1016/j.neuroimage.2021.117828
https://doi.org/10.1016/j.neuroimage.202... . Proper nutrition, in a critical period like childhood, is critical for lifelong brain functioning³⁵35. Galler JR, Bringas-Vega ML, Tang Q, Rabinowitz AG, Musa KI, Chai WJ, et al. Neurodevelopmental effects of childhood malnutrition: a neuroimaging perspective. Neuroimage. 2021 May;231(January):117828. https://doi.org/10.1016/j.neuroimage.2021.117828
https://doi.org/10.1016/j.neuroimage.202... . In addition, children with adequate nutritional status are able to interact better with their caregivers and the environment, fundamental factors for their full development³⁶36. Prado EL, Dewey KG. Nutrition and brain development in early life. Nutr Rev. 2014 Apr;72(4):267-84. https://doi.org/10.1111/nure.12102
https://doi.org/10.1111/nure.12102... .

A limitation of this study was the loss of follow-up of the subjects, especially during the third phase, due to the difficulty in locating young adults, despite all the search strategies used. With a larger sample, it would be possible to detect other effects of important determinants.

A strong point is the type of study. Cohort studies have advantages in relation to reverse causality and the possibility of monitoring the same population. Another point is the statistical method used: structural equation modeling. This modeling has the advantage of simultaneously dealing with several dependency relationships and can represent latent variables in these relationships, in addition to modeling the measurement error in the estimation process¹⁷17. Kline RB. Principles and practice of structural equation modeling. [place unknown]: The Guilford Press; 2011..

This study demonstrated that IQ in adulthood is directly influenced by levels of cognitive development in childhood. During childhood, favorable socioeconomic status can positively influence IQ in adulthood, but the presence of depressive symptoms can negatively influence IQ in adulthood.

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