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Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com Prospective morbidity surveillance of Shell refinery and petrochemical employees. S P Tsai, C M Dowd, S R Cowles, et al. Br J Ind Med 1991 48: 155-163 doi: 10.1136/oem.48.3.155 Updated information and services can be found at: http://oem.bmj.com/content/48/3/155 Email alerting service These include: Receive free email alerts when new articles cite this article. Sign up in the box at the top right corner of the online article. Notes To order reprints of this article go to: http://oem.bmj.com/cgi/reprintform To subscribe to British Journal of Industrial Medicine go to: http://oem.bmj.com/subscriptions Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com British Journal of Industrial Medicine 1991;48:155-163 155 Prospective morbidity surveillance of Shell refinery and petrochemical employees Shan P Tsai, Catherine M Dowd, Sally R Cowles, Charles E Ross Abstract The Shell Health Surveillance System (HSS) was Results for a prospective morbidity study of established in 1979.3 One purpose of the HSS is to 14 170 refinery and chemical workers from provide both occupational and non-occupational 1981 through 1988 are presented. Mllness/ illness/absence information that can be used to assess absence data for this study were extracted overall effectiveness of medical programmes, to from the morbidity section of the Shell Health formulate preventive strategies, and to reduce cor- Surveillance System which includes records of porate health care costs. The present paper reports all illness/absences in excess of five days. Age findings from a prospective morbidity surveillance adjusted annual morbidity frequency rates evaluation of 14 170 Shell refinery and petro- and annual durations of absence are presented chemical employees from 1981 through 1988. The by age, sex, job, and work status. Generally, study examined the morbidity patterns for rates and durations ofabsence were highest for employees by sex, work status, and job group utilis- older age groups, women, and production ing data from the HSS. Also, selected disease risk workers. Increased risk was associated with the factors (for example, high blood pressure, hyper- presence of known disease risk factors. cholesterolaemia, and obesity) were examined for Overall, 48% of the employees had at least one those who had an illness/absence(s) and for those who illnessiabsence in excess offive days during the had not. eight year period. Twelve per cent of the employees had four or more absences, which accounted for 54% of the total number of Methods absences and 52% of the total work days lost. STUDY POPULATION Among men, the five most common conditions The study population consisted of all regular accounted for 72% of all illnesslabsences. In employees who worked at any of 14 Shell manufac- descending order they were injuries (25%), turing locations during the period 1 January 1981 respiratory illnesses (17%), musculoskeletal through 31 December 1988. These employees were disorders (14%), digestive illnesses (9%), and identified from the Shell payroll and personnel heart disease (7%). Similar patterns were computer system. The demographic information noted among women. These findings may be included, but was not limited to, name, date of birth, useful in setting priorities and directing efforts race, sex, date of hire, date of retirement or last such as health education programmes and separation, date of death, job title, and pay status. other strategies for the prevention of disease. Each employee was classified as either production or staffand placed into one of four job groups (operator, Morbidity data are routinely collected as a part of maintenance, office, or others) that were used as industrial health surveillance programmes in the broad classifications of occupations. United States to detect potential adverse health The term production operator refers to employees effects due to environment hazards or personal risk with such job titles as operators, process technicians, factors.' General morbidity patterns among workers, compounders, loaders/unloaders, and pumper however, have rarely been reported.2 This is partly gaugers. Staff operators, on the other hand, are the because of the frequent lack of reliable diagnoses. foremen and supervisors of the operations. Mainten- Many programmes also suffer from inconsistent ance includes those who work as craftsmen. Ex- administration and incomplete reporting. amples are boilermakers, pipefitters, machinists, and electricians who are considered production employees, and the related foremen and supervisors Shell Oil Company Corporate Medical Department, PO Box 2463, Houston, Texas 77252-2463, USA S P Tsai, C M Dowd, S R Cowles, C E Ross who are considered staff. Everyone else was included in either the production "others" category or the staff office category. The "others" category was Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com 1516 6'sai, Dowd, Cowles, Ross typically made up of testers, laboratory assistants, truck drivers, and