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There was an old saying in the past that the poor family has a precious son.
This means that children whose family environment is not dominant may make up for their disadvantages through their own efforts and achieve social achievements.
But in recent years, I have to admit that it may be difficult to make up for the gap caused by the external environment with personal efforts, and the old saying has gradually evolved into "No matter how difficult it is to have a son in a poor family.
"
In fact, poverty not only brings a lack of learning resources, it is more likely to have a profound impact on children's brain development and cognitive level.
Recently, Dardo Tomasi and others from the National Institute for the Prevention of Alcohol Abuse and Alcoholism (NIAAA) in the United States published important research results in the journal Molecular Psychiatry [1].
They found that low family income levels may bring disadvantages to children’s brain development.
Improving the quality of parental support and education for low-income families may help offset the negative impact of poverty.
Children from poor families are often more likely to face problems such as malnutrition, poor health, and lower levels of education [2].
Low socioeconomic status (SES) in childhood/adolescence may have a profound impact on people's social behavior, cognitive ability and health [3].
It has been reported in the literature that family income and parental education are significantly related to the thickness of the prefrontal cortex in children and adolescents [4]; the more common risk of lead exposure (RLE) in poor areas is related to low intelligence [5].
A study published in "Natural Medicine" in 2020 showed that the negative correlation between lead exposure risk and cognitive test scores is significant in children from low-income families, but not significant among children from middle- and high-income families.
This also means that in areas with a high risk of lead exposure, the cognitive impairment of poor children is more serious [6].
Although there are many studies related to socioeconomic status and brain structure and cognitive level, the relative contribution of different socioeconomic status factors to brain development and the mediating effect of cognition on socioeconomic status and brain structure have not been evaluated .
Therefore, Dardo Tomasi and others intend to quantify the impact of some factors on children's cognition and brain structure (cortical volume (CV) and cortical thickness (CT)), and conduct reproducibility studies in two independent subgroups.
Specific factors include the following: 1) Socio-economic factors: family income (FI), risk of lead exposure (RLE), parental education (PED), regional deprivation index (ADI), an indicator that measures the lack of social resources, which can be understood as poverty 2) Family environment: whether it is an only child (SIB), time spent on screen media activities (SMA) 3) Demographic factors: overweight (EW), gender, age They made two assumptions: 1.
Compared with other socioeconomic status factors, family income has a stronger influence on cognition and brain development; second, cognitive performance can mediate the influence of family income on brain structure.
The analysis data comes from the well-known ABCD study (adolescent brain cognition research) [7], the study lasts for 10 years, involving 21 data collection points across the United States, tracking analysis and depicting the longitudinal study of the dynamic relationship between individual development and brain development.
The study finally included the data of 7784 children and randomly divided them into 2 groups, namely the study group and the verification group (3892 persons each), and the baseline levels of the two groups were similar.
Sure enough, the baseline characteristics are not surprising.
Among the socio-economic status factors, the strongest correlation with the recognition score and brain structure is the family income, and the reproducibility is good! In contrast, the influence of other factors (PED, RLE, ADI) is very low.
Household income is strongly linearly correlated with Fluid Composite and Crystallized Composite in cognitive scores, while Crystallized Composite (which examines oral reading and picture vocabulary) has a steeper line.
This means that the development of language skills is particularly vulnerable to the impact of family poverty, which may be due to the lack of high-quality education for these children and difficulty in accessing more complex spoken and written language in their daily lives.
The strongest correlation between family income (FI) and cognitive scores The strongest correlations between family income and total cortical volume (CV) are the superior frontal gyrus, the middle temporal gyrus, the anterior orbital gyrus, and the anterior cingulate gyrus.
The correlation between household income and average cortical thickness (CT) is most significant in sensory, default mode networks, and language areas, which are very similar to autonomous brain networks.
The impact of household income on CV and CT is slightly different.
Causal Mediation Analysis (CMA) further validates the second hypothesis.
The researchers found that the language and executive function scores in cognitive performance, including inhibitory control and working memory, only partially mediate the relationship between family income and cerebral cortex thickness; while processing speed partially mediates the effect of family income on cerebral cortex thickness and cerebral cortex thickness.
The influence of both volume.
The above results indicate that cognitive stimulation related to family income (for example, the quality of childcare, school quality, family learning environment, etc.
) may mediate the relationship between family income and the thickness and volume of children’s cerebral cortex.
Reports have shown that family management training for parents, including problem handling and support for learning activities, can prevent the adverse effects of poverty on children’s brain development [8].
The research of Dardo Tomasi and others is of great significance to global public health.
They sounded the alarm for everyone, emphasizing the importance of taking preventive measures to reduce the adverse effects of poverty on children.
Studies have shown that the protective effect of prevention strategies can reduce poverty when children enter early adulthood [9].
More importantly, prevention strategies are not only beneficial to the target children, but also have intergenerational effects.
When these children become parents, the cognitive and mental health of their next generation will also improve [10].
References: [1] Tomasi D, Volkow ND.
Associations of family income with cognition and brain structure in USA children: prevention implications [published online ahead of print, 2021 May 14].
