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The Worksite Blood Pressure Study (Cornell University Medical Center)

The Cornell University cohort study of ‘job strain’ and ambulatory blood pressure, begun in 1985, has enrolled 372 initially healthy full-time employees from a wide variety of job titles, aged 30-60, most with at least 3 years tenure with their employer. Of the 372 participants, 80 (22%) are women, and 95 (25%) are members of minority racial/ethnic groups, including 67 Black, 21 Hispanic and 4 Asian participants. An additional 100 participants, nurses and nurses aides from a new worksite (almost all are female and 50% members of minority groups), are being recruited in 1995 and their evaluation will be completed by 11/1/95. Every three years, participants wear an ambulatory (portable) blood pressure monitor for 24 hours on a work day. Subjects also receive medical tests and complete a questionnaire. Every 15 minutes during waking hours (and during hourly sleep) the monitor inflates and records blood pressure. During waking hours, the subject is asked to remain as motionless as possible and then to record his/her activity, location, position, and mood in a diary. The diary information (i.e., whether the subjects reported being at work, home or sleep) has been used to calculate average AmBPs for each location category.

The Cornell study was one of the first work stress studies to use an ambulatory blood pressure monitor. The monitor provides a more reliable measure of blood pressure, since there is no “observer bias” and the number of readings is increased. It also has a more valid (accurate) measure of average blood pressure than causal blood pressure measurements, since blood pressure is measured during a person’s normal daily activities. Studies using an ambulatory monitor, including the Cornell study, have generally found positive associations between ‘job strain’ and blood pressure.

[372 subjects at 9 New York City worksites w/ 150+ employees (22% women, 25% minorities)]

Eligibility criteria for entry into the study:

  • aged 30-60 at recruitment
  • full-time employee (30+ hours/wk)
  • no second job requiring more than 15 hours/wk
  • able to read and speak English
  • body mass index < 32.5 kg/m² at screening
  • no evidence of CHD
  • screening BPs less than 160/105 mm Hg

General Characteristics of the Cornell Worksite Blood Pressure Project


General Characteristics of the Sample

Among the demographic characteristics of the sample, sex differences were compared in relation to variables with a previously established association with high blood pressure, e.g. age, body mass, race, education and occupation (Table 1). Percentage differences were statistically significant (P < 0.05). The men in the worksites screened were older (41 ± 13 versus 35 ± 12 years, range 16-89 years), taller (176 ± 8 versus 163 ± 7cm) and heavier (80 ± 13 versus 62 ± 13kg) than the women. The men had a larger arm circumference (30 ± 3 versus 27 ± 4cm), more education (38% male versus 30% female college graduates), and were more likely to be white (77% versus 58%). A1though the men were less likely to be in white-collar jobs, when these white-collar jobs were further separated into clerical, managerial or other, 49% of the women were in clerical white&SHY;collar jobs, while only 19% of the men were in this type of positions.

Prevalence of Hypertension by Sex, Age and Worksite

Table 2 compares the prevalence of hypertension across sites by sex and age. Differences between prevalence rates were statistically significant for males (P< 0.001). The overall prevalence of high blood pressure among males was 26%. The site&SHY;specific rate was highest in the two worksites with older, blue&SHY;collar workers, typographers and skilled crafts and sanitation men, with 48 and 33% hypertension, respectively. However, among men aged 50-60 years, brokerage workers were most likely to be hypertensive (53%). The higher crude rates for typographers thus reflected their greater age. The surprisingly high prevalence of hypertension in the stock&SHY;brokerage, where the high educational level suggests a lower than average risk of hypertension, is further examined in the multivariate analysis below, comparing other factors for the individual subject (beyond the occupation and the work environment) which may be related to this outcome.

Among women, the overall prevalence of hypertension was 12%. Differences in prevalence rates for women across sites were also statistically significant (P < 0.001), with the highest prevalence observed in the warehouse, where women were mainly employed in time&SHY;paced packing jobs. When the age&SHY;adjusted rates are compared, differences across sites were significant only for women aged over 50 years (P < 0.05). The highest rates were observed in the warehouse and stock&SHY;brokerage (57 and 50%, respectively) for this age group. Although the warehouse was the site where the proportion of non&SHY;white women was highest (71%), the women at both sites were over represented in clerical or unskilled jobs.

Multivariate analysis of blood pressure differences in 1766 men and 1000 women with complete data, we used analysis of covariance models, testing effects in a stepwise manner, to control simultaneously for factors that might explain blood pressure differences between workers. Of the variance in systolic pressure, 34% was predicted by eight variables (Table 3). While the strongest effects on blood pressure variation were due to age, body mass index and arm circumference (all P~ 0.001), differences between males and females (7.2 mmHg), worksites (9.0 mmHg), years of education completed (4.3 mmHg), marital status (1.8mnHg) and occupational category (2.9 mmHg) accounted for higher systolic pressures. Similar, although somewhat weaker, results for diastolic pressure (Table 4) suggest that after controlling for biological characteristics such as age, body mass index and arm circumference, blood pressure levels differed more by worksite than by any other demographic variable.

Blood Pressure and Race

Consistent with the observation of a higher prevalence of hypertension in the USA among blacks than whites, Table 4 indicates that race was significantly associated with diastolic blood pressure differences (P < 0.05). However, marital status and education were not significant in the equations for diastolic pressure, possibly due to the relatively small sample of blacks.

Blood Pressure and Gender

To test for interactions among sex, biological, demographic and work environment variables, separate analyses were conducted for males and females. The results, while somewhat weaker for men, were similar to those for the previous analysis, with worksite accounting for the highest percentage of explained variance, after sex was controlled (Tables 5-8). Among men, worksite, marital status and education were related to systolic blood pressure after controlling for biological covariates. Among women, only worksite and occupation were related to blood pressure differences, after control variables were entered.

The reference for these tables is: Schlussel YR, Schnall PL, Zimbler M, Warren K, Pickering TG. The effect of work environments on blood pressure: evidence from seven New York organizations. J of Hypertension; 8:679-685, 1990


Table 1. – Biological and demographic characteristics of worksites by sex.