equipment operators. Included in the office category were clerks, engineers, laboratory technicians, and superintendents and managers. The job categories represent varying levels of occupational exposure. An employee's inclusion into one of the job groups was based on his or her last job title. MORBIDITY DATA Morbidity data for this study were extracted from the morbidity section of the HSS which includes all illness/absence events in excess of five work days. Since records of absences originate from personnel and payroll systems, the absence reporting is virtually complete. Ninety four per cent of the morbidity reports had statements from physicians identifying the reason for the absence. The causes of morbidity were coded according to the International Classification of Diseases ninth revision clinical modification (ICD 9-CM).4 Only the primary cause was used in the analysis. Pregnancy and childbirth related absences were excluded. SELECTED DISEASE RISK FACTORS The data for risk factors were derived from the HSS, which contains all employee preplacement and periodic examinations done since 1 January 1978. Data from the most current examination were used; three quarters of these were done in the period 1984-8. The smoking history was used to determine whether an employee was a current cigarette smoker. Raised cholesterol was defined as a value equal to or greater than 200 mg/dl. Raised blood pressures were those diastolic blood pressure readings equal to or greater than 90 mm Hg or systolic blood pressure readings equal to or greater than 140 mm Hg. Obesity was defined as body mass index (BMI = weight (kg)/height2 (m))greater than or equal to 27-2 for men and 26 9 for women. This value represents 20% more than the ideal body weight based on the National Institutes of Health Consensus Development Panel recommendations.5 ANALYTICAL METHODS Person-years at risk were accumulated for each Table 2 Number of workers according to work status, sex, and number of absences No of absences Women Production Staff No* (%) No* (%) Men Production Staff No (%) Nlo (%) 0 1 2 3 4 5 6 7 8 9 10 >10 Total 148 (30-7) 71 (14 7) 61 (12-7) 46 (9-5) 37 (7-7) 25 (5 2) 26 (5 4) 11 (2-3) 10 (2-1) 17(3 5) 8 (1-7) 22 (4 5) 482 (100-0) 812 (50-9) 410 (25-7) 183 (11-5) 105 (6-6) 40 (2 5) 23 (1-4) 9 (0 5) 9 (0 5) 2 (0-1) 2(0-1) 1 (0-1) 1 (0-1) 1597 (100-0) 2534 (37-7) 1400 (20 8) 896 (13-3) 614 (9 2) 380 (5 7) 291 (43) 188 (2 8) 135 (2 0) 97 (1-4) 48(07) 51 (0 8) 86 (1-3) 3502 (65-2) 1066 (19-9) 442 (8 2) 176 (3-3) 86 (1-6) 41 (08) 26 (0 5) 18 (0 4) 7 (0-1) 2(00) 0 (0 0) 3 (0-0) 6720 (100-0) 5369 (100-0) Excludes absences due to pregnancy. *Adjusted for duration of follow up. worker beginning 1 January 1981 or the date of employment (whichever was later) and ending at the closing date of study (31 December 1988), the date of retirement, the date of death, or the date of termination (whichever was earlier). The number of years contributed by each worker was classified by age (<30, 30-39, 40-49, 50-59, and ) 60), by work status (production and staff), and by sex. Directly age adjusted frequency rates for morbidity by sex and work status and by diagnostic category for the three job groups and the combined group were computed with the age specific personyear distribution of the combined group as the standard set of weights. The same standardisation method was used to calculate age adjusted prevalence rates for selected disease risk factors. Age adjusted rates were compared by a two sided test of significance.6 Results Included in this study were 484 female production personnel, 1597 female staff, 6270 male production personnel, and 5369 male staff (table 1). The age of entry into the cohort was 8-11 years younger for women than for men. The average number of years of follow up was 5-8 for both male production workers Table I Cohort statistics of workers by sex and work status 1981-8 No studied No of person-years observed Average years of age at entry Average years of follow up (1981-8) Average total duration of employment (y) Women Production 484 2313 29-5 4-8 7-0 Staff 1597 7213 28-8 4-5 8-9 Men Production 6720 39141 36-9 5-8 14-7 Staff 5369 31401 40 2 5-8 20-1 Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com Prospective morbidity surveillance of Shell refinery and petrochemical employees Table 3 Morbidity frequency rates* according to work status, sex, and age Age (y) Women Production Staff Men Production < 30 30-39 40-49 50-59 >60 Totalt 21 2 (29) 52-5 (609) 62-0 (509) 62 1 (103) 79-3 (23) 58 61 (1273) 5 6 (71) 11 0 (321) 16 9 (303) 16 5 (131) 16 2 (68) 14 1 (894) 20-8 (319) 31 4 (5003) 32 9 (3917) 32-0 (1844) 45-5 (1823) 33 111 (12906) *Per 100 person-years. Numbers in parentheses are morbidity episodes. Excludes absences due to pregnancy. tAge adjusted to the total population using the direct standardisation method. $Significantly different from production men at p < 0 05. Significantly different from staff women at p < 0 05. IlSignificantly different from staff men at p < 0-05. IJ Significantly different from staff employees at p < 0 05. Staff 2 2 (24) 