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Article

Diminished Returns of Parental Education in Terms of Youth School Performance: Ruling out Regression toward the Mean

by
Shervin Assari
1,*,
Shanika Boyce
2,
Mohsen Bazargan
1,3 and
Cleopatra H. Caldwell
4
1
Department of Family Medicine, Charles R. Drew University of Medicine and Science, Los Angeles, CA 90059, USA
2
Department of Pediatrics, Charles R. Drew University of Medicine and Science, Los Angeles, CA 90059, USA
3
Department of Family Medicine, UCLA Health, Los Angeles, CA 90095, USA
4
Department of Health Behavior and Health Education, University of Michigan, Ann Arbor, MI 48109, USA
*
Author to whom correspondence should be addressed.
Children 2020, 7(7), 74; https://doi.org/10.3390/children7070074
Submission received: 25 May 2020 / Revised: 16 June 2020 / Accepted: 6 July 2020 / Published: 7 July 2020
Browse Figure
Versions Notes

Abstract

:
Background: Minorities’ Diminished Returns (MDRs) refer to systemically weaker effects of socioeconomic status (SES) indicators on various developmental, behavioral, and health outcomes of ethnic minorities compared to non-Hispanic (non-Latino) Whites. Similar MDRs also exist for the effects of parental education on the school performance of ethnic minority youth. Aim: To assess whether regression toward the mean (RTM) has any role in explaining the diminished effects of parental education on the school performance of Black and Hispanic youth relative to non-Hispanic White youth. Materials and methods: Data for this cross-sectional study came from the Monitoring the Future survey (MTF, 2017), a nationally representative survey of American youth in 12th grade. The sample included 10,262 youth who were 12th graders (typically 17–18 years old). The independent variable was parental education with five categories: Some high school, High school graduate, Some college, College graduate, and Graduate school. The outcome was self-reported school performance measured as grade point average (GPA). Ethnicity was the effect modifier. Analysis of variance (ANOVA) and the Tukey Post Hoc test was used to analyze the data. Data visualization (line graphs) was used to visualize the shape of youth GPA as a function of parental education levels across ethnic groups. Results: While a perfect stepwise increase was seen in youth school performance as a result of parental education improvement, this pattern differed considerably across ethnic groups. Such a perfect stepwise increase in youth school performance as a result of the incremental increase in parental education was missing for Black and Hispanic youth. The shape of the association between parental education and youth school performance ruled out regression toward the mean (RTM) as an explanation for the observed diminished effects of parental education on the school performance of Black and Hispanic youth. Conclusion: Diminished returns of parental education on the school performance of Black and Hispanic youth cannot be explained by regression toward the mean. Other factors and contextual processes, such as segregation, discrimination, racism, and poor quality of schools in urban areas, should be investigated in future research.

1. Introduction

“Minorities’ Diminished Returns” (MDRs) refers to the smaller benefit of socioeconomic status (SES) resources for Blacks and Hispanics than for non-Hispanic Whites [1,2]. The literature on MDRs suggests that educational achievement, whether one’s own [3] or that of one’s parents [4], is associated with unequal outcomes across diverse ethnic groups. Compared to non-Hispanic (non-Latino) Whites, Hispanics and Non-Hispanic Blacks experience fewer benefits from their own and their parents’ education, across a wide range of tangible outcomes [2,5,6].
In line with the MDRs phenomenon, educational achievement differentially translates to tangible outcomes for non-Hispanic White families and Black families [1,2]. Among adults, educational attainment shows a weaker negative association with smoking [7], drinking [8], poor diet [9], obesity [10], depression [11], suicidality [12], and mortality [13] for Blacks and Hispanics than for non-Hispanic Whites. Researchers have replicated these findings for children [14], youth [15], adults [11], and older adults [16,17].
MDRs are frequently exhibited in youth. MDRs of family SES on youth outcomes is a mechanism by which ethnic disparities are transmitted from one generation to the next [6,10,18]. Many studies [6,10,18] have shown weaker effects of family SES on youth body mass index (BMI) [10], self-rated health (SRH) [18], attention deficit hyperactivity disorder (ADHD) [19], mental health [20], and impulse control [6] for Black and Hispanic youth than non-Hispanic White youth. Similarly, parental education also shows a weaker association with upward educational mobility [4], school bonding [21], and school performance [22] for Black and Hispanic youth than non-Hispanic White youth.
Researchers have explored several potential underlying mechanisms to explain the MDRs phenomenon. One potential explanation is the close proximity of high SES Hispanic and Black families to non-Hispanic White families, which means an increase in discriminatory experiences [23]. Extensive research has shown a link between discrimination and poor outcomes across domains [24,25]. Another explanation for MDRs may be the low quality of education in urban areas where most ethnic minorities attend schools [26,27]. Finally, highly educated ethnic minorities are more likely to work in worse jobs, which are associated with more stress and less income [28]. As a result, highly educated ethnic minorities accumulate less wealth than non-Hispanic Whites. Thus, MDRs of education may be due to labor market discrimination.
Why MDRs exist is still unclear. Some scholars have attributed the MDRs to the lower quality of education in urban areas where most Black and Hispanic children and youth attend schools. Structural and institutional racism impact the practices and preferences of the labor market [5]. As society differently treats sub-populations, Blacks and non-Hispanic Whites differ in how well they can mobilize their education to secure desired outcomes [1,2]. Non-Whites must expend higher levels of psychosocial effort than Whites in order to achieve the same upward social mobility [4]. Non-Whites consistently put additional psychological and physiological effort into climbing the social ladder, in comparison to Whites [4]. Given the history and legacy of slavery and Jim Crow over centuries and even what is left of that legacy today (e.g., segregation and discrimination), education produces better gains in income, social power, and purchasing power for Whites than for non-Whites [1,2]. As a result, similar educational credentials have a greater positive impact on the living conditions of non-Hispanic Whites than on that of Blacks [1,2]. Blacks are more likely to gain their education in an inner-city school, which are low in resources. Black children and youth commonly experience discrimination [29,30]. Such discrimination increases the risk of problems across domains [24,25,31]. Discrimination may result in MDRs of education [32,33]. These processes are likely to reduce the impact of one’s own and one’s parents’ education on tangible outcomes for Black and Hispanic individuals compared to non-Hispanic White people. Some critics of MDRs, however, have proposed that Regression Toward the Mean (RTM) may explain MDRs. No previous studies, however, have ever explored whether RTM can explain MDRs.
In brief, RTM can be characterized by the high likelihood of values close to the average (mean) of the dependent value for extreme levels of an independent variable [34,35,36]. RTM frequently leads to inaccurate conclusions, wrong inferences, and spurious associations. RTM is observed both in cross-sectional and longitudinal data; however, it is more commonly discussed for repeated measures in the presence or absence of an intervention or a treatment [34,35,36]. Given that RTM has the potential to lead to wrong conclusions, it has been examined extensively in the literature [37,38,39]. This literature shows that RTM is a common problem and source of bias in the health sciences [26,27,37,38,39,40,41]. However, the investigator is not aware of any previous studies that have explored the role of RTM as an explanation for observed MDRs. In other words, it is unknown if the pattern of associations in the MDRs theory follows the expectations that occur in RTM. This is of increasing importance, given that MDRs are receiving growing attention [3,16,19,21,42,43,44,45,46] and have significant policy implications [1,47].
This study aimed to investigate the role of RTM in explaining MDRs of parental education on school performance (academic achievement) of ethnic minority youth. The hypothesis was that RTM does not explain the MDRs of parental education on school performance in ethnic minority groups. To produce generalizable results, a nationally representative sample of non-Hispanic White, Black, and Hispanic youth was used.

