1. Ana Progovac, PhD1,2,3 Benjamin Lê Cook, PhD MPH 1,2
Trends in Childhood PSYCHOLOGICAL Impairment by Household income and parental college education
Ana Progovac, PhD1,2,3
Benjamin Lê Cook, PhD MPH 1,2
Department of Health Care Policy, Harvard Medical School
Department of Psychiatry, Harvard Medical School
Health Equity Research Lab , Cambridge Health alliance
Aug 2, 2016
MHSR

2. Introduction

3. Many disparities persist in health and health care
Many race-based disparities in access to healthcare persist, and some have grown (Lê Cook, McGuire, Zuvekas 2009; Lê Cook et al 2016)

4. Disparities particularly large by Socioeconomic status (SES)
Disparities in having health insurance or a regular place to go for medical care have narrowed but persist, especially among low-income and Hispanic individuals (AHRQ National Healthcare Disparities Disparities Report 2015)
Disparities in health care quality remain largest for low vs. high income patients (AHRQ National Healthcare Disparities Report 2015)
2015 AHRQ National Healthcare Disparities Report

5. SES-based disparities are increasing across many outcomes

6. Growing SES disparities in adult and child health
Life expectancy (Pappas et. al 1993; Chetty, Stepner, Abraham et al 2016)
CVD risk factors (Kanjilal, Gregg, Cheng et. al 2006)
Obesity rates for children & adolescents (Stamatakis, Wardle, & Cole 2010; Frederick, Snellman & Putnam 2014)
Childhood asthma (Akinbami, Simon, & Rossen 2016)
racial/ethnic disparities ↑ , concentrated among very poor

7. DO similar trends exist for mental health in Children ?
We attempt to answer this question using the Medical Expenditure Panel Survey (MEPS).
Hypothesis: Income- and education- based SES disparities in childhood mental health impairment have increased over time, as they have with many physical health outcomes.

8. Data and methods

9. data
Dataset
Medical Expenditure Panel Survey (MEPS) years , children ages 6-17
103, 209 observations
Pooling data in 3-year endpoints
and
N=36,863

10. variables Outcome Variables Predictors:
Severe childhood impairment Columbia Impairment Scale (0-52, 16+)
Predictors:
Household income level
Parental college education (at least one parent finished college)

11. Outcome: Psychological impairment
Columbia Impairment Scale (CIS) (Bird 1993; Bird 1996)
Good psychometric properties
Correlated with physician-rated impairment and pediatric DSM diagnoses
0-52. Severe impairment ≥16
Can be administered by lay interviewer (in MEPS, it is answered by child’s parent/caregiver)

12. Statistical Methods:
Trends models for income and parent’s college completion:
Linear regression for severe impairment
Covariates: age, time, income (college), income (college)*time
Second model adding sex, race/ethnicity, region, child’s health status
(preliminary) adding parental poor health indicator, and parental mental health (self reported), as well as national unemployment rate
(Repeat with Logit models)
Linear and Logit models account for survey weights and sampling design using svy command in Stata
Three way interactions
Repeat steps above

13. Results

14. Table 1. Sample Characteristics
Psychological
Impairment = 0
(CIS<16)
Impairment =1
(CIS≥16)
p-value
Age (mean, SD)
11.4 (3.4)
12.1 (3.3)
<0.001 **
Female (%)
49.5
43.3
White (%)
Black (%)
Hispanic (%)
Other (%)
39.0
19.4
35.0
6.6
22.7
23.0
4.9
Northeast (%)
Midwest (%)
South (%)
West (%)
14.9
18.6
37.5
29.0
14.3
23.3
36.3
26.10
At least one parent finishing college (%)
25.0
20.7
Lowest quartile of household income (%)
29.6
33.2
Child’s overall health (1-5, mean SD)
1.7 (0.89)
2.1 (1.01)
Mom in poor health (%)
4.4
7.8
Dad in poor health (%)
3.6
5.5
Mom’s mental health (1-5, mean SD)
2.4 (0.97)
2.8 (1.01)
Dad’s mental health (1-5, mean SD)
2.3
2.6

15. Impairment Trends by income
(Adjusted for individual level survey weights)

16. Linear models: impairment by income (1)

17. Linear models: impairment by income (2)

18. Linear models: impairment by income (3)

19. Impairment Trends by parental college
(Adjusted for individual level survey weights)

20. Linear models: impairment by parental college

21. Linear Models: Impairment by parental college (2)

22. Linear Models: Impairment by parental college (3)

23. Three way interaction Three way interaction: Model 1 p=0.071*

24. Discussion

25. Discussion - 1
Disparities in impairment may be increasing for household income depending on model specification (p=0.059 for different trends; p=0.079 after further adjustment; if unemployment and parental health/mental health added )
Opposite trends seen for parental college education, which may be shrinking (p=0.093 for different trends; after adjustment for child variables; if unemployment and parental health/mental health added)
Three way interaction highlights need to include multiple SES measures together (p=0.071 for three way interaction, p=0.025 after adjustment for child variables, p=0.084 when unemployment rate and parental health variables added)

26. Discussion - 2
Appear to see growing disparities by income only in lower educated group (no college)
Conversely narrowing disparities in better educated group (at least one parent finishing college)

27. Discussion - 3 Limitations (and some next steps)
CIS not a diagnostic measure
Missing data
Family structure
Parent-child concordance on CIS
Next – disparities in use of services given severe impairment (by income)
Current analysis treats years independently (have not used panel data structure)
Using panel data, could potentially study influence of past years’ use of health and mental health services

28. Discussion - 4 Conclusion:
Preliminary analysis shows we may be seeing widening disparities in childhood psychological impairment by income level among children living with relatively less-educated parents
Policies, programs, and interventions which seek to reduce detrimental health and mental health outcomes for children in most vulnerable SES groups will likely be of greater importance if these disparities continue to grow.

29. Thank you Feedback/comments - aprogovac@cha.harvard.edu Funding:
National Institutes of Mental Health (NIMH):
T32 MH01973, PI Tom McGuire
Agency for Healthcare Research and Quality (AHRQ):
R01 HS021486, PI Benjamin Cook
Feedback/comments -
Thank you