8-4 (709) 8-8 (844) 12 6 (943) 18 9 (910) 10-2 (3430) 157 Total Production 20-8 (348) 32 9 (5612) 34-8 (4426) 32-8 (1947) 45-7 (1846) 34311 (14179) Staff 4-0 (95) 9-1 (1030) 10-1 (1147) 13-0 (1074) 18 7 (978) 10-9 (4324) and staff and 4 8 and 4 5 for female production workers and staff. The total duration of employment for women was less than half that for men. Of the 14 170 employees included in the study, 6806 (48%) had had at least one illness/absence in excess of five days during the eight year period from 1981 through 1988. Overall, 12% of the employees had had four or more absences, which accounted for 54% of the total number of absences and 52% of the total work days lost. When adjusted for duration of folldw up, the percentage of employees who had never had an illness/absence was 31 % for female production personnel, 38% for male production personnel, 51 % for female staff, and 65% for male staff (table 2). Among staff employees, only 5% of women and 3% of men had had four or more absences but these accounted for almost 30% of each of their total number of absences as well as their total number of days of absence. By contrast, for production employees, 32% of women and 19% of men had had four or more absences. These employees were responsible for 75% of the total number of absences and days among women and 60% among men. Table 4 Average duration of absence in days* according to work status, sex, and age Women Men Total Age (y) Production Staff Production Staff Production Staff <30 30-39 40-49 50-59 >60 Totalt 39 144 216 25 5 266 194 1 1 4.4 27 72 54 88 5 2 10.6 48 194 411 96 04 4.4 1.9 77 2.1 96 4 1 11 0 78 195 30 10111 08 2-1 27 4-2 76 32 *Per person-year. Excludes absences due to pregnancy. tAge-adjusted to the total population using the standardisation method. +Significantly different from staff men at p < 0 05. Significantly different from staff men at p < 0-05. ISignificantly different from staff employees at p < 0-05. direct The frequency rates for morbidity generally increased with age, ranging from 20 8 per 100 for those less than 30 years old to 45 7 per 100 for those 60 and older for production workers, and 4 0 per 100 to 18 7 per 100 for corresponding staff workers (table 3). The rate was four times higher for female production workers (58-6 per 100) than for female staff (14-1 per 100) and three times higher for male production workers (33-1 per 100) than for male staff (10 2 per 100). These differences between the total rates for production and staff employees were statistically significant. Women had significantly higher rates than men (p < 0 05). The annual average duration of absence also increased with age (table 4). For production employees, it ranged from 4-4 days for those less than 30 years old to 19 5 days for those 60 and older, whereas for staff counterparts, it ranged from 0-8 to 7-6 days. Statistically significant differences existed between the rates for female and male staff, the rates for male production workers and staff and the rates for all production and staff employees. Table 5 presents the number of episodes and the average duration of absence per episode by diagnosis and sex. Among male employees, the five most common disease categories accounted for 72% of all illness/ absences. In decreasing order these were injuries (25%), respiratory illnesses (17%), musculoskeletal disorders (14%), digestive illnesses (9%), and heart disease (7%). For female employees, the five leading disease categories were respiratory illnesses (20%), injuries (16%), musculoskeletal disorders (12%), genitourinary illnesses (10%), and digestive illnesses (8%). These conditions accounted for 66% of all female illness/absences. Across all causes of morbidity, the average duration of absence per episode was 30 days for women and 29 days for men. Among women, the average duration ranged between 13 days for respiratory illnesses and 47 days for musculoskeletal disorders. The next longest average duration of absence was for mental disorders (42 days), Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com 158 Tsai, Dowd, Cowles, Ross Table 5 Number of morbidity episodes and average duration of absence per episode by diagnosis and sex Cause of morbidity (ICD-CM 9th revision codes) Infective and parasitic diseases (000-139) All neoplasms (140-239) Endocrine and metabolic diseases (240-279) Mental disorders (290-319) Nervous system (320-389) Circulatory system (390-459) Respiratory system (460-519) Digestive system (520-579) Genitourinary system (580-629) Skin and subcutaneous tissue (680-709) Musculoskeletal (710-739) Symptoms and ill-defined conditions (780-799) Injury and poisoning (800-999) Allothercauses All causes (000-999) Excludes absences due to pregnancy. Women No (%) 62 (2 8) 79 (3-6) 34 (1-6) 92 (4 2) 78 (3-6) 58 (2 7) 433 (20 0) 177 (8 2) 215 (9 9) 37 (1-7) 270 (12-5) 67 (3 1) 347 (16.0) 218(101) 2167 (100-0) Average duration 18 3 40 8 32-4 41-7 28-2 39 9 12-9 20-8 32-5 20-0 47-4 17-3 38-9 31-1 30-0 Men No (%) 502 (3-1) 366 (2-2) 208 (1-3) 491 (3-0) 700 (4-3) 1113 (6-8) 2733 (16 7) 1485 (91) 577 (3 5) 408 (2-5) 2303 (14-1) 454 (2 8) 4052 (24 8) 944(58) 16336 (100-0) Average duration 15 0 60-2 33-8 35-8 31 8 53-0 10-9 23-9 19-7 18-3 41 2 19-4 29-9 27-0 28-8 followed by neoplasms (41 days), heart disease (40 days), and injuries (39 days). Among men, the average duration ranged between 11 days for res- piratory disorders and 60 days for neoplasms. After neoplasms were heart disease (53 days), musculoskeletal disorders (41 days), mental disorders (36 days), and endocrine and metabolic disorders includ- ing diabetes (34 days). Table 6 shows the age adjusted prevalence rates for disease risk factors by job group. Women generally had higher rates of smoking and lower rates of the other risk factors than men. Overall, production workers of both sexes had higher rates of smoking, hypertension, and obesity and lower rates of hyper- cholesterolaemia compared with staff workers. For male production personnel, rates for disease risk factors were similar among the three job groups of workers. For male staff, operators and maintenance workers generally had higher rates than the combined group while office workers had lower rates. Among the three job groups the smoking rates (31-4 per 100 for operators, 28 7 per 100 for maintenance workers, and 18 9 per 100 for office workers) and the obesity rates (47 4 per 100 for operators, 45 0 per 100 for maintenance workers, and 34-5 per 100 for office workers) were significantly different from those of the combined population (23-6 per 100 for smoking and 38-8 per 100 for obesity). No clear patterns of rates by job category existed among women. The annual average duration of absence per person-year (table 7) for the combined population was over four times higher for female production person- nel (19 4 days) than for female staff (4 1 days) and over three times higher for male production personnel (9-6 days) than for male staff (3-0 days). Among the three job categories for production employees, other workers had the longest average duration (21 2 days for women, 11 6 days for men), followed by maintenance workers (17-7 days for women, 10 9 days for men) and then operators (16 2 days for women, 8-3 days for men). Operatorshad the longest duration among female staff (9 1 days) and male staff (4 1 days), followed by maintenance workers (5-8 and 3-4 days) and office workers (4 1 and 2-3 days). Table 6 Age adjusted prevalence ratest for selected disease risk factors according to work status,job, and sex Risk factors Production Op M Staff Others Combined Op M Office Combined Women: Smoking High blood pressure Hypercholesterolaemia Obesity Men: Smoking High blood pressure Hypercholesterolaemia Obesity 35 3 36-1 47-6 43-1 8-0 1.9* 30-5* 14-2 31-7 37 9 49 7 38 9 46.9* 12-5* 34 9 34-4 35-8 32-0 39-8 34-2 25-6 22.2* 26-5 24-6 55 9 58-3 54-1 56-7 44 0 43*3 49.9 43-6 42.9* 26-2 27-6 28-1 6-4 - 13-3 13 1 19.8* - 47-1 46-4 34.7 - 25-4 25-5 31-4* 28.7* 18-9* 23-6 23 2 19 9 20 8 21-5 58-6 59-1 56-6 57-5 47.4* 45.0* 34-5* 38-8 *Significantly different from combined at p < 0-05. tPer 100 workers. Adjusted to the total population using the direct standardisation method. Op = operator, M = maintenance. Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com Prospective morbidity surveillance of Shell refinery and petrochemical employees 159 Table 7 Age adjusted annual average duration of absence in dayst by work status, sex, andjob Jobs Women Men Production: Operator Maintenance Others Combined Staff: Operator Maintenance Office Combined 16 2 17-7 21-2 19 4 9-1 5-8 41 4-1 *Significantly different from combined at p < 0-05. tPer person-year. Excludes absences due to pregnancy. 8.3* 10.9* 116 9-6 4.1* 3.4* 2.3* 30 Tables 8 and 9 present age adjusted morbidity frequency rates for women (table 8) and men (table 9) by cause of morbidity. For both sexes production workers had higher rates than staff workers across all diagnostic categories. Among production employees, operators had the lowest rates followed by maintenance personnel, with other workers having the highest morbidity frequency rates. Among both male and female production personnel, the morbidity rate of musculoskeletal disorders for operators was significantly lower than that for the combined job category (p < 0 05). Also, for male production workers, operators had significantly lower rates of injuries and disorders of the respiratory, nervous, and digestive systems (p < 0-05). The three diagnostic categories with the highest morbidity frequency rates for all female production workers were diseases of the respiratory system (125 per 1000 person-years, n = 294), injury and poisoning (115 per 1000,. n = 259), and musculoskeletal disorders (79 per 1000, n = 153). The three leading causes of morbidity were the same for male produc- tion workers, but the order was different. Injury and poisoning (87 per 1000, n = 3471) led the list, then diseases of the respiratory system (60 per 1000, n = 2365), and musculoskeletal disorders (48 per 1000,n = 1866). Among staff workers, operators had the highest frequency rates for morbidity for both men and women. Female staff office workers had