2. Materials and Methods

2.1. Design and Settings

This cross-sectional study is a secondary analysis of existing data from the Monitoring the Future (MTF-12th grade) survey. The MTF is a nationally representative survey of American 12th-grade students. The primary aim of the study is to examine the epidemiology and risk factors of youth substance use in the United States. The MTF-12th grade enrolls a national sample of 12th graders that are being followed into adulthood. In the United States, almost 3.8 million students are enrolled in the 12th grade [48]. The MTF used variables such as gender, ethnicity, and urbanity to generate a nationally representative sample.

2.2. Sample and Sampling

The 2017 MTF-12th grade study enrolled individuals who were enrolled in their 12th grade. Exclusion criteria: Not reporting school performance, not reporting ethnicity, not reporting education for either parent, not having any parent in the household, not reporting the number of parents in the household, not being in 12th grade, and Hispanic ethnicity (measured as self-identified). The analytical sample in this study was 10,262 youth.

2.3. Study Variables

Ethnicity. Ethnicity was measured as self-identified. Ethnicity in the current study was a nominal variable, and the moderator variable (non-Hispanic White, Hispanic, and Black).
Parental education. Parental education was a five-level variable as below: 1 = “Some high school,” 2 = “Completed high school,” 3 = “Some college,” 4 = “Completed college,” 5 = “Graduate or professional school after college.” This variable was a nominal variable.
School Performance. Participants’ school performance was measured by asking participants to report their grade point average (GPA). The exact item was, “What is your current overall school performance?” The possible answers were 9 = A (“93–100”), 8 = A- (“90–92”), 7 = B+ (“87–89”), 6 = B (“83–86”), 5 = B- (“80–82”), 4 = C+ (“77–79”), 3 = C (“73–76”), 2 = C- (“70–72”), and 1 = D (”69 or below”). School performance was a continuous measure, with a potential range from 1 to 9. A higher score indicated better school performance.

2.4. Statistics

The investigator used SPSS 23.0 (IBM Inc., Armonk, NY, USA) for data analyses. School performance, a continuous variable, was the outcome. Parental education, a 5-level categorical variable, was the independent variable. Ethnicity was the moderator. Analysis of variance (ANOVA) was used to analyze the data. ANOVA was followed using the Tukey Post Hoc test. Line graphs were used for data visualization. We graphed mean school performance (GPA) by parental education and by ethnicity. In our visualization, RTM would be a potential explanation for MDRs, only if the data showed less than expected effects of the SES resource (independent variable = parental education) at the right tail of the distribution (where parental education is highest). That is, RTM would be a possible explanation if and only if diminished returns were most pronounced at the highest level of parental education. However, if diminished returns are consistent throughout all levels of parental education, then RTM can be ruled out as an explanation for MDRs. In other words, if MDRs are seen for any incremental increase in parental education, then RTM is ruled out as an explanation.

2.5. Ethics

The MTF study protocol is approved by the University of Michigan Institutional Review Board (IRB). All participants gave a written consent/assent, depending on their age at the time of the survey. For the participants who were younger than 18 years old, their parents also signed informed consent.

3. Results

3.1. Univariate Analysis

The sample was composed of 10,262 youth who were all 12th graders. This sample was composed of Hispanics (22.75%), non-Hispanic Blacks (14.90%), or non-Hispanic Whites (62.35%). The sample contained slightly more females (51.6%) than males (48.4%) (Table 1).
Table 2 also described the educational attainment across ethnic groups. As this table shows, non-Hispanic Whites had the highest education, followed by non-Hispanic Blacks. Hispanics had the lowest level of education.

