Beyond Original Intent – The Use of a Corporation’s Administrative Databases for Academic Research

Large corporations maintain a variety of administrative databases as part of their normal operations. These databases, created for distinct functions by separate organizational entities, are generally independent. For instance, a company’s Human Resources organization typically maintains a database containing information such as demographics, job and salary history, and employee status for all employees.. The environmental, health and safety department maintains information regarding work-place exposures and exposure levels for various agents within each job as well as injury and illness surveillance records. The medical department maintains occupational health information including audiometric and pulmonary function test results. As many large corporations are self-insured, they also have medical claims data available by employee that includes diagnosis codes, procedure codes, and prescription drug codes. Additional data maintained by corporations may include production output and quality information, employee contributions to retirement plans and health savings accounts, as well as workers compensation information. A synergistic partnership between industry and academia allows for linkage between company maintained databases to enable the conduct of research to examine associations between demographic, occupational and social factors not otherwise available to researchers, and the ability to define and test interventions to promote health and safety in the workplace. An almost 20 year relationship between Alcoa, Inc. and Yale University School of Medicine continues to facilitate investigation of root causes of disease and injury risk in a large manufacturing cohort. To date, over 50 peer-reviewed research papers have resulted from this joint venture

Occupational noise exposure and risk of hypertension in an industrial workforce

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140051/1/ajim22775_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/140051/2/ajim22775.pd

Development of a job-exposure matrix for exposure to total and fine particulate matter in the aluminum industry

Increasing evidence indicates that exposure to particulate matter (PM) at environmental concentrations increases the risk of cardiovascular disease, particularly PM with an aerodynamic diameter of less than 2.5 μm (PM(2.5)). Despite this, the health impacts of higher occupational exposures to PM(2.5) have rarely been evaluated. In part, this research gap derives from the absence of information on PM(2.5) exposures in the workplace. To address this gap, we have developed a job-exposure matrix (JEM) to estimate exposure to two size fractions of PM in the aluminum industry. Measurements of total PM (TPM) and PM(2.5) were used to develop exposure metrics for an epidemiologic study. TPM exposures for distinct exposure groups (DEGs) in the JEM were calculated using 8385 personal TPM samples collected at 11 facilities (1980-2011). For eight of these facilities, simultaneous PM(2.5) and TPM personal monitoring was conducted from 2010 to 2011 to determine the percent of TPM that is composed of PM(2.5) (%PM(2.5)) in each DEG. The mean TPM from the JEM was then multiplied by %PM(2.5) to calculate PM(2.5) exposure concentrations in each DEG. Exposures in the smelters were substantially higher than in fabrication units; mean TPM concentrations in smelters and fabrication facilities were 3.86 and 0.76 mg/m(3), and the corresponding mean PM(2.5) concentrations were 2.03 and 0.40 mg/m(3). Observed occupational exposures in this study generally exceeded environmental PM(2.5) concentrations by an order of magnitude

Incident ischemic heart disease and recent occupational exposure to particulate matter in an aluminum cohort

Fine particulate matter (PM(2.5)) in air pollution, primarily from combustion sources, is recognized as an important risk factor for cardiovascular events but studies of workplace PM(2.5) exposure are rare. We conducted a prospective study of exposure to PM(2.5) and incidence of ischemic heart disease (IHD) in a cohort of 11,966 US aluminum workers. Incident IHD was identified from medical claims data from 1998 to 2008. Quantitative metrics were developed for recent exposure (within the last year) and cumulative exposure; however, we emphasize recent exposure in the absence of interpretable work histories before follow-up. IHD was modestly associated with recent PM(2.5) overall. In analysis restricted to recent exposures estimated with the highest confidence, the hazard ratio (HR) increased to 1.78 (95% CI: 1.02, 3.11) in the second quartile and remained elevated. When the analysis was stratified by work process, the HR rose monotonically to 1.5 in both smelter and fabrication facilities, though exposure was almost an order of magnitude higher in smelters. The differential exposure-response may be due to differences in exposure composition or healthy worker survivor effect. These results are consistent with the air pollution and cigarette smoke literature; recent exposure to PM(2.5) in the workplace appears to increase the risk of IHD incidence

Development of the Anthropometric Grouping Index for the Eastern Caribbean Population Using the Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study Data

