Qualitative Environmental Health Research: An Analysis of the Literature, 1991-2008

BACKGROUND. Recent articles have advocated for the use of qualitative methods in environmental health research. Qualitative research uses nonnumeric data to understand people's opinions, motives, understanding, and beliefs about events or phenomena. OBJECTIVE. In this analysis of the literature, I report the use of qualitative methods and data in the study of the relationship between environmental exposures and human health. DATA SOURCES. A primary search on ISI Web of Knowledge/Web of Science for peer-reviewed journal articles dated from 1991 through 2008 included the following three terms: qualitative, environ*, and health. Inclusion and exclusion criteria are described. DATA EXTRACTION. Searches resulted in 3,155 records. Data were extracted and findings of articles analyzed to determine where and by whom qualitative environmental health research is conducted and published, the types of methods and analyses used in qualitative studies of environmental health, and the types of information qualitative data contribute to environmental health. DATA SYNTHESIS. Ninety-one articles met inclusion criteria. These articles were published in 58 different journals, with a maximum of eight for a single journal. The results highlight a diversity of disciplines and techniques among researchers who used qualitative methods to study environmental health, with most studies relying on one-on-one interviews. Details of the analyses were absent from a large number of studies. Nearly all of the studies identified increased scientific understanding of lay perceptions of environmental health exposures. DISCUSSION AND CONCLUSIONS. Qualitative data are published in traditionally quantitative environmental health studies to a limited extent. However, this analysis demonstrates the potential of qualitative data to improve understanding of complex exposure pathways, including the influence of social factors on environmental health, and health outcomes.National Institute of Environmental Health Sciences (R25 ES012084, P42ES007381

Exposure to benzene at work and the risk of leukemia: a systematic review and meta-analysis

Background A substantial number of epidemiologic studies have provided estimates of the relation between exposure to benzene at work and the risk of leukemia, but the results have been heterogeneous. To bridge this gap in knowledge, we synthesized the existing epidemiologic evidence on the relation between occupational exposure to benzene and the risk of leukemia, including all types combined and the four main subgroups acute myeloid leukemia (AML), acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), and chronic myeloid leukemia (CML). Methods A systematic literature review was carried out using two databases 'Medline' and 'Embase' from 1950 through to July 2009. We selected articles which provided information that can be used to estimate the relation between benzene exposure and cancer risk (effect size). Results In total 15 studies were identified in the search, providing 16 effect estimates for the main analysis. The summary effect size for any leukemia from the fixed-effects model was 1.40 (95% CI, 1.23-1.57), but the study-specific estimates were strongly heterogeneous (I2 = 56.5%, Q stat = 34.47, p = 0.003). The random-effects model yielded a summary- effect size estimate of 1.72 (95% CI, 1.37-2.17). Effect estimates from 9 studies were based on cumulative exposures. In these studies the risk of leukemia increased with a dose-response pattern with a summary-effect estimate of 1.64 (95% CI, 1.13-2.39) for low (< 40 ppm-years), 1.90 (95% CI, 1.26-2.89) for medium (40-99.9 ppm-years), and 2.62 (95% CI, 1.57-4.39) for high exposure category (> 100 ppm-years). In a meta-regression, the trend was statistically significant (P = 0.015). Use of cumulative exposure eliminated heterogeneity. The risk of AML also increased from low (1.94, 95% CI, 0.95-3.95), medium (2.32, 95% CI, 0.91-5.94) to high exposure category (3.20, 95% CI, 1.09-9.45), but the trend was not statistically significant. Conclusions Our study provides consistent evidence that exposure to benzene at work increases the risk of leukemia with a dose-response pattern. There was some evidence of an increased risk of AML and CLL. The meta-analysis indicated a lack of association between benzene exposure and the risk of CML

Mortality following development of breast cancer while using oestrogen or oestrogen plus progestin: a computer record-linkage study

