Poisson regression analysis of ungrouped data

Loomis, Dana; Richardson, David B.; Elliott, Leslie

doi:10.1136/oem.2004.017459

Cited by 69 publications

(52 citation statements)

References 24 publications

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“…Author manuscript; available in PMC 2015 October 28. event occurred; and (c) the shift during which each event was first reported. Poisson regression analyses for ungrouped data (Loomis et al, 2005) were used to estimate the incidence rates (IRs) of sick leave for each shift. The analysis is a retrospective cohort in design where past payroll records were used to follow the shift, work hours, age, and occurrence of sick leave for each participant from 1994 to date of first sick leave or to date of examination, whichever came first.…”

Section: Discussionmentioning

confidence: 99%

Shiftwork and Sickness Absence Among Police Officers: The BCOPS Study

Fekedulegn

Burchfiel

Hartley

et al. 2013

Chronobiology International

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Shiftwork, regarded as a significant occupational stressor, has become increasingly prevalent across a wide range of occupations. The adverse health outcomes associated with shiftwork are well documented. Shiftwork is an integral part of law enforcement, a high-stress occupation with elevated risks of chronic disease and mortality. Sickness absence is an important source of productivity loss and may also serve as an indirect measure of workers' morbidity. Prior studies of shiftwork and sickness absenteeism have yielded varying results and the association has not been examined specifically among police officers. The objective of this study was to compare the incidence rate of sick leave (any, ≥3 consecutive days) among day-, afternoon-, and night-shift workers in a cohort of police officers and also examine the role of lifestyle factors as potential moderators of the association. Participants (N = 464) from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study examined between 2004 and 2009 were used. Daily work history records that included the shift schedule, number of hours worked, and occurrence of sick leave were available for up to 15 yrs starting in 1994 to the date of the BCOPS study examination for each officer. Poisson regression analysis for ungrouped data was used to estimate incidence rates (IRs) of sick leave by shift, and comparison of IRs across shifts were made by computing incidence rate ratios (IRRs) and their 95% confidence intervals (CIs). Sick leave occurred at a higher rate on the night shift (4.37 per 10 000 person-hours) compared with either day (1.55 per 10000 person-hours) or afternoon (1.96 per 10000 person-hours) shifts. The association between shiftwork and sickness absence depended on body mass index (BMI). For overweight individuals (BMI ≥ 25 kg/m 2 ), the covariate-adjusted incidence rate of sick leave (≥1 day) was twice as large for night-shift officers compared with those working on the day (IRR = 2.29, 95% CI: 1.69-3.10) or afternoon (IRR= 1.74, 95% CI: 1.29-2.34) shift. The IR of three or more consecutive days of sick leave was 1.7 times larger for those working on night shift (IRR = 1.65, 95% CI: 1.17-2.31) and 1.5 times larger for those working on afternoon shift (IRR= 1.50, DECLARATION OF INTERESTThe authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper. HHS Public Access Author Manuscript Author ManuscriptAuthor ManuscriptAuthor Manuscript 95% CI: 1.08-2.08) compared with day shiftworkers. For subjects with normal BMI (<25 kg/m 2 ), the incidence rates of sick leave did not differ significantly across shifts. In conclusion, shiftwork is independently associated with sickness absence, with officers who work the night shift having elevated incidence of sick leave. In addition, overweight officers who work the night shift may be at additional risk for sickness absence.

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Section: Discussionmentioning

confidence: 99%

Shiftwork and Sickness Absence Among Police Officers: The BCOPS Study

Fekedulegn

Burchfiel

Hartley

et al. 2013

Chronobiology International

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“…An "ungrouped" approach to Poisson regression 30 was used to assess properties of procedures while still providing unbiased incidence rate estimates. Events were stratified by device type (suture needles and all other types); separate models were generated to analyze risk of BBF exposure.…”

Section: Discussionmentioning

confidence: 99%

Surgical Procedure Characteristics and Risk of Sharps-Related Blood and Body Fluid Exposure

Myers

Lipscomb

Epling

et al. 2015

Infect. Control Hosp. Epidemiol.

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OBJECTIVETo use a unique multicomponent administrative data set assembled at a large academic teaching hospital to examine the risk of percutaneous blood and body fluid (BBF) exposures occurring in operating rooms.DESIGNA 10-year retrospective cohort design.SETTINGA single large academic teaching hospital.PARTICIPANTSAll surgical procedures (n=333,073) performed in 2001–2010 as well as 2,113 reported BBF exposures were analyzed.METHODSCrude exposure rates were calculated; Poisson regression was used to analyze risk factors and account for procedure duration. BBF exposures involving suture needles were examined separately from those involving other device types to examine possible differences in risk factors.RESULTSThe overall rate of reported BBF exposures was 6.3 per 1,000 surgical procedures (2.9 per 1,000 surgical hours). BBF exposure rates increased with estimated patient blood loss (17.7 exposures per 1,000 procedures with 501–1,000 cc blood loss and 26.4 exposures per 1,000 procedures with >1,000 cc blood loss), number of personnel working in the surgical field during the procedure (34.4 exposures per 1,000 procedures having ≥15 personnel ever in the field), and procedure duration (14.3 exposures per 1,000 procedures lasting 4 to <6 hours, 27.1 exposures per 1,000 procedures lasting ≥6 hours). Regression results showed associations were generally stronger for suture needle–related exposures.CONCLUSIONSResults largely support other studies found in the literature. However, additional research should investigate differences in risk factors for BBF exposures associated with suture needles and those associated with all other device types.Infect. Control Hosp. Epidemiol. 2015;37(1):80–87

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“…The IR of long-term injury by shift and the associated 95% confidence intervals (95% CI) were calculated using Poisson regression for ungrouped data (19). The IR of long-term injury were then compared across the three shifts by computing incidence rate ratios (IRR) and the corresponding 95% CI using the Poisson model.…”

Section: Discussionmentioning

confidence: 99%