Tag Archives: Public Health

An Executive Summary

Screenshot (94)Pathopoiesis Mechanism of Smoking and Shared Genes in Pancreatic Cancer

DOI: 10.13140/RG.2.2.33028.63362

To raise new questions, new possibilities, to regard old problems from a new angle requires creative imagination and marks the real advance in science (Einstein & Infeld, 1938, p. 92).

Pancreatic cancer (PC) at the start of the 21st century continues to be a vital unresolved health problem, remaining as one of the deadliest human cancers. By the year 2030, it is projected that PC will be the second leading cause of cancer death after lung cancer among the major types of cancer (Rahib et al. 2014). The outcome of this study would provide valuable insights into the etiopathogenesis of PC and cancer types with a shared-gene association (CTSG-A), as well as the possible recognition of the probable unique pattern of PC malignancy among defined age groups, between men and women, in correlation to the modification effect of smoking to cancer predisposition genes (CPG), or its combined impact. Additional understanding of the pathopoiesis dynamics of smoking status, gender, and age in individuals with CPG in the induction and promotion of PC could help promote pre- and post behavioral diagnosis change. This study may assist in developing a novel patient management approach to accurately assess the disease burden under the lens of public health and modern epidemiology. Although genetic changes can be either somatic or hereditary, described as de novo (new), PC does not arise de novo (Maitra & Hruban, 2008), but rather initiated by a probable gene mutation such as p16/CDKN2A that results to debilitating metabolic effects of uncontrolled growth. Given the assumption that a disease is caused by a factor that can be controlled, exploring the relationship between modifiable health behaviors such as smoking and family cancer history (FCH), CPG or shared genes was a legitimate endeavor. In this study, genetic syndromes associated with PC were interchangeably referred to as FCH, CPG, or shared genes. Pancreatic cancer and other cancers found to have a shared-gene association (S-GA) were the dependent variables, and smoking status, age, and gender were the independent variables; this study addressed the following research questions (RQs) and hypotheses:

RQ1: Is cigarette smoking associated with the etiopathogenesis of pancreatic cancer and cancer types with shared gene association (CTSG-A)?

H01: Smoking level has no correlation with prevalence of PC and CTSG-A.

H1: Smoking can increase the risk of PC and CTSG-A.

RQ2: Is there a relationship between the combined role of age and gender in the etiopathogenesis of PC and CTSG-A?

H02: Age and gender have no correlation with prevalence of PC and CTSG-A.

H2: Age and gender are correlated with the prevalence of PC and CTSG-A.

The unique contribution of this dissertation to the current body of knowledge involved examining the links between tobacco use, gender, age, PC, and shared genes. This dissertation could promote population health, and lessons learned could reshape the current understanding of cancer epidemiology by providing the scientific justification for the implementation of screening, surveillance, and education programs. The outcome of this dissertation would fit into the practical intervention approach of adopting a healthy lifestyle such as smoking cessation as part of positive, meaningful social change to improve prognosis and quality of life during PC progression.

Background

Pandol et al. (2012) noted the economic burden of PC with an expected yearly cost of $4.9 billion and underscored the significance of determining the mechanisms underlying the effect of smoking compounds that may provide additional insights into the pathogenesis of the disease. The investigation gave valuable insights into the etiopathogenesis of pancreatic growth from its induction and promotion. Moreover,  findings of Hart, Kennedy, and Harvey (2008); and Schenk et al. (2001) support the unique probable contribution of this dissertation to the existing body of knowledge, generating a snapshot of a possible correlation of smoking, gender, and age to the development of PC and CTSG-A, enhancing the knowledge on the pathopoiesis mechanism of these predictors in disease induction and promotion. The plethora of findings of the past and present studies highlighted the causal significance of modifiable risk factors and genetics in the pathosis of PC. The goal of these studies falls largely within the confines of understanding the insights of genetic alterations and specific modifiable risk factors. Much of the recent research concentrates in this line of inquiry; therefore, recognizing the modifying effect of smoking to individuals with family aggregation justifies the merit of this dissertation and future endeavors.

Blackford et al. (2009) noted that previous researchers overlooked the distinction between the passenger and driver mutations that explains the often unconvincing associations between smoking and driver mutations. Recognizing this gap, and while there are continued studies on different aspects of the PC genomic landscape, this dissertation intends to provide a descriptive analysis of the prevalence pattern of PC and CTSG-A known to have increased risk of extrapancreatic malignancies versus nonsmokers. The mechanisms through which smoking, gender, age, and CPG affect PC remain unknown, making it critical to explore the role of these three predictors in the disease clustering to develop a more efficient management and clinical approach. With an exhaustive understanding of the patterns of somatic alteration in pancreatic carcinogenesis comes the opportunity to understand the influence of these factors on metastatic progression (Yachida & Iacobuzio-Donahue, 2013). The burden of chronic diseases such as PC is often neglected on the public agendas. The increasing annual economic burden of PC is beyond genetics and social inequalities, making it necessary to embrace the shift in the level of analysis from traditional to modern epidemiologic and New Public Health approach. The significance of the successful delivery of the New Public Health both at the level of society and individual behavior (Halpin et al., 2010) justifies the intent of this dissertation on the need for further exploration of the pathopoiesis mechanism of tobacco use and FCH, the etiopathogenic role of gender and age. The unveiling of the “Precision Medicine Initiative” during the State of the Union Address of President Barack Obama on January 20, 2015, springboard the new effort of revolutionizing a new model of patient-powered research that could accelerate biomedical discoveries and provide clinicians with new tools, knowledge, and therapies. New research directions are warranted to reverse the lethal outcome of this disease.