The literature on the relationship between breast cancer mortality and postmenopausal oestrogen and combined oestrogen/progestin therapy is seemingly contradictory. This study explored survival after exposure to oestrogen or oestrogen plus progestin at or in the year prior to breast cancer diagnosis. Information on patients first diagnosed with invasive breast cancer between 1993 and 1998 was linked with outpatient pharmacy data from 1992 to 2000. Patients were classified according to use of oestrogen alone or oestrogen plus progestin at or in the year prior to diagnosis. Compared to nonusers, and adjusting for age at diagnosis, race/ethnicity, tumour size and grade, oestrogen receptor status, surgery status, and chemotherapy and hormone therapy for breast cancer treatment, oestrogen plus progestin users had lower all-cause mortality (stage I hazard ratio (HR)=0.69, 95% confidence interval (CI)=0.48–0.99; stage II HR=0.53, 95% CI=0.39–0.72) and breast cancer mortality (stage I HR=0.52, 95% CI=0.26–1.04; stage II HR=0.69, 95% CI=0.48–0.98). Oestrogen users experienced little or no survival benefit for all-cause mortality (stage I HR=1.04, 95% CI=0.77–1.42; stage II HR=0.86, 95% CI=0.65–1.14) or breast cancer mortality (stage I HR=1.23, 95% CI 0.72–2.10; stage II HR=1.01, 95% CI 0.72–1.41). Our findings suggest, relative to nonusers, a lower risk of death from all causes and from breast cancer in patients who were diagnosed with breast cancer while exposed to oestrogen plus progestin, but not in patients exposed to oestrogen only

Oral Contraceptives and Periodontal Diseases: Rethinking the Association Based Upon Analysis of National Health and Nutrition Examination Survey Data

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141450/1/jper1374.pd

PedGenie: meta genetic association testing in mixed family and case-control designs

<p>Abstract</p> <p>Background-</p> <p>PedGenie software, introduced in 2006, includes genetic association testing of cases and controls that may be independent or related (nuclear families or extended pedigrees) or mixtures thereof using Monte Carlo significance testing. Our aim is to demonstrate that PedGenie, a unique and flexible analysis tool freely available in Genie 2.4 software, is significantly enhanced by incorporating meta statistics for detecting genetic association with disease using data across multiple study groups.</p> <p>Methods-</p> <p>Meta statistics (chi-squared tests, odds ratios, and confidence intervals) were calculated using formal Cochran-Mantel-Haenszel techniques. Simulated data from unrelated individuals and individuals in families were used to illustrate meta tests and their empirically-derived p-values and confidence intervals are accurate, precise, and for independent designs match those provided by standard statistical software.</p> <p>Results-</p> <p>PedGenie yields accurate Monte Carlo p-values for meta analysis of data across multiple studies, based on validation testing using pedigree, nuclear family, and case-control data simulated under both the null and alternative hypotheses of a genotype-phenotype association.</p> <p>Conclusion-</p> <p>PedGenie allows valid combined analysis of data from mixtures of pedigree-based and case-control resources. Added meta capabilities provide new avenues for association analysis, including pedigree resources from large consortia and multi-center studies.</p

