To investigate potential links between environmental exposure to petrochemical plant emissions and lung cancer, a population-based case-control study (LMRICS) was conducted in eleven Louisiana parishes bordering the Mississippi River. Cases and age, gender, and race-matched controls were interviewed regarding potential risk factors. Residential history was geocoded to provide indices of long-term proximity to industrial sites. Cases were more likely to have lived near a petrochemical site. Models adjusted for other risk factors, however, showed small or no association with lung cancer (odds ratio for residence within a half-mile of a site
The petrochemical industry in Louisiana includes over 100 plants. Together they account for a quarter of the total U.S. petrochemical production, ranking second only to Texas in total refinery output [
The state of Louisiana has consistently presented higher rates of lung cancer incidence and mortality compared to the U.S. as a whole for the past five decades. During 1998–2003, for example, white male lung and bronchial cancer incidence per 100,000 persons was 108.8 in Louisiana compared to 75.3 for the U.S. [
A review by Whitrow et al. [
A number of studies of varying designs have investigated proximity to a specific industrial site(s). Most focused on nonferrous smelters, with more finding a significant association between smelter proximity and lung cancer [
One older and two recent studies examined associations between cancer and the petrochemical industry or industrial corridor in Louisiana. Gottlieb et al. [
A study of the Norco Manufacturing Complex, a large refining and manufacturing complex, followed workers from 1973 through 1999 and found no increase in mortality from respiratory cancer or other major causes of death [
Tsai et al. [
In order to further investigate the potential link between environmental exposure to petroleum and chemical plant emissions and lung cancer, a case-control study was carried out as part of the Lower Mississippi River Interagency Cancer Study (LMRICS). This case-control study was designed to incorporate detailed information on proximity to key industrial sites as well as information allowing control for other known and potential individual-level risk factors including smoking habits and occupational history. The basic hypothesis understudy was that residential proximity to petrochemical industry sites, particularly those releasing hydrocarbons rated as suspected human carcinogens, is associated with lung cancer risk in the lower Mississippi River industrial corridor.
The LMRICS study-area included 11 Louisiana parishes (counties) bordering the Mississippi River: East Baton Rouge, West Baton Rouge, Iberville, Ascension, St. John, St. James, St. Charles, Orleans, Jefferson, St. Bernard, and Plaquemine parishes (Figure
Louisiana parishes included in the LMRICS case-control study (Study parishes are shown in yellow.).
A rapid case ascertainment system encompassing 25 medical institutions was set up within the catchment area to identify persons newly diagnosed with lung cancer. Ascertainment was carried out in conjunction with the Louisiana Tumor Registry to assure completeness. Eligible cases were those aged 20–74 years and residing in one of the LMRICS parishes at the time of diagnosis with histologically confirmed primary carcinoma of the lung (International Classification of Diseases-9, 162.2–162.9), diagnosed between January 1, 1998 and March 1, 2001, and with no prior history of cancer (except basal or squamous carcinoma of the skin). Further, only persons living and able to participate in an interview were eligible for the study; no proxy respondents utilized. Controls were identified from state driver’s license and personal identification card files and frequency matched to cases on age, gender, and race using stratified random sampling of residents in the study parishes. Determination of race was based on self-report, obtained first from medical records and confirmed by the respondent at interview. While no exclusions were made based on race or ethnicity, most study subjects were either African-American or non-Hispanic Caucasian. The study was approved by the Institutional Review Board of the Louisiana State University Health Sciences Center and adhered to all applicable protocols of other participating medical institutions. All study volunteers gave their informed consent before inclusion in this study.
Participants undertook an extensive interview using a standardized questionnaire to identify potential risk factors. In addition to demographics, lifetime history of cigarette and other tobacco usage was obtained along with estimates of environmental tobacco smoke exposure. Residential histories were elicited for every place since 1970 where the subject resided for at least six months. All jobs held for at least six months were recorded, along with self-reported exposure to any of 12 potential lung carcinogens on each job. Vitamin intake, diet, family, and medical histories were also obtained. In addition, blood and/or buccal cell samples were obtained from participants, and tumor tissue blocks were obtained from participating hospitals as available.