Study Design and Approach

The causality of tobacco-related mutagenic risk factors and the correlation between gender and age and CPG will not only raise awareness of the significance of cancer risk screening and counseling but will also increase the understanding of environmental, genetic, and biodemographic interaction (EGBI) contributing to the development and progression of PC. The results of this study may be used to promote lifestyle change in reducing cancer risk. Improving the perceived corollary of individuals with inherited genes and quality of life during the expression or final stage of the disease is dependent on the favorable adjustment of behavioral risk factors. This study intended to explore the association between smoking, gender, and age in individuals with CPG. I used a cross-sectional design to determine the prevalence of pancreatic cancer and CTSG-A among smokers and non-smokers.  The potential association of smoking, gender, and age as predictors of the outcome variable (PC/CTSG-A) were explored using a cross-sectional design. Secondary data were recoded and randomized using IBM Statistical Package for the Social Sciences (SPSS, Version 23, 64-bit edition). Although logistic regression makes no assumptions about the distributions of the predictor variables (smoking, gender, age), ordinal modeling was the fundamental property of the design of this study to test whether smoking level and age are effect modifiers to inherited genes or combined causative predictors in the induction and promotion of PC and CTSG-A.

The population for the study was defined as participants of the Behavioral Risk Factor Surveillance System (BRFSS) survey. Subject selection criteria were set narrowly, by selecting specifically those who smoke and do not smoke with PC/CTSG-A (survivorship module), versus non-smokers with PC/CTSG-A. Association between smoking, age, gender, PC, and PC/CTSG-A are explored using hypothetical conceptual cohort. A hypothetical conceptual cohort is defined as participants from the 2014 BRFSS survey who qualified as high-risk based on the level of smoking. The dependent variable under Level 1 or Category 1 in this dissertation comprised cancer types with P16(CDKN2A) and PRSS1 mutations. The cancer types that were included as part of this category were pancreatic, melanoma, esophageal, leukemia, lung, bladder, renal, brain, osteosarcoma (bone), and cancer of the head and neck. Level two or category two includes cancer types with BRCA1, STK11, and LKB1 mutations. While p16 is related to breast cancer, BRCA1 is two times to have a relative risk of PC, with higher risk by age 70. The cancer types that are considered to be part of this category are breast, ovarian, and prostate cancer. Level three or category three are composed of cancer types with bMLH1, and bMSH2 mutations. The cancer types in this category are endometrial, colorectal, and stomach cancer. Regression methods were used to assess and adjust for confounding, and determine whether there is effect modification, as well as simultaneously evaluate the relationships of risk factors (smoking, age, gender). Given that this study involves PC/CTSG-A, and more than one independent variables, ordinal logistic regression analysis was performed to assess confounding and effect modification. The impact of multiple risk factors (smoking, gender, age) is examined as opposed to focusing on a single risk factor. Two separate logistic regression analyses were conducted to assess differences in induction and promotion of pancreatic cancer/CTSG-A by gender and three age groups (<51, 52-69, 70>).

Research Findings

The effect of tobacco use, age, and sex in the etiopathogenesis of PC and CTSG-A was assessed using cumulative odds ordinal logistic regression with proportional odds. While the results of this study supported the null hypotheses that smoking does not correlate with the prevalence of PC and CTSG-A as confirmed by the GENLIN parameter estimates, both gender and age are statistically significant predictors with <.05 p-values. The odds of male respondents developing PC and CTSG-A versus the female respondents is .418 (95% Cl, .344 to .509) with a statistically significant effect, X2 (1) = 75.507. The odds ratio of 1.374 (95% CI, 1.184 to 1.595), Wald χ2(1) = 17.538 is suggestive to the increased probability of developing the disease as the persons reach the age between 62 and 69 years of age. Separate binomial logistic regression analysis shows age was associated with an increased likelihood of developing the disease. Analogous to the results of the ordinal logistic regression analysis, the odds of the male participants of the 2014 BRFSS survey is 2.472 times greater to develop the disease as opposed to female respondents. The findings of this study could support the importance of behavioral risk factor and their roles in reducing the prevalence of PC and CTSG-A, enhancing the late-stage quality of life.

Ab-initio studies have established that family history of PC can manifest due to genetic factors and shared environmental factors. The scientific perspective of this dissertation, current, and past studies are parallel to Albert Einstein’s concept of “natura naturans”—everything is connected. In this dissertation, the assumption that P16(CDKN2A), PRSS1, BRCA1, STK11, LKB1, bMLH1, and bMSH2 are correlated with the development of the disease is mathematically or statistically correct and deserves further investigation.