3.2. ANOVA Results

Table 3 shows the results of four sets of ANOVAs, one in the pooled sample, then one in non-Hispanic Whites, one in non-Hispanic Blacks, and one in Hispanics. Then, Table 4 and Table 5 show the results of Tukey Post Hoc test to better understand the ANOVAs presented in Table 3. While a stepwise increase in youth school performance was present as parental education improved in the pooled sample, this pattern differed across various ethnic groups. The stepwise increase in school performance was perfect only for the pooled sample, meaning that with no exception, an increase in parental education was always associated with an increase in school performance. For non-Hispanic White youth, this pattern was almost perfect. However, for non-Hispanic Black and Hispanic youth, the effects of an incremental increase in the level of parental education did not always enhance the student’s school performance, as this pattern was irregular. Thus, there was no stepwise increase in school performance as a result of parental education for ethnic minority youth.

3.3. Data Visualization

We drew five line-graphs. These graphs present mean youth school performance based on parental education. The first two graphs are for the overall sample, first pooled, and then separate lines for each ethnic group. Then, we added three similar graphs; one for Blacks, one for Hispanics, and one for non-Hispanic Whites. In the first graph, there was a perfect stepwise increase in GPA as parental education improved in the pooled sample. As the second graph shows, however, this stepwise increase in GPA could be seen for non-Hispanic White youth but not Black or Hispanic youth. The last graphs also showed the most significant deviation for the form of shape for Black youth. For Black youth, a major anomaly could be seen, which was not due to the end tale of the distribution (highest education) but the lowest educational level. As such, our data visualization ruled out the RTM as an explanation for the observed diminished effects (MDRs) of parental education on the school performance of Black and Hispanic relative to White and non-Hispanic youth (Figure 1).

4. Discussion

This study documented a stepwise increase in school performance for the overall sample of youth. However, such a stepwise increase in school performance as a result of an increase in parental education was absent for non-Hispanic Black and Hispanic youth. As our data visualization showed, RTM seems not to be a plausible explanation for the observed diminished effects of parental education on the school performance of non-Hispanic Black and Hispanic youth relative to non-Hispanic White youth.
While each additional level of parental education always resulted in a significant enhancement of the 12th graders’ school performance in the US, this effect was diminished for ethnic minorities. In addition, MDRs could be seen at all levels of parental education, not merely at the extreme high of parental education, which would be expected if RTM was the reason behind the MDRs. That is, the effect of parental education on youth school performance was always smaller at all thresholds for ethnic minorities, when compared to Whites and non-Hispanics. Thus, RTM is ruled out as the statistical explanation for MDRs.
A large body of research has documented MDRs of various SES indicators for Hispanics and Blacks compared to Whites and non-Hispanics [3,5,46,49]. Similar MDRs are shown across age groups, SES resources, and outcomes [1,2]. Education results in more gain for White and non-Hispanic than for Black and Hispanic children [14], youth [6,10,18], adults [5], and older adults [8]. We have documented similar MDRs in Blacks [17,22], Asian Americans [43], Native Americans [50], Hispanics [3,51], and members of the LGBTQ community [46].
For youth, MDRs of parental education results in the trans-generational transmission of ethnic inequalities [6,10,18]. Many studies [6,10,18] have shown weaker effects of family SES on youth upward educational mobility [4], school bonding [21], and school performance [22] for Black and Hispanic youth than for non-Hispanic White youth. MDRs are not limited to educational outcomes and extend to health outcomes such as tobacco use [7,52,53], alcohol use [3], body mass index (BMI) [10], self-rated health (SRH) [18], attention deficit hyperactivity disorder (ADHD) [19], mental health [20], and impulse control [6].
As shown by Bumpus, Umeh, and Harris [54], Black youth receive smaller benefits from their parents’ social class than non-Hispanic Whites. They found that for youth not in married households, Blacks gain less benefits from their mothers’ occupational prestige on their youth outcomes (particularly college enrollment) than non-Hispanic Whites [54]. Previous research has shown that these patterns hold for education [3], employment [55], income [19,49,51,56,57], and marital status [58].
The difference in the shape of the association between parental education and school performance across ethnic groups is not limited to the right tail of the distribution and can be seen across education levels. This pattern rules out RTM as an explanation for MDRs. We have previously argued that MDRs may be due to racism and discrimination in the US education system and labor market. As a result of racism, segregation, and social stratification, schools have fewer resources in the areas where ethnic minorities receive an education [29,59]. Another mechanism of the MDRs is the US labor market. Due to differential treatment, racism, segregation, and discrimination by the US labor market, Black Americans work in worse jobs than White Americans at all levels of education [60]. Thus, at higher levels of education, Black and Hispanic parents make considerably less income than White and non-Hispanic parents.
The US social system has increased the psychosocial cost of upward social mobility for Black and Hispanic families. Being charged with extra costs for their upward social mobility, Black families gain less from their education. Upward social mobility is qualitatively different for ethnic groups, being more difficult for Blacks than non-Hispanic whites [1,2]. Historically, Blacks have had less political power. Thus, their voice is underrepresented in writing laws and policies. As a result, policies, written by the dominant group, have historically maximized their gain, ignoring the structural barriers and challenges that Blacks and other minority populations deal with daily [1,2].
At each level of family SES, Hispanic and Black parents face disproportionately higher levels of environmental and societal problems in their daily lives. Hispanic and Black families with high SES still experience high levels of discrimination that reduces their outcomes [30,61,62]. In a society that is aware of ethnicity and color, people are often treated based on their skin color and ethnicity rather than their potential. As a result of such prejudice, highly educated Hispanic and Black families do not have the same opportunities and access that their White counterparts do.
Due to existing MDRs [1,2], equal SES resources result in unequal outcomes. Due to the MDRs, ethnic minority groups are at a relative disadvantage compared to the majority group. MDRs conceptualize ethnicity as a social rather than a biological construct [63]. Thus, MDRs-related differences in school performance are due to social processes such as segregation and stratification, as opposed to genetics or IQ [64,65,66]. Ethnicity in the US is a proxy of living conditions, history, and inequality in daily life, as well as racism, discrimination, a legacy of slavery, oppression, and Jim Crow policies [63,67,68,69]. While genes and IQ may also play a role, our focus is on sociological mechanisms [63,67,68,69]. We argue that contextual factors such as neighborhood stress and concentrated poverty may reduce the academic success of high SES youth [64,65,66,70].
Some solutions are increasing political participation of power, social justice, reduction of segregation, and affirmative action policies, as well as reducing any form of discrimination across institutions. Such efforts should be multi-level and include schools, correctional settings, and policing. A decline in stop and frisk, mass incarceration, and affirmative action may be needed.
There is a need for future research. Religious aspects, involvement in sports, parenting, and availability of resources are linked to ethnicity and youth behavior. Future research should test if MDRs of SES in Black families may be related to any of the above factors. Differential engagement in sports, for example, may explain why high SES Black, Hispanic, and non-Hispanic White youth have different GPA school averages.