In order to determine residential proximity to industrial sites, every reported address of residence held by participants from 1970 through 1997 inclusive was geocoded using the Map Marker geocoding engine. Residence data were missing for less than 2% of the study period on average. Exact address matches were obtained for 95% of the reported residential addresses. Some residences could only be traced to a specific street and block. When this occurred, the address was mapped to the midpoint of the street. Other addresses were limited to rural route box numbers, which were mapped to the centroid of the zip code boundary for that box. This extended geocoding to 97% of the residential addresses. Residences with missing or unlocatable addresses were not mapped and thus were not included in subsequent analyses. Following the primary analyses, sensitivity analyses were carried out to assure that the exclusion of residences geocoded to zip code centroids did not measurably affect the results.
Industrial sites with potential for toxic chemical emissions to the environment in the LMRICS study area were identified in conjunction with the state’s Office of Public Health. The boundaries of each of these sites were determined from aerial or satellite photographs, verified with site representatives, and mapped, again using Map Marker. Sites were characterized in three ways. First, all sites were considered as a whole, without regard to specific emissions. Second, sites were classified on the basis of their Standard Industrial Classification (SIC) code as either belonging to the petrochemical industry or not. The specific SIC codes used to identify petrochemical sites are provided in the appendix. Third, sites were classified on the basis of the International Agency for Research on Cancer (IARC) carcinogen rating assigned to their specific chemical releases [
To determine an individual’s proximity to industrial sites, the distance from that individual’s residence to the closest boundary of each site was then determined. Using this measure, proximity was then characterized in terms of whether an individual’s residence fell within the area extending outward from the boundaries of a site to a given distance, or “buffer.” Three such buffers were computed: 0.5 miles, 1 mile, and 2 miles. Distances were considered both on the basis of whether the individual was ever within a particular distance in the course of their residential history from 1970 to 1997 and on the basis of how many years over the course of their residential history they were within a particular distance of a given site type.
For purposes of the primary analyses, site distance calculations were restricted to only those years within which a particular site was actually active. For years before (or after) a site was actually operational, distances were set to missing. For computational reasons, all distances exceeding 30,000 m were set to 30,000 on the assumption that exposure potential at such distances was essentially null. This had no effect on the primary analyses, which were based on residence within buffers of up to 2 miles (3,219 m) in radius. Analyses were carried out both with and without a 5-year lag period to reflect the assumption that past exposures are more important than very recent ones. Incorporating a more lengthy lag period such as 15 or 20 years in the main analyses would lose over half of the residential (and hence exposure) history available for the study and would ignore potential postinitiation promotional effects by those exposures. Exploratory analyses to assess the sensitivity of results to a 15-year lag were nevertheless carried out.
Following simple descriptive statistics and comparisons of means, odds ratios were computed using SAS version 9.1 software. Logistic regression analyses conditioned on age (20–39, 40–54, 55–64, and 65–74 years), gender, and race were run in order to retain the frequency matching incorporated in the study’s sampling scheme (SAS 9.1’s PROC PHREG). Unconditional logistic regression analyses incorporating binary indicators for gender and race (Caucasian non-Hispanic) as well as a continuous age term were then carried out (PROC LOGISTIC). All adjusted models also included current smoking status, duration and intensity of smoking, and educational level. Unconditional logistic regression results are presented here as they differed little from the conditional regression results.
A total of 998 potentially eligible lung cancer cases were ascertained during the study period. Of these, 119 (12%) refused to participate. A further 54 (5%) were uncontactable, while 363 were deceased, or deemed too ill to interview. The remaining 462 cases comprised the participating study sample. Of 767 apparently eligible controls, 442 (58%) were contacted and agreed to participate. This yields a response rate among eligible cases of 73% and 58% among controls. Since eligibility could not be fully assessed among nonrespondents, the pool of true eligibles is overestimated. Nonrespondents tended to be slightly older than respondents among cases and younger (by over four years) among controls. For the main analytical dataset, seven cases and five controls that were missing values for one or more of the variables used in the fully adjusted logistic regression were excluded to ensure comparability of the populations used in all comparisons, leaving a total of 455 cases and 437 controls.