Mol Psychiatry.
2021;10.
1038/s41380-021- 01130-0.
doi:10.
1038/s41380-021-01130-0.
[2] Hair NL, Hanson JL, Wolfe BL, Pollak SD.
Association of Child Poverty, Brain Development, and Academic Achievement [published correction appears in JAMA Pediatr.
2015 Sep;169(9):878].
JAMA Pediatr.
2015;169(9):822-829.
doi:10.
1001/jamapediatrics.
2015.
1475.
[3] Hertzman C.
The biological embedding of early experience and its effects on health in adulthood.
Ann NY Acad Sci.
1999;896:85-95.
doi:10.
1111/j.
1749-6632.
1999.
tb08107.
x.
[4] Lawson GM, Duda JT, Avants BB, Wu J, Farah MJ.
Associations between children's socioeconomic status and prefrontal cortical thickness.
Dev Sci.
2013;16(5):641-652.
doi:10.
1111/desc.
12096.
[5] Canfield RL, Henderson CR Jr, Cory-Slechta DA, Cox C, Jusko TA, Lanphear BP.
Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter.
N Engl J Med.
2003;348(16):1517-1526.
doi:10.
1056/NEJMoa022848.
[6] Marshall AT, Betts S, Kan EC, McConnell R, Lanphear BP, Sowell ER.
Association of lead-exposure risk and family income with childhood brain outcomes.
Nat Med.
2020;26(1):91-97.
doi:10.
1038/s41591-019-0713-y.
[7] Jernigan TL, Brown SA, Dowling GJ.
The Adolescent Brain Cognitive Development Study.
J Res Adolesc.
2018;28(1):154-156.
doi:10.
1111/jora.
12374.
[8] Brody GH, Gray JC, Yu T, et al.
Protective Prevention Effects on the Association of Poverty With Brain Development.
JAMA Pediatr.
2017;171(1):46-52.
doi:10.
1001/jamapediatrics.
2016.
2988.
[9] Brody GH, Yu T, Beach SR.
Resilience to adversity and the early origins of disease.
Dev Psychopathol.
2016;28(4pt2):1347-1365.
doi:10.
1017/S0954579416000894.
[10] Hill KG, Bailey JA, Steeger CM, et al.
Outcomes of Childhood Preventive Intervention Across 2 Generations: A Nonrandomized Controlled Trial.
JAMA Pediatr.
2020;174(8):764-771.
doi:10.
1001/jamapediatrics.
2020.
1310.
Author of this article | Responsible editor of Davina | Daisiyu
This means that children whose family environment is not dominant may make up for their disadvantages through their own efforts and achieve social achievements.
But in recent years, I have to admit that it may be difficult to make up for the gap caused by the external environment with personal efforts, and the old saying has gradually evolved into "No matter how difficult it is to have a son in a poor family.
"
In fact, poverty not only brings a lack of learning resources, it is more likely to have a profound impact on children's brain development and cognitive level.
Recently, Dardo Tomasi and others from the National Institute for the Prevention of Alcohol Abuse and Alcoholism (NIAAA) in the United States published important research results in the journal Molecular Psychiatry [1].
They found that low family income levels may bring disadvantages to children’s brain development.
Improving the quality of parental support and education for low-income families may help offset the negative impact of poverty.
Children from poor families are often more likely to face problems such as malnutrition, poor health, and lower levels of education [2].
Low socioeconomic status (SES) in childhood/adolescence may have a profound impact on people's social behavior, cognitive ability and health [3].
It has been reported in the literature that family income and parental education are significantly related to the thickness of the prefrontal cortex in children and adolescents [4]; the more common risk of lead exposure (RLE) in poor areas is related to low intelligence [5].
A study published in "Natural Medicine" in 2020 showed that the negative correlation between lead exposure risk and cognitive test scores is significant in children from low-income families, but not significant among children from middle- and high-income families.
This also means that in areas with a high risk of lead exposure, the cognitive impairment of poor children is more serious [6].
Although there are many studies related to socioeconomic status and brain structure and cognitive level, the relative contribution of different socioeconomic status factors to brain development and the mediating effect of cognition on socioeconomic status and brain structure have not been evaluated .
Therefore, Dardo Tomasi and others intend to quantify the impact of some factors on children's cognition and brain structure (cortical volume (CV) and cortical thickness (CT)), and conduct reproducibility studies in two independent subgroups.
Specific factors include the following: 1) Socio-economic factors: family income (FI), risk of lead exposure (RLE), parental education (PED), regional deprivation index (ADI), an indicator that measures the lack of social resources, which can be understood as poverty 2) Family environment: whether it is an only child (SIB), time spent on screen media activities (SMA) 3) Demographic factors: overweight (EW), gender, age They made two assumptions: 1.
Compared with other socioeconomic status factors, family income has a stronger influence on cognition and brain development; second, cognitive performance can mediate the influence of family income on brain structure.
The analysis data comes from the well-known ABCD study (adolescent brain cognition research) [7], the study lasts for 10 years, involving 21 data collection points across the United States, tracking analysis and depicting the longitudinal study of the dynamic relationship between individual development and brain development.
