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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