Table
Demographic and smoking characteristics of the LMRICS study population1.
Descriptor | Total study population | Cases | Controls |
---|---|---|---|
Number | 892 | 455 | 437 |
Age (mean, in years) | 60.0 (10.2) | 60.4 (9.2) | 59.6 (11.1) |
Male (%) | 64.5 | 65.3 | 63.6 |
Black (%) | 35.3 | 36.0 | 34.6 |
High school graduate or higher (%) | 75.0 | 66.2 | 84.2 |
Residences (1970–99)—total number (mean) | 2.98 (2.41) | 2.89 (2.33) | 3.07 (2.48) |
Residences—total number geocodable (mean) | 2.91 (2.35) | 2.82 (2.26) | 3.01 (2.41) |
Current smokers (%) | 44.4 | 64.6 | 23.3 |
Smoking-years (mean) | 26.9 (18.7) | 36.1 (14.4) | 17.4 (17.9) |
Cig/day while smoking (mean) | 21.6 (21.6) | 28.6 (17.6) | 14.3 (17.9) |
1Means are presented followed by standard deviations in parentheses as appropriate.
Basic comparisons of proximity to industrial sites for cases and controls are presented in Table
Proximity to industrial sites for lung cancer cases and controls in the LMRICS study: mean distance to sites and distribution of ever residing within buffer around specific site types, 1970–19971.
Site type | Cases | Controls |
---|---|---|
Average distance to any active site (m) | 7745 | 8530 |
Average distance to IARC 1, 2A or 2B rated site2 (m) | 9662 | 9952 |
Ever within 0.5 mi buffer, any active site | 10.1% | 8.2% |
Ever within 1.0 mi buffer, any active site | 22.0% | 20.1% |
Ever within 2.0 mi buffer, any active site | 51.9% | 47.1% |
Ever within 0.5 mi buffer, any petrochemical site | 7.9% | 6.4% |
Ever within 1.0 mi buffer, any petrochemical site | 14.9% | 15.8% |
Ever within 2.0 mi buffer, any petrochemical site | 39.8% | 35.2% |
Ever within 0.5 mi buffer, any IARC 1, 2A or 2B rated2 site | 7.0% | 5.9% |
Ever within 1.0 mi buffer, any IARC 1, 2A or 2B rated2 site | 12.7% | 14.4% |
Ever within 2.0 mi buffer, any IARC 1, 2A or 2B rated2 site | 31.2% | 32.0% |
Ever within 0.5 mi buffer, any IARC 1 rated3 site | 5.9% | 5.3% |
Ever within 1.0 mi buffer, any IARC 1 rated3 site | 11.0% | 12.8% |
Ever within 2.0 mi buffer, any IARC 1 rated3 site | 26.2% | 29.1% |
1None of the differences between cases and controls approached nominal statistical significance
2Site reporting release of at least one chemical rated as a known, probable, or possible human carcinogen by IARC.
3Site reporting release of at least one chemical rated as a known human carcinogen by IARC.
Table
Ever Living within Buffer around Specific Site Types, Lung Cancer Crude and Adjusted Odds Ratios with 95% Confidence Intervals1.