Presenting a New Metatheory

The Unified Paradigm of Cancer Causation (UPCC), a metatheory introduced in this dissertation could provide arguments on the positive association (synergism) between tobacco use and FCH, giving more clarity to Rothman’s notion of epidemiologic interaction or the paradigm of sufficient cause. UPCC is a composite construct of the germ theory and the somatic mutation theory of carcinogenesis (SMT) in combination with the traditional or Darwinian evolutionary system (Greaves & Maley, 2012), Knudson’s two-hit theory (Hermanowicz, 2015), genome theory, Darwinian theory of social change (Richerson & Boyd, 2000), and the multi-level biologic, social integrative construct (MBASIC). The theoretical cocktail of UPCC could interlock new insights on tumor initiation, metastases diagnostic, and treatment strategies. The dynamic interplay of gene-culture transmission recognized in UPCC could initiate the evolution of culture that embraces the value of evidence-based screening, surveillance, management, and personal genomics. Central to human adaptations is the use of socially learned information (Richerson, Boyd & Henrich, 2010), from literacy program of a health system, emphasizing the significance of 21st-century approach. The combined causal association of a variety of levels as recognized by Lynch and Rebbeck (2013) that are linked to cancer incidence and mortality justify the supposition of UPCC. It is critical to underscore the magnitude of intercalating the mandatory early screening, and management of the health system. The complex, integrative approach of UPCC supports the views of Loomis, and Wing (1990), Pearce (1996), and McEwen and Getz (2013) in embracing the new epidemiologic paradigm congruent to the advances in cancer genome sequencing. Theorizing the pathopoiesis mechanism of smoking, inherited genes, and association of gender and age in the etiopathogenesis of PC/CTSG-A warrants exploration of its causal footprints, conjoining both biomedical and lifestyle (Krieger, 2011).

New Public Health at the Level of Society and Individual Behavior

Darwinism is a collection of concepts, empirical methods and mathematical tools designed to understand the dynamics of genetics and cultural evolution (Richerson & Boyd, 2000). Therefore, this dissertation supports the rationale of cultural value transmission of smoking cessation that could lower the risk to individuals with CPG. Smoking cessation as a cultural item is a clear implication for positive social change. While smoking cessation is the probable social implication of this dissertation, it is important to stress the epidemiologic value of a study on the apparent correlation between gender and age, modification effect of tobacco use among individuals with PC and CTSG-A. The outcome of a risk factor epidemiologic study in individual terms could uplift precision medicine to meet the challenges in tailoring medical interventions based on patient’s biological profile, genetic and epigenetic traits, giving a better understanding of EGBIs. The results of this dissertation have several implications for social change, such as recognizing cultural values in developing effective communication structured from the statistically significant etiopathogenic role of gender and age in the development of PC and CTSG-A. This will give a clear understanding of what to ask, and what actions to take, allowing the family to openly explore treatment alternatives during the terminal phase of the illness (Ballard-Reisch & Letner, 2003). Primary prevention must be prioritized as an integral part of global cancer control. No regulatory standards nor advanced innovations could change the hearts and minds of the general population unless evidence-based studies support it. Social change will be dependent upon the continued dissemination of current cancer research built on integrative social molecular pathological epidemiology (MPE). Pearce (1996) argue that epidemiology must reintegrate itself into public health and must rediscover the population perspective. However, while the new paradigm of downstream (individual) approach could produce a lifestyle approach to social policy, the cumulative outcome of research in cancer epidemiology could equate positive implications to population health.

Improving the future of individuals diagnosed with PC through the concerted efforts of policymakers, public health professionals, clinicians and scientists, the Recalcitrant Cancer Research Act of 2012 lays the foundation for a heightened focused on further development and use of prevention, screening and therapeutic strategy (Rahib et al., 2014). The genuine progress against PC as recalcitrant cancer warrants strategic direction and guidance on the continued understanding, development of efficient early detection strategy and identifying therapeutic targets that could stem the tide of its growing economic burden.

References

Amundadottir, L. T., Thorvaldsson, S., Gudbjartsson, D. F., Sulem, P., Kristjansson, K., Arnason, S.,…Stefansson, K. (2004). Cancer as a complex phenotype: Pattern of cancer distribution within and beyond the nuclear family. PLoS Med1(3), e65. doi: 10.1371/journal.pmed.0010065

Ballard-Reisch, D. S., & Letner, J. A. (2003). Centering families in cancer communication research: Acknowledging the impact of support, culture and process on client/provider communication in cancer management. Patient Education and Counseling, 50(1), 61-66. http://dx.doi.org/10.1016/S0738-3991(03)00082-X

Blackford, A., Parmigiani, G., Kensler, T. W., Wolfgang, C., Jones, S., Zhang, X., … & Goggins, M. (2009). Genetic mutations associated with cigarette smoking in pancreatic cancer. Cancer research69(8), 3681-3688. doi: 10.1158/0008-5472.CAN-09-0015

Einstein, A & Infeld, L. (1938). The evolution of modern physics. New York: Simon and Schuster.

Garcia, M., Jemal, A., Ward, E. M., Center, M. M., Hao, Y., Siegel, R. L., & Thun, M. J. (2007). Global cancer facts & figures 2007. Atlanta, GA: American cancer society1(3), 52. https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/global-cancer-facts-and-figures/global-cancer-facts-and-figures-2007.pdf

Greaves, M., & Maley, C. C. (2012). Clonal evolution in cancer. Nature, 481(7381), 306-313. doi: 10.1038/nature10762

Halpin, H.A., Morales-Suarez-Varela, M. M., & Martin-Moreno, J. M. (2010). Chronic disease prevention and the new public health. Public Health Reviews32(1), 120. https://doi.org/10.1007/BF03391595

Hart, A. R., Kennedy, H., & Harvey, I. (2008). Pancreatic cancer: a review of the evidence on causation. Clinical Gastroenterology and Hepatology, 6(3), 275-282. https://doi.org/10.1016/j.cgh.2007.12.041

