Rachel Schmidt
This study assessed the effects of asthma and lead poisoning on academic achievement for children enrolled in the Providence public school system. Lead poisoning and asthma are the most important childhood environmental health concerns in Providence. Lead exposure produces a variety of adverse health effects in children who are in a period of growth and development of the central and peripheral nervous system. Early stages of childhood development are characterized by undergoing anatomic and physiologic changes that underlie language, visual, motor and cognitive development. Evidence strongly suggests that exposure to lead strongly impairs cognitive development and long-term effects of childhood exposure have been reported including learning disabilities, decreased intelligence, delayed reaction time, distractibility, and behavioral disorders-- all markers of poor academic achievement.
Asthma is the most common cause of absence from school. Children with asthma may experience problems in their adaptation to school and impediments to their learning. Frequent school absenteeism interrupts the process of learning and interferes with childrens' social interactions and participation in extracurricular activities. Although it has been found that asthma does not directly alter brain development or neuropsychological functioning, asthma symptoms may cause children to have more frequent absences from school and a general malaise which may affect academic performance. Children experiencing asthma or allergic symptoms may be unable to concentrate and consequently may be less able to learn new skills and information. Fatigue, irritability, and intermittent hearing loss may accompany seasonal allergies which trigger asthma and can lead to inattentiveness in a classroom setting. The more significant effects affecting academic performance occur because of sleep loss and general ill feeling that accompany these conditions. In this study, academic achievement was assessed using education data obtained by the Providence Plan from the Providence School Department and the Rhode Island Department of Education. Blood lead screening data obtained from the Rhode Island Department of Health for Providence residents for children tested in 1993 to 1998 were used in this analysis. Data for asthma hospitalizations were obtained from Lifespan. These data included emergency room visits, and inpatient and outpatient admissions at Rhode Island and Miriam Hospitals with a primary diagnosis of asthma between January 1978 and March 2000. Blood lead levels (BLLs) measured in 1993 to 1996 were used for correlating with promotion to the next grade. Data for blood lead tests in 1993 to 1998 were used for correlating with standardized educational test scores. The educational measures that were used in this analysis are promotion to the next grade for 1993 to 1998 academic years and scores on standardized tests taken in the 3rd and 4th grades in 1996 to 1999. A case-control analysis was used to test for correlations of lead poisoning [15+ µg/dl] with promotion to the next grade and standardized test scores. BLLs were used to classify exposed and unexposed populations as the independent variable. The cases were the students who repeated a grade or had low test scores and the controls were the students who advanced a grade or had high test scores. The cases and controls were arranged in a 2X2 table. The odds ratio and 95% confidence intervals were calculated. A cohort study based on cumulative incidence was used to correlate asthma hospitalizations with promotion to the next grade and standardized test scores. All members of the population not identified by hospital visits as asthmatic were categorized as non-asthmatics. Thus, this cohort includes a larger number of children than is considered in the case-control analysis. The cases are the students who repeated a grade or had low test scores and the controls are the students who advanced a grade or had high test scores. Data was also arranged in a 2X2 table. Odds ratio and 95% confidence intervals were also calculated. In addition, two linear regression models for two tests were done, one of which raw scores were available. This allows us to see the relationship between individual's BLLs and their corresponding test score. The results for the case-control and cohort analysis for lead and asthma are shown in the following two tables:
Summary of Lead Results:
|
Test: |
Year of Test: |
Grade: |
Odds Ratio: |
95% CI: Lower Bound |
95% CI: Upper Bound |
Cases: |
Controls: |
|
ELA Reading: Understn. |
1998 |
4 |
1.6 |
1 |
2.5 |
195 |
373 |
|
ELA Reading: Analysis |
1998 |
4 |
2 |
1.3 |
3.2 |
214 |
354 |
|
ELA Writing Std. Level |
1998 |
4 |
1.4 |
0.9 |
2 |
234 |
334 |
|
ELA Writing Convention |
1998 |
4 |
1.5 |
1 |
2.4 |
267 |
301 |
|
Math: Concepts |
1998 |
4 |
1.3 |
0.7 |
1.8 |
425 |
144 |
|
Math: Skills |
1998 |
4 |
1.6 |
1 |
2.5 |
171 |
398 |
|
Math: Problem Solving |
1998 |
4 |
4.8 |
1.2 |
20 |
516 |
53 |
|
Math |
1996 |
4 |
0.74 |
- |
- |
58 |
44 |
|
Writing |
1998 |
3 |
1.5 |
1 |
2.3 |
740 |
187 |
|
Writing |
1999 |
3 |
2.1 |
1.5 |
3 |
750 |
367 |
Summary of Asthma Results:
|
Test: |
Year of Test: |
Grade: |
Odds Ratio: |
95% CI: Lower Bound |
95% CI: Upper Bound |
Cases: |
Controls: |
|
ELA Reading: Understn. |
1998 |
4 |
1.4 |
1 |
1.9 |
576 |
1228 |
|
ELA Reading: Analysis |
1998 |
4 |
1.4 |
1.1 |
1.9 |
630 |
1174 |
|
ELA Writing Std. Level |
1998 |
4 |
1.6 |
1.3 |
2 |
732 |
1072 |
|
ELA Writing Convention |
1998 |
4 |
1.3 |
1 |
1.7 |
799 |
1005 |
|
Math: Concepts |
1998 |
4 |
1.04 |
0.9 |
1.2 |
1403 |
482 |
|
Math: Skills |
1998 |
4 |
0.95 |
0.63 |
1.42 |
591 |
1294 |
|
Math: Problem Solving |
1998 |
4 |
1.04 |
0.97 |
1.1 |
1687 |
198 |
This study does not establish a causal relationship between lead poisoning/asthma and educational success measures. It establishes that some educational success measures have significant negative correlations with lead poisoning and asthma. There are confounders such as income level and parents' education which are not corrected for in this analysis. These variables are known to influence a student's academic achievement. Extensions of this study should attempt to control for socio-economic status. Parent education, language proficiency, family structure, and the community's socioeconomic status are strong predictors of student academic achievement and in the future, may be accounted for if the data are available.