Biological and demographic characteristics Males Females
Age (years) 41 +/- 13 35 +/- 12
Height (cm) 176 +/- 8 163 +/- 7
Weight (kg) 80 +/- 13 62 +/- 13
Arm Circumference (cm) 30 +/- 3 27 +/- 4
Systolic blood pressure (mmHg) 125 +/- 16 114 +/- 16
Diastolic blood pressure (mmHg) 79 +/- 11 72 +/- 11
White % 77 58
Married % 66 36
College graduate % 38 30
White-collar % 50 62
Total (n) 2556 1643

Table 2. – Prevalence (%) of hypertension by worksite, sex and age.

Males Females
Work site 30-39 years 40-49 years 50+ years 30-39 years 40-49 years 50+ years Total
Typographers 50 (2) 34 (59) 52 (207) 0 (0) 0 (0) 0 (6) 47 (275)
Federal agency 8 (123) 31 (77) 41 (63) 11 (119) 23 (75) 45 (71) 19 (648)
Brokerage 24 (182) 37 (90) 53 (66) 10 (84) 15 (34) 50 (20) 17 (1003)
Liquor Marketer 15 (168) 20 (146) 31 (115) 4 (185) 13 (48) 28 (75) 13 (1124)
Hospital 13 (39) 32 (41) 32 (47) 7 (43) 32 (41) 44 (48) 22 (340)
Sanitation 21 (182) 36 (164) 49 (162) 5 (22) 16 (19) 18 (11) 30 (625)
Retail warehouse 9 (53) 25 (32) 47 (34) 18 (17) 21 (14) 57 (23) 20 (259)
Total 17 (749) 31 (609) 45 (694) 8 (470) 20 (231) 39 (254) 21 (4274)
P <0.005 <0.05 <0.005 NS NS <0.05 <0.001

 

Table 3. – Analysis of covariance for systolic blood pressure by biological and demographic variables (n=2766).

Covariate or factor Unadjusted coefficient Difference in blood pressure (mmHg) Significance of F
Arm Circumference 0.94 P=<0.001
Age 0.48 P=<0.001
Body mass index 0.45 P=<0.001
Sex 0.35 P=<0.001
– Male +2.6
– Female -4.6
Worksite 0.29 P=<0.001
– Stock-brokerage +3.5
– Hospital Employees +0.7
– Sanitation Facility +0.2
– News typographers -1.8
– Federal agency -2.6
– Retail warehouse -3.5
– Liquor marketer -5.5
Occupation 0.23 P<0.005
– Clerical +1.4
– Blue Collar +0.5
– Managerial -0.6
– White collar -1.6
Education 0.19 P<0.05
– Grade school +2.9
– High school +0.4
– College -0.3
– Graduate school -1.4
Marital status 0.17 P<0.005
– Single/divorced
/widowed
+1.0
– Married -0.8
R2 = 0.34

Table 4. – Analysis of covariance for diastolic blood pressure by biological and demographic variables (n=2857).

Covariate or factor Unadjusted coefficient Difference in blood pressure (mmHg) Significance of F
Body mass index 0.50 P<0.001
Arm circumference 0.45 P<0.001
Age 0.29 P<0.001
Sex 0.31 P<0.001
– Male +1.3
– Female -2.3
Worksite 0.29 P<0.001
– News typographer +2.0
– Stock-brokerage +1.5
– Sanitation facility +0.5
– Hospital employees -0.8
– Federal agency -1.4
– Retail warehouse -1.9
– Liquor marketer -3.5
Occupation 0.25 P<0.005
– Clerical +0.8
– Blue collar +0.5
– White collar -1.2
– Managerial +0.4
Race 0.05 P<0.05
– Non-white +0.7
– White -0.3
R2 = 0.30

Table 5. – Analysis of covariance of systolic blood pressure by biological and demographic variables in males (n=1766).

Covariate or factor Unadjusted coefficient Difference in blood pressure (mmHg) Significance of F
Age 0.39 P<0.001
Body mass index 0.50 P<0.001
Arm circumference 0.55 P<0.001
Education 0.18 P<0.05
– Grade school +3.1
– High school -0.0
– College -0.1
– Graduate school -1.8
Marital status 0.09 P<0.01
– Single/divorced
/widowed
+1.4
– Married -0.7
Worksite 0.26 P<0.001
– Stock-brokerage +2.9
– Sanitation facility +1.3
– News typographers +0.4
– Hospital employees -1.3
– Federal agency -3.7
– Retail warehouse -5.2
– Liquor marketer -5.9
Occupation 0.15 P<0.10
– Clerical +1.8
– Blue collar -0.5
– White collar -0.3
– Managerial -0.7
R2 = 0.21

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Wave 1 Protocol for Case Control Study and Cross-Sectional Study


The Relationship Between “Job Strain,” Workplace Diastolic Blood Pressure, and Left Ventricular Mass Index: Results of a Case&SHY;Control Study

Peter L. Schnall M.D.,M.P.H.; Carl Pieper Dr.PH; Joseph E. Schwartz Ph.D; Robert A. Karasek Ph.D; Yvette Schlussel Ph.D; Richard B. Devereux M.D.; Antonello Ganau M.D.; Michael Alderman M.D.; Katherine Warren; Thomas G. Pickering M.D., D.Phil


To determine whether “job strain” (defined as high psychological demands and low decision latitude on the job) is associated with increased workplace diastolic blood pressure and the left ventricular mass index, we conducted a case&SHY;control study at seven urban work sites of 215 employed men aged 30 to 60 years without evidence of coronary heart disease. After comprehensive blood pressure screening of male employees (N=2556) at the work site, 87 cases of hypertension and a random sample of 128 controls were studied. In a multiple logistic regression model, job strain was significantly related to hypertension, with an estimated odds ratio of 3.1, after adjusting for age, race, body&SHY;mass index, type A behavior, alcohol intake, smoking, work site, 24&SHY;hour urine sodium excretion, education, and physical demand level of the job. Controlling for the above variables in subjects aged 30 to 40 years with job strain, we found that the echocardiographically determined left ventricular mass index was, on average, 10.8 g/m2 greater than in subjects without job strain. We conclude that job strain may be a risk factor for both hypertension and structural changes of the heart in working men. (]AMA. 1990;263:1929&SHY;1935)

