Teachers on the margins: How low-income public schools burden our teachers

Abstract

BACKGROUND:

Teachers experience high work-related stress, which can lead to missed workdays and lower quality of life.

OBJECTIVE:

The objective of this exploratory pilot study was to assess occupational and environmental stressors in public school districts by income level to examine the influence these stressors have on teachers perceived stress and biological stress response.

METHODS:

Fifty-nine teachers were recruited from four school districts in Michigan (three low-income and one high-income). Participants completed a self-administered survey on teaching stressors, health, and demographics. Stress response was measured through blood pressure, heart rate, and salivary cortisol. Six salivary cortisol measurements were collected for each participant; three in the afternoon and three in the evening. Each teacher’s classroom and school underwent an environmental assessment on quality and proximity to environmental hazards.

RESULTS:

Teachers at low-income school districts had significantly higher afternoon cortisol levels, lower self-reported health, higher body mass index, higher perceived teaching stressors, and worked at schools within one km of a greater number of environmentally-contaminated sites, in comparison to their high-income school district counterparts.

CONCLUSIONS:

This research aims to inform future interventions that could lessen occupational and environmental stressors for teachers, improve teacher health outcomes and retention, and impact student success rates.

Keywords

School poverty psychosocial stressors environmental stressors occupational health

1 Introduction

Teaching is widely recognized as a stressful and demanding occupation, however high stress loads can lead to burnout and high turnover rates [1, 2]. In 2013, teacher job satisfaction was at a 25-year low of only 39% [3], and understanding occupational stressors may be important for understanding job satisfaction and retention. Tennant [4] concluded that the work setting and work stress were precursors to teacher burnout. Kindergarten through twelfth (K-12) grade teachers are faced with unique occupational health hazards that are challenging to quantify, including ergonomic hazards, infectious disease, physical violence, and mental and emotional psychosocial stressors in their daily work [5 –7]. Additional financial concerns from income stagnation or funding cuts, health care cuts, or job insecurity fears are substantial, especially for teachers at lower income school districts [8 –10].

Psychosocial stress for public school teachers may come from personal, occupational, or environment related factors. Teachers at low-income school districts in particular are at a greater risk for exposure to psychological and environmental stressors that can worsen health outcomes than teachers at high-income school districts [5, 11]. Chronic psychosocial stress has been associated with depression, cardiovascular disease, hypertension, and inflammation [4 , 12–15], and teachers have been observed to have higher rates of respiratory tract problems than non-teachers [6]. Teachers’ classroom and school conditions are associated with increased rates of allergies, headaches, fatigue, and difficulty concentrating [16 –18]. Conversely, improved air quality and reduced student stressors, such as school dissatisfaction and bullying, reduced teacher absenteeism and illnesses in a Finnish cohort study [19].

This pilot study is an assessment of the impact of school district income level on Michigan teachers’ cumulative occupational stressors, and the influence work-related stressors have on perceived stress and biological stress response through salivary cortisol and blood pressure measures. Research has found greater psychosocial stress for teachers at low-income school districts [5], but there are limited studies examining cumulative psychosocial and environmental stressors by school district characteristics and income level. Some school districts in Michigan have reported having poor heating conditions, pest infestations, broken windows, and large class sizes [9 , 21]. K-12 grade teachers are not traditionally examined as a vulnerable group for occupational risks, but face unique stressors and exposures that can influence health outcomes. A fuller understanding of perceived occupational and environmental stressors and the biological response they have on teachers by school district income level can better support intervention efforts to improve teacher health, reduce burnout, and reduce missed workdays.

2 Methods

2.1 Study design and recruitment

A cross-sectional study was conducted with K-12 teachers from four public school districts in southeast Michigan from March through May 2017. School districts were selected by the median household income level of the district, to include high and low-income school districts. Low-income school districts were classified as those with a median household income below the qualification level for the U.S. National School Breakfast and Lunch Program for Michigan for a family of four ($46,435) in 2017, which provides free or low-cost meals for low-income students [22]. High-income school districts were classified as those with a median household income approximately double this level (at least $90,000).

No more than 25 teachers were recruited per school district. All teachers were eligible to participate if they had been in their current positions since at least the start of the 2016-2017 academic year and employed by the school district for at least one year. Institutional Review Board approval (ID: 907079) was obtained through Oakland University. Permission to work in each school district was granted through the Superintendent or Assistant Superintendent of each school district. All participants received a $50 Amazon gift card at the completion of sample collection.

The authors employed two convenience sampling recruitment methods for this study. For three school districts, the Superintendent or Assistant Superintendent forwarded a recruitment email to teachers asking for participation in this study. One of the school districts invited research personnel to recruit participants through a table at an annual school district event. Teachers were contacted individually to schedule a meeting time with a member of the research team during a break, prep hour, or lunch period, or prior to the start or at the end of their school day. During each meeting, teachers were surveyed and their primary classrooms and schools were assessed.

2.2 Surveys and assessment

Each participating teacher completed a survey on teaching roles, other employment, education level, sex, race, ethnicity, age, income, average hours of sleep per night, weight, height, and overall health; and smoking, alcohol consumption, asthma, and hypertensive history. Demographic, smoking, alcohol consumption, asthma, and hypertensive history questions were adapted from the U.S. National Health and Nutrition Examination Survey (NHANES) [23].

Occupational stressors were assessed through questions from the National Union of Teachers’ Teacher Stress Study, which were modified to add questions on school and classroom environments and to US American English [24]. Teachers rated how significantly they agreed with 39 occupational teaching stressor statements (e.g., strongly disagree, disagree, agree, strongly agree) on six categories (demands, control, support, relationships, roles, and work environment) [24]. Agreement to each statement was given a numeric value (1, 2, 3, or 4), with the highest numeric value (4) associated with the strongest level of concern/stress (i.e., either strong agreement or strong disagreement, depending on which aligned with strongest perceived stress for each statement). The numeric scores were summed and standardized out of four points into a standardized composite score for each of the six stressor categories. A standardized composite score for all teaching stressors was calculated to assess overall teaching stressors.

Participants’ body mass index (BMI), used to assess obesity status, was calculated by dividing the participant’s self-reported weight (kg) by her/his squared height (m). Smoking history was assessed to classify participants as current, past, and never smokers (i.e., smoked less than 100 cigarettes in their lifetime) [25]. Smoking pack-years was calculated from the average packs of cigarettes smoked per day for the duration of a participant’s smoking years. Alcohol consumption was estimated as the typical number of alcoholic drinks consumed per week.

2.3 Stress response measures

Participant’s blood pressure, heart rate, and salivary cortisol were measured to assess physiological stress response [26 –28]. Salivary cortisol is a hormonal biomarker that is used to assess psychological stress [27, 29], as an indicator of biological stress reactivity [30]. Cortisol levels follow a diurnal pattern typically characterized by high levels upon waking and then declines throughout the day [27, 30]. Average salivary cortisol levels are 15.4 nmol/L in the morning and 2.8 nmol/L in the late evening [31]. Cortisol levels have been associated with stress levels [27], acute smoking [32, 33], alcohol consumption [34, 35], physical activity [33, 36], seasonality [33], age [37], and food and caffeine consumption [35].