5. Limitations

This study is limited in a few ways. First, the outcomes were self-reported. There is a need to conduct future studies to replicate these findings using administrative data. Second, the only SES indicator in this study was parental education. Parental income, wealth, and family status are other SES indicators that need to be investigated. Furthermore, we only explored the association between parental education and GPA without studying why this association varies across ethnic groups. In addition, GPA was self-reported in this study. Some research could apply other sources such as administrative and school data. Some research suggests that self-reported GPA is valid and reliable, however, it is not perfect. Finally, GPA is not the only indicator of school performance. School performance includes multiple aspects of academic success that depend on behavioral, cognitive, and emotional characteristics. Despite these limitations, this is the first study to rule out RTM as an explanation of MDRs.

6. Conclusions

Compared to White and non-Hispanic youth, Black and Hispanic youth gain less school performance from an increase in their parental education. For non-Hispanics and Whites, however, a perfect stepwise increase can be seen in youth school performance as parental education improves; this stepwise pattern may not exist in Black and Hispanic youth. Given that the stepwise increase in school performance is perfect for non-Hispanic and White but not in Black and Hispanic youth, and as the anomaly in shape was not limited to the end of the distribution, RTM is ruled out. Thus, RTM should not be regarded as an explanation for MDRs. Future research may explore the contextual causes of MDRs.

Author Contributions

Conceptualization, data analysis, first draft, literature review, revision, and approval, S.A. Conceptualization, revision, and approval, S.B., M.B. and C.H.C. All authors have read and agreed to the published version of the manuscript.