Hermanowicz, S. (2015). The Impact of BRCA2 on Homologous Recombination and PARP Inhibitor Sensitivity Examined in BRCA2 Heterozygous Cell Lines. Retrieved from http://skemman.is/stream/get/1946/21851/51118/1/Stefan_Hermanowicz_Thesis_Final_.pdf

Hidalgo, M. (2010). Pancreatic cancer. New England Journal of Medicine, 362(17), 1605-1617. http://dx.doi.org/10.1056/NEJMra0901557

Hidalgo, M., Cascinu, S., Kleeff, J., Labianca, R., Löhr, J. M., Neoptolemos, J., … & Heinemann, V. (2015). Addressing the challenges of pancreatic cancer: future directions for improving outcomes. Pancreatology15(1), 8-18. https://doi.org/10.1016/j.pan.2014.10.001

Hoeijmakers, J. H. (2009). DNA damage, aging, and cancer. New England Journal of Medicine361(15), 1475-1485. doi: 10.1056/NEJMra0804615

Krieger, N. (2011). Epidemiology and the people’s health: theory and context (Vol. 213). New York: Oxford University Press.

Krier, J. B., & Green, R. C. (2013). Management of incidental findings in clinical genomic sequencing. Current Protocols in Human Genetics, 9-23. doi: 10.1002/0471142905.hg0923s77

Labilles, U. (2015a). Reevaluating the Impact of Cigarette Smoking on Pancreatic Cancer. Unpublished manuscript, College of Health Sciences, Public Health, Epidemiology, Walden University, Minneapolis.

Labilles, U. (2015b, September 27). A Promise to a Dying Brother [Web log post]. Retrieved from https://onenationsecho.com/2015/09/27/a-promised-to-a-dying-brother/.

Labilles, U. (2015c). Prospectus: Tobacco Use and Family Cancer History in the Pathopoiesis of Pancreatic Cancer. Unpublished manuscript, College of Health Sciences, Public Health, Epidemiology, Walden University, Minneapolis.

Labilles, U. (2016). The New Public Health: Beyond Genetics and Social Inequalities. Unpublished manuscript, College of Health Sciences, Public Health, Epidemiology, Walden University, Minneapolis.

Loomis, D., & Wing, S. (1990). Is molecular epidemiology a germ theory for the end of the twentieth century?. International journal of epidemiology, 19(1), 1-3. http://dx.doi.org/10.1093/ije/19.1.1

Lynch, S. M., & Rebbeck, T. R. (2013). Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach. Cancer Epidemiology Biomarkers & Prevention22(4), 485-495. doi: 10.1158/1055-9965.EPI-13-0010

Maitra, A., & Hruban, R. H. (2008). Pancreatic cancer. Annu. Rev. pathmechdis. Mech. Dis.3, 157-188. doi:  10.1146/annurev.pathmechdis.3.121806.154305

Makohon-Moore, A., Brosnan, J. A., & Iacobuzio-Donahue, C. A. (2013). Pancreatic cancer genomics: insights and opportunities for clinical translation. Genome medicine5(3), 26. https://doi.org/10.1186/gm430

McEwen, B. S., & Getz, L. (2013). Lifetime experiences, the brain and personalized medicine: An integrative perspective. Metabolism62, S20-S26. https://doi.org/10.1016/j.metabol.2012.08.020

Pandol, S. J., Apte, M. V., Wilson, J. S., Gukovskaya, A. S., & Edderkaoui, M. (2012). The burning question: why is smoking a risk factor for pancreatic cancer?. Pancreatology12(4), 344-349. doi: 10.1016/j.pan.2012.06.002

Pearce, N. (1996). Traditional epidemiology, modern epidemiology, and public health. American journal of public health86(5), 678-683.

Rahib, L., Smith, B. D., Aizenberg, R., Rosenzweig, A. B., Fleshman, J. M., & Matrisian, L. M. (2014). Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer research74(11), 2913-2921. doi: 10.1158/0008-5472.CAN-14-0155

Richerson, P. J., & Boyd, R. (2000). Evolution: The Darwinian theory of social change: an homage to Donald T. Campbell. Paradigms of Social Change: Modernization, Development, Transformation, Evolution, pp. 1-30. http://www.des.ucdavis.edu/faculty/richerson/evolutionberlin.pdf

Richerson, P. J., Boyd, R., & Henrich, J. (2010). Gene-culture coevolution in the age of genomics. Proceedings of the National Academy of Sciences, 107(Supplement 2), 8985-8992. doi: 10.1073/pnas.0914631107

Schenk, M., Schwartz, A. G., O’Neal, E., Kinnard, M., Greenson, J. K., Fryzek, J. P., … & Garabrant, D. H. (2001). Familial risk of pancreatic cancer. Journal of the National Cancer Institute93(8), 640-644. http://dx.doi.org/10.1093/jnci/93.8.640

Yachida, S., & Iacobuzio-Donahue, C. A. (2013). Evolution and dynamics of pancreatic cancer progression. Oncogene32(45), 5253-5260. doi: 10.1038/onc.2013.29