Cortisol was measured through saliva samples [38]. Saliva samples were collected with Salimetrics Saliva Bio Oral Swabs (SOS), following the Salimetrics SOS collection methods (Salimetrics, LLC, Carlsbad, CA, USA) [39]. Each participant was coached on proper collection protocol and provided with a handout of protocols and the materials for sample collection. They were advised to avoid consuming any dairy products, acidic foods, or beverages for at least 20 minutes prior to collecting a sample; refrain from eating a large meal within one hour; and abstaining from alcohol for the duration of the sample collection period. The swab was placed under the tongue for at least 60 seconds until the swab was saturated in saliva and then placed into a labeled collection tube. Each sample tube was placed in a labeled Ziploc bag, where participants were directed to record the time and date of the sample.

Each participating teacher collected SOS samples twice a day for three days during the school week (Monday through Friday). Participants were advised to collect each sample at approximately the same time each day. They were encouraged to collect the first sample of the day prior to lunch when possible, which was either in the late morning or early afternoon. Three additional samples were collected about 30 minutes before the participants went to sleep. Teachers stored SOS samples in a refrigerator until a research team member was able to collect them, usually up to three days later. SOS samples were stored at –80°C before analysis.

SOS samples were analyzed for salivary cortisol through a DPC Coat-A-Count Cortisol modified protocol for saliva at the University of Michigan Core Assay Facility. The intra-assay coefficient of variation (CV) for salivary cortisol samples was 8.9%. The majority (89%) of samples had a CV below 15%. The inter-assay CV for salivary cortisol samples were 8.3–14.4%. SOS samples with too little saliva for analysis or with cortisol levels below the detection limit were excluded from analysis. Samples with missing time points or if they were taken more than four hours before/after other samples in the same time frame were excluded from analysis. Three individual salivary cortisol samples that had cortisol levels at more than five times the standard deviation of the average cortisol level of all participants (11.9 nmol/L) were excluded as outliers. Afternoon and evening salivary cortisol levels for all SOS samples were averaged for each participant (one to four samples per participant at each time point).

Blood pressure (BP) and hypertensive status are also used to assess chronic stress and biological stress response [26]. Teachers’ resting systolic and diastolic BP and heart rate were measured three times according to American Heart Association (AHA) guidelines [40], using an electronic sphygmomanometer (Omron Healthcare, Inc., Lake Forest, IL, USA) about 2 cm above the right elbow, above the brachial artery. Participants were asked to sit on a chair with back support for the duration of the survey and had the first measurement at least five minutes after sitting. The three BP and heart rate measurements were collected at three-minute intervals and were averaged. BP values were classified by the 2018 AHA standards for hypertensive status [41]. Under the 2018 AHA standards, apparent hypertension is defined as systolic BP (SBP) ≥130 mmHg or diastolic BP (DBP) ≥80 mmHg. Participants with elevated BP according to the 2017 AHA standards or who expressed interest were provided with AHA information sheets on high blood pressure [42]. Participants’ SBP and DBP were adjusted if they were currently taking anti-hypertensive medications to control their BP by adding 10 mmHg to SBP and DBP [43, 44].

2.4 School and classroom assessment

Participating teachers’ primary school and classroom were evaluated for environmental stressors including nearby industrial facilities and roadways, outdoor sound level, overall building maintenance, temperature, and classroom maintenance [45]. The classroom assessments were conducted at the time of the survey or immediately after if the survey took place outside of the teacher’s primary classroom. Classroom assessments evaluated the overall maintenance of the floor, ceiling, and walls; the presence of windows/doors and odors; room temperature; and humidity. School assessments of overall exterior maintenance and classroom assessments of interior maintenance were evaluated qualitatively by trained researchers.

Environmental assessments of a one (1) km area surrounding each school were conducted using online mapping tools by the research team. Traffic volume on federally-funded roadways within 1 km of each school were assessed using the Southeast Michigan Council of Governments (SEMCOG) database on the average annual daily traffic (AADT) [46]. The number of moderate AADT volume (5,000–10,000 vehicles/day) and high AADT volume (> 10,000 vehicles/day) roadways within a 1 km radius were tallied for each school. The number of sites of environmental contamination, designated by the Michigan Department of Environmental Quality (MDEQ), within 1 km of each school were assessed through the MDEQ’s Environmental Mapper program [47]. The U.S. Environmental Protection Agency’s (EPA’s) Toxic Release Inventory (TRI) data via the My Right-to-Know program was utilized to assess if there were any active or inactive facilities within 1 km of the schools that meet the qualifications to report to the Toxic Release Inventory [48] under the Emergency Planning and Community Right to Know Act (EPCRA, 1986). Schools were also designated as a neighborhood school if they were located in or surrounded by a residential neighborhood. Outdoor sound was measured with a Pulsar Nova sound level meter (Pulsar Instruments, Plc., North Yorkshire, UK).

2.5 Analysis

Data were analyzed with SPSS Statistical Software (v.24; IBM Corp., Armonk, NY, USA). Descriptive analyses, correlations, and statistical tests were performed on key variables, including demographics, reported stressors, salivary cortisol, BP, classroom characteristics, and school environmental hazards. Statistical significance was evaluated at p < 0.05. Cortisol levels were not normally distributed and therefore comparisons of means were assessed through the Mann-Whitney U test and bivariate analyses utilized Spearman’s rho. Bivariate correlation analyses were performed for standardized composite scores for teaching stressor categories and overall, salivary cortisol, SBP, DBP, heart rate, BMI, age, sex, cigarette pack-years, alcoholic drinks per week, average hours of sleep per night, average hours working at a second job, classroom temperature, environmental contamination and traffic volume within 1 km of the school, and the year school was built. All linear regression models included all participants with valid cortisol measurements. Linear regressions were performed with backward stepwise regressions and adjusted for district income level, teaching stressor scores, environmentally-contaminated sites, moderate and high vehicle AADT, age, sex, BMI, smoking pack-years, and alcoholic drinks per week.

3 Results

3.1 School districts

There were four participating public school districts in southeast Michigan; three were low-income and one was high-income. The high-income school district (HISD) had a median household income that was almost double the Michigan state median ($50,800 from the 2012–2016 U.S. Census Bureau American Community Survey estimates), while the three low-income school districts (LISDs) had an average median household income of approximately $33,000 from 2012–2016 [49]. The average percentage of families with children in the school district living below the poverty line was 43% in the LISDs and less than 10% in the HISD, compared to 12% of families in Michigan overall from 2012–2016 [49]. School district rankings on student achievement and improvement values were also consistently lower in LISDs (12th percentile) compared to the HISD (∼85th percentile) [50].

3.2 Demographics

Fifty-nine (n = 59) K-12 teachers were recruited from 26 schools at four public school districts in southeast Michigan (Table 1). There were 39 participating teachers from 15 schools in the LISDs and 20 participating teachers from 11 schools in the HISD. The majority of the participating school teachers taught at elementary schools (n = 28) and high schools (n = 21), although some taught at middle (n = 6) and alternative schools (n = 4; schools that generally serve K-12 grades for students that are at risk of not graduating or have specific needs) [51]. The mean interview date was 31 days later in LISD than HISD schools.