Site type | Buffer extension | ||
0.5 mile | 1 mile | 2 mile | |
Any active site | 1.05 | 0.86 | 0.97 |
(0.59–1.86) | (0.57–1.28) | (0.70–1.34) | |
Any petrochemical site | 1.10 | 0.73 | 0.95 |
(0.58–2.08) | (0.46–1.15) | (0.68–1.34) | |
Any IARC 1, 2A or 2B rated site | 1.05 | 0.70 | 0.69 |
(0.53–2.06) | (0.43–1.14) | (0.48–0.99) | |
Any IARC 1 rated site | 0.90 | 0.64 | 0.60 |
(0.44–1.85) | (0.38–1.07) | (0.42–0.88) | |
Any active site | 1.25 | 1.12 | 1.21 |
(0.79–1.98) | (0.81–1.54) | (0.93–1.57) | |
Any petrochemical site | 1.26 | 0.94 | 1.21 |
(0.75–2.10) | (0.65–1.35) | (0.93–1.59) | |
Any IARC 1, 2A or 2B rated site | 1.20 | 0.87 | 0.96 |
(0.70–2.04) | (0.59–1.27) | (0.73–1.28) | |
Any IARC 1 rated site | 1.14 | 0.84 | 0.87 |
(0.64–2.01) | (0.56–1.26) | (0.64–1.16) |
1All odds ratios are for persons ever living within buffer of specified extension around a specified type of site. Adjusted results include control for age, gender, race (Caucasian non-Hispanic: yes versus no), current smoker status (yes/no), years smoked, average cigarettes/day if and when smoking, education, and residence within New Orleans metropolitan area.
To factor in duration as well as proximity, the results of models based on total years lived within the buffer are presented in Table
Adjusted odds of lung cancer for increasing categories of years lived within the buffer around specific site types, with 95% confidence intervals in parentheses1.
Site type | Years within buffer: 16 + versus under 16 years | Years within buffer: 16 + or 1–15 versus 0 years | |||
0–15 | 16 or more | 0 | 1–15 | 16 or more | |
Any active site | 1.00 | 1.37 (0.63–2.96) | 1.00 | 0.68 (0.31–1.49) | 1.35 (0.62–2.91) |
Any petrochemical site | 1.00 | 1.45 (0.61–3.48) | 1.00 | 0.68 (0.29–1.64) | 1.43 (0.60–3.44) |
Any IARC 1, 2A or 2B rated site | 1.00 | 1.25 (0.51–3.07) | 1.00 | 0.68 (0.27–1.74) | 1.24 (0.50–3.04) |
Any IARC 1 rated site | 1.00 | 1.10 (0.42–0.92) | 1.00 | 0.61 (0.23–1.62) | 1.09 (0.41–2.89) |
Any active site | 1.00 | 0.89 (0.53–1.50) | 1.00 | 0.81 (0.48–1.37) | 0.87 (0.51–1.47) |
Any petrochemical site | 1.00 | 0.70 (0.38–1.31) | 1.00 | 0.76 (0.41–1.41) | 0.66 (0.37–1.17) |
Any IARC 1, 2A or 2B rated site | 1.00 | 0.68 (0.37–1.24) | 1.00 | 0.68 (0.35–1.35) | 0.66 (0.36–1.21) |
Any IARC 1 rated site | 1.00 | 0.64 (0.34–1.21) | 1.00 | 0.63 (0.31–1.27) | 0.62 (0.33–1.18) |
Any active site | 1.00 | 1.05 (0.75–1.48) | 1.00 | 0.86 (0.54–1.36) | 1.02 (0.71–1.46) |
Any petrochemical site | 1.00 | 0.96 (0.68–1.48) | 1.00 | 0.88 (0.54–1.44) | 0.94 (0.64–1.38) |
Any IARC 1, 2A or 2B rated site | 1.00 | 0.80 (0.52–1.23) | 1.00 | 0.55 (0.32–0.93) | 0.74 (0.50–1.10) |
Any IARC 1 rated site | 1.00 | 0.84 (0.54–1.30) | 1.00 | 0.42 (0.24–0.72) | 0.72 (0.47–1.11) |
1All odds ratios are for persons living for a given number of years within the buffer of specified extension around a specified type of site, adjusted for: age, gender, race (Caucasian non-Hispanic: yes versus no), current smoker status (yes/no), years smoked, average cigarettes/day if and when smoking, and education (less than high school, high school, post-high school).