Indoor Tanning and Melanoma: A Public Health Issue

Indoor TanningIndoor Tanning and Melanoma: A Public Health Issue

Ulysses Labilles and Jennifer Beito

In Minnesota and other parts of the U.S., increase melanoma continue to be common among women than men younger than 50 years. Lazovich et al. (2016) highlighted the gap between age- and the sex-specific association studies between indoor tanning and melanoma. It was found that the strongest correlation between indoor tanning and melanoma is the anatomic site, commonly developed on the trunk in women. Lazovich et al. (2016) stated that while not as strong as for women, 2-fold increase among men who tanned indoors was found to have a higher risk of developing melanomas of the trunk. Furthermore, the findings in this 2016 study are “consistent with the divergent pathway hypothesis for melanoma, which suggest that intermittent solar ultraviolet radiation exposure among those with many nevi, in contrast to chronic solar ultraviolet radiation exposure in persons with fewer nevi, induce the development of the lesion at a younger age, with tumors developing on anatomic sites typically protected from the sun” (Lazovich et al., 2016). Whereas Lazovich et al. (2016) found considerable variation in the correlation between indoor tanning and melanoma by anatomic site, confirming indoor tanning as a possible predictor, responsible for the increased among younger women. Given the timing of increased risk among women indoor tanning users, it is expected for the melanoma epidemic to continue unless indoor tanning is restricted and reduced (Lazovich et al., 2016).

Background

The field of melanoma genetics with new platforms to investigate, makes this area epidemiology move at a high pace. According to Ribero, Glass and Bataille (2016), genes involved in the cell cycle and senescence, identified in the genome-wide association studies over the last ten years, explains the development of the lesion, in addition to telomere biology that further links to reduced senescence. In this study, the role of clinicians was highlighted in recognizing the phenotypic, environmental, and familial risk factors for melanoma to identify those patients at risk who require screening and long-term follow-up (Ribero et al., 2016, p. 338). In this country, skin cancer is the most commonly diagnosed cancer and increasingly becoming a major public health problem with more than 60,000 melanomas diagnosed in 2010 (Rogers et al. 2015; Guy et al. 2015). The potential causality for increased melanoma incidence was discussed by  Rivera, Han, and Qureshi (2013), traced to the 1980 obbligato explosion in indoor tanning. It is, therefore, essential for continued investigation from scientists, professional societies and legislators (Rivera et al., 2013). Using REP resources aggregated from residents of Olmsted County, Minnesota between 1970 and 2009, 256 young adults their first lifetime diagnosis of melanoma, between the ages of 18 and 39 years of age (Reed et al. (2012). The study confirms the arguments of Bleyer et al. (2006) that “the incidence of cutaneous melanoma is increasing among young adults, with this rate increasing more than 6-fold among adult men than women, but incidence are reversed among young adults and adolescents, with the female-male incidence ratio of 1.8 in young adults aged 20 to 24 years.” (Reed et al., 2012, p. 331) Reed et al. (2012) noted that the results of studies from the Rochester Epidemiology Project (REP) might be explained by some sex-specific behaviors such the increase likelihood of young women to participate to different UV light exposure than young men. While De Giorgi et al. (2012) stated that only minimal changes in mortality had been observed, there is a continuous increase in melanoma incidence worldwide. De Giorgi et al. (2012) supported the argument that indoor tanning may have been responsible for increased melanoma incidence in women and younger tanning bed users with higher estimated risk ratio in the general population. Debates over reducing indoor tanning tend to dominate discussions for its potential to reduce melanoma incidence, mortality, and treatment costs, the findings of the 2016 study of Guy et al. underscored the increased economic benefits and quantified the significance of continued efforts to reduce indoor tanning in preventing melanoma. Using a Markov model to estimate the expected number of melanoma cases,  lives and treatment costs saved, Guy et al. (2016) estimated 61,839 melanoma cases, prevent 6735 melanoma deaths, saving $342.9 million in treatment costs over the lifetime of the 61.2 million youth age 14 years or younger in the U.S. by restricting the use of  indoor tanning among minors younger than 18 years (Acscan.org, n.d.).

Discussion. Melanoma remains a public health issue, despite efforts to reduce indoor tanning, making melanoma incidence to rise continuously in the U.S. and globally, over and above-attempted prevention efforts (Le Clair, & Cockburn, 2016). The increased risk of malignant melanoma and other forms of skin cancer are found to be correlated with the ultraviolet radiation from indoor tanning device, considered to be an urgent public health issue need to adopt the Action Model to Achieve Healthy People 2020. Ultraviolet light emitted from tanning beds is classified carcinogenic by the World Health Organization International Agency for Research on Cancer (IARC) in 2009, as an interceptive response to the associated risk of exposure with the initiation of melanoma (El Ghissassi et al., 2009). Tanning beds and its carcinogen, the length of time the skin is exposed, and whether or not the skin is protected with prescribed protection such sunscreen are all the key influences contributing the increased risk. Many individuals are exposed to sunlight during their quotidian lives, and popular alfresco activities elevate a person’s chance of developing skin cancer. For example, athletes who spend countless hours training and competing in the sun, workers who need to be under the direct sun exposure all day and children who play outside for countless hours are more prone to developing skin cancer. Exposure to UV radiation during childhood plays is a major role in the future development of melanoma and non-melanoma skin conditions. Many studies have determined that even short, intermittent but excruciating exposure to sunlight during childhood and adolescence significantly increase one’s risk of developing melanoma. More than one moiety of a person’s lifetime UV exposure occurs during childhood and adolescence. If a person has a history of one or more blistering sunburns during childhood or adolescence, such exposure could put these individuals two times greater risk to developing melanoma than those who did not have such exposures (Glanz, & Wechsler, 2002). Ultraviolet radiation is divided into three wavelengths ranges, however; only two of the ranges authentically perforate our atmosphere, UVA, and UVB. Scientists initially believed that only UVB rays played a role in the formation of skin cancer. UVB light does cause deleterious transmutations in skin cell DNA. UVB rays are responsible for sunburn and many basal and squamous cell cancers (English, Canchola & Finley, 1998). However, there are no safe UV rays. UVA rays withal contribute to skin cancer. These rays could cause a deeper skin damage than UVB, emasculates the skin’s immune system and increases the peril of cancer development, especially melanoma. Tanning lamps and tanning beds distribute high doses of UVA, which makes them especially hazardous (Goldstein & Goldstein, 2001). A 2002 Dartmouth study as noted by Goldstein and Goldstein (2001) showed tanning bed users had 2.5 times the peril of SCC and 1.5 times the jeopardy for BCC. Individuals more predisposed than others to the damaging effects of UV radiation could develop skin cancers. The increased risk of melanoma is shown to be higher among individual with family history. Melanoma and other types of skin cancer, risk factors include light or fair skin color, natural blond or red hair, sun sensitivity, immune suppression disease, vocation and geographic location (Goldstein & Goldstein, 2001).