Table 1
Participating teachers’ demographic data at low and high-income school districts

Low- High-

income income

districts district

n % n %

n of participants 39 20

n schools 14 12

Age (mean [SD])^* 44.3 (8.1) 38.9 (9.2)

Years in school district (mean [SD]) 12.1 (10.0) 12.3 (7.7)

Sex: Male 4 10% 5 25%

Race and ethnicity:

White 32 84% 20 100%

Black or African 5 13% 0 0%

Asian 1 3% 0 0%

Latino or Hispanic 0 0% 0 0%

Marital status:

Single 7 18% 3 15%

Married 23 61% 17 85%

Divorced 6 16% 0 0%

Separated 1 3% 0 0%

Not married, cohabitating 1 3% 0 0%

Household income (USD):

$20,000 to $40,000 4 11% 0 0%

$40,000 to $60,000 7 19% 1 5%

$60,000 to $80,000 8 22% 4 20%

$80,000 to $100,000 4 11% 3 15%

$100,000 to $120,000 5 14% 2 10%

$120,000 to $140,000 2 6% 3 15%

> $140,000 6 17% 7 35%

Education:

Bachelor degree 5 13% 2 10%

Graduate degree 33 87% 18 90%

	Low-	High-
n of participants	39	20
n schools	14	12
Age (mean [SD])^*	44.3 (8.1)	38.9 (9.2)
Years in school district (mean [SD])	12.1 (10.0)	12.3 (7.7)
Sex: Male	4	10%	5	25%
Race and ethnicity:
White	32	84%	20	100%
Black or African	5	13%	0	0%
Asian	1	3%	0	0%
Latino or Hispanic	0	0%	0	0%
Marital status:
Single	7	18%	3	15%
Married	23	61%	17	85%
Divorced	6	16%	0	0%
Separated	1	3%	0	0%
Not married, cohabitating	1	3%	0	0%
Household income (USD):
$20,000 to $40,000	4	11%	0	0%
$40,000 to $60,000	7	19%	1	5%
$60,000 to $80,000	8	22%	4	20%
$80,000 to $100,000	4	11%	3	15%
$100,000 to $120,000	5	14%	2	10%
$120,000 to $140,000	2	6%	3	15%
> $140,000	6	17%	7	35%
Education:
Bachelor degree	5	13%	2	10%
Graduate degree	33	87%	18	90%

^*Significantly different means (p < 0.05); independent t-test.

The majority of teachers were female (86%), white (90%), Christian (67%), married (69%), and held a graduate degree (88%). LISD teachers were more likely to be divorced and have lower household incomes (< $60,000), and were significantly older (44.3 years) than HISD teachers (38.9 years). Fifty percent of HISD and 39% of LISD teachers held a second job during the school year, and worked an average of 8.4 and 9.7 additional hours each week, respectively.

3.3 Health, blood pressure, and salivary cortisol

Teachers from the HISD reported significantly better overall self-reported health, received more sleep, and had lower body mass index (BMI) and afternoon cortisol levels compared to LISD teachers (Table 2). Systolic and diastolic BP levels and hypertensive status (51%) were not significantly different among participants, although all of the participants currently taking anti-hypertensive medications were LISD teachers (n = 8).

Table 2
Health and biological stress response in low and high-income school districts

Low- High-

income income

districts district

n % n %

Overall health^**

Excellent 4 11% 4 20%

Very good 10 26% 14 70%

Good 17 45% 2 10%

Fair 7 18% 0 0%

Poor 0 0% 0 0%

Hours of sleep per night (mean [SD])^* 6.5 (1.1) 7.0 (0.6)

Ever smoker 15 39% 2 10%

Current smoker 3 8% 1 5%

Cigarette pack-years (mean [SD])^* 3.5 (7.6) 0.2 (0.8)

Consumes alcohol 27 69% 17 85%

Drinks per week (mean [SD]) 0.8 (1.1) 1.4 (1.2)

BMI^a

Underweight: < 18.5 0 0% 0 0%

Normal: 18.5 to 24.9 5 13% 9 45%

Overweight: 25 to 29.9 8 21% 7 35%

Obese: 30 or higher 26 67% 4 20%

Mean (SD)^ 33.8 (8.8) 25.2 (4.8)

BP classification: Hypertensive^b 21 54% 9 45%

Current BP Medication 8 31% 0 0%

Blood pressure (mean [SD])

Systolic BP (mmHg)^c 119.6 (17.0) 113.5 (13.8)

Diastolic BP (mmHg)^c 84.2 (12.5) 78.8 (9.0)

Heart rate 76.9 (9.2) 71.8 (10.2)

Salivary cortisol (mean [SD]) 3.74 (2.60) 2.84 (1.85)

Afternoon sample collection time 12:34 (0:56) 12:55 (1:16)

Afternoon (nmol/L)^* 4.33 (2.44) 3.21 (1.70)

Evening sample collection time 21:33 (1:07) 21:26 (1:01)

Evening (nmol/L) 3.11 (3.29) 2.51 (2.29)

A-E Change (nmol/L)^d 1.22 (3.24) 0.70 (1.55)

	Low-	High-
Overall health^**
Excellent	4	11%	4	20%
Very good	10	26%	14	70%
Good	17	45%	2	10%
Fair	7	18%	0	0%
Poor	0	0%	0	0%
Hours of sleep per night (mean [SD])^*	6.5 (1.1)	7.0 (0.6)
Ever smoker	15	39%	2	10%
Current smoker	3	8%	1	5%
Cigarette pack-years (mean [SD])^*	3.5 (7.6)	0.2 (0.8)
Consumes alcohol	27	69%	17	85%
Drinks per week (mean [SD])	0.8 (1.1)	1.4 (1.2)
BMI^a **
Underweight: < 18.5	0	0%	0	0%
Normal: 18.5 to 24.9	5	13%	9	45%
Overweight: 25 to 29.9	8	21%	7	35%
Obese: 30 or higher	26	67%	4	20%
Mean (SD)^**	33.8 (8.8)	25.2 (4.8)
BP classification: Hypertensive^b	21	54%	9	45%
Current BP Medication	8	31%	0	0%
Blood pressure (mean [SD])
Systolic BP (mmHg)^c	119.6 (17.0)	113.5 (13.8)
Diastolic BP (mmHg)^c	84.2 (12.5)	78.8 (9.0)
Heart rate	76.9 (9.2)	71.8 (10.2)
Salivary cortisol (mean [SD])	3.74 (2.60)	2.84 (1.85)
Afternoon sample collection time	12:34 (0:56)	12:55 (1:16)
Afternoon (nmol/L)^*	4.33 (2.44)	3.21 (1.70)
Evening sample collection time	21:33 (1:07)	21:26 (1:01)
Evening (nmol/L)	3.11 (3.29)	2.51 (2.29)
A-E Change (nmol/L)^d	1.22 (3.24)	0.70 (1.55)

^aBMI calculated as weight (kg) / height squared (m). ^bNormal BP is SBP < 120 and DBP < 80; pre-hypertensive BP is SBP: 120–129 and DBP < 80; apparent hypertension is SBP ≥130 or DBP ≥80 (41). ^cSystolic and diastolic BP adjusted for current anti-hypertensive medication use (for n = 8 participants) by adding 10 mmHg to SBP and DBP (43,44). ^dA-E Change calculated as the difference between the mean afternoon sample and the mean evening sample. ^*Significantly different means (p < 0.05) in independent t-test or Mann-Whitney U test (only salivary cortisol). ^**Significantly different means (p < 0.002) in independent t-test and Pearson Chi-square.