Further analyses were run to assess the potential effect of other factors on these results. Socioeconomic status in its various measures has been linked to lung cancer, so alternative measures were examined. Substitution of income for education in the regression models produced similar results; inclusion of both variables simultaneously had little effect beyond adding variance to the model. Addition of fruit and vegetable intake, self-reported occupational exposure to one or more potential lung carcinogens, or high risk occupation based on job history likewise produced no meaningful change in results. The same held for use of the square root of pack-years in place of the separate years smoked and cigarettes per day terms used in the main analyses, or exclusion of residences that had been geocoded to the zip code centroid rather than via exact street match. An index based on years within a buffer wherein weights of 2, 1, and 0.5 were assigned if the highest IARC carcinogen rating of any chemical reported released by the site was known, probable, or possible was also used. Results were similar to those for unweighted years in Table
Analyses extending the lag period to 15 years were conducted. While many of the odds ratios became larger to a degree, the basic conclusions were similar to those reached with a 5-year lag: the strongest associations were seen for a 0.5 mile buffer, and none of them approached statistical significance. There was no consistent increase in odds with increasing years of exposure.
This analytic study is generally consistent with the findings of two earlier ecologic studies of lung cancer and industrial proximity in Louisiana that found no statistically significantly elevated risk of lung cancer [
Most previous studies of industrial site proximity and lung cancer have focused on smelters. Few studies have addressed petrochemical sites, and most of those employed an ecologic study design and did not control for competing individual level risk factors. Belli et al. [
The current study’s findings thus fall in the range observed across these recent case-control studies and other previous studies of lung cancer around petrochemical sites. The observation that no evidence of any elevated odds of lung cancer was found among women differs from the findings in the studies of the Teesside population, but among other studies reporting relevant results Kaldor found an association only in men and Tsai in neither men nor women [
Confounding due to potential effects of particulate matter or other pollutants derived from nonindustrial sources could have contributed to the lack of association noted between industrial site proximity and lung cancer. A number of studies in the U.S. and Europe have observed a positive association between such measures, particularly PM2.5, PM10, or TSP, and lung cancer [
Strengths of the study include the restriction to histologically confirmed cancers (minimizing risk of misdiagnosis) and in-person interviews (avoiding potential inaccurate or biased recall of exposure history or personal habits introduced by use of proxy interviews). Thorough data on smoking, occupation, socioeconomic status, diet, and other potential risk factors was available and thus could be controlled for. This is critical as smoking, low socioeconomic status, and residence close to an industrial site tend to correlate, and failure to account for each factor can potentially leave results overrun with bias [
The study was a population-based case-control study. While an analytical sample of 892 people with detailed data is substantial, less than 10% of the population held a residence within half a mile of any industrial site for even a single year, yielding limited power for assessment of associations with high-proximity exposures. Power is greater for residence within one or two-mile buffers, but it is unclear to what degree extending residential coverage to one or two miles from a site still represents an indicator of high exposure risk rather than of being at a “safer” distance from the site.
The potential for recall bias exists in any case-control study. Given that site proximity measures were obtained by mapping residential address information and calculating distances across that history to over 90 potential exposure sites rather than asking participants directly about their exposure, however, systematic recall bias is unlikely for the main exposure under study. Further, all smoking (and other) histories were obtained without use of proxies, reducing potential differences in data quality between cases and controls, and all interviews were conducted using standardized forms and techniques.
Case accrual in population-based studies of lung cancer presents special challenges due to short survival periods following diagnosis and debilitating illness. Even with rapid case ascertainment, nearly as many cases were deceased or too ill to interview as were enrolled. Lung cancer patients who died rapidly or were too ill to interview shortly after diagnosis were likely to have presented at later stage than those who stayed healthy long enough to participate. The implications of missing these more advanced cancers are unclear. It is possible that if exposure to petrochemical plant emissions promotes more aggressive tumors, these cases would be underrepresented in the study population. All but 54 eligible cases were able to be contacted, reducing any threat to the representativeness of the sample from this source.