Cases ascertained by a population-based, statewide cancer registry known as the Minnesota Cancer Surveillance System Skin Health Study and approved by the Institutional Review Board at the University of Minnesota, Lazovich et al. (2010) addressed the limitations on past studies in adjusting sun exposure and dose response of individuals using indoor tanning. Individuals diagnosed with any histologic type of melanoma between July 2004 and December 2007, between the ages of 25 and 59 was collected based on state driver’s license or state identification card. Previous studies show that indoor tanning use decreases with age. Therefore, the researchers truncated the age limit to 59 years old. Multiple regression was performed, and adjusted odd ratios show the likelihood of melanoma among users of indoor tanning, and never users were similarly elevated regardless of the age when indoor tanning began (Lazovich et al., 2010). The study of Lazovich et al. (2010) has several significant findings: “First, melanoma was found to be more frequent among indoor tanners compared with persons that never engaged in this activity. Second, measured by total hours, sessions, or years, a strong dose-response relationship was found between melanoma risk. Lastly, an increased risk of melanoma was found with the use of each type of tanning device examined as well as with each period of tanning use, suggesting that no device could be considered safe. Burns from indoor tanning seemed to be fairly common and conferred a similar risk of melanoma to sunburns, strengthening the associations explored significant even after adjusting for the potential confounding effects of known risk factors for melanoma.” (pp. OF9-OF10) Le Clair and Cockburn (2016) asserted the importance of prevention through doctor’s consultation, focusing on the significant impact of behavioral change than written intervention. The findings of this study suggest that knowledge of sun sensitivity in individuals with high UVR sensitivity may reinforce a positive outcome in sun exposure habits, and could represent a useful tool for reducing indoor tanning (Le Clair, & Cockburn, 2016, p.142). Spending an abundance of time alfresco for work or recreation without protective apparel and sunscreen increases the risk to develop skin cancers.  However, no matter what treatment you may cull; the primary cause is something which is kenned and avoidable – natural and artificial UV rays. As a result, the 2 primary aversion methods are simple to recollect, edify and implement – they are endeavored and proven (Goldstein & Goldstein, 2001): “Significantly limit exposure to the sun between the hours of 10 am and 4 pm, utilizing a sunscreen with an SPF of 15 or higher at all times each day, cover your skin with apparel, wear a hat and use sunglasses. Second, verbally express “no” to all other sources of UV radiation such as tanning beds and tanning lamps. Ergo, the next time you visually perceive someone exiting the tanning salon, relaxing midday in the direct sun at the beach or ambulating around with a flamboyantly discernible tan, do not be envious. Instead, view this person as you would a person smoking a cigarette. They are acting temerariously and jeopardizing their lives in an endeavor to imitate what is occasionally introduced by the media. Recollect, despite what the media may lead you to believe; you do not require a tan to look good. During the 2012 meeting by the Centers for Disease Control and Prevention (CDC), it was concluded that future cases of skin cancer could be prevented, along with the associated morbidity, mortality, and healthcare costs through discussion of research gaps and current body of evidence on strategies to reduce indoor. The overarching goals of Healthy People 2020 should be the framework of existing and future studies embracing the state of the evidence on strategies to reduce indoor tanning; the tools necessary to adequately assess, monitor, and evaluate the short- and long-term impact of interventions designed to reduce indoor tanning; and strategies to align efforts at the national, state, and local levels through transdisciplinary collaboration and coordination across multiple sectors (Holman et al., 2013).