Funding

Shervin Assari is supported by the National Institutes of Health (NIH) grants D084526-03, CA201415 02, DA035811-05, U54MD008149, U54MD007598, and U54CA229974.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Assari, S. Health disparities due to diminished return among Black Americans: Public policy solutions. Soc. Issues Policy Rev. 2018, 12, 112–145. [Google Scholar] [CrossRef]
  2. Assari, S. Unequal gain of equal resources across racial groups. Int. J. Health Policy Manag. 2017, 7, 1–9. [Google Scholar] [CrossRef] [Green Version]
  3. Assari, S.; Farokhnia, M.; Mistry, R. Education attainment and alcohol binge drinking: Diminished returns of hispanics in Los Angeles. Behav. Sci. 2019, 9, 9. [Google Scholar] [CrossRef] [Green Version]
  4. Assari, S. Parental education attainment and educational upward mobility; Role of race and gender. Behav. Sci. 2018, 8, 107. [Google Scholar] [CrossRef] [Green Version]
  5. Assari, S. Blacks’ diminished return of education attainment on subjective health; Mediating effect of income. Brain Sci. 2018, 8, 176. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Assari, S.; Caldwell, C.H.; Mincy, R. Family socioeconomic status at birth and youth impulsivity at age 15; Blacks’ diminished return. Children 2018, 5, 58. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Assari, S.; Mistry, R. Educational attainment and smoking status in a national sample of American adults; Evidence for the Blacks’ diminished return. Int. J. Env. Res. Public Health 2018, 15, 763. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Assari, S.; Lankarani, M.M. Education and alcohol consumption among older Americans; Black-White differences. Front. Public Health 2016, 4, 67. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Assari, S.; Lankarani, M. Educational attainment promotes fruit and vegetable intake for Whites but not Blacks. J 2018, 1, 5. [Google Scholar] [CrossRef] [Green Version]
  10. Assari, S.; Thomas, A.; Caldwell, C.H.; Mincy, R.B. Blacks’ diminished health return of family structure and socioeconomic status; 15 years of follow-up of a national urban sample of youth. J. Urban. Health 2018, 95, 21–35. [Google Scholar] [CrossRef]
  11. Assari, S. Separate and combined effects of anxiety, depression and problem drinking on subjective health among Black, hispanic and non-hispanic White men. Int. J. Prev Med. 2014, 5, 269–279. [Google Scholar] [PubMed]
  12. Assari, S. Ethnic and gender differences in additive effects of socio-economics, psychiatric disorders, and subjective religiosity on suicidal ideation among Blacks. Int. J. Prev Med. 2015, 6, 53. [Google Scholar] [CrossRef] [PubMed]
  13. Assari, S.; Lankarani, M.M. Race and urbanity alter the protective effect of education but not income on mortality. Front. Public Health 2016, 4, 100. [Google Scholar] [CrossRef]
  14. Assari, S.; Moghani Lankarani, M. Poverty status and childhood asthma in White and Black families: National survey of children’s health. Healthcare 2018, 6, 62. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Assari, S.; Caldwell, C.H. High risk of depression in high-income African American boys. J. Racial Ethn. Health Disparities 2018, 5, 808–819. [Google Scholar] [CrossRef]
  16. Assari, S. Income and mental well-being of middle-aged and older Americans: Immigrants’ diminished returns. Int. J. Travel Med. Glob. Health 2020, 8, 37–43. [Google Scholar] [CrossRef]
  17. Chalian, H.; Khoshpouri, P.; Assari, S. Patients’ age and discussion with doctors about lung cancer screening: Diminished returns of Blacks. Aging Med. 2019, 2, 35–41. [Google Scholar] [CrossRef]
  18. Assari, S.; Caldwell, C.H.; Mincy, R.B. Maternal educational attainment at birth promotes future self-rated health of White but not Black youth: A 15-year cohort of a national sample. J. Clin. Med. 2018, 7, 93. [Google Scholar] [CrossRef] [Green Version]
  19. Assari, S.; Caldwell, C.H. Family income at birth and risk of attention deficit hyperactivity disorder at Age 15: Racial differences. Children 2019, 6, 10. [Google Scholar] [CrossRef] [Green Version]
  20. Assari, S. Parental educational attainment and mental well-being of college students; Diminished returns of Blacks. Brain Sci. 2018, 8, 193. [Google Scholar] [CrossRef] [Green Version]
  21. Assari, S. Family socioeconomic position at birth and school bonding at age 15; Blacks’ diminished returns. Behav. Sci. 2019, 9, 26. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Assari, S. Parental educational attainment and academic performance of American college students; Blacks’ diminished returns. J. Health Econ. Dev. 2019, 1, 21–31. [Google Scholar] [PubMed]
  23. Assari, S. Does school racial composition explain why high income Black youth perceive more discrimination? A gender analysis. Brain Sci. 2018, 8, 140. [Google Scholar] [CrossRef] [Green Version]
  24. Benner, A.D.; Wang, Y.; Shen, Y.; Boyle, A.E.; Polk, R.; Cheng, Y.P. Racial/ethnic discrimination and well-being during adolescence: A meta-analytic review. Am. Psychol 2018, 73, 855–883. [Google Scholar] [CrossRef]
  25. Lockwood, K.G.; Marsland, A.L.; Matthews, K.A.; Gianaros, P.J. Perceived discrimination and cardiovascular health disparities: A multisystem review and health neuroscience perspective. Ann. N. Y. Acad Sci. 2018, 1428, 170–207. [Google Scholar] [CrossRef] [PubMed]