the next highest rate, whereas for male staff, maintenance workers had the next highest rate. As was the case for production workers, female staff as a whole had more episodes of disorders of the respiratory system (22 per 1000, n = 138) than any other cause; male staff had more injury and poisoning (19 per 1000, n = 581). Overall, only about 5% of all illness/absence events were work related. Table 10 presents age adjusted morbidity frequency rates for women by job group for occupational and non-occupational disorders. For both occupational and non-occupational conditions all rates were much higher for production workers than for staff workers. Among female production personnel, "other" workers had the highest rates for all non-occupational disorders. Maintenance workers had the highest rates for occupational injuries and musculoskeletal disorders. Table 11 shows similar analyses for male employees. As was the case for women, production workers had much higher rates than staff workers for both occupational and non-occupational disorders. Among male production personnel, operators had lower rates than the combined group whereas maintenance workers had higher rates than combined for both occupational and non-occupational disorders. Among male staff, operators had the highest rate for non-occupational illnesses whereas maintenance workers had the highest rates for both non- Table 8 Age adjusted morbidity frequency rates for women by work status,job, and diagnosis Cause of morbidity (ICD-CM 9th revision codes) Production Op M Staff Others Combined Op Infective and parasitic diseases (000-139) Allneoplasms(140-239) Endocrine and metabolic diseases (240-279) Mental disorders (290-319) Nervous system (320-389) Circulatory system (390-459) Respiratory system (460-519) Digestive system (520-579) Genitourinary system (580-629) Skin and subcutaneous tissue (680-709) Musculoskeletal (710-739) Symptoms and ill-defined conditions (780-799) Injury and poisoning (800-999) All other causes All causes(000-999) 14 7 95 3-3 15 3 19 2 98 120 2 42-8 35-9 7-2 51.4* 28-4 92 7 13 7 485-1* 67 210 20-0 11 8 22 6 29-1 121 2 18 3 34-6 9-2 104 7 22-8 122 2 25-9 570 1 26 1 623 95 18 1 19.0 31 6 130 9 55-2 85-9 94 102 5 18 6 124-5 19 2 662-1 24-8 115 6-2 15 0 23-0 18 3 129-4 45-2 50 3 10 9 78 8 22-7 114 9 29-4 585-4 2-9 29 2-9 9-4 00 7-6 31-1 10 5 27 8 9-4 32-5 00 18 8 20 2 176 0 *Significantly different from combined at p < 0-05. tPer 1000 person-years. Excludes absences due to pregnancy. Op = operator, M = maintenance. M 00 00 00 0.0 00 0.0 51-1 0.0 00 0o0 0-0 67 00 0.0 64-5 Office 38 86 2-9 76 41 5-5 21 5 10 2 15-1 27 18-8 2-8 13 4 21-0 138-1 Combined 37 85 2-9 7-6 40 5-6 22-2 10 3 15-6 3-1 19 3 27 13 6 21 2 140-5 Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com 160 Tsai, Dowd, Cowles, Ross Table 9 Age adjusted morbidity frequency rates for ment by work status, job, and diagnosis Cause of morbidity (ICD-CM 9th revision codes) Production Op M Others Combined Infective and parasitic diseases (000-139) All neoplasms (140-239) Endocrine and metabolic diseases (240-279) Mental disorders (290-319) Nervous system (320-389) Circulatorysystem(390-459) Respiratory system (460-519) Digestive system (520-579) Genitourinary system (580-629) Skin and subcutaneous tissue (680-709) Musculoskeletal (710-739) Symptoms and ill-defined conditions (780-799) Injury and poisoning (800-999) All other causes All causes(000-999) 9.1 54 4-6 10 1 10.4* 18-3 44-6* 22.7* 8-5* 6.7* 38-7* 7.0* 72.1* 13-8 271.9* *Significantly different from combined at p < 0 05. tPer 1000 person-years. Op = operator, M = maintenance. 11-8 78 41 85 17.6* 21 3 77.8* 32.3* 13.2* 11.5* 59.6* 12.3* 102.6* 12 4 392.9* 99 66 39 20.5* 18 8 23 5 80.6* 37-4* 14 3 11-2 53*7 12 6 118.3* 7.0* 418.2* 10-5 64 43 99 13 9 19 8 60-1 27-8 10 9 90 48-4 97 86 9 12 7 330 3 Staff Op M Office 4.8* 3-4 1-0 3-4 64 13-7* 17-0* 11-5 5-3 3-0 17.7* 3.3 28.2* 21-2* 140-0* 1-5 19 1-8 2-7 63 13-3 14-1 13-1 7-6* 19 20.1* 4-4 33-6* 14-0 136 1* 23 34 13 24 4-0 8.0* 8-3* 11-4 3.3* 12 9-8* 1.3* 13.9* 9.0* 79.7* Combined 2-8 32 13 27 47 10-3 11 2 11 8 4.4 1-8 13-2 2-2 19.1 13-0 101-7 occupational and occupational injuries and musculoskeletal disorders. Within the subgroup of persons having four or more absences there were 139 female production workers, 50 female staff, 1276 male production workers, and 183 male staff. Among women the average age at entry (33 3 years for production workers and 37-2 years for staff employees), years of follow up (7 2 and 7 5), and total duration of employment (10 5 and 15-0 years) were higher than those for all employees. Among men, those with four or more absences were also older and employed longer, but the differences were small. Table 12 compares the age adjusted prevalence rates for the selected disease risk factors between absentees and non-absentees. In general, absentees with one to three absences had higher rates than nonabsentees, and absentees with four or more absences had higher rates than those with three or less. Statistically significant differences existed between absentees and non-absentees