The study finally included the data of 7784 children and randomly divided them into 2 groups, namely the study group and the verification group (3892 persons each), and the baseline levels of the two groups were similar.
Sure enough, the baseline characteristics are not surprising.
Among the socio-economic status factors, the strongest correlation with the recognition score and brain structure is the family income, and the reproducibility is good! In contrast, the influence of other factors (PED, RLE, ADI) is very low.
Household income is strongly linearly correlated with Fluid Composite and Crystallized Composite in cognitive scores, while Crystallized Composite (which examines oral reading and picture vocabulary) has a steeper line.
This means that the development of language skills is particularly vulnerable to the impact of family poverty, which may be due to the lack of high-quality education for these children and difficulty in accessing more complex spoken and written language in their daily lives.
The strongest correlation between family income (FI) and cognitive scores The strongest correlations between family income and total cortical volume (CV) are the superior frontal gyrus, the middle temporal gyrus, the anterior orbital gyrus, and the anterior cingulate gyrus.
The correlation between household income and average cortical thickness (CT) is most significant in sensory, default mode networks, and language areas, which are very similar to autonomous brain networks.
The impact of household income on CV and CT is slightly different.
Causal Mediation Analysis (CMA) further validates the second hypothesis.
The researchers found that the language and executive function scores in cognitive performance, including inhibitory control and working memory, only partially mediate the relationship between family income and cerebral cortex thickness; while processing speed partially mediates the effect of family income on cerebral cortex thickness and cerebral cortex thickness.
The influence of both volume.
The above results indicate that cognitive stimulation related to family income (for example, the quality of childcare, school quality, family learning environment, etc.
) may mediate the relationship between family income and the thickness and volume of children’s cerebral cortex.
Reports have shown that family management training for parents, including problem handling and support for learning activities, can prevent the adverse effects of poverty on children’s brain development [8].
The research of Dardo Tomasi and others is of great significance to global public health.
They sounded the alarm for everyone, emphasizing the importance of taking preventive measures to reduce the adverse effects of poverty on children.
Studies have shown that the protective effect of prevention strategies can reduce poverty when children enter early adulthood [9].
More importantly, prevention strategies are not only beneficial to the target children, but also have intergenerational effects.
When these children become parents, the cognitive and mental health of their next generation will also improve [10].
References: [1] Tomasi D, Volkow ND.
Associations of family income with cognition and brain structure in USA children: prevention implications [published online ahead of print, 2021 May 14].
Mol Psychiatry.
2021;10.
1038/s41380-021- 01130-0.
doi:10.
1038/s41380-021-01130-0.
[2] Hair NL, Hanson JL, Wolfe BL, Pollak SD.
Association of Child Poverty, Brain Development, and Academic Achievement [published correction appears in JAMA Pediatr.
2015 Sep;169(9):878].
JAMA Pediatr.
2015;169(9):822-829.
doi:10.
1001/jamapediatrics.
2015.
1475.
[3] Hertzman C.
The biological embedding of early experience and its effects on health in adulthood.
Ann NY Acad Sci.
1999;896:85-95.
doi:10.
1111/j.
1749-6632.
1999.
tb08107.
x.
[4] Lawson GM, Duda JT, Avants BB, Wu J, Farah MJ.
Associations between children's socioeconomic status and prefrontal cortical thickness.
Dev Sci.
2013;16(5):641-652.
doi:10.
1111/desc.
12096.
[5] Canfield RL, Henderson CR Jr, Cory-Slechta DA, Cox C, Jusko TA, Lanphear BP.
Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter.
N Engl J Med.
2003;348(16):1517-1526.
doi:10.
1056/NEJMoa022848.
[6] Marshall AT, Betts S, Kan EC, McConnell R, Lanphear BP, Sowell ER.
Association of lead-exposure risk and family income with childhood brain outcomes.
Nat Med.
2020;26(1):91-97.
doi:10.
1038/s41591-019-0713-y.
[7] Jernigan TL, Brown SA, Dowling GJ.
The Adolescent Brain Cognitive Development Study.
J Res Adolesc.
2018;28(1):154-156.
doi:10.
1111/jora.
12374.
[8] Brody GH, Gray JC, Yu T, et al.
Protective Prevention Effects on the Association of Poverty With Brain Development.
JAMA Pediatr.
2017;171(1):46-52.
doi:10.
1001/jamapediatrics.
2016.
2988.
[9] Brody GH, Yu T, Beach SR.
Resilience to adversity and the early origins of disease.
Dev Psychopathol.
2016;28(4pt2):1347-1365.
doi:10.
1017/S0954579416000894.
[10] Hill KG, Bailey JA, Steeger CM, et al.
Outcomes of Childhood Preventive Intervention Across 2 Generations: A Nonrandomized Controlled Trial.
JAMA Pediatr.
2020;174(8):764-771.
doi:10.
1001/jamapediatrics.
2020.
1310.
Author of this article | Responsible editor of Davina | Daisiyu