  26. Richards, M.; James, S.N.; Sizer, A.; Sharma, N.; Rawle, M.; Davis, D.H.J.; Kuh, D. Identifying the lifetime cognitive and socioeconomic antecedents of cognitive state: Seven decades of follow-up in a British birth cohort study. BMJ Open 2019, 9, e024404. [Google Scholar] [CrossRef] [Green Version]
  27. Manly, J.J.; Jacobs, D.M.; Touradji, P.; Small, S.A.; Stern, Y. Reading level attenuates differences in neuropsychological test performance between African American and White elders. J. Int. Neuropsychol Soc. 2002, 8, 341–348. [Google Scholar] [CrossRef]
  28. Assari, S. Parental education better helps White than Black families escape poverty: National survey of children’s health. Economies 2018, 6, 30. [Google Scholar] [CrossRef] [Green Version]
  29. Assari, S.; Caldwell, C.H. Teacher discrimination reduces school performance of African American youth: Role of gender. Brain Sci. 2018, 8, 183. [Google Scholar] [CrossRef] [Green Version]
  30. Assari, S.; Caldwell, C.H. Social determinants of perceived discrimination among Black youth: Intersection of ethnicity and gender. Children 2018, 5, 24. [Google Scholar] [CrossRef] [Green Version]
  31. Vines, A.I.; Ward, J.B.; Cordoba, E.; Black, K.Z. Perceived racial/ethnic discrimination and mental health: A review and future directions for social epidemiology. Curr. Epidemiol. Rep. 2017, 4, 156–165. [Google Scholar] [CrossRef] [PubMed]
  32. Hudson, D.L.; Bullard, K.M.; Neighbors, H.W.; Geronimus, A.T.; Yang, J.; Jackson, J.S. Are benefits conferred with greater socioeconomic position undermined by racial discrimination among African American men? J. Mens Health 2012, 9, 127–136. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Hudson, D.L.; Neighbors, H.W.; Geronimus, A.T.; Jackson, J.S. The relationship between socioeconomic position and depression among a US nationally representative sample of African Americans. Soc. Psychiatry Psychiatr. Epidemiol. 2012, 47, 373–381. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Moore, M.N.; Atkins, E.R.; Salam, A.; Callisaya, M.L.; Hare, J.L.; Marwick, T.H.; Nelson, M.R.; Wright, L.; Sharman, J.E.; Rodgers, A. Regression to the mean of repeated ambulatory blood pressure monitoring in five studies. J. Hypertens 2019, 37, 24–29. [Google Scholar] [CrossRef]
  35. Novack, G.D.; Crockett, R.S. Regression to the mean. Ocul. Surf. 2009, 7, 163–165. [Google Scholar] [CrossRef]
  36. Stout, R.L. Regression to the mean in addiction research. Addiction 2008, 103, 53. [Google Scholar] [CrossRef]
  37. Gu, Y.; Razlighi, Q.R.; Zahodne, L.B.; Janicki, S.C.; Ichise, M.; Manly, J.J.; Devanand, D.P.; Brickman, A.M.; Schupf, N.; Mayeux, R.; et al. Brain amyloid deposition and longitudinal cognitive decline in nondemented older subjects: Results from a multi-ethnic population. PLoS ONE 2015, 10, e0123743. [Google Scholar] [CrossRef] [Green Version]
  38. Jefferson, A.L.; Gibbons, L.E.; Rentz, D.M.; Carvalho, J.O.; Manly, J.; Bennett, D.A.; Jones, R.N. A life course model of cognitive activities, socioeconomic status, education, reading ability, and cognition. J. Am. Geriatr. Soc. 2011, 59, 1403–1411. [Google Scholar] [CrossRef]
  39. Gao, S.; Jin, Y.; Unverzagt, F.W.; Liang, C.; Hall, K.S.; Ma, F.; Murrell, J.R.; Cheng, Y.; Matesan, J.; Bian, J.; et al. Hypertension and cognitive decline in rural elderly Chinese. J. Am. Geriatr. Soc. 2009, 57, 1051–1057. [Google Scholar] [CrossRef] [Green Version]
  40. Roche, M.; Mukadam, N.; Adelman, S.; Livingston, G. The idemcare study-improving dementia care in Black African and Caribbean groups: A feasibility cluster randomised controlled trial. Int. J. Geriatr. Psychiatry 2018, 33, 1048–1056. [Google Scholar] [CrossRef] [Green Version]
  41. Huang, H.; Tanner, J.; Parvataneni, H.; Rice, M.; Horgas, A.; Ding, M.; Price, C. Impact of total knee arthroplasty with general anesthesia on brain networks: Cognitive efficiency and ventricular volume predict functional connectivity decline in older adults. J. Alzheimers Dis 2018, 62, 319–333. [Google Scholar] [CrossRef] [Green Version]
  42. Assari, S. Parental education and youth inhibitory control in the Adolescent Brain Cognitive Development (ABCD) Study: Blacks’ diminished returns. Brain Sci. 2020, 10, 312. [Google Scholar] [CrossRef]
  43. Assari, S.; Boyce, S.; Bazargan, M.; Caldwell, C.H. Mathematical performance of American youth: Diminished returns of educational attainment of Asian-American parents. Educ. Sci. 2020, 10, 32. [Google Scholar] [CrossRef] [Green Version]
  44. Assari, S.; Caldwell, C.H.; Bazargan, M. Parental Educational attainment and relatives¡¯ Substance use of American youth: Hispanics¡¯ diminished returns. J. BioSci. Med. 2020, 8, 13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Assari, S.B.M.; Caldwell, C.H.; Zimmerman, M.A. Educational attainment and tobacco harm knowledge among American Adults: Diminished returns of African Americans and Hispanics. Int. J. Epidemiol. Res. 2020, 7, 6–11. [Google Scholar] [CrossRef]
  46. Assari, S. Education attainment and obesitydifferential returns based on sexual orientation. Behav. Sci. 2019, 9, 16. [Google Scholar] [CrossRef] [Green Version]
  47. Assari, S. Family socioeconomic status and exposure to childhood trauma: Racial differences. Children 2020, 7, 57. [Google Scholar] [CrossRef]
  48. NCES. Enrolments to the 9–12 Grades in the US. Available online: https://nces.ed.gov/programs/projections/projections2020/tables/table_01.asp (accessed on 5 May 2020).