for smoking, hyper- cholesterolaemia, and obesity rates. The hypertension rates increased with the number of absences for women but not for men. The distribution of morbidity episodes by diagnosis for employees with four or more absences was similar to the distribution for all absentees presented in table 5. Overall, the average duration of absence per episode was also about the same. Table 13 shows the age adjusted frequency rates for employees with four or more absences. Production employees had much higher rates than staff employees. They accounted for 75% (439 5 per 1000 v 585 4 per 1000) of overall frequency rates for men and 61% (200-7 per 1000 v 330 3 per 1000 for women). The difference between the combined job groups was tenfold for women and sevenfold for men. Subjects who had had at least one illness/absence Table 10 Age adjustedfrequency ratest for women by occupational status, work status, andjob Occupational Motor Non-motor Musculo- vehicle vehicle skeletal Job Illness injury injury disorder Production: Operator Maintenance Others Combined Staff: Operator Maintenance Others Combined 6-5 (9) 4-7 (2) 3 7 (2) 5 9 (13) 0 0 (0) 0.0 (0) 0 0 (0) 0-0 (0) 0 0 (0) 0 0 (0) 1-0 (5) 1 0 (5) 0 0 (0) 0 0 (0) 0 0 (0) 0 0 (0) 18 8 (31) 29-2 (9) 18 5 (5) 231 (45) 7-6 (2) 0 0 (0) 0-5 (4) 0 8 (6) 4-1 (8) 11 2 (5) 6 5 (6) 5-8 (17) 0 0 (0) 0 0 (0) 1 1 (4) 1 0 (4) *Significantly different from combined at p < 0 05. tPer 1000 person-years. Numbers in parentheses are morbidity episodes. Non-occupational Illness Motor vehicle injury 336.4* (542) 6 2 (11) 338-4 (132) 143 (6) 431 4 (176) 14 9 (5) 387 3 (850) 8-6 (22) 127 7 (37) 95 4 (5) 104 6 (641) 106 3 (683) 0 0 (0) 0.0 (0) 2 0 (14) 1 9 (14) Non-motor vehicle injury 67-8 (119) 78-8 (34) 91-1 (39) 83-2 (192) 11-2 (2) 0 0 (0) 10-9 (66) 10-9 (68) Musculoskeletal disorder 47.3* (74) 93 5 (29) 96 0 (33) 73-0 (136) 32 5 (9) 0 0 (0) 17 7 (102) 18 3 (111) Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com Prospective morbidity surveillance of Shell refinery and petrochemical employees Table 11 Age adjustedfrequency ratest for men by occupational status, work status, andjob Occupational Motor Non-motor Musculo- vehicle vehicle skeletal Job Illness injury injury disorder Production: Operator Maintenance Others Combined Staff: Operator Maintenance Office Combined 3-5 (72) 0-1 (2) 5-2 (83) 0-3 (4) 1 9* (8) 0 5 (1) 4-2 (163) 0-2 (7) 0-4 (5) 2-4 (8) 03(7) 0-6 (20) 0-0 (0) 0 0 (0) 0.0(1) 0.0 (1) 70* (151) 14.9* (157) 10-3 (29) 10-2 (407) 3-8* (79) 9.8* (157) 5-3 (18) 6-5 (254) 1-5 (13) 3-9 (13) 0-8(15) 1-4 (41) 1-0 (9) 1-8 (5) 0-7(13) 0-9 (27) *Significantly different from combined at p < 0 05. tPer 1000 person-years. Numbers in parentheses are morbidity episodes. Non-occupational Illness Motor vehicle injury 157-9* (3191) 7-7 (174) 225-8* (3572) 7-0 (114) 244-7* (645) 11-2 (27) 1911 (7408) 7-7 (315) 93 7* (822) 3-9* (29) 80-1* (388) 2-3 (9) 55-6*(1180) 1 1*(21) 68-8 (2390) 2-0 (59) 161 Non-motor vehicle injury Musculoskeletal disorder 57-2* (1222) 34-8* (694) 81.3* (1305) 49-8* (788) 96-4* (215) 48-4 (130) 68-8 (2742) 419 (1612) 22-8* (179) 27-5 (79) 11-9*(222) 15-7 (480) 16-7* (147) 18-3* (77) 9-1*(186) 12-3 (410) due to injuries, respiratory illnesses, or musculoskeletal disorders were most likely to have had another absence of the same diagnostic type. About one third of all absentees had had more than one absence due to these three causes. Among those who had had four or more absences, about half had had at least one other absence due to these causes. Overall, one sixth of all absences were longer than two months (42 working days). Of these, 324 or 11% directly preceded the absentee's retirement and con- tributed 19% of the days of absence. For women, 70% of all absences longer than two months were due to the five most common disorders-namely, musculoskeletal disorders, injuries, genitourinary disorders, neoplasms, and mental disorders. For men the five leading disorders (injuries, musculoskeletal, circulatory, and digestive disorders, and neoplasms) accounted for 78% of total absences longer than two months. Across all causes of morbidity, the average duration of absence for this long term absentee group was 93 days for women and 101 days for men. Table 13 Age adjustedfrequency ratest employees with four or more absences by sex, work status, andjob Jobs Women Men Production: Operator Maintenance Others Combined Staff: Operator Maintenance Office Combined 352.9* (597) 422-5 (160) 583.7* (222) 439.5 (979) 68-5 (21) 0-0 (0) 414 (241) 42-5 (262) 143.1* (2983) 261.6* (4174) 291-4* (715) 200 7 (7872) 48.1* (411) 38.7* (164) 18.0* (375) 28-1 (950) *Significantly different from combined at p < 0 05. tPer 1000 person-years. Numbers in parentheses are morbidity episodes. Excludes absences due to pregnancy. Discussion In this study we illustrate the utility of routinely collected health surveillance data for epidemiological monitoring. From 1 January 1981 through 31 Table 12 Age adjusted prevalence ratest for selected disease risk factors: absentees v non-absentees by sex and work status Women Men Risk