Low response rates, particularly markedly lower rates among controls, heighten the potential for bias in results. With response rates of 73% among cases and 58% among controls, the latter is higher than typically achieved in field studies, reducing potential for bias. Demographic information regarding nonresponding controls was limited. Nonrespondents did tend to be older by around two years among cases and among controls, younger by around four years. Thus characteristics tracking with age should tend to be overrepresented in the control population, although the small magnitude of the age shift argues against a major impact. As a comparison, Edwards et al. [
The TRI data used to classify sites according to the IARC carcinogen ratings of their reported releases of specific chemicals is a putative study strength. Detailed data were only available from 1988 or later, depending upon when the reporting of a particular chemical became mandatory. It is possible that some sites may have released IARC 1, 2A, or 2B rated chemicals only prior to this period and thus been misidentified as nonreleasers. Further, the actual amount of each chemical released was not addressed due to the difficulty in estimating differences in chemicals’ carcinogenic potency. Both factors may have contributed to inaccurate potential dose and effect estimation. Further complicating estimation of dose is the potential contribution of wind direction and stack height on distribution of releases. The latter could in fact result in released chemicals passing over very near areas before settling at greater distances from the site. Differences in dispersion characteristics may combine with release height to affect dose (e.g., near-ground release of a volatile organic versus high air release of a particulate). The inability to incorporate stack height coupled with specific pollutant dispersion characteristics into the model could have had an influence on results.
The issue of latency was addressed to a degree by the incorporation of a 5-year lag in the main analyses. There was, however, no increase in the observed associations between site proximity and lung cancer when a 5-year lag was included compared to no lag. Most associations, in fact, grew somewhat weaker after adoption of the lag. A limitation of the study is that the available residential history is restricted to approximately 30 years. This makes exploration of longer lags problematic. A 15-year lag did yield stronger associations on average, but again even the largest of these did not approach statistical significance. Further, the longer lag sacrifices much of the available residential history, forcing reliance on a smaller timeframe as well as greater dependence on extrapolation beyond available chemical release data, which makes it unclear whether the observed differences support a longer latency effect or simply reflect random change produced by excluding some of the data. It is notable that a recent case-control study of petrochemical and other plant emissions similar in design to our own [
The evidence linking environmental exposure to petrochemical plant releases with lung cancer is equivocal. Both ecologic and case-control studies have yielded mixed conclusions. The current case-control study found only small indications of an association between residential proximity to petrochemical or other industrial plants in the lower Mississippi river corridor and odds of lung cancer, with no evidence of dose-response observed. The study’s findings do not support a statistically significant effect of petrochemical or other industrial sites releases on the risk of lung cancer among the general population. Larger sample sizes and more definitive measures of exposure would be needed to conclusively resolve whether any effects on risk actually exist, or whether any effect is observed in subgroups defined by genetically determined host response.
Standard Industrial Classification codes for all industrial sites served as the basis for determining whether these should be classified as petrochemical sites for purposes of the study analyses. Sites with any of the SIC codes listed in Table
SIC Code | Type of industry |
---|---|
2865 | Cyclic crudes and intermediates |
2869 | Industrial organic chemicals NEC |
5169 | Chemicals and allied products NEC |
2812 | Alkalies and chlorine |
2899 | Chemical preparations NEC |
2911 | Petroleum refining |
2821 | Plastics materials and resins |
2851 | Paints and allied products |
2822 | Synthetic rubber |
The codes for 5171 (PETROLEUM BULK) and 2824 (ORGANIC FIBERS) were not included among those classified as petrochemical sites due to their low potential for exposure of off-site populations to carcinogenic chemical release. For facilities with code 5169 (CHEMICALS AND ALLIED PRODUCTS NEC), TRI chemical release data for that facility were checked and if no releases of chemicals rated 1, 2A, or 2B by IARC were reported in the available data, the facility was not classified as a petrochemical site. The same approach was taken for codes of 2851 (PAINTS AND ALLIED PRODUCTS).
Support for this study was provided by a grant from the U.S. Environmental Protection Agency (EPA825548).