  49. Assari, S. Family Income Reduces Risk of Obesity for White but Not Black Children. Children 2018, 5, 73. [Google Scholar] [CrossRef] [Green Version]
  50. Assari, S.; Bazargan, M. Protective effects of educational attainment against cigarette smoking; Diminished returns of American Indians and Alaska natives in the national health interview survey. Int. J. Travel Med. Glob. Health 2019, 7, 105. [Google Scholar] [CrossRef]
  51. Assari, S. Socioeconomic determinants of systolic blood pressure; Minorities’ diminished returns. J. Health Econ. Dev. 2019, 1, 1–11. [Google Scholar] [PubMed]
  52. Assari, S.; Mistry, R.; Bazargan, M. Race, educational attainment, and e-cigarette use. J. Med. Res. Innov. 2020, 4, e000185. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Assari, S.; Mistry, R. Diminished return of employment on ever smoking among Hispanic Whites in Los Angeles. Health Equity 2019, 3, 138–144. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Bumpus, J.P.; Umeh, Z.; Harris, A.L. Social class and educational attainment: Do Blacks benefit less from increases in parents’ social class status? Sociol. Race Ethn. 2020, 6, 223–241. [Google Scholar] [CrossRef]
  55. Assari, S. Life Expectancy gain due to employment status depends on race, gender, education, and their intersections. J. Racial Ethn. Health Disparities 2018, 5, 375–386. [Google Scholar] [CrossRef] [PubMed]
  56. Assari, S. High income protects whites but not african americans against risk of depression. Healthcare 2018, 6, 37. [Google Scholar] [CrossRef] [Green Version]
  57. Assari, S.; Lapeyrouse, L.M.; Neighbors, H.W. Income and self-rated mental health: Diminished returns for high income Black Americans. Behav. Sci. 2018, 8, 50. [Google Scholar] [CrossRef] [Green Version]
  58. Assari, S.; Caldwell, C.H.; Zimmerman, M.A. Family structure and subsequent anxiety symptoms; Minorities’ diminished return. Brain Sci. 2018, 8, 97. [Google Scholar] [CrossRef] [Green Version]
  59. Chavous, T.M.; Rivas-Drake, D.; Smalls, C.; Griffin, T.; Cogburn, C. Gender matters, too: The influences of school racial discrimination and racial identity on academic engagement outcomes among African American adolescents. Dev. Psychol. 2008, 44, 637. [Google Scholar] [CrossRef]
  60. Assari, S.; Bazargan, M. Unequal associations between educational attainment and occupational stress across racial and ethnic groups. Int. J. Env. Res. Public Health 2019, 16, 3539. [Google Scholar] [CrossRef] [Green Version]
  61. Assari, S.; Lankarani, M.M.; Caldwell, C.H. Does discrimination explain high risk of depression among high-income African American men? Behav. Sci. 2018, 8, 40. [Google Scholar] [CrossRef] [Green Version]
  62. Assari, S.; Preiser, B.; Lankarani, M.M.; Caldwell, C.H. Subjective socioeconomic status moderates the association between discrimination and depression in African American youth. Brain Sci. 2018, 8, 71. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Bailey, Z.D.; Krieger, N.; Agenor, M.; Graves, J.; Linos, N.; Bassett, M.T. Structural racism and health inequities in the USA: Evidence and interventions. Lancet 2017, 389, 1453–1463. [Google Scholar] [CrossRef]
  64. Assari, S.; Boyce, S.; Akhlaghipour, G.; Bazargan, M.; Caldwell, C.H. Reward responsiveness in the Adolescent Brain Cognitive Development (ABCD) study: African Americans’ diminished returns of parental education. Brain Sci. 2020, 10, 391. [Google Scholar] [CrossRef]
  65. Kendler, K.S.; Turkheimer, E.; Ohlsson, H.; Sundquist, J.; Sundquist, K. Family environment and the malleability of cognitive ability: A Swedish national home-reared and adopted-away cosibling control study. Proc. Natl. Acad. Sci. USA 2015, 112, 4612–4617. [Google Scholar] [CrossRef] [Green Version]
  66. Rimfeld, K.; Malanchini, M.; Krapohl, E.; Hannigan, L.J.; Dale, P.S.; Plomin, R. The stability of educational achievement across school years is largely explained by genetic factors. Npj Sci. Learn. 2018, 3, 16. [Google Scholar] [CrossRef] [PubMed]
  67. Krieger, N. Living and dying at the crossroads: Racism, embodiment, and why theory is essential for a public health of consequence. Am. J. Public Health 2016, 106, 832–833. [Google Scholar] [CrossRef] [PubMed]
  68. Krieger, N.; Smith, K.; Naishadham, D.; Hartman, C.; Barbeau, E.M. Experiences of discrimination: Validity and reliability of a self-report measure for population health research on racism and health. Soc. Sci. Med. 2005, 61, 1576–1596. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Krieger, N. Does racism harm health? Did child abuse exist before 1962? On explicit questions, critical science, and current controversies: An ecosocial perspective. Am. J. Public Health 2008, 98, S20–S25. [Google Scholar] [CrossRef] [PubMed]
  70. Odenstad, A.; Hjern, A.; Lindblad, F.; Rasmussen, F.; Vinnerljung, B.; Dalen, M. Does age at adoption and geographic origin matter? A national cohort study of cognitive test performance in adult inter-country adoptees. Psychol Med. 2008, 38, 1803–1814. [Google Scholar] [CrossRef]
Children 07 00074 g001 550
Figure 1. Association between parental education and school performance in Non-Hispanic Whites (NHWs), Non-Hispanic Blacks (NHBs), and Hispanic Whites (HWs). (a) All (Pooled); (b) All (by ethnicity); (c) Non-Hispanic Whites; (d) non-Hispanic Blacks; (e) Hispanic Whites.