A role for psychosocial factors, such as environmental stress, in the etiology of essential hypertension has been suspected for many years but remains unproved. One reason for this may be that the assessment of the two principal variables involved-stress and blood pressure (BP)-has been problematic. Traditional methods of BP measurement, particularly those done in a clinic, have a low reliability because of error in measurement and high biological variability between measurements. An alternative is to measure BP at the work site, either casually or with the new technology of ambulatory BP monitors (ABPMs). The ABPMs have addressed several problems associated with casual BP measurements. They can obtain readings that are more reliable than casual BP measurement, due to the absence of observer error and the increased number of readings. In addition, ABPM estimates of BP may be a more valid reflection of an individual’s true BP, because ABPMs can sample BP during subjects’ usual activities. Using ABPMs, we recently showed that BP tends to be highest during working hours and that BP measured on a working day was more highly correlated with echocardiographically determined left ventricular mass than BPs measured either in the clinic or on a non-working day. Most of the subjects in these studies had sedentary jobs, suggesting that the higher BPs at work were due to job&SHY;associated psychosocial factors rather than to increased physical activity. One model of stress at work has been shown to be predictive of an increased risk of coronary heart disease as well as psychological symptoms, such as exhaustion and depression. “Job strain,” in this model, is a variable according to which jobs characterized by both high levels of psychological work demands (working fast and hard) and low levels of control over the work process (low job autonomy and little use of skill discretion) are stressful (Fig 1). In these studies, however, the effect of job strain on BP and heart mass was not examined. The present study was designed to test the hypothesis that job strain is a risk factor for hypertension and for increased left ventricular mass. Repeated casual measurements of BP taken at the workplace were used to diagnose hypertension and determine our sample. Ambulatory BP monitoring was then used in a further analysis to verify the validity of the diagnoses of hypertension based on casual BP measurements.

SUBJECTS AND METHODS

This is a case&SHY;control study of working men conducted at seven New York, NY, work sites employing at least 150 men. These sites were a newspaper typography department, a federal health agency, a stock&SHY;brokerage firm, a liquor marketer, a private hospital, a sanitation collection and repair facility, and a department store warehouse. To maximize the generalizability of the findings, work sites and departments within work sites were selected that included a wide range of occupations (both blue-collar and white&SHY;collar). However, a number of types of occupations were not sampled (high&SHY;strain jobs such as manual laborers, assembly&SHY;line workers, and minimum&SHY;wage workers and low strain jobs such as scientists and artists) because of problems of logistics or management resistance at a number of work sites. At least 80% of the employees in a department had to participate in the screening for the employees from that department to be eligible for the study. All employed men underwent an initial BP screening procedure conducted by specially trained staff; this included three sitting readings of BP (using the American Heart Association protocol) and a brief evaluation of medical and demographic variables. Altogether, 2556 male employees were screened at the seven work sites. From this screened sample, subjects were eligible for the study if they were between 30 and 60 years old, were employed more than 30 hours per week, were educated in the United States and able to read English, had a body&SHY;mass index (BMI) of 30 kg/m2 or less, had no second job of 15 or more hours per week, and had been in their current job for at least 3 years. Cases with a history of high BP had to have entered their current job at least 3 years prior to diagnosis. Subjects were excluded if they had a history of coronary, cerebrovascular, or peripheral vascular disease; electrocardiographic evidence of myocardial infarction, ischemia, or atrial fibrillation; funduscopic changes; evidence of any secondary cause of hypertension; diastolic BP (DBP) greater than 105 mm Hg, or systolic BP greater than 160 mm Hg at screening. In addition, subjects who reported taking any drug that might affect their BP (higher or lower) were also excluded from the study, unless they were taking antihypertensive medication for hypertension. Subjects with diagnosed hypertension were eligible only if they could have their medication stopped for at least 3 weeks before wearing the ABPM, with a DBP below 105 mm Hg. Altogether, 1291 men were eligible for the study after the first screening.

BP Criteria for Selection of Cases and Controls

Based on the average of the last two (of three) casual BP measurements taken during the work&SHY;site screening, Subjects who met the above eligibility criteria and had none of the exclusion criteria were divided into two groups: (1) those who had a DBP greater than 85 mm Hg or who were taking antihypertensive medication for hypertension (n = 155) vs. (2) those who had a DBP of 85 mm Hg or less (n= 1136) and were not taking antihypertensive medication. At each work site, all subjects in the first group and a random sample of the second group were invited to a recruitment session. This stratified design was chosen to maximize our ability to test the average within&SHY;site association between job strain and hypertension. At the time of recruitment, 4 to 6 weeks after the initial screening, casual BP measurements were again made at the work site, using the same American Heart Association protocol. Subjects from the first group willing to participate in the study whose recruitment DBP again exceeded 85 mm Hg or who were taking antihypertensive medication were defined as cases, while those willing to participate from the second group whose DBP was again 85 mm Hg or less were defined as controls. Cases and controls were recruited in a ratio of two cases to three controls. Subjects whose BP crossed over at the recruitment visit (initial screening DBP >85 mm Hg and recruitment session DBP </=85 mm Hg, or initial screening DBP </=85 mm Hg and recruitment session DBP >85 mm Hg) were not invited to participate (Fig 2). Based on the initial work&SHY;site screening, 155 men who had a DBP greater than 85 mm Hg or who were taking antihypertensive medication met all the eligibility and exclusin criteria; all of these men were then invited to a recruitment session. Of this group, 87 individuals who had a DBP still above 85 mm Hg or who were taking antihypertensive medication at the recruitment session agreed to participate in the study; all of them subsequently completed the protocol. From the larger population of individuals (n=1136) with a DBP of 85 mm Hg or less at screening, 233 subjects who met the eligibility and exclusion criteria were randomly selected (stratified by work site) and invited to the recruitment session. Of this group, 136 individuals had a recruitment DBP of 85 mm Hg or less and agreed to participate; 128 completed the protocol. The combined group of cases (n=87) and controls (n=128), totaling 215 subjects, constitutes the case control sample. All subjects gave informed consent. Ambulatory BP monitoring was included as part of the evaluation of all 215 subjects, as a check on the validity of our standardized casual BP measuremnts to identify elevated BP and also to determine whether the observed association between job strain and case-contol status was related to the severity of hypertension. A secondary analysis based on ambulatory BP results was performed, in which three subgroups of cases were defined according to their work-time ambulatory DBP: group 1, above 85mm Hg (n=67); group 2, above 90 mm Hg (n=45); and group 3, above 95 mm Hg (n=23). Controls had an ambulatory DBP of 85 mm Hg or less (n=100). Subjects whose worktime ambulatory SBP was inconsistent with their original classification as a case or control (eg, for group 1, controls with an ambulatory DBP >85 mm Hg or cases with an amblatory DBP.