factors Absentees Absentees Non- ( 4 absences) (1-3 absences) absentees Absentees ( 4 absences) Production: Smoking 60.9* 41.0* 25-8 40.0* High blood pressure 24-0* 8-0 5-3 23-4 Hypercholesterolaemia 49.8* 23-8 26-6 57-4 Obesity 34 5* 35.3* 18-2 47-1* Staff: Smoking 34-6 34.0* 24-6 26-9 High blood pressure 16 8 13 7 11-6 20 4 Hypercholesterolaemia 59-5* Obesity 54.5* 45-7 30.7* 44-2 69-3* 19 0 56.9* *Significantly different from non-absentees at p < 0 05. tPer 100 workers. Adjusted to the total population using the direct standardisation method. Absentees (1-3 absences) 33-6 25-1 56-8 44.4* 27-6* 22-6 62.1* 45.0* Nonabsentees 31 7 24-2 56-2 39-9 20-9 21-2 56-0 36-0 Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com 162 Tsai, Dowd, Cowles, Ross December 1988, a total of 18 503 reported episodes and men in this study are not clear. The smoking of absence with more than half a million (535 487) rates among female production workers may be work days lost were attributed to illness/absence partly responsible for their higher illness/absence events in excess of five days. This was equivalent to and severity rates. Future investigations will address the absence from work of about 270 workers (3% of this issue more fully. the average workforce) each year during this period. The results show consistent relations between Substantial numbers of long illness/injury episodes morbidity rates of the three job groups. For both occurred; in fact one third of all absences were longer female and male production employees, the average than four work weeks. duration of absence and the morbidity frequency These analyses show the disproportionately large rates were highest for "other" workers, followed by impact on morbidity rates and duration of absence maintenance workers and operators. For staff from the small percentage of employees with four or employees, on the other hand, operators had the more illness/absences over the eight year period. As highest rates, followed by maintenance workers and had been expected illness/absence rates increased then office workers. These patterns also held true with increasing age. Similar observations have been when analyses were done only on non-occupational noted by other researchers.78 The rates for older illnesses and injuries. These results are consistent workers (60 years and older) were more than double with the sickness/absence experience of the French those of younger ones (less than 30 years old). Rates National Electric and Gas Company workers.8 for women were greater than those for men in similar Illness/absence in a working population is a com- occupational categories for all ages except for older plex phenomenon incorporating many factors. It is men holding staff positions. Differences in illness/ unlikely that the relatively poor health experience of absence rates were most pronounced between "other" workers among production employees is due production and staff workers. Male and female to occupational exposure factors as they generally production personnel had much higher rates for have minimal contact with chemical agents. More diagnostic categories across all job groups than their likely this experience is in part a product of lifestyle staff counterparts. Also, both male and female as evidenced by the fact that in this production production workers had higher rates regardless of population "other" workers were more likely to whether the illness/absence episode was work related smoke than operators and maintenance workers. The or not work related. benefits of a healthy lifestyle seem to be represented Personal characteristics related to morbidity by the relative good health of the group of staff office frequency in a working population include age, sex, workers. lifestyle, education level, pay status, alcohol use, Age adjusted prevalence rates for the four selected smoking habits, and occupational factors. These disease risk factors (smoking, hypertension, hyper- variables influence both occupational and non- cholesterolaemia, and obesity) by levels of absen- occupational morbidity. It is important to note that teeism (non-absentees, absentees with one to three in this study production workers have significantly absences, and absentees with four or more absences) higher age adjusted prevalence rates for two lifestyle were examined in this study, to quantify their impact indicators, smoking and obesity, both of which have on illness/absence. It is important to note that among been associated with increased morbidity. absentees, the proportions of both male and female Furthermore, the differences in morbidity rates may employees who had the disease risk factors were relate to job duties. For example, for most illnesses significantly higher than those of non-absentees. and injuries, the duration of absence will be longer These results suggest that it may be possible to for a job that requires greater physical activity than reduce overall illness/absence through implementa- for one that is primarily sedentary. tion of successful health promotion programmes. Comparisons between the experiences of