Figure 1. Association between parental education and school performance in Non-Hispanic Whites (NHWs), Non-Hispanic Blacks (NHBs), and Hispanic Whites (HWs). (a) All (Pooled); (b) All (by ethnicity); (c) Non-Hispanic Whites; (d) non-Hispanic Blacks; (e) Hispanic Whites.
Children 07 00074 g001
Table
Table 1. Descriptive data.
Table 1. Descriptive data.
All n = 10,262
n%
Ethnicity
Non-Hispanic White639862.4
Hispanic White233522.7
Non-Hispanic Black152914.9
Age
<18 Years433542.3
18+ Years591357.7
Gender
Female506251.6
Male473948.4
Parents Present in the Household
One325832.0
Two693968.0
Parental Education
Some Highschool99110.7
Highschool Graduate142615.4
Some College161117.3
College Graduate313233.7
Graduate School212822.9
Parental Education
Some Highschool99110.7
Highschool Graduate142615.4
Some College161117.3
College Graduate313233.7
Graduate School212822.9
MeanSD
School Performance6.691.86
Table
Table 2. Education level by ethnicity.
Table 2. Education level by ethnicity.
HispanicNon-Hispanic WhiteNon-Hispanic Black
n%n%n%
Parental Education
Some Highschool68735.52043.41007.9
Highschool Graduate42221.877812.822617.8
Some College34918.098616.227621.7
College Graduate27014.0248240.838029.9
Graduate School20610.7163226.829022.8
All1934100.06082100.01272100.0
Table
Table 3. Analysis of variance (ANOVA) results overall and by ethnicity.
Table 3. Analysis of variance (ANOVA) results overall and by ethnicity.
AllNon-Hispanic WhitesBlacksHispanics
MeanSDMeanSDMeanSDMeanSD
Some Highschool6.161.986.492.166.671.996.001.89
Highschool Graduate6.301.916.431.986.161.846.131.81
Some College6.581.876.771.866.221.806.321.89
College Graduate6.861.806.991.786.431.766.211.87
Graduate School7.341.587.491.506.841.766.851.66
p value<0.001 <0.001 <0.001 <0.001
Table
Table 4. Post Hoc test overall and by ethnicity.
Table 4. Post Hoc test overall and by ethnicity.
All Non-Hispanic Whites Non-Hispanic Blacks Hispanics
(J) Parental EducationMean Difference (I-J)SEpMean Difference (I-J)SEpMean Difference (I-J)SEpMean Difference (I-J)SEp
Some HighschoolHighschool Graduate−0.130.070.3680.050.140.9950.510.220.127−0.130.110.764
Some College−0.42 *0.07<0.001−0.290.140.2150.450.210.206−0.330.120.054
College Graduate−0.69 *0.07<0.001−0.51 *0.130.0010.240.200.772−0.220.130.466
Graduate School−1.18 *0.07<0.001−1.01 *0.13<0.001−0.170.210.924−0.86 *0.15<0.001
Highschool GraduateSome Highschool0.130.070.368−0.050.140.995−0.510.220.1270.130.110.764
Some College−0.28 *0.07<0.001−0.34 *0.080.001−0.060.160.995−0.190.130.598
College Graduate−0.56 *0.06<0.001−0.56 *0.07<0.001−0.270.150.365−0.080.140.977
Graduate School−1.04 *0.06<0.001−1.06 *0.08<0.001−0.68 *0.16<0.001−0.72 *0.16<0.001
Some CollegeSome Highschool0.42 *0.07<0.0010.290.140.215−0.450.210.2060.330.120.054
Highschool Graduate0.28 *0.07<0.0010.34 *0.080.0010.060.160.9950.190.130.598
College Graduate−0.28 *0.06<0.001−0.22 *0.070.009−0.210.140.5650.110.150.950
Graduate School−0.76 *0.06<0.001−0.72 *0.07<0.001−0.62 *0.150.000−0.53 *0.160.010
College GraduateSome Highschool0.69 *0.07<0.0010.51 *0.130.001−0.240.200.7720.220.130.466
Highschool Graduate0.56 *0.06<0.0010.56 *0.07<0.0010.270.150.3650.080.140.977
Some College0.28 *0.06<0.0010.22 *0.070.0090.210.140.565−0.110.150.950
Graduate School−0.49 *0.05<0.001−0.50 *0.06<0.001−0.41 *0.140.031−0.64 *0.170.002
Graduate SchoolSome Highschool1.18 *0.07<0.0011.01 *0.13<0.0010.170.210.9240.86 *0.15<0.001
Highschool Graduate1.04 *0.06<0.0011.06 *0.08<0.0010.68 *0.16<0.0010.72 *0.16<0.001
Some College0.76 *0.06<0.0010.72 *0.07<0.0010.62 *0.15<0.0010.53 *0.160.010
College Graduate0.49 *0.05<0.0010.50 *0.06<0.0010.41 *0.140.0310.64 *0.170.002
* p < 0.05; Standard Error (SE); I and J; education levels.
Table
Table 5. Post Hoc test overall and by ethnicity.
Table 5. Post Hoc test overall and by ethnicity.
12345
AllnMeanMeanMeanMean
Some Highschool9916.16
Highschool Graduate14266.30
Some College1611 6.58
College Graduate3132 6.86
Graduate School2128 7.34
p value 0.2121.0001.0001.000
NHWs
Some Highschool7786.43
Highschool Graduate2046.49
Some College986 6.77
College Graduate2482 6.99
Graduate School1632 7.49
p value 0.9850.1921.000
NHBs
Some Highschool2266.16
Highschool Graduate2766.226.22
Some College3806.436.436.43
College Graduate100 6.676.67
Graduate School290 6.84
p value 0.5280.0830.145
HWs
Some Highschool6876.00
Highschool Graduate4226.13
Some College2706.21
College Graduate3496.32
Graduate School206 6.85
p value 0.1551.000
NHWs: Non-Hispanci Whites; HWs: Hiapanic Whites, NHBs: Non-Hispanic Blacks.

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Assari, S.; Boyce, S.; Bazargan, M.; Caldwell, C.H. Diminished Returns of Parental Education in Terms of Youth School Performance: Ruling out Regression toward the Mean. Children 2020, 7, 74. https://doi.org/10.3390/children7070074

AMA Style

Assari S, Boyce S, Bazargan M, Caldwell CH. Diminished Returns of Parental Education in Terms of Youth School Performance: Ruling out Regression toward the Mean. Children. 2020; 7(7):74. https://doi.org/10.3390/children7070074

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Assari, Shervin, Shanika Boyce, Mohsen Bazargan, and Cleopatra H. Caldwell. 2020. "Diminished Returns of Parental Education in Terms of Youth School Performance: Ruling out Regression toward the Mean" Children 7, no. 7: 74. https://doi.org/10.3390/children7070074

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