Conclusion. The participation of health care providers is required for information dissemination as well as physical and psychological screenings to improve education to address the misconception about tanning safety. According to Friedman et al. (2105) “Public perception of the purported health benefits of indoor tanning can be blamed for the popularity of tanning salons as a desire to prepare the skin before sun exposure, the most commonly cited motivations for indoor tanning.” improve education to address the misconception about tanning safety. Artificial UVR is often misconceived to produce a “safer” tan than outdoor sunlight (CDC, 2014). Le Clair, & Cockburn (2016) argued that this belief is  “contradicted by scientific evidence, and must be addressed to effectively reduce the burden of indoor tanning on health outcomes worldwide.” (p. 140) According to Whitmore et al. (2001), Karagas et al. (2002), and Green et al. (2007), DNA damage in skin cells caused by exposure to indoor tanning UVR is associated with an increased risk of melanoma induction and other types of non-melanoma skin cancers. In-depth understanding of clinicians providing public health education outreach programs is critical from the epidemiology of melanoma to the increased risk of the developing tumors with the frequent use or use of tanning beds. Lobbying efforts such as the Indoor Tanning Association are the most significant barrier to state indoor tanning legislation (Obayan et al., 2010). The risk and benefits of indoor tanning was discussed during the 2012 report of the minority staff of the House Committee on Energy and Commerce, asserted that 80 % of tanning salons told investigators that indoor tanning was beneficial to fair-skinned teenage girls, while 90 % of tanning salons denied that sunlamp use posed any health risks to this vulnerable group (Gottlieb et al., 2015). Such argument not supported by peer-reviewed study should always be challenged, and leaders both political, healthcare and public health should continue to cooperate in drafting evidence-based legislations to ease the economic and individual burden of melanoma induced by indoor tanning. It is paramount to increase the height of prevention efforts, not only limiting the use of tanning beds to children aged 18 or younger, but also to young adults over 18 years old who have increased the risk to melanoma. The transdisciplinary, multilevel, and coordinated approach has the potential to combat future cases melanoma and other forms of skin cancers by reducing indoor tanning, withal many barriers and challenges. While the role of new common sense legislation in tandem with public education campaigns is paramount, mass media campaigns are critical in introducing strategies and highlighting shared environmental risk, as well as the avoidable risk of indoor tanning use. Holman et al. (2013) posit that by reducing indoor tanning use, future cases of skin cancer could be prevented through tailored interventions following the context of comprehensive skin cancer prevention that promotes sun protection and sunburn avoidance when outdoors (Coups, Manne & Heckman,2008). Addressing contextual factors that promote tanning, including environmental and systems changes, social norms, the indoor tanning industry and the media will be dependent upon close coordination and collaboration of key partner across multiple levels. Continued literature must be encouraged among legislators, clinicians, and public health leaders, spreading its highlights through effective mass media outreach.

References

Bleyer, A., O’Leary, M., Barr, R., & Ries, L. A. G. (2006). NIH Publication No 06-5767. Bethesda, MD: National Cancer Institute. Cancer epidemiology in older adolescents and young adults, 15, 1975-2000.

Coups, E. J., Manne, S. L., & Heckman, C. J. (2008). Multiple skin cancer risk behaviors in the US population. American journal of preventive medicine, 34(2), 87-93.

CDC (2014). The Burning Truth. Retrieved from http://www.cdc.gov/cancer/skin/burningtruth/index.htm (2014)

El Ghissassi, F., Baan, R., Straif, K., Grosse, Y., Secretan, B., Bouvard, V., … & Cogliano, V. (2009). A review of human carcinogens—part D: radiation. The lancet oncology, 10(8), 751-752.

English 3rd, J. C., Canchola, D. R., & Finley, E. M. (1998). Axillary basal cell carcinoma: a need for full cutaneous examination. American family physician, 57(8), 1860-1864.

De Giorgi, V., Gori, A., Grazzini, M., Rossari, S., Oranges, T., Longo, A. S., … & Gandini, S. (2012). Epidemiology of melanoma: is it still epidemic? What is the role of the sun, sunbeds, Vit D, betablocks, and others?. Dermatologic Therapy, 25(5), 392-396.

Faculty Expertise in Cancer – School of Public Health. (n.d.). Retrieved from http://sph.umn.edu/faculty1/expertise/cancer/name/deann-lazovich/

Friedman, B., English, J. C., & Ferris, L. K. (2015). Indoor tanning, skin cancer, and the young female patient: a review of the literature. Journal of pediatric and adolescent gynecology, 28(4), 275-283.

Glanz, K., Saraiya, M., & Wechsler, H. (2002). Guidelines for school programs to prevent skin cancer. MMWR. Recommendations and reports: Morbidity and mortality weekly report. Recommendations and reports/Centers for Disease Control, 51(RR-4), 1-18.

Goldstein, B. G., & Goldstein, A. O. (2001). Diagnosis and management of malignant melanoma. American family physician, 63(7), 1359-68.

Gottlieb, M., Balk, S. J., Geller, A. C., & Gershenwald, J. E. (2015). Teens and Indoor Tanning: Time to Act on the US Food and Drug Administration’s Black-Box Warning. Annals of surgical oncology, 22(3), 701-703.

Green, A., Autier, P., Boniol, M., Boyle, P., Doré, J. F., Gandini, S., … & Westerdahl, J. (2007). The association of use of sunbeds with cutaneous malignant melanoma and other skin cancers. International Journal of Cancer120(5), 1116-1122.

Guy, G. P., Machlin, S. R., Ekwueme, D. U., & Yabroff, K. R. (2015). Prevalence and Costs of Skin Cancer Treatment in the US, 2002− 2006 and 2007− 2011. American journal of preventive medicine, 48(2), 183-187.

Guy, G. P., Zhang, Y., Ekwueme, D. U., Rim, S. H., & Watson, M. (2016). The potential impact of reducing indoor tanning on melanoma prevention and treatment costs in the United States: An economic analysis. Journal of the American Academy of Dermatology.

Holman, D. M., Fox, K. A., Glenn, J. D., Guy, G. P., Watson, M., Baker, K., … & Sampson, B. P. (2013). Strategies to reduce indoor tanning: current research gaps and future opportunities for prevention. American journal of preventive medicine, 44(6), 672-681.