men and Further subgroup analyses to assess effects of age, women among production workers seen in this study retirement patterns, and risk factor distributions by are noteworthy. Female production workers had cause of morbidity are planned to identify twice the number of days of illness/absence as did appropriate intervention targets and more specific their male counterparts. They also had an approxi- high risk groups. mately 80% higher frequency rate than male work- Health surveillance is one of the important com- ers. The difference came mainly from workers 30 ponents of occupational epidemiology. Illness/ years of age or older. Disorders of the respiratory and absence statistics are invaluable for answering ques- genitourinary systems, as well as musculoskeletal tions on the health of employees. Medical and disorders and injuries, accounted for two thirds of administrative recommendations carry much more the difference. It is interesting to note that for weight when they are backed by facts. This study has injuries, however, male staff had a higher rate than identified worker groups at increased risk of illness/ 'female staff. absence. These findings are useful in setting The reasons for the disparities between women priorities for medical programmes and directing Downloaded from oem.bmj.com on August 11, 2010 - Published by group.bmj.com Prospective morbidity surveillance of Shell refinery and petrochemical employees 163 efforts such as illness/absence control measures, health education programmes, and other preventive strategies. Also, examination of health surveillance data can quickly identify areas of concern and can be a useful prelude to the design of more specific casecontrol or cohort studies. We thank Dr Philip Cole for his helpful comments. 1 Medical Information Systems Roundtable. J Occup Med 1982;24(suppl):781-866. 2 Tabershaw/Cooper Associates. A morbidity study of petroleum refinery workers. Washington, DC: the American Petroleum Institute, 1975. (Progect OH-4 final report.) 3 Joyner RE, Pack PH. The Shell Oil Company's computerised health surveillance system. J Occup Med 1982;24:812-4. 4 International Classifications of Diseases, 9th revision, Clinical Modification. Ann Arbor, Michigan: Commission on Professional and Hospital Activities, 1978. 5 National Institutes of Health consensus development panel on the health implications of obesity, Health implications of obesity: National Institutes of Health consensus development conference statement. Ann Intern Med 1985;103:1073-7. 6 Chiang CL. The life table and its application. Malabar, Florida: Robert E Krieger Publishing Co, 1984. 7 Taylor PJ. Occupational and regional associations of death, disablement, and sickness absence among Post Office staff 1972-75. Br J Ind Med 1976;33:230-5. 8 Chevalier A, Luce D, Blanc C, Goldberg M. Sickness absence at the French National Electric and Gas Company. Br J Ind Med 1987;44: 101-10. 9 US Department of Health, Education and Welfare. Public Health Service: Smoking and health. A report of the Surgeon General. Washington, DC: US Government Printing Office, 1979. (PHS publ No 79-50066.) 10 Doll R. Smoking and disease, the prospect for control. Royal Society of Health Journal 1977;94:167-76. 11 Kral JG. Morbid obesity and related health risks. Ann Intern Med 1985;103:1043-7. 12 Fielding JE. Health promotion and disease prevention at the worksite. Annual Review of Public Health 1984;5:237-65. Accepted 3 September 1990 Vancouver style All manuscripts submitted to the Br J Ind Med should conform to the uniform requirements for manuscripts submitted to biomedical journals (known as the Vancouver style) The Br J Ind Med, together with many other international biomedical journals, has agreed to accept articles prepared in accordance with the Vancouver style. The style (described in full in Br Med J, 24 February 1979, p 532) is intended to standardise requirements for authors. References should be numbered consecutively in the order in which they are first mentioned in the text by Arabic numerals above the line on each occasion the reference is cited (Manson' confirmed other reports2- 5...). In future references to papers submitted to the Br J Ind Med should include: the names of all authors if there are six or less or, if there are more, the first three followed by et al; the title of journal articles or book chapters; the titles of journals abbreviated according to the style of Index Medicus; and the first and final page numbers of the article or chapter. Examples of common forms of references are: I International Steering Committee of Medical Editors. Uniform requirements for manuscripts submitted to biomedical journals. Br Med J 1979;1:532-5. 2 Soter NA, Wasserman SI, Austen KF. Cold urticaria: release into the circulation of histamine and eosino-phil chemo- tactic factor of anaphylaxis during cold challenge. N EngI J Med 1976;294:687-90. 3 Weinstein L, Swartz MN. Pathogenic properties of invading micro-organisms. In: Sodeman WA Jr, Sodeman WA, eds. Pathologic physiology: mechanisms of disease. Philadelphia: W B Saunders, 1974:457-72.