Wave 2 Protocol for Cohort Study


Subjects and Methods

Begun in 1985, this is a prospective cohort study of working men and women conducted at eight New York City work sites each employing at least 150 men. These sites are: a newspaper typography department, a federal health agency, a stock brokerage firm, a liquor marketer, a private hospital, a sanitation collection and repair facility, a department store warehouse and the headquarters for a large insurance company.

The methods for the first round of data collection of this study (Time 1) have been reported in detail elsewhere (JAMA 1990, JAMA 1992, Hypertension 1992). In brief, potential subjects received casual blood pressure screening by department at their worksites and demographic data was collected. For the employees of a department to be eligible for the study at least 75% had to participate in the screening.

From this screened sample, subjects were eligible to be selected for the study if they were between 30 and 60 years old, were employed more than 30 hours/week, were able to read English, had a body mass index (kg/m2) less than 32.5, had no second job of 15 or more hours per week and had been at their current worksite for at least three years before being approached for this study and, if applicable, before being diagnosed as having high blood pressure. To increase the number of eligible subjects for the cohort study at the eighth and last site the following eligibility criteria were changed: (1) subjects were no longer recruited in a fixed ratio (2:3) of cases to controls as at the previous sites; (2) subjects no longer needed to be at their worksite for three years but instead for only one year; and (3) those subjects who had casual screening and recruitment BP changes that resulted in their being classified as “crossovers” and excluded from the analysis for the initial Time 1 of the study were allowed to remain in the cohort study. The third criteria was no longer relevant to the outcome of interest (change in AmBP over time) None of these changes should effect either the effect estimates nor the validity of the findings.

Subjects were excluded from the study if they had a history of coronary, cerebrovascular, or peripheral vascular disease, electro-cardiographic evidence of myocardial infarction, ischemia or atrial fibrillation, funduscopic changes, evidence of any secondary cause of hypertension, screening systolic blood pressure greater than 160 mm Hg or screening diastolic blood pressure greater than 105 mm Hg. Subjects who reported any of the above mentioned cardiovascular events between Time 1 and Time 2 evaluation were excluded from these analyses.

Of the initial 285 male subjects recruited at Time 1, 195 subjects were alive, located and completed Time 2. Twenty-three subjects on anti-hypertensive medications at the time of evaluation at Time 1 and/or Time 2 were included in most analyses despite the potential influence of medications on AmBP changes over time.

Procedures

Subjects wore an AmBP monitor (Spacelabs 5200) for 24 hours during a normal work day, using procedures described previously (James etal 1986) at Time 1 and a Spacelabs 90202 device at Time 2 (ref needed). Readings were collected every 20 minutes during the day at Time 2 instead of every 15 minutes at Time 1. Otherwise the methodology of AmBP data collection was unchanged. The monitor was attached at either the subject’s work site or at the Hypertension Center at Cornell University Medical College (CUMC) Hypertension Center and calibrated by comparing five successive systolic and diastolic readings against simultaneously determined auscultatory readings taken by a trained observer with a mercury column, in which both had to be within 5 mm Hg to be acceptable. The timer on the monitor was set to take readings at 20 minute intervals during the day, and 30 minute intervals during normal hours of sleep, and the subject was instructed to proceed through a normal workday. Each time the monitor inflated and recorded blood pressure during waking hours the subject was asked to remain as motionless as possible and then to record his activity, location, position, and mood in a diary. The diary information (i.e., whether subjects reported being at work, home or sleep) was used to calculate average AmBP for each location category.

Subjects also received a routine medical examination, which included a full history, a cardiovascular physical examination, assessment of alcohol intake, current smoking history, and exercise habits. Height and weight were determined at the physical examination and body mass index (BMI) was calculated according to the formula – weight(kg)/height(m)2. Blood testing, EKG and an M-mode echocardiogram under two dimensional guidance performed according to standard procedures (Devereaux etal 1986) were carried out at the Hypertension Center at CUMC.

Subjects completed a questionnaire packet which included the Job Content Questionnaire (JCQ) to evaluate ‘job strain’. The JCQ is a 42-item questionnaire developed by Dr. Robert Karasek, based, in part, on questions drawn from the US. Department of Labor/University of Michigan Quality of Employment Surveys (Karasek etal 1985). Two scales were used to define ‘job strain’ – job decision latitude and psychological job demands (see Fig. 1). Job decision latitude, an operationalization of the concept of “job control” was defined as the sum of two subscales each given equal weight: 1) skill discretion, measured by 6 items (keep learning new things; can develop skills; job requires skill; task variety; repetitious; job requires creativity), and 2) decision authority, measured by 3 items (have freedom to make decisions; can choose how to perform work; have a lot of say on the job). Psychological job demands was defined by 5 items (excessive work; conflicting demands; insufficient time to do work; work fast; work hard). All questions are scored on a Likert scale of 1 to 4, and both decision latitude and psychological job demands were constructed to have a range of 12 to 48. Scale reliability was acceptable for both decision latitude (Cronbach’s alpha=.82) and workload demands (alpha=.74).

Previous research (Karasek etal 1988) in a nationally representative working male population indicated that about 20% of the men have jobs simultaneously high in demands and low in decision latitude, a situation labeled ‘job strain’ or “high strain jobs”. Cut points for psychological workload demands and job decision latitude were selected so that 20% of our study sample would also be classified as having ‘high strain’ jobs. Jobs were classified as ‘high strain’ if subjects scored both 37 or below for decision latitude and 32 or above for psychological job demands. In addition, the jobs of persons located in the three other quadrants defined by these cut points were labeled active, passive and low strain as shown in Figure 1 (e.g., active jobs were those in which subjects scored both 37 or above for decision latitude and 32 or above for psychological job demands, etc.).