Increasing Incidence of Melanoma Among Young Adults: An … (n.d.). Retrieved from http://www.sciencedirect.com/science/article/pii/S0025619612002091

Indoor tanning for kids? Might as well expose them to … (n.d.). Retrieved from https://acscan.org/news/indoor-tanning-kids-might-well-expose-them-plutonium

Karagas, M. R., Stannard, V. A., Mott, L. A., Slattery, M. J., Spencer, S. K., & Weinstock, M. A. (2002). Use of tanning devices and risk of basal cell and squamous cell skin cancers. Journal of the National Cancer Institute94(3), 224-226.

Lazovich, D., Vogel, R. I., Berwick, M., Weinstock, M. A., Anderson, K. E., & Warshaw, E. M. (2010). Indoor tanning and risk of melanoma: a case-control study in a highly exposed population. Cancer Epidemiology and Prevention Biomarkers, 1055-9965.

Lazovich, D., Vogel, R. I., Weinstock, M. A., Nelson, H. H., Ahmed, R. L., & Berwick, M. (2016). Association between indoor tanning and melanoma in younger men and women. JAMA Dermatology, 152(3), 268-275.

Le Clair, M. Z., & Cockburn, M. G. (2016). Tanning bed use and melanoma: Establishing risk and improving prevention interventions. Preventive Medicine Reports, 3, 139-144.

Obayan, B., Geller, A. C., Resnick, E. A., & Demierre, M. F. (2010). Enacting legislation to restrict youth access to tanning beds: A survey of advocates and sponsoring legislators. Journal of the American Academy of Dermatology63(1), 63-70.

Position Statement on Indoor Tanning (Approved by the … (n.d.). Retrieved from https://www.aad.org/Forms/Policies/Uploads/PS/PS-Indoor%20Tanning.pdf

Reed, K. B., Brewer, J. D., Lohse, C. M., Bringe, K. E., Pruitt, C. N., & Gibson, L. E. (2012). Increasing incidence of melanoma among young adults: an epidemiological study in Olmsted County, Minnesota. In Mayo Clinic Proceedings (Vol. 87, No. 4, pp. 328-334). Elsevier.

Ribero, S., Glass, D., & Bataille, V. (2016). Genetic epidemiology of melanoma. European Journal of Dermatology, 26(4), 335-339.

Rivera, A. R., Han, J., & Qureshi, A. A. (2013). Has too much blame been placed on tanning beds for the rise in melanoma diagnosis?. Expert Review of Dermatology, 8(2), 135-143.

Rogers, H. W., Weinstock, M. A., Feldman, S. R., & Coldiron, B. M. (2015). Incidence estimate of nonmelanoma skin cancer (keratinocyte carcinomas) in the US population, 2012. JAMA Dermatology151(10), 1081-1086.

US House of Representatives Committee on Energy and Commerce (2012). A new report reveals indoor tanning industry’s false and

misleading practices. Retrieved from HTTP://

democrats.energycommerce.house.gov/index.php?q=news/newreport-reveals-indoor-tanning-industry-s-false-and-misleadingpractices.

Whitmore, S. E., Morison, W. L., & Potten, C. S. (2001). Tanning salon exposure and molecular alterations. Journal of the American Academy of Dermatology44(5), 775-780.

“In our fight against cancer—we must be unwilling to postpone—for the loved ones we’ve lost and the ones we can save.”

The Silent Killer: Improving the Understanding of Chagas Disease

Chagas Disease

The protozoan parasite Trypanosoma cruzi was first described by Carlos Chagas after isolation of the organism from the blood of a Brazilian patient in 1909 (Garcia et al., 2015). An estimated 7.5 to 10 million persons are infected with Chagas disease worldwide (Hotez et al., 2008; Hotez et al., 2014). In the United States, the disease is anecdotally referred to as a “silent killer” with a 30% chance of those infected to develop a potentially fatal cardiac disease. According to Cantey et al. (2012), Chagas disease is emerging as a significant public health concern in the United States. Given the proximity of Texas to Latin America, cases imported from highly endemic areas in Latin America would likely occur in Texas. Recent communication from the Centers for Disease Control and Prevention that the bite of blood-sucking triatomine bugs in the subfamily Triatominae also termed “kissing bugs” that transfers the parasites to humans have now been found in 28 states, including California and Pennsylvania. Garcia et al. (2015) argued that despite the numerous publications related to Chagas disease in the southern US and northern regions of Mexico, very little is known about the disease burden from imported and locally acquired T. cruzi infection.There is concern that Chagas disease might be undiagnosed in the US as a result of documented low physician awareness (Stimpert & Montgomery, 2010). While the zoonotic nature of Chagas’ life cycle implies unfeasible eradication; entomological surveillance is and will remain crucial to containing Chagas disease transmission (Tarleton et al., 2007).

While it is considered safe to breastfeed even if the mother has Chagas disease (Centers for disease control and prevention, 2013); people can also become infected through blood transfusion, congenital transmission (from a pregnant woman to her baby), organ transplantation, accidental laboratory exposure and consumption of uncooked food contaminated with feces from infected bugs. If the mother has cracked nipples or blood in the breast milk, it is warranted to pump and discard the milk until the bleeding resolves and the nipples heal  (Centers for disease control and prevention, 2013). The enduring challenge of household reinfestation by locally native vectors as stated by Abad-Franch et al. (2011), horizontal strategies works better when the community takes on a protagonist role. Encouraging vector notification by residents and other simple forms of participation can substantially enhance the effectiveness of surveillance (Abad-Franