EMPLOYMENT AND EXPOSURES IN THE PETROLEUM REFINING AND PETROCHEMICAL INDUSTRIES AND THE RISK OF LUNG CANCER (EPIDEMIOLOGY, ASSESSMENT)

This dissertation addresses the risk of lung cancer associated with occupational exposures in the petroleum refining and petrochemical industries. Earlier epidemiologic studies of this association did not adjust for cigarette smoking or have specific exposure classifications. The Texas EXposure Assessment System (TEXAS) was developed with data from a population-based, case-comparison study conducted in five southeast Texas counties between 1976 and 1980. The Texas Exposure Assessment System uses job and process categories developed by the American Petroleum Institute, as well as time-oriented variables to identify high risk groups.^ An industry-wide, increased risk for lung cancer was associated with jobs having low-level hydrocarbon exposure that also include other occupational inhalation exposures (OR = 2.0--adjusted for smoking and latency effects). The prohibition of cigarette smoking for jobs with high-level hydrocarbon exposure might explain part of the increased risk for jobs with low-level hydrocarbon exposures. Asbestos exposure comprises a large part of the risk associated with jobs having other inhalation exposures besides hydrocarbons. Workers in petroleum refineries were not shown to have an increased, occupational risk for lung cancer. The increased risk for lung cancer among petrochemical workers (OR = 3.1--smoking and latency adjusted) is associated with all jobs that involve other inhalation exposure characteristics (not only low-level hydrocarbon exposures). Findings for contract workers and workers exposed to specific chemicals were inconclusive although some hypotheses for future research were identified.^ The study results demonstrate that the predominant risk for lung cancer is due to cigarette smoking (OR = 9.8). Cigarette smoking accounts for 86.5% of the incident lung cancer cases within the study area. Workers in the petroleum industry smoke significantly less than persons employed in other industries (p << 0.001). Only 2.2% of the incident lung cancer cases may be attributed to petroleum industry jobs; lifestyle factors (e.g., nutrition) may be associated with the balance of the cases. The results from this study also suggest possible high risk time periods (OR = 3.9--smoking and occupation adjusted). Artifacts in time-oriented findings may result because of the latency interval for lung cancer, secular peaks in age-, sex-specific incidence rates, or periods of hazardous exposures in the petroleum industry. ^

Identifying and removing barriers to cycling as a viable means of transportation in Houston, Texas

The citizens of Houston, Texas, spend much time commuting. It has repeatedly been named among the “Fattest Cities” by Men’s Fitness Magazine (The fittest and fattest cities in America – Men’s Fitness. ). Obesity is one of its major public health problems as Houstonians often do not engage in enough physical activity to help them maintain their ideal weights. The use of bicycles provides a healthy and ecological alternative to commuting by driving. However, because urban cyclists must often share the roads with motorized vehicles, cyclists are often exposed to high levels of emissions. As vulnerable users of the roadways, urban cyclists also face the threat of injury. Nevertheless, there are some programs that encourage the use of bicycles. Laws and ordinances not only reveal public policy relating to bicycling but are a means to develop policy which can encourage bicycling. ^

The role of chronic irritation and inflammation in tumor promotion in CD-1 mice by petroleum middle distillates

An initiation-promotion bioassay in CD-1 mice was used to examine the role of chronic irritation and inflammation in tumor promotion by petroleum middle distillates. A representative hydrodesulfurized middle distillate (API 81-07) was selected as the test article. Test groups (54 mice per group) were initiated once with 50 ug of 7,12-dimethylbenzanthracene (DMBA). Promotion with API 81-07 consisted of twice weekly treatments for 25 weeks with either 25 ul, 50 ul, 50 ul + daily treatment with 15 ug dexamethasone, 50 ul + post-application washings, and 100 ul. Three mice from each group were sacrificed at 21 day intervals (24 total per group). The skin from interim sacrificed (IS) mice was examined histopathologically for tumor, acanthosis, hyperkeratosis, pseudo-epitheliomatous hyperplasia, epidermal crusting, and subacute inflammation. In-life observations included examination of all mice for erythema and edema for 8 weeks following the first promotion treatment. Tumor incident at study termination was as follows: 25 ul (45%), 50 ul (43%), 50 ul + dexamethasone (0%), 50 ul + washing (70%), and 100 ul (81%). An overall correlation of $>$0.90 between tumor incidence and group means for acanthosis and hyperkeratosis was observed in IS mice at all intervals. Correlations of $<$0.75 were observed for other group mean histopathological parameters and tumor incidence. The overall correlation of group mean erythema and edema with tumor incident was $>$0.90. The results of this study support the hypothesis that induction of a lasting, albeit mild, hyperplasia is an essential, but not sufficient requirement, for tumor promotion. Furthermore, subacute inflammation does not appear to be a significant factor in tumor promotion by petroleum middle distillates. However, inflammation may be a factor in tumor progression. ^