Ever-smoking status was higher among LISD teachers than HISD teachers, driven primarily by past-smokers (31% and 5%, respectively). The mean cigarette pack-years, however, was low among all teachers (2.4). The prevalence of alcohol consumption (69%) and the number of drinks per week (0.8) was lower for LISD teachers compared to HISD teachers (85% and 1.4 drinks per week). The prevalence of respiratory infections in the past month was similar in LISD and HISD (∼30%) (data not shown). Asthma rates were not significantly different between LISD and HISD teachers, although the prevalence of ever experiencing asthma symptoms and diagnosed asthma were higher in HISD teachers (data not shown). BMI was positively correlated to SBP and DBP for all teachers (Pearson coefficient = 0.500 and 0.493, respectively, p < 0.001), and cigarette pack-years for all teachers (Pearson: 0.432, p = 0.001) and LISD teachers (Pearson: 0.392, p = 0.016).

Salivary cortisol samples, on average, were collected by teachers at the LISDs and HISD at a similar time in the evening (7 minutes later in LISDs), but 21 minutes earlier among LISD teachers in the early afternoon (Table 2). Average salivary cortisol levels from the early afternoon were significantly higher among LISD teachers (4.33±2.44 nmol/L) than HISD teachers (3.21±1.70 nmol/L). Neither the evening salivary cortisol levels nor the change in afternoon to evening (A-E) cortisol levels were significantly different by district type. There was a decrease in cortisol levels from the early afternoon to evening samples among all teachers. There was no significant difference in cortisol levels in teachers with second jobs than those without a second job. Afternoon and evening cortisol levels were not significantly correlated to age, cigarette pack-years, BMI, BP, or hours of sleep per night for LISD or HISD teachers. Alcoholic drinks per week were negatively correlated with evening cortisol levels for all participants (Spearman’s rho: –0.291, p = 0.043).

3.4 Teaching stressors

The occupational stressors that at least 60% of teachers expressed being strongly concerned or concerned about (“agree”/“strongly agree” and “disagree”/“strongly disagree”, as appropriate) included: unsuitable classroom temperature (92%), lack of consultation for significant changes (83%), lack of school support staff (81%), disruptive students (80%), lack of appropriate training and support for required changes (78%), lack of time to complete tasks (76%), uncertain job security and school funding (71%), lack of value for work done at home (68%), over-burdensome lesson planning requirements (66%), inadequate classroom maintenance (63%), unreasonable deadlines and time pressures (61%), too many students per class (61%), lack of work-life balance (61%), and the inability to take a proper break during the school day (60%). The occupational stressors that 30% or less of teachers expressed being strongly concerned or concerned about included: poor relationships with colleagues (3%), poor relationships with a supervisor (10%), unclear work expectations (12%), violence from aggressive parents (15%), lack of opportunities to share ideas and perspectives (19%), lack of encouragement to use skills and initiatives in their work (20%), unsupportive supervisors (24%), and unacceptable total working hours (27%). A full list of teaching stressor questions and responses are in listed in the Appendix.

The ten occupational stressors that LISD and HISD teachers rated most differently are presented in Table 3 (additional data are in Table A1). Concerns about job security and funding, disruptive and violent students, aggressive parents, acceptability of physical working conditions, and effective leadership in the school were all significantly different between the two district types. LISD teachers “agreed” or “strongly agreed” more frequently that they deal with disruptive (95% vs. 50% in HISD) and violent students (67% vs. 5% in HISD), and are concerned about violence from aggressive parents (23% vs. 0% in HISD) and job security (87% vs. 40% in HISD). LISD and HISD teachers largely “agreed” and “strongly agreed” that their classrooms were often too cold or warm (95% and 85%, respectively).

Table 3
Selected responses on perceived occupational teaching stressors, where responses were most disparate between the LISD and HISD teachers

Strongly Disagree Agree Strongly

disagree Agree

n % n % n % n %

I am concerned about school funding and job security: (demands)^*

Low-income districts 1 3% 4 10% 13 33% 21 54%

High-income district 4 20% 8 40% 4 20% 4 20%

The school benefits from effective leadership (support)^*

Low-income districts 2 5% 14 36% 16 41% 7 18%

High-income district 3 15% 2 10% 6 30% 9 45%

Staff are afraid to complain in case they are “picked on” (relationships)

Low-income districts 1 3% 16 41% 15 39% 7 18%

High-income district 5 25% 8 40% 5 25% 2 10%

I regularly have to deal with disruptive students (relationships)^*

Low-income districts 0 0% 2 5.10% 8 21% 29 74%

High-income district 1 5% 9 45% 6 30% 4 20%

I have to deal with violent students (relationships)^*

Low-income districts 4 10% 9 23% 14 36% 12 31%

High-income district 11 55% 8 40% 1 5% 0 0%

I am concerned about violence from aggressive parents (relationships)^*

Low-income districts 7 18% 23 59% 7 18% 2 5%

High-income district 13 65% 7 35% 0 0% 0 0%

I’m clear about what is expected of me at work (role)

Low-income districts 1 3% 5 13% 23 59% 10 26%

High-income district 0 0% 1 5% 7 35% 12 60%

My physical working conditions are acceptable (environment)^*

Low-income districts 5 13% 10 26% 22 56% 2 5%

High-income district 0 0% 4 20% 6 30% 10 50%

The school and classrooms are well maintained (environment)

Low-income districts 9 23% 18 46% 12 31% 0 0%

High-income district 1 5% 9 45% 8 40% 2 10%

The classrooms are often too cold/warm (environment)

Low-income districts 0 0% 2 5% 13 33% 24 62%

High-income district 0 0% 3 15% 11 55% 6 30%

	Strongly	Disagree	Agree	Strongly
I am concerned about school funding and job security: (demands)^*
Low-income districts	1	3%	4	10%	13	33%	21	54%
High-income district	4	20%	8	40%	4	20%	4	20%
The school benefits from effective leadership (support)^*
Low-income districts	2	5%	14	36%	16	41%	7	18%
High-income district	3	15%	2	10%	6	30%	9	45%
Staff are afraid to complain in case they are “picked on” (relationships)
Low-income districts	1	3%	16	41%	15	39%	7	18%
High-income district	5	25%	8	40%	5	25%	2	10%
I regularly have to deal with disruptive students (relationships)^*
Low-income districts	0	0%	2	5.10%	8	21%	29	74%
High-income district	1	5%	9	45%	6	30%	4	20%
I have to deal with violent students (relationships)^*
Low-income districts	4	10%	9	23%	14	36%	12	31%
High-income district	11	55%	8	40%	1	5%	0	0%
I am concerned about violence from aggressive parents (relationships)^*
Low-income districts	7	18%	23	59%	7	18%	2	5%
High-income district	13	65%	7	35%	0	0%	0	0%
I’m clear about what is expected of me at work (role)
Low-income districts	1	3%	5	13%	23	59%	10	26%
High-income district	0	0%	1	5%	7	35%	12	60%
My physical working conditions are acceptable (environment)^*
Low-income districts	5	13%	10	26%	22	56%	2	5%
High-income district	0	0%	4	20%	6	30%	10	50%
The school and classrooms are well maintained (environment)
Low-income districts	9	23%	18	46%	12	31%	0	0%
High-income district	1	5%	9	45%	8	40%	2	10%
The classrooms are often too cold/warm (environment)
Low-income districts	0	0%	2	5%	13	33%	24	62%
High-income district	0	0%	3	15%	11	55%	6	30%

^*Significantly different means (p < 0.05); Chi-square test.

The overall standardized composite stressor score and four of the six stressor categories (demands, relationships, role, and environment) showed significant differences between LISD and HISD teachers (Table 4). The overall standardized composite stressor score and individual stressor categories were all significantly correlated with each other (p < 0.005) for all participants, except for demands and control composite scores with the environment composite score.

Table 4

Standardized composite scores for perceived teaching stressors

	Low-income		High-income
	school		school
	districts		district
	Mean	SD	Mean	SD
n	39 (38)		20
Demands^*	2.9	0.49	2.5	0.59
Control	2.4	0.52	2.2	0.63
Support	2.6	0.49	2.3	0.64
Relationships^**	2.4	0.38	1.9	0.43
Role^*	2.6	0.43	2.3	0.53
Environment^*	2.7	0.46	2.3	0.57
Overall^**	2.63	0.31	2.29	0.45

^*Significantly different means (p < 0.05); independent t-test. ^**Significantly different means (p≤0.001); independent t-test.

3.5 School and classroom environmental assessments

School characteristics varied for the 15 LISD schools and 11 HISD schools (Table 5). Schools were built significantly more recently in the HISD (1978) than in the LISDs (1953). All HISD schools were observed as having a well maintained exterior, while only 67% of LISD schools had a similar designation. The mean number of roadways within 1 km of each school with greater than 5,000 vehicles per day AADT was similar at LISDs (3.1) and at HISD (2.9). The mean number of high AADT volume roads (> 10,000 AADT) within 1 km of the school were more common in HISD schools than LISD schools (2.6 vs. 2.1, respectively) (data not shown). There were more schools within 1 km of Toxic Release Inventory-reporting facilities at LISD schools (27%) than at the HISD schools (9%), although this was not a significant difference. The number of environmentally-contaminated sites as reported by the MDEQ was significantly higher (p = 0.013) within 1 km of LISD schools (3.8) than HISD schools (0.8). There was no significant difference between outdoor sound measurements at each school (LAeq 55.6±5.5 at LISDs and LAeq 53.4±4.7 at HISD).

Table 5
School and classroom characteristics, including school type and environmental hazards, and classroom maintenance and temperature

Low-income High-income

school school

districts district

n % n %

School n schools 15 11

n participants per school (mean [SD]) 2.6 (2.6) 1.8 (1.3)

School type:

Elementary school 11 73% 5 46%

Middle school 1 7% 4 36%

High school 2 13% 2 18%

Alternative school (K-12)^a 1 7% 0 0%

Year built (mean [SD])^** 1953 (14) 1978 (13)

Neighborhood school 9 60% 6 55%

School exterior well maintained 10 67% 11 100%

TRI-reporting sites within 1 km^b 4 27% 1 9%

MDEQ contaminated sites within 1 km (mean [SD])^c * 3.8 (4.0) 0.8 (1.0)

Moderate and high-volume roads within 1 km (mean [SD]) 3.1 (0.6) 2.9 (0.7)

Classroom Maintenance

Flooring well maintained 24 62% 19 95%

Ceiling well maintained 28 72% 18 90%

Walls well maintained 29 74% 20 100%

Odor present 3 8% 0 0%

Room temperature (F) (mean [SD])^* 72.8 (4.1) 69.4 (3.6)

Room humidity (%) (mean [SD]) 40.7 (9.7) 36.8 (8.8)

		Low-income	High-income
School	n schools	15	11
	n participants per school (mean [SD])	2.6 (2.6)	1.8 (1.3)
	School type:
	Elementary school	11	73%	5	46%
	Middle school	1	7%	4	36%
	High school	2	13%	2	18%
	Alternative school (K-12)^a	1	7%	0	0%
	Year built (mean [SD])^**	1953 (14)	1978 (13)
	Neighborhood school	9	60%	6	55%
	School exterior well maintained	10	67%	11	100%
	TRI-reporting sites within 1 km^b	4	27%	1	9%
	MDEQ contaminated sites within 1 km (mean [SD])^c *	3.8 (4.0)	0.8 (1.0)
	Moderate and high-volume roads within 1 km (mean [SD])	3.1 (0.6)	2.9 (0.7)
Classroom	Maintenance
	Flooring well maintained	24	62%	19	95%
	Ceiling well maintained	28	72%	18	90%
	Walls well maintained	29	74%	20	100%
	Odor present	3	8%	0	0%
	Room temperature (F) (mean [SD])^*	72.8 (4.1)	69.4 (3.6)
	Room humidity (%) (mean [SD])	40.7 (9.7)	36.8 (8.8)

^aAlternative schools are schools which usually serve K-12 grades for students who are at risk of not graduating or have specific needs (51). ^bToxic Release Inventory (TRI)-reporting facilities within a 1 km radius of the school (48). ^cEnvironmentally contaminated sites reported by the Michigan Department of Environmental Quality (MDEQ) within a 1 km radius of the school (47). ^dModerate-volume roads refers to 5,000–10,000 vehicles per day (of the average annual daily traffic; AADT); high-volume roads refers to > 10,000 vehicles per day (AADT) within a 1 km radius of the school (46). ^*Significantly different means (p < 0.05); independent t-test. ^**Significantly different means (p = 0.001); independent t-test.

Most classrooms had windows or doors that could be opened in both school district types (83%). Mean classroom temperatures were significantly higher in LISD classrooms (72.8±4.1 °F) compared to the HISD (69.4±3.6 °F; p = 0.003). Relative humidity was only slightly higher in LISD classrooms (41% vs. 37% in HISD). Classroom flooring, ceiling, and wall maintenance quality were lower in LISDclassrooms.

3.6 Overall analysis

Bivariate analyses of standardized composite scores for teaching stressors overall and by categories were performed with health, occupational, and environmental measures. The teaching stressors standardized composite score for demands was negatively correlated with average hours of sleep per night for all teachers (Pearson coefficient: –0.332, p = 0.013) and HISD teachers (–0.467, p = 0.044), and the year a school was built for all teachers (–0.342, p = 0.019). The year a school was built was negatively correlated with the standardized composite score for all teaching stressors (–0.386, p = 0.007) for all teachers. The teaching standardized composite score for relationships was positively correlated to BMI for all teachers (0.266, p = 0.046) and negatively correlated to hours spent working in a second job for LISD teachers (–0.668, p = 0.012). Cortisol levels and BP were not significantly correlated with teaching stressors, for all participants or by HISD or LISD separately.

Bivariate analyses were also performed for environmental measures with health, occupational, and other environmental measures. The number of environmentally-contaminated sites within 1 km of the school for all teachers was positively correlated with heart rate (Pearson coefficient = 0.316, p = 0.015), the number of moderate and high volume AADT roadways within 1 km (0.392, p < 0.002), and classroom temperature (0.286, p = 0.028). Among LISD teachers, the year a school was built was negatively correlated with average afternoon cortisol levels (Spearman’s rho: –0.328, p = 0.043), years in the position (Pearson coefficient: –0.419, p = 0.030), average hours of sleep per night (–0.449, p = 0.021) and positively correlated to the number of moderate and high volume AADT roadways within 1 km (0.879, p < 0.001) and the number of environmentally-contaminated sites within 1 km (0.538, p = 0.003).

In linear regressions of SBP and DBP for all teachers adjusting for the school district type, standardized teaching stressor score, environmentally contaminated sites near the school, moderate and high vehicle AADT volume, age, sex, and cigarette pack-years, BMI was significantly associated with increased SBP (p < 0.001) and DBP (p < 0.001; adjusted for BP medication usage). The number of alcoholic drinks per week was associated with an increase in DBP (p = 0.049) but not SBP (medication usage-adjusted) when adjusting for the same variables. Other demographic, health, stressor, and environmental quality variables were not significantly associated with SBP or DBP.

In linear regressions of cortisol levels for all teachers adjusting for the school district type, standardized teaching stressor score, environmentally contaminated sites near the school, age, sex, and cigarette pack-years, moderate and high vehicle AADT volume was significantly associated with a decrease in afternoon cortisol levels (p = 0.025). Age and the number of alcoholic drinks per week were significantly associated with a decrease in evening cortisol levels when adjusting for the same variables (p = 0.043 and 0.038, respectively). Other demographic, health, stressor, and environmental quality variables were not significantly associated with cortisol levels. Overall standardized teach stressor scores were only significantly associated with the district income level (p = 0.013) in models adjusted for the same demographic, health, and environmental quality variables.

4 Discussion

This study observed some notable differences in occupational and environmental stressors and biological stress response in teachers from high and low-income school districts. LISD teachers had higher cumulative standardized score for overall and individual categories of teaching stressors, and were significantly more concerned about student and parent behaviors, working conditions, effective leadership, and job security than teachers in the HISD. The higher stress in LISDs suggests concerns for more significant job strain and stress responses in LISD teachers than in HISDs. Concerns over job security align with a national trend of decreasing teacher wages. In 2015, overall compensation was 11% lower and weekly wages were 17% lower for public school teachers than other comparable workers, which is a significant decrease from a 1.8% disparity in 1994 [8]. While LISD teachers were significantly more likely to be older, they have worked in the school district for a similar number of years as the HISD teachers (∼12 years).

Cortisol levels were comparable to other working populations, particularly for evening cortisol measures [31]. Evening salivary cortisol levels of participating teachers (3.11 nmol/L and 2.51 nmol/L for LISD and HISD teachers, respectively, sampled at 21:30) were comparable to the average level found in U.S. adults (2.8 nmol/L) [31] and Finnish health care professionals working morning shifts with high strain (2.9 nmol/L) and low-strain (2.93 nmol/L) positions sampled at approximately 22:00–23:00 [52]. Afternoon salivary cortisol levels of participating teachers (4.33 nmol/L and 3.21 nmol/L for LISD and HISD teachers, respectively, sampled at 12:30–13:00) were higher than observed cortisol levels measured at about 15:00 among urban teachers in Malaysia (2.84 nmol/L) [53], and comparable to Singaporean general ward (3.59 nmol/L) and emergency ward nurses (3.31 nmol/L) sampled at 13:00–14:00 [54]. Our study did not measure morning cortisol levels, however morning salivary cortisol levels for U.S. adults are comparable to levels found in two studies noted earlier for Singaporean nurses [54] and Finnish healthcare workers [52], suggesting they are a reasonable comparison.

Higher cortisol levels among LISD teachers, particularly in the afternoon, may be related to significantly higher perceived teaching stressors and/or sampling differences. Afternoon cortisol levels were taken approximately 20 minutes later, on average, in the HISD than in the LISDs, which could explain the observed difference between the two groups since cortisol generally decreases throughout the day. If stressors are higher for LISD teachers, the implications for self-rated health and health outcomes are important. Elevated evening cortisol levels are associated with stress and poor self-rated health among healthy office workers [27, 29], but not with burnout or exhaustion among teachers, despite a noted subtle HPA axis dysregulation [7].

Cigarette smoking, alcohol consumption, and caffeine consumption can all influence cortisol levels, although their influence varies depending on other factors [34, 35]. Cortisol may not have been significantly correlated to cigarette pack-years in this study due to relatively low levels of cigarette use [32, 55]. Research findings on the influence of alcohol consumption on cortisol levels are mixed and have often examined the effect in heavy drinkers and chronic alcoholics [35], and does not compare to our study population, which had relatively low levels of alcohol consumption.

New guidelines on hypertension set by the American Heart Association in 2018 [41] have resulted in a higher prevalence of hypertension among participating teachers (51%). Using previous guidelines of hypertension (SBP ≥140 or DBP ≥90), 26% of LISD teachers and 10% of HISD teachers would be hypertensive [42]. The hypertension prevalence from the 2017 guidelines for LISD teachers would exceed the prevalence among general U.S. teachers (19.3%) [56], although would fall just below the national average (29%) [57]. While there were not significant differences in BP or hypertension for LISD and HISD teachers under the new guidelines, differences in occupational stressors, personal stressors, diet, and lifestyle between teachers working in low- or high-income school districts may play a role in BP since high job strain has been associated with elevated risks of cardiovascular disease [58, 59].

Environmental hazards and perceived environmental stressors were greater at LISD schools than HISD schools. While there were not significant differences in the number of moderate and high traffic volume roadways and the number of Toxic Release Inventory-reporting sites within 1 km of participating schools, there were significantly more sites of environmental contamination within 1 km of LISD schools than HISD schools. Other research has found similar results, that schools with a greater number of students eligible to receive free or low-cost school meals have higher nearby air pollution releases [11, 60].

School buildings were significantly older in the LISDs by about 25 years. Two of the LISDs were in older urban areas while the HISD was a relatively younger suburban community. A report by the Michigan Land Use Institute concluded that Michigan constructed schools in suburban and rural areas at a higher rate in recent years than did other states [61], which may explain why school buildings were older in the more urban LISDs. The older school buildings may also explain greater maintenance concerns. Concerns about schools’ exterior and interior classroom maintenance were observed at a more pronounced rate in the LISD schools in our study. A study of U.S. public schools found that investments in school infrastructure in the late 1990s and early 2000s was disproportionately higher in higher income school districts, which could contribute to poorer quality school and classroom environments and additional occupational stressors for teachers in low income school districts [62]. Higher classroom temperatures in LISD classrooms were likely due to the later timing of sampling in the spring season and warmer outdoor temperatures.

Overall, LISD teachers had significantly lower self-rated health and less reported sleep per night; higher perceived occupational teaching stressors, BMI, cigarette pack-years, and afternoon cortisol levels; worked at older schools and schools with a greater number of environmentally-contaminated sites within 1 km; and worked in classrooms that were less likely to have well-maintained floors and walls than HISD teachers. There were no significant observable differences in BP, hypertension prevalence, evening cortisol, alcohol consumption, having a second job or hours working a second job, asthma rates, respiratory infection rates, school exterior maintenance, the number of moderate- and high-volume AADT roadways and TRI-reporting facilities within 1 km of the school, and school sound levels among LISD and HISD participant schools. All significant differences that were observed between LISD and HISD teachers were in the direction of a higher amount of stress or worse health outcomes for LISD teachers. The results of this pilot study indicate that we may expect higher cumulative stressors and possibly worse health outcomes for teachers in lower-income school districts compared to their counterparts in higher-income school districts, although differences in individual stressors may be less remarkable.