Towards an integrated crowdsourcing definition

Crowdsourcing is a relatively recent concept that encompasses many practices. This diversity leads to the blurring of the limits of crowdsourcing that may be identified virtually with any type of internet-based collaborative activity, such as co-creation or user innovation. Varying definitions of crowdsourcing exist, and therefore some authors present certain specific examples of crowdsourcing as paradigmatic, while others present the same examples as the opposite. In this article, existing definitions of crowdsourcing are analysed to extract common elements and to establish the basic characteristics of any crowdsourcing initiative. Based on these existing definitions, an exhaustive and consistent definition for crowdsourcing is presented and contrasted in 11 cases.Estelles Arolas, E.; González-Ladrón-De-Guevara, F. (2012). Towards an integrated crowdsourcing definition. Journal of Information Science. 32(2):189-200. doi:10.1177/0165551512437638S189200322Vukovic, M., & Bartolini, C. (2010). Towards a Research Agenda for Enterprise Crowdsourcing. Leveraging Applications of Formal Methods, Verification, and Validation, 425-434. doi:10.1007/978-3-642-16558-0_36Brabham, D. C. (2008). Crowdsourcing as a Model for Problem Solving. Convergence: The International Journal of Research into New Media Technologies, 14(1), 75-90. doi:10.1177/1354856507084420Vukovic, M. (2009). Crowdsourcing for Enterprises. 2009 Congress on Services - I. doi:10.1109/services-i.2009.56Doan, A., Ramakrishnan, R., & Halevy, A. Y. (2011). Crowdsourcing systems on the World-Wide Web. Communications of the ACM, 54(4), 86. doi:10.1145/1924421.1924442Brabham, D. C. (2008). Moving the crowd at iStockphoto: The composition of the crowd and motivations for participation in a crowdsourcing application. First Monday, 13(6). doi:10.5210/fm.v13i6.2159Huberman, B. A., Romero, D. M., & Wu, F. (2009). Crowdsourcing, attention and productivity. Journal of Information Science, 35(6), 758-765. doi:10.1177/0165551509346786Andriole, S. J. (2010). Business impact of Web 2.0 technologies. Communications of the ACM, 53(12), 67. doi:10.1145/1859204.1859225Denyer, D., Tranfield, D., & van Aken, J. E. (2008). Developing Design Propositions through Research Synthesis. Organization Studies, 29(3), 393-413. doi:10.1177/0170840607088020Egger, M., Smith, G. D., & Altman, D. G. (Eds.). (2001). Systematic Reviews in Health Care. doi:10.1002/9780470693926Tatarkiewicz, W. (1980). A History of Six Ideas. doi:10.1007/978-94-009-8805-7Cosma, G., & Joy, M. (2008). Towards a Definition of Source-Code Plagiarism. IEEE Transactions on Education, 51(2), 195-200. doi:10.1109/te.2007.906776Brabham, D. C. (2009). Crowdsourcing the Public Participation Process for Planning Projects. Planning Theory, 8(3), 242-262. doi:10.1177/1473095209104824Alonso, O., & Lease, M. (2011). Crowdsourcing 101. Proceedings of the fourth ACM international conference on Web search and data mining - WSDM ’11. doi:10.1145/1935826.1935831Bederson, B. B., & Quinn, A. J. (2011). Web workers unite! addressing challenges of online laborers. Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems - CHI EA ’11. doi:10.1145/1979742.1979606Grier, D. A. (2011). Not for All Markets. Computer, 44(5), 6-8. doi:10.1109/mc.2011.155Heer, J., & Bostock, M. (2010). Crowdsourcing graphical perception. Proceedings of the 28th international conference on Human factors in computing systems - CHI ’10. doi:10.1145/1753326.1753357Heymann, P., & Garcia-Molina, H. (2011). Turkalytics. Proceedings of the 20th international conference on World wide web - WWW ’11. doi:10.1145/1963405.1963473Kazai, G. (2011). In Search of Quality in Crowdsourcing for Search Engine Evaluation. Advances in Information Retrieval, 165-176. doi:10.1007/978-3-642-20161-5_17La Vecchia, G., & Cisternino, A. (2010). Collaborative Workforce, Business Process Crowdsourcing as an Alternative of BPO. Lecture Notes in Computer Science, 425-430. doi:10.1007/978-3-642-16985-4_40Liu, E., & Porter, T. (2010). Culture and KM in China. VINE, 40(3/4), 326-333. doi:10.1108/03055721011071449Oliveira, F., Ramos, I., & Santos, L. (2010). Definition of a Crowdsourcing Innovation Service for the European SMEs. Lecture Notes in Computer Science, 412-416. doi:10.1007/978-3-642-16985-4_37Porta, M., House, B., Buckley, L., & Blitz, A. (2008). Value 2.0: eight new rules for creating and capturing value from innovative technologies. Strategy & Leadership, 36(4), 10-18. doi:10.1108/10878570810888713Ribiere, V. M., & Tuggle, F. D. (Doug). (2010). Fostering innovation with KM 2.0. VINE, 40(1), 90-101. doi:10.1108/03055721011024955Sloane, P. (2011). The brave new world of open innovation. Strategic Direction, 27(5), 3-4. doi:10.1108/02580541111125725Wexler, M. N. (2011). Reconfiguring the sociology of the crowd: exploring crowdsourcing. International Journal of Sociology and Social Policy, 31(1/2), 6-20. doi:10.1108/01443331111104779Whitla, P. (2009). Crowdsourcing and Its Application in Marketing Activities. Contemporary Management Research, 5(1). doi:10.7903/cmr.1145Yang, J., Adamic, L. A., & Ackerman, M. S. (2008). Crowdsourcing and knowledge sharing. Proceedings of the 9th ACM conference on Electronic commerce - EC ’08. doi:10.1145/1386790.1386829Brabham, D. C. (2010). MOVING THE CROWD AT THREADLESS. Information, Communication & Society, 13(8), 1122-1145. doi:10.1080/13691181003624090Giudice, K. D. (2010). Crowdsourcing credibility: The impact of audience feedback on Web page credibility. Proceedings of the American Society for Information Science and Technology, 47(1), 1-9. doi:10.1002/meet.14504701099Stewart, O., Huerta, J. M., & Sader, M. (2009). Designing crowdsourcing community for the enterprise. Proceedings of the ACM SIGKDD Workshop on Human Computation - HCOMP ’09. doi:10.1145/1600150.1600168Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370-396. doi:10.1037/h0054346Veal, A. J. (Ed.). (2002). Leisure and tourism policy and planning. doi:10.1079/9780851995465.0000Dahlander, L., & Gann, D. M. (2010). How open is innovation? Research Policy, 39(6), 699-709. doi:10.1016/j.respol.2010.01.01