For the cohort analysis a new categorical job strain variable was constructed based on the subjects ‘job strain’ scores at Time 1 and Time 2. Subjects reporting no ‘job strain’ at both Time 1 and Time 2 (Group 1, N=138) are the referent group. Subjects without job strain at Time 1 and with ‘job strain’ at Time 2 are Group 2, N=17, while those reporting ‘job strain’ at Time 1 but no ‘job strain’ at Time 2 are Group 3, N=25. Subjects who reported ‘job strain’ at both Time 1 and Time 2 are classified as having ‘chronic job strain’ Group 4, N=15 (see Fig. 1).

The same battery of psychosocial questionnaires as were administered at Time 1 were again administered at Time 2. The Jenkins Activity Survey was administered to evaluate Type A behavior, and subjects were classified as ‘Type A’ if they scored above 0. A demographic questionnaire elicited information on years of education, individual and family income, marital status, religion, race, age, and employment history. Age was treated as a continuous variable in this analysis. Education was included in this analysis as a control variable because of the known potential impact of low socioeconomic status (often measured as low education) on blood pressure and was entered as a continuous variable in years of education when used as a control variable or as a dichotomous variable for analyses examining effects on AmBP (1 for subjects with 12 years or less education, 0 for subjects with >12 years of education). Alcohol and smoking behavior were assessed by questionnaire at the time of the medical examination with the responses reviewed by a nurse. Subjects were classified either as non-drinkers if they reported they drink not at all or occasionally, or as drinkers if they reported regular consumption (at least 4 or more times per week) or binge drinking. Subjects were classified as smokers if they currently smoke. Race was classified as either Caucasian or other. Finally, physical activity on the job was evaluated by a single item from the JCQ (‘job requires lots of physical effort’) and scored on a Likert scale of 1 to 4. “Job title change” was assessed by an interviewer and defined as either change in job title or a significant change in job duties even if a subjects’ job title was officially unchanged.

Experience of Cohort Sample

A total of 90 subjects who participated at Time 1 were excluded from analysis at Time 2 of the study for the following reasons: 3 were deceased, 6 developed cardiovascular disease, 16 were not employed due to retirement, unemployment, 6 could not be located, 41 refused participation, and 18 failed to complete the protocol (see Table 1 where N=65, those deceased or have developed cardiovascular disease N=9, and those not employed N=16 are excluded due to lack of eligibility for the 2nd wave of study). There are very little missing data for the subjects included in this analysis. Those missing data on either the outcome measure, AmBP or ‘job strain’, the focal predictor, were excluded from the analyses of that outcome. The modal category (or mean) has been substituted for missing data on all categorical (or continuous) covariates.

Case-Control Results


(7 Worksites, n=196 men)

The odds of a Mild Hypertensive (case)
being in a High Strain Job were

2.8 times

that of a Normotensive (p=.03),

controlling for age, body mass, race education smoking, Type A behavior, alcohol consumption, 24-hour urine sodium, and worksite

JAMA (1990,1992)


Descriptive Statistics for Study Sample


As expected, age and BMI were also significantly related to case-control status in the logistic regression model. Regular alcohol consumption was the only other variable found to have a substantial relationship to case-control status, with an adjusted odds ratio of 2.8 (P=.01) after controlling for other risk factors. Cases and controls did not differ significantly on any of the administered psychological measures after controlling for age (Table 4). To assess the validity of casual BP measurement for determining case-control status and to decrease misclassification of subjects, a further analysis was performed using the criterion of average work-time DBP determined by the ABPM. Application of this selection criterion with cutoff points of greater than 85, greater than 90, and greater than 95 mm Hg applied to the cases and 85 mm Hg or less for the controls resulted in three groups: group 1, n=167 (67 cases and 100 controls); group 2, n=145 (45 cases and 100 controls; and group 3, n=123 (23 cases and 100 controls). Logistical regression analyses, controlling for the same variables as above, showed that job strain was a highly significant predictor of case-control status, with adjusted odds ratios of 3.1 for group 1 (95% CI, 1.2 to 8.0), 3.6 for group 2 (95% CI, 1.2 to 10.7, and 24.4 for group 3 (95% CI, 3.6 to 167.0). Despite the sharp reductions in sample size that result from adding an additional selection criterion based on work-time ambulatory BP, the strength and statistical significance of the relationship of job strain to case-control status are clearly greater when we use this more stringent definition of cases and controls.

The reference for these tables is: Schnall PL, Pieper C, Schwartz JE, Karasek RA, Schlussel Y, Devereux RB, Ganau A, Aldermen M, Warren K, Pickering TG. The relationship between job strain, workplace diastolic blood pressure, and left ventricular mass index. JAMA. 1990;263:1929-1935.


Table 1. – Descriptive Statistics for Study Sample

Variable All Subjects (n=215) Controls (9n=128) Cases (n=87)
Screening systolic BP, mm Hg * ^ 125.8 (14.0) 118.9 (10.7) 136.0 (11.9) ~
Screening diastolic BP, mm Hg ^ 81.9 (10.6) 75.2 (6.9) 91.8 (6.4) ~
Age, y ^ 45.0 (8.7) 42.6 (8.5) 48.5 (7.8) ~
Body-mass index, kg/cm2 ^ 26.2 (3.1) 25.4 (2.6) 27.3 (3.3) ~
Education, y ^ 14.2 (2.5) 14.3 (2.5) 13.9 (2.6)
Regular drinkers, % 27 20 38 ~
Type A behavior, % 40 42 36
Physical exertion level ^ $ 1.9 (0.79) 1.9 (0.78) 1.9 (0.81)
White Race, % 81 81 82
Current Smokers, % 22 22 23
Decision latitude ^ || 35.4 (6.1) 36.1 (5.8) 34.4 (6.5) @
Psychological work load ^ || 30.9 (6.1) 31.0 (5.9) 30.7 (6.5)
Job strain, % 21 17 28

*BP indicates blood pressure.