Karasek et al.’s (1981) job-strain model, which proposes that occupational demands and degree of control, or decision latitude, determines occupational stress, suggests that a high strain position with high demands and low control produces the most stress [63]. Participating teachers expressed concern about over-burdensome work demands and expectations and a lack of control/certainty, but generally expressed positive relationships with coworkers and control to express ideas and expertise. Within teaching, Siegrist (1994) proposed the effort-reward imbalance model of occupational stress, where high-cost (effort) and low-gain (rewards) produces the most stress [64]. Using Siegrist’s effort-reward imbalance model, teachers in this study expressed high effort workloads and moderate rewards, signifying a slight imbalance. In other studies, poor social support and staff relationships, disruptive students, and “red tape” were key factors identified in teacher burnout [65, 66]. Positive relationships and support may help to ameliorate the negative impacts of over-burdensome workloads.

Stressors for teachers can play an important role in health and student success. A study of 55 healthy teachers found a dampened immune defense in teachers with high over commitment and effort-reward-imbalance [67]. In a study of salivary cortisol among elementary school students, teachers’ burnout levels were significantly associated with their students’ morning cortisol levels, signifying that occupational teaching stressors may trickle down to impact students [68]. This implies that teachers’ occupational stress may impact students’ stress and stress responses [68]. Better classroom quality was also associated with increased teacher-child relationship quality and academic skills in high-needs elementary schools [69], suggesting a critical role of resource availability and school quality in occupational teacher stress and student success for at-risk students. Worse environmental quality near schools has also been associated with increased exposure to pollution and worse student academic performance [11, 60].

Owens, Reardon and Jencks [70] found that income segregation between school districts grew by 17% from 1990 to 2010 among all U.S. families with children enrolled in public schools and by about 40% from 1990 to 2012 in the 100 largest U.S. school districts, driven mostly be segregation among families within the top 60% of income distribution [70]. Growing income inequality has been linked with residential income segregation, which affects economic segregation between school districts and schools [70 –72]. While this study did not examine income levels of families at specific schools, it is noteworthy that there are likely within-district school effects of school income on teacher stress. Given the increasing income segregation occurring between school districts, there is cause for concern over occupational stressors for teachers in low-income school districts that could have implications on teacher health and student learning more broadly.

4.1 Limitations

As a pilot study with a relatively low sample size, these results are limited and a larger sample size is needed to elucidate further relationships. Robust conclusions from linear regressions to assess associations while adjusting for covariates are limited given the small sample size. Owing to the use of convenience sampling, there is a possibility of selection bias, as teachers that are under significant stress or with significant health problems may have disproportionately participated in the study. At the recruitment event or through other contact with teachers before participation, all teachers were encouraged to participate regardless of any stated stress level or health concern. We relied on self-reported data for the majority of our measures, which could have influenced participants’ responses (e.g., smoking or drinking history, weight, income). The survey was completed by participants directly, to afford additional privacy and reduce pressures to modify answers to social norms.

Participants provided information on demographics, behavior, occupation, and perceived stress from occupational factors. It is noteworthy, however, that there are a multitude of non-occupational factors that may influence stress that were not assessed, including other physical health concerns, mental health, relationships, and financial concerns. Household income, the number of children living at home, and hours of sleep per night were assessed to have a rudimentary reflection of some of these factors. The impact of these other stressors is unknown and may have a significant role in stress response for participants.

For most participants, we have six salivary cortisol measurements, which aids our ability to capture a more accurate cortisol reading. Participants were advised to collect saliva samples shortly prior to lunch and before going to bed, however, there was some variability in timing between each of the three samples at each time point, as sleeping times varied and some samples during the day were delayed due to unforeseen demands at work. Additionally, collecting cortisol samples in the morning would have improved our ability to interpret the data relative to other research. Another limitation includes the risk for improper saliva collection methods. If the SOS was not fully saturated, cortisol measurements could have been skewed. Despite these limitations, to our knowledge, this is one of the only studies of its kind to assess perceived stress related to teaching, blood pressure, and salivary cortisol with public school teachers by income level in the U.S.

5 Conclusions

While the conclusions from this pilot study are limited, the results indicate that although differences in individual occupational or environmental stressors may be not be very dissimilar between teachers at low or high-income school districts, there may be a larger difference when examining cumulative stressors. Despite being a significant portion of the labor force with widely recognized high stress loads and burnout [73], our understanding of stressors related to teaching and the environment, especially in lower-income school districts, is limited for public school teachers in the United States. Higher rates of environmentally-contaminated sites near LISDs and worse school infrastructure contribute to cumulative stress loads for teachers in low-income school districts. Occupational stressors are likely compounded by additional financial, economic, and environmental concerns for teachers living in lower-income school districts. Furthermore, quantifying cumulative teaching and school-related stressors may be important in addressing the upstream factors associated with downstream health outcomes. It is unclear if proximity to environmentally-contaminated sites or worse classroom or school quality is associated with higher teaching stress and worse health outcomes, or how teaching stressors influence health. Follow-up research on stressors and health outcomes in low-income school districts may help to identify factors to mitigate teacher stress. In order to address rapid turnover rates and burnout for teachers, and inadvertently influence child health and student success [68, 69], education and municipal systems should work to target key areas for interventions.

Funding

This study was funded by the Centers for Disease Control and Prevention (Grant or Cooperative Agreement Number T42 OH008455). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the Department of Health and Human Services.

Conflict of Interest

The authors declare no conflict of interest.

Footnotes

Acknowledgments

We would like to thank the contributions of all of the participants, school district superintendents, and school office staff. Other members of the research team, Leah Meyers, Lauren Simancek, and Diana Zhang, were integral for data collection.

Appendix

All perceived occupational teaching stressors by low-income school districts (LISDs) and high-income school district (HISD) teachers, by demands, control, support, relationships, role, and environment