Risk of Stillbirth in the Relation to Water Disinfection By-Products: A Population-Based Case-Control Study in Taiwan

Background: Few epidemiological studies that have assessed the relation between water disinfection by-products (DBPs) and the risk of stillbirth provide inconsistent results. The objective was to assess the relation between exposure to water disinfection by-products and the risk of stillbirth. Methods: We conducted a population-based case-control study of 3,289 cases of stillbirth and a random sample of 32,890 control subjects from 396,049 Taiwanese newborns in 2001–2003 using information from the Birth Registry and Waterworks Registry in Taiwan. We compared the risk of stillbirth in four disinfection by-product exposure categories based on the levels of total trihalomethanes (TTHMs) representing high (TTHMs 20+ mg/L), medium (TTHMs 10–19 mg/L), low exposure (TTHMs 5–9 mg/L), and 0–4 mg/L as the reference category. In addition, we conducted a meta-analysis of the results from the present and 5 previous studies focusing on stillbirth. Findings: In logistic regression analysis adjusting for gender, maternal age, plurality, conception of season and population density of the municipality where the mother lived during pregnancy, the odds ratio (OR) for stillbirth was 1.10 (95 % CI 1.00–1.21) for medium exposure and 1.06 (95 % 0.96–1.17) for high exposure compared to reference category. In the metaanalysis, the summary odds ratio for stillbirth (1.11, 95 % CI: 1.03, 1.19) was consistently elevated. Conclusions: The present study is consistent with the hypothesis that the risk of stillbirth is related to prenatal exposure t

Through the looking glass: understanding non-inferiority

Non-inferiority trials test whether a new product is not unacceptably worse than a product already in use. This paper introduces concepts related to non-inferiority, and discusses the regulatory views of both the European Medicines Agency and the United States Food and Drug Administration

Dental management considerations for the patient with an acquired coagulopathy. Part 1: Coagulopathies from systemic disease

Current teaching suggests that many patients are at risk for prolonged bleeding during and following invasive dental procedures, due to an acquired coagulopathy from systemic disease and/or from medications. However, treatment standards for these patients often are the result of long-standing dogma with little or no scientific basis. The medical history is critical for the identification of patients potentially at risk for prolonged bleeding from dental treatment. Some time-honoured laboratory tests have little or no use in community dental practice. Loss of functioning hepatic, renal, or bone marrow tissue predisposes to acquired coagulopathies through different mechanisms, but the relationship to oral haemostasis is poorly understood. Given the lack of established, science-based standards, proper dental management requires an understanding of certain principles of pathophysiology for these medical conditions and a few standard laboratory tests. Making changes in anticoagulant drug regimens are often unwarranted and/or expensive, and can put patients at far greater risk for morbidity and mortality than the unlikely outcome of postoperative bleeding. It should be recognised that prolonged bleeding is a rare event following invasive dental procedures, and therefore the vast majority of patients with suspected acquired coagulopathies are best managed in the community practice setting