^ Values are mean (SD)

~ P<.01 according to t test

$ Responses are scored on a Likert scale of 1 to 4

|| Responses are scored on a scale of 12 to 48

@ P=<.05 according to t test


Table 2. – Comparison of Participants and Nonparticipants on Selected Risk Factors

Participants (n=125) Nonparticipants (n=165)
Outcome Variables
Hypertensive, % 40 41
Screening systolic BP* 125.8 127.3
Screening diastolic BP 81.9 82.8
Independent Variables
Age, y 45.0 43.5 ^
White race, % 81 80
Education, y 14.2 14.0
Body-mass index, kg/m2 26.2 26.0
Job Strain, % 21 25 ||

*BP indicates blood pressure

^ P<.05.

|| Thirty-six non participants completed the Job Content Survey


Table 3. – Logistical Regression Analysis (n=215)*

Odds Ratio 95% Confidence Interval z
Age,y
41-50 vs 30-40 4.74 1.97 to 11.39 3.47
51-60 vs 30-40 8.3 3.03 to 22.75 4.11
Body-mass index, kg/m2 1.33 1.17 to 1.51 4.46
Regular drinker vs other 2.76 1.28 to 5.93 2.59
High job strain vs other 3.09 1.30 to 7.30 2.57

* After controlling for race, education, smoking, type A behavior, physical exertion level, 24-hour urine sodium excretion, and work site.


Table 4. – Job Characteristics and Psychological Variables by Case Status*

Controls (n=128) All Cases (n=87) New Cases (n=20) ^ Cases Receiving Treatment (n=30) @
Job Content Questionaire
Decision latitude $ 36.0 34.5 34.1 36.3
Psychological work load $ 30.7 31.1 31.9 32.5
Job strain, % 17 28 || 30 23
Jenkins Activity Survey
Type A behavior, % 40.3 38.3 39.8 42.8
Symptom Checklist 90R ~
Anxiety 52.8 55.3 54.8 53.4
Hostility 52.5 53.6 52.9 54.4
Speilberger Anger Questionaire
Anger in # 24.4 24.6 24.2 24.3
Anger out # 14.2 14.3 14.0 15.0
Total Anger** 46.7 46.8 45.7 47.7

* Analysis of covariance was used, controlling for age. There was no statistically significant differences between groups.

^ Cases no currently receiving antihypertensive medication and who had no history of treatment or of high blood pressure.

@ At time of recruitment.

$ Responses are scored on a scale of 12 to 48.

|| P=<.05.

~ Responses are scored on a scale of 35-81.

# Responses are scored on a scale of 8 to 32.

** Responses are scored on a scale of 20 to 80.

Job Strain and Ambulatory Blood Pressure

Summarized from the article: Schnall PL, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. Relation between job strain, alcohol, and ambulatory blood pressure. Hypertension; 19:5, 1992.


One purpose of the present study was to compare analyses of AmBP with our previously published parallel analysis of hypertension. Accordingly, we reexamined the effects of job strain on hypertension and left ventricular mass index (LVMI) now that we have added an eighth site to our study (see Table 2).


Table 2. Effect of Job Strain on Hypertension Case Status and Left Ventricular Mass Index. Controlling for age, body mass index, body mass index stratum, 24-hour urine sodium, work site, Type A behavior, race, education, alcohol, smoking, and physical exertion level on job.

Effect Odds Ratio Effect size (g/m2) x2 F p value*
Case Status (N=264)
Job strain 2.7 5.90 0.015
Left ventricular mass index (N=203)
Job Strain 9.7 3.37 0.001
*Two tailored probability levels

After controlling for the effects of age, BMI, BMI stratum, Type A behavior, 24 hour sodium excretion, physical activity level of the job, education level, smoking status, alcohol intake, and work site, job strain is a significant predictor of case-control status (estimated odds ratio, OR=2.7; p=0.015). After excluding those subjects receiving anti-hypertensive medication, 203 subjects had technically satisfactory echocardiograms. Using an ANCOVA model, we showed that the relation of job strain to LVMI was 9.7 g/m2 (F=3.37; p=0.001) after controlling for the same variables as above. This relation with LVMI was consistent across the three 10-year age groups.

Our job strain model predicts that blood pressure will be elevated in the high-strain quadrant of the model. ANCOVA (high strain versus the three other quadrants combined) supports the job strain hypothesis. The effect of job strain on systolic AmBP at work is 6.8mm Hg (F=5.0; p=0.03) is also statistically significant. It is worth noting that the three non-high strain quadrants are similar to each other in AmBP.

Job strain has the same magnitude of effect on systolic AmBP during at home and asleep hours as it does for working hours, demonstrating a strong effect of job strain on 24-hour AmBP. We also examined the effect of job strain as well as other independent variables on work minus home differences an AmBP. AmBP’s were about 3.5 mm Hg higher at work compared with home, and no variable was found to be related to this difference.

As expected, age and BMI have a large and substantive effects on all measures of AmBP. Regular alcohol consumption has an effect on both systolic and diastolic AmBP at work of about 3.6 mm Hg (p=0.06) and 2.8 mm Hg (p=0.02), respectively. Cigarette smoking has a main effect on systolic AmBP of 4 mm Hg at work (NS), 5.2 mm Hg at home (F=5.5; p=0.02), and 3.9 mm Hg while asleep (NS). The effects of smoking on diastolic AmBP are consistently positive but small and nonsignificant. However, in our study population, Type A behavior and education level were not associated with a significant increase in any measure of blood pressure after controlling for the other known risk factors.

We next turn to the issue of whether job strain may interact with the other significant predictors of AmBP at work. The global test for the set of job strain interactions was highly significant for work systolic AmBP (p=0.009) and not significant for diastolic AmBP. The most significant interaction term for systolic AmBP was job strain with alcohol (F=7.4, p=0.007). Workers not in high strain jobs exhibit no relation between alcohol consumption and systolic AmBP at work, whereas those in high strain jobs exhibit a very substantial relation. Viewed from the opposite perspective, there is a weak, presumably insignificant, 4-mm Hg effect of job strain on systolic AmBP for low alcohol consumption and a large effect (17 mm Hg) for regular consumption of alcohol. It is important to note that, although this interaction suggests that either job strain moderates the effect of alcohol on systolic AmBP, there is no evidence that the effect of job strain is mediated through alcohol consumption, e.g., that increased alcohol use is a response to job strain. In fact, the proportion of heavy alcohol consumes is the same for those in high-strain jobs (23%) as those in other jobs.

The global test of the remaining job strain interaction terms is again significant, and the most significant term is the interaction with age (F=3.7; p=0.026). With each successive age cohort, job strain is associated with a greater increase in systolic AmBP at work. The difference between those in high-strain jobs is 15 mm Hg greater than in the youngest age cohort. Just as those not in high-strain jobs showed no relation between alcohol and systolic AmBP at work, they also show virtually no relation between age and systolic AmBP at work.