	Strongly		Disagree		Agree		Strongly		Pearson
	disagree						Agree		Chi-square
	n	%	n	%	n	%	n	%
Demands
My total working hours are acceptable:
High-income district	1	5%	5	25%	9	45%	5	25%	0.750
Low-income districts	4	10%	6	15%	20	51%	9	23%
There are too many after school meetings:
High-income district	3	15%	6	30%	7	35%	4	20%	0.893
Low-income districts	9	23%	11	28%	13	33%	6	15.4%
Unreasonable deadlines and time pressures are often imposed on me:
High-income district	3	15%	8	40%	6	30%	3	15%	0.286
Low-income districts	3	8%	9	23%	14	36%	13	33.3%
The balance between work and home life is about right:
High-income district	2	10%	8	40%	8	40%	2	10%	0.396
Low-income districts	11	28%	15	39%	10	26%	3	8%
The school values the time we put in at home:
High-income district	4	20%	10	50%	4	20%	2	10%	0.264
Low-income districts	15	39%	11	28%	11	28%	2	5%
I am able to take a proper break during the school day:
High-income district	5	25%	5	25%	7	35%	3	15%	0.739
Low-income districts	10	26%	14	36%	10	31%	3	8%
Lesson planning requirements are over-burdensome:
High-income district	1	5%	9	45%	4	20%	6	30%	0.250
Low-income districts	2	5%	8	21%	14	36%	15	39%
I feel burdened by too many students in each class:
High-income district	2	10%	8	40%	6	30%	4	20%	0.304
Low-income districts	4	10%	9	23%	9	23%	17	44%
I am concerned about school funding and job security:
High-resource district	4	20%	8	40%	4	20%	4	20%	0.002
Low-resource districts	1	3%	4	10%	13	33%	21	54%
Control
I have opportunities to express my ideas and points of view
High-income district	1	5%	2	10%	14	70%	3	15%	0.960
Low-income districts	3	8%	5	13%	26	67%	5	13%
I have to neglect some tasks because I have too much to do
High-income district	2	10%	4	20%	7	35%	7	35%	0.551
Low-income districts	1	3%	7	18%	19	49%	12	31%
There is too much classroom observation
High-income district	4	20%	12	60%	3	15%	1	5%	0.445
Low-income districts	5	13%	18	46%	12	31%	4	10%
I am encouraged to use my skills and initiative to do my work
High-income district	1	5%	2	10%	10	50%	7	35%	0.610
Low-income districts	1	3%	8	21%	21	54%	9	23%
Support
I receive appropriate training
High-income district	2	10%	5	25%	10	50%	3	15%	0.409
Low-income districts	6	16%	15	40%	15	40%	2	5%
I do not have enough support in dealing with bureaucratic paperwork
High-income district	4	20%	6	30%	8	40%	2	10%	0.837
Low-income districts	5	13%	11	28%	14	36%	9	23%
My supervisors are supportive
High-income district	2	10%	4	20%	5	25%	9	45%	0.198
Low-income districts	4	10%	4	10%	22	56%	9	23%
I regularly receive positive feedback on my work
High-income district	2	10%	8	40%	4	20%	6	305	0.330
Low-income districts	2	5%	22	56%	10	26%	5	13%
There are too few support staff in the school
High-income district	1	5%	5	25%	8	40%	6	30%	0.210
Low-income districts	0	0%	5	13%	14	36%	20	51%
The school benefits from effective leadership
High-income district	3	15%	2	10%	6	30%	9	45%	0.032
Low-income districts	2	5%	14	36%	16	41%	7	18%
Relationships
I have a good relationship with my supervisor
High-income district	1	5%	2	10%	7	35%	10	50%	0.271
Low-income districts	0	0%	3	8%	22	56%	14	36%
I get along well with colleagues
High-income district	0	0%	1	5%	9	45%	10	50%	0.670
Low-income districts	0	0%	1	3%	22	56%	16	41%
Management promotes positive behaviors at work to avoid conflict and ensure fairness in the workplace
High-income district	2	10%	4	20%	8	40%	6	30%	0.398
Low-income districts	3	8%	12	31%	19	49%	5	13%
Staff are afraid to complain in case they are ‘picked on’
High-income district	5	25%	8	40%	5	25%	2	10%	0.050
Low-income districts	1	3%	16	41%	15	39%	7	18%
I regularly have to deal with disruptive students
High-income district	1	5%	9	45%	6	30%	4	20%	< 0.001
Low-income districts	0	0%	2	5.10%	8	21%	29	74%
I have to deal with violent students
High-income district	11	55%	8	40%	1	5%	0	0%	< 0.001
Low-income districts	4	10%	9	23%	14	36%	12	31%
I am concerned about violence from aggressive parents
High-income district	13	65%	7	35%	0	0%	0	0%	0.002
Low-income districts	7	18%	23	59%	7	18%	2	5%
Role
I’m clear about what is expected of me at work
High-income district	0	0%	1	5%	7	35%	12	60%	0.072
Low-income districts	1	3%	5	13%	23	59%	10	26%
My skills are well-used
High-income district	0	0%	3	15%	10	50%	7	35%	0.221
Low-income districts	2	5%	13	33%	17	44%	7	18%
I feel valued in my role
High-income district	2	10%	4	20%	8	40%	6	30%	0.118
Low-income districts	5	13%	19	49%	10	26%	5	13%
I find it difficult to cope with the pace of organizational or curriculum change
High-income district	3	15%	9	45%	4	20%	4	20%	0.205
Low-income districts	1	3%	17	44%	15	39%	1	3%
I find the introduction of new initiatives intimidating
High-income district	4	20%	10	50%	3	15%	3	15%	0.164
Low-income districts	4	10%	13	33%	17	44%	5	13%
There is full staff consultation when any significant change is proposed
High-income district	7	35%	11	55%	2	10%	0	0%	0.572
Low-income districts	16	41%	15	39%	7	18%	1	3%
Changes are accompanied by appropriate support and training, where necessary
High-income district	4	20%	12	60%	4	20%	0	0%	0.340
Low-income districts	14	36%	16	41%	9	23%	0	0%
Environment
My physical working conditions are acceptable
High-income district	0	0%	4	20%	6	30%	10	50%	< 0.001
Low-income districts	5	13%	10	26%	22	56%	2	5%
Our restrooms are poorly maintained
High-income district	6	30%	6	30%	6	30%	2	10%	0.420
Low-income districts	5	13%	13	33%	14	36%	7	18%
The school and classrooms are well maintained
High-income district	1	5%	9	45%	8	40%	2	10%	0.079
Low-income districts	9	23%	18	46%	12	31%	0	0%
I am concerned about outdoor air quality at the school
High-income district	9	45%	8	40%	2	10%	1	5%	0.265
Low-income districts	8	21%	22	56%	5	13%	4	10%
I am concerned about indoor air quality at the school
High-income district	3	15%	4	20%	8	40%	5	25%	0.752
Low-income districts	3	8%	11	28%	17	44%	8	21%
The classrooms are often too cold/warm
High-income district	0	0%	3	15%	11	55%	6	30%	0.060
Low-income districts	0	0%	2	5%	13	33%	24	62%

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	Low-		High-
	income		income
	districts		district
	n	%	n	%
n of participants	39		20
n schools	14		12
Age (mean [SD])^*	44.3 (8.1)		38.9 (9.2)
Years in school district (mean [SD])	12.1 (10.0)		12.3 (7.7)
Sex: Male	4	10%	5	25%
Race and ethnicity:
White	32	84%	20	100%
Black or African	5	13%	0	0%
Asian	1	3%	0	0%
Latino or Hispanic	0	0%	0	0%
Marital status:
Single	7	18%	3	15%
Married	23	61%	17	85%
Divorced	6	16%	0	0%
Separated	1	3%	0	0%
Not married, cohabitating	1	3%	0	0%
Household income (USD):
$20,000 to $40,000	4	11%	0	0%
$40,000 to $60,000	7	19%	1	5%
$60,000 to $80,000	8	22%	4	20%
$80,000 to $100,000	4	11%	3	15%
$100,000 to $120,000	5	14%	2	10%
$120,000 to $140,000	2	6%	3	15%
> $140,000	6	17%	7	35%
Education:
Bachelor degree	5	13%	2	10%
Graduate degree	33	87%	18	90%