Improving public health initiative requires an accurate anthropometric index that is better suited to a specific community. In this study, the anthropometric grouping index is proposed as a more efficient and discriminatory alternative to the popular BMI for the Eastern Caribbean population. A completely distribution-free cluster analysis was performed to obtain the 11 categories, leading to AGI-11. Further, we studied these groups using novel non-parametric clustering summaries. Finally, two generalized linear mixed models were fitted to assess the association between elevated blood sugar, AGI-11 and BMI. Our results showed that AGI-11 tends to be more sensitive in predicting levels of elevated blood sugar compared to BMI. For instance, individuals identified as obese III according to BMI are (POR: 2.57; 95% CI: (1.68, 3.74)) more likely to have elevated blood sugar levels, while, according to AGI, individuals with similar characteristics are (POR: 3.73; 95% CI: (2.02, 6.86)) more likely to have elevated blood sugar levels. In conclusion, the findings of the current study suggest that AGI-11 could be used as a predictor of high blood sugar levels in this population group. Overall, higher values of anthropometric measures correlated with a higher likelihood of high blood sugar levels after adjusting by sex, age, and family history of diabetes

Classification of blood pressure during sleep impacts designation of nocturnal nondipping.

The identification of nocturnal nondipping blood pressure (< 10% drop in mean systolic blood pressure from awake to sleep periods), as captured by ambulatory blood pressure monitoring, is a valuable element of risk prediction for cardiovascular disease, independent of daytime or clinic blood pressure measurements. However, capturing measurements, including determination of wake/sleep periods, is challenging. Accordingly, we sought to evaluate the impact of different definitions and algorithms for defining sleep onset on the classification of nocturnal nondipping. Using approaches based upon participant self-reports, applied definition of a common sleep period (12 am -6 am), manual actigraphy, and automated actigraphy we identified changes to the classification of nocturnal nondipping, and conducted a secondary analysis on the potential impact of an ambulatory blood pressure monitor on sleep. Among 61 participants in the Eastern Caribbean Health Outcomes Research Network hypertension study with complete ambulatory blood pressure monitor and sleep data, the concordance for nocturnal nondipping across methods was 0.54 by Fleiss' Kappa (depending on the method, 36 to 51 participants classified as having nocturnal nondipping). Sleep quality for participants with dipping versus nondipping was significantly different for total sleep length when wearing the ambulatory blood pressure monitor (shorter sleep duration) versus not (longer sleep duration), although there were no differences in sleep efficiency or disturbances. These findings indicate that consideration of sleep time measurements is critical for interpreting ambulatory blood pressure. As technology advances to detect blood pressure and sleep patterns, further investigation is needed to determine which method should be used for diagnosis, treatment, and future cardiovascular risk

Patient preferences for facility-based management of hypertension and diabetes in rural Uganda: a discrete choice experiment

Objective To explore how respondents with common chronic conditions—hypertension (HTN) and diabetes mellitus (DM)—make healthcare-seeking decisions.Setting Three health facilities in Nakaseke District, Uganda.Design Discrete choice experiment (DCE).Participants 496 adults with HTN and/or DM.Main outcome measures Willingness to pay for changes in DCE attributes: getting to the facility, interactions with healthcare providers, availability of medicines for condition, patient peer-support groups; and education at the facility.Results Respondents were willing to pay more to attend facilities that offer peer-support groups, friendly healthcare providers with low staff turnover and greater availabilities of medicines. Specifically, we found the average respondent was willing to pay an additional 77 121 Ugandan shillings (UGX) for facilities with peer-support groups over facilities with none; and 49 282 UGX for 1 month of medicine over none, all other things being equal. However, respondents would have to compensated to accept facilities that were further away or offered health education. Specifically, the average respondent would have to be paid 3929 UGX to be willing to accept each additional kilometre they would have to travel to the facilities, all other things being equal. Similarly, the average respondent would have to be paid 60 402 UGX to accept facilities with some health education, all other things being equal.Conclusions Our findings revealed significant preferences for health facilities based on the availability of medicines, costs of treatment and interactions with healthcare providers. Understanding patient preferences can inform intervention design to optimise healthcare service delivery for patients with HTN and DM in rural Uganda and other low-resource settings