To investigate the possible influence of our stratified recruitment scheme for case subjects and control subjects, we weighted the sample to approximate what would have been achieved if case subjects and control subjects had been sampled proportionately at each site. The ANCOVA results for this re-weighted analysis did not differ substantially from the results presented above, supporting the conclusion that our sampling scheme has not biased the relation between job strain and AmBP in our target population. (We reestimated the “unweighted” ANCOVA model, adding a dummy variable for whether the subject was a case subject in our case-control study, and found that this reduced the effect size of job strain on AmBP by 25%. The overall pattern of relations between job strain and AmBP was unchanged, and the systolic AmBP findings were still statistically significant. We decided to present the results for the entire group regardless of hypertension status in the model since we believe hypertension status to be an intervening variable between job strain and AmBP and therefore inappropriate to control when testing the overall effects of job strain and the other significant predictors (including the two-way interaction effects of job strain with alcohol and age) were the same for case subjects and control subjects was not significant (p>0.10) for both systolic and diastolic AmBP at work.

The reference for theses tables is: Schnall PL, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. Relation between job strain, alcohol, and ambulutory blood pressure. Hypertension;19(5):488-494, 1992


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Publications from the Cornell Worksite Blood Pressure Study


Friedman R, Schnall PL, Pieper CF, Gerin W, Landsbergis PA, Pickering TG. Psychological Variables in Hypertension: The “Hypertensive Personality” Revisited. (under review)

Schnall PL, Landsbergis PA, Schwartz JE, Warren K, Pickering TG. A Longitudinal Study of Job Strain and Ambulatory Blood Pressure: Results from a 3-Year Follow-up. Psychosomatic Medicine; 60:697-706, 1998.

Landsbergis PA, Schnall PL, Dietz D, Warren K, Pickering TG, Schwartz JE. Job and Health Behaviors: Results of a Prospective Study. American Journal of Health Promotion; 12(4)237-245, 1998.

Landsbergis PA, Schnall PL, Schwartz JE, Warren K, Pickering TG. The Association of Ambulatory Blood Pressure with Alternative Formulations of Job Strain. Scandinavian Journal of Work, Environment, and Health; 20:349-63, 1994.

Schnall PL, Landsbergis PA, Schwartz JE, Pickering TG. Job Strain and Hypertension. (Letter to the editor). American Journal of Public Health; 82(2):320-321,1994.

Landsbergis PA, Schnall PL, Dietz D, Friedman R, Pickering TG. The Patterning of Psychological Attributes and Distress by ‘Job Strain’ and Social Support in a Sample of Working Men. Journal of Behavioral Medicine, Vol. 15, No.4, 1992.

Schnall PL, Schwartz J, Landsbergis PA, Warren K, Pickering TG. The Relationship Between Job Strain, Alcohol, and Ambulatory Blood Pressure. Hypertension, May, 1992.

Schnall PL, Landsbergis PA, Pieper CF, Dietz D, Gerin W, Schlussel Y, Warren K, Pickering TG. The Impact of Anticipation of Job Loss on Psychological Distress and Worksite Blood Pressure. American Journal of Industrial Medicine 21:417-432, 1992.

Schnall et al. Letter to the Editor. The Relationship Between ‘Job Strain,’ Workplace Diastolic Blood Pressure, and Left Ventricular Mass Index: A Correction. JAMA, March 4,; Vol 267, No. 9, 1209, 1992.

Pickering T, Schnall PL, Schwartz JE, Pieper CF. Can Behavioral Factors Produce a Sustained Elevation of Blood Pressure? Some Observations and a Hypothesis. Journal of Hypertension, 9(suppl 8):S66-S68, 1991.

Gerber LM, Schnall PL, Pickering T. Body Fat and its Distribution in Relation to Casual and Ambulatory 1 Blood Pressure, Hypertension, Vol. 15, August, 1990.

Pickering TG, Devereux D, Gerin W, James G, Pieper CF, Schlussel Y, Schnall PL. The Role of Behavioral Factors in White Coat and Sustained Hypertension. Journal of Hypertension; 8:514 – 517, 1990.

Schnall PL, Pieper C, Schwartz JE, Karasek RA, et al. The Relationship Between ‘Job Strain,’ Workplace Diastolic Blood Pressure, and Left Ventricular Mass Index. JAMA April 11,; Vol 263, No. 14, 1929-1935, 1990.

Ganau A, Devereux RB, Pickering TG, Roman MJ, Schnall PL, et al. Relation of Left Ventricular Hemodynamic Load and Contractile Performance to Left Ventricular Mass. Circulation Vol 81, No.1, January 1990.

Schlussel YR, Schnall PL, Zimbler M, Warren K, Pickering TG. The Effect of Work Environments on Blood Pressure: Evidence From 7 New York Organizations, The Journal of Hypertension 8:679-685, 1990

Karasek R, Theorell T, Schwartz J, Schnall P, Pieper C, Michela J, 1988:Job Characteristics in Relation to the Prevalence of Myocardial Infarction in the U.S. Health Examination Survey (HES) and the Health and Nutrition Examination Survey (HANES), AJPH,78(7):1-9, July, 1988.


Book Chapters

Landsbergis PA, Schnall PL, Schwartz JE, Warren K, Pickering TG. Job strain, hypertension, and cardiovascular disease: empirical evidence, methodological issues, and recommendations for the future. In: Sauter SL, Murphy LR, eds. Organizational Risk Factors for Job Stress. Washington DC: American Psychological Association, 1995.


Abstracts and Proceedings

Schnall PL, Landsbergis PA, Schwartz JE, Pickering TG. The relationship between job strain, ambulatory blood pressure and hypertension. Proceedings of the Ninth International Symposium on Epidemiology in Public Health September 23-25, 1992. Cincinnati, OH: National Institute for Occupational Safety and Health, 1994:594-9.

Landsbergis PA, Schnall PL, Schwartz JE, Warren K, Pickering TG. The relationship between job strain, race, gender and blood pressure. Proceedings of The Fourth National Forum on Cardiovascular Health, Pulmonary Disorders and Blood Resources. June 26-27, 1992. Bethesda, MD: National Heart, Lung and Blood Institute; 120, 1993.