Endemic tuberculosis, the homeless, and public transportation: A merging of geographical information systems surveillance and the Houston Tuberculosis Initiative Surveillance project

To reach the goals established by the Institute of Medicine (IOM) and the Centers for Disease Control's (CDC) STOP TB USA, measures must be taken to curtail a future peak in Tuberculosis (TB) incidence and speed the currently stagnant rate of TB elimination. Both efforts will require, at minimum, the consideration and understanding of the third dimension of TB transmission: the location-based spread of an airborne pathogen among persons known and unknown to each other. This consideration will require an elucidation of the areas within the U.S. that have endemic TB. The Houston Tuberculosis Initiative (HTI) was a population-based active surveillance of confirmed Houston/Harris County TB cases from 1995–2004. Strengths in this dataset include the molecular characterization of laboratory confirmed cases, the collection of geographic locations (including home addresses) frequented by cases, and the HTI time period that parallels a decline in TB incidence in the United States (U.S.). The HTI dataset was used in this secondary data analysis to implement a GIS analysis of TB cases, the locations frequented by cases, and their association with risk factors associated with TB transmission. ^ This study reports, for the first time, the incidence of TB among the homeless in Houston, Texas. The homeless are an at-risk population for TB disease, yet they are also a population whose TB incidence has been unknown and unreported due to their non-enumeration. The first section of this dissertation identifies local areas in Houston with endemic TB disease. Many Houston TB cases who reported living in these endemic areas also share the TB risk factor of current or recent homelessness. Merging the 2004–2005 Houston enumeration of the homeless with historical HTI surveillance data of TB cases in Houston enabled this first-time report of TB risk among the homeless in Houston. The homeless were more likely to be US-born, belong to a genotypic cluster, and belong to a cluster of a larger size. The calculated average incidence among homeless persons was 411/100,000, compared to 9.5/100,000 among housed. These alarming rates are not driven by a co-infection but by social determinants. The unsheltered persons were hospitalized more days and required more follow-up time by staff than those who reported a steady housing situation. The homeless are a specific example of the increased targeting of prevention dollars that could occur if TB rates were reported for specific areas with known health disparities rather than as a generalized rate normalized over a diverse population. ^ It has been estimated that 27% of Houstonians use public transportation. The city layout allows bus routes to run like veins connecting even the most diverse of populations within the metropolitan area. Secondary data analysis of frequent bus use (defined as riding a route weekly) among TB cases was assessed for its relationship with known TB risk factors. The spatial distribution of genotypic clusters associated with bus use was assessed, along with the reported routes and epidemiologic-links among cases belonging to the identified clusters. ^ TB cases who reported frequent bus use were more likely to have demographic and social risk factors associated with poverty, immune suppression and health disparities. An equal proportion of bus riders and non-bus riders were cultured for Mycobacterium tuberculosis, yet 75% of bus riders were genotypically clustered, indicating recent transmission, compared to 56% of non-bus riders (OR=2.4, 95%CI(2.0, 2.8), p<0.001). Bus riders had a mean cluster size of 50.14 vs. 28.9 (p<0.001). Second order spatial analysis of clustered fingerprint 2 (n=122), a Beijing family cluster, revealed geographic clustering among cases based on their report of bus use. Univariate and multivariate analysis of routes reported by cases belonging to these clusters found that 10 of the 14 clusters were associated with use. Individual Metro routes, including one route servicing the local hospitals, were found to be risk factors for belonging to a cluster shown to be endemic in Houston. The routes themselves geographically connect the census tracts previously identified as having endemic TB. 78% (15/23) of Houston Metro routes investigated had one or more print groups reporting frequent use for every HTI study year. We present data on three specific but clonally related print groups and show that bus-use is clustered in time by route and is the only known link between cases in one of the three prints: print 22. (Abstract shortened by UMI.)^