Schlussel YR, Schnall P, Wachtel N, et al. Physical and Demographic Characteristics Predict Blood Pressure Differences in a Screened Worksite. American Journal of Hypertension, Vol 3, #5II; 1390, May 1990.

Schnall P, Pickering T. The Relationship Between ‘Job Strain’ and Ambulatory Blood Pressure. American Journal of Hypertension, Vol 3, #5II;1327, May 1990.

Schnall PL, Pickering T, Deitz D. The Effect of ‘Job Strain’ on Ambulatory Blood Pressure, Occupational Health, February 1990.

Pieper C, Schnall P, Warren K, Pickering T. Comparison of Work Day and Off Day at Work and Home on Ambulatory Blood Pressure. American Journal of Hypertension, Vol 3, #5II; 1326, May 1990.

Pieper C, Schnall PL, Warren K, Pickering TG. Comparison of Ambulatory Blood Pressure and Heart Rate on a Work Day and a Non-Work Day: Evidence of a “Carry-over Effect”, American Journal of Hypertension, March 1990.

Schlussel YR, Schnall P, Zimbler M, Warren K Pickering TG. Worksite Characteristics Predict Blood Pressure Differences in Large Screened Working Populations,. American Society of Hypertension, May 1989.


Presentations

Pickering TG, Devereux RB, James GD, Gerin W, Landsbergis PA, Schnall PL, Schwartz JE. Environmental influences on blood pressure and the role of job strain. Paper presented at the 16th Annual Meeting of the International Society of Hypertension, Glasgow, Scotland, June, 1996.

Landsbergis PA, Schnall PL, Schwartz JE, Warren K, Pickering TG. Cumulative exposure to job strain and ambulatory blood pressure. Paper presented at the APA/NIOSH Conference on Occupational Stress, Washington, DC, September 14, 1995.

Schnall PL, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. The effect of job strain on the 3-year change in mean ambulatory blood pressure of male employees. Paper presented at the First International Symposium on Work Environment and Cardiovascular Diseases, Copenhagen, Denmark, May 31st, 1995.

Baker D, Schnall Pl, Landsbergis PA, Cahill J. Occupational stress, hypertension and cardiovascular disease: update on research findings and intervention strategies. Poster presented at the American Occupational Health Conference, Las Vegas, Nevada, May 3rd, 1995.

Schnall PL, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. The effect of job strain on the 3-year change in mean ambulatory blood pressure at work of male employees. Poster presented at the International Society of Hypertension, Melbourne, Australia: March 20-24, 1994.

Schnall PL, Landsbergis PA. Job strain and cardiovascular disease. Paper presented at the American Public Health Association, San Francisco, CA. October 26, 1993.

Schnall PL, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. The relationship between job strain and ambulatory blood pressure: the results of a prospective cohort study. Poster presented at the American Public Health Association, San Francisco, CA. October 25, 1993.

Schnall PL, Landsbergis PA, Schwartz JE, Warren K, Pickering TG. The relationship between job strain, ambulatory blood pressure and hypertension. Paper presented at the APA/NIOSH Conference on Occupational Stress, Washington, DC. November 28, 1992.

Schwartz JE, Schlussel YR, Schnall PL, Landsbergis PA. Symposium: Job Strain, organizational environment and cardiovascular disease. APA/NIOSH Conference on Occupational Stress, Washington DC. November 28, 1992.

Schnall PL, Landsbergis PA, Schwartz JE, Warren K, Pickering TG. The relationship between job strain, ambulatory blood pressure and hypertension. Paper presented at the Ninth International Symposium on Epidemiology in Occupational Health, Cincinnati, OH. September 24, 1992.

Schnall Pl, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. The relationship between job strain and change in ambulatory blood pressure. Poster presented at the International Congress of Behavioral Medicine, Hamburg, Germany. July 17, 1992.

Landsbergis PA, Schnall PL, Schwartz JE, Warren K, Pickering TG. The relationship between job strain, race, gender and blood pressure. Poster presented at the Fourth National Forum on Cardiovascular Health, Pulmonary Disorders and Blood Resources. Washington DC. June 26-27, 1992.

Schnall PL, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. Relationships between job strain, alcohol intake, and ambulatory blood pressure. Paper presented at the International Society of Hypertension, Madrid, Spain. June 15, 1992.

Schnall PL, Schwartz JE, Landsbergis PA, Warren K, Pickering TG. Relationships between job strain, alcohol intake, and ambulatory blood pressure. Poster presented at the American Society of Hypertension, New York, NY. May 8, 1992.

Schnall PL, Schwartz JE, Landsbergis PA, Pickering TG. The relationship between job strain and ambulatory blood pressure. Paper presented at the Society of Behavioral Medicine, New York, NY. March 27, 1992.

Schnall PL, Landsbergis PA, Pickering TG. The relationship between job strain, hypertension and coronary heart disease. Paper presented at the American Public Health Association, Atlanta, GA. November 12, 1991.

Landsbergis PA, Schnall PL, Pickering TG. A prospective study of the impact of anticipation of job loss on worksite blood pressure. Paper presented at the American Public Health Association, Atlanta, GA. November 12, 1991.

Schnall PL, Landsbergis PA, Pickering TG, The relationship between job characteristics and psychological attributes in a sample of healthy working men: Implications for stress interventions. Paper presented at “Work and Well-Being: An Agenda for the 90’s, American Psychological Association/National Institute for Occupational Safety and Health, Washington, DC. November 15, 1990

Landsbergis PA, Schnall PL. Session Co-Chairs: Progress in Occupational Stress Research, Annual Meeting of the American Pubic Health Association, Chicago, IL. October 2, 1990.

Karasek R, Schnall PL, Warren K, Pieper C. A diary for assessing psychosocial job characteristics in ambulatory blood pressure monitoring. American Public Health Association 117th Annual Meeting, Chicago, October 22-26, 1989.

Schlussel YR, Schnall PL, Zimbler M, Warren K, Pickering T. The effect of work environments on blood pressure: evidence from 7 New York City organizations. American Public Health Association 117th Annual Meeting, Chicago, October 22-26, 1989.

Schlussel Y, Schnall P, Pickering T, Zimbler M, 1988: Worksite characteristics predict blood pressure differences in large screened working populations, American Heart Association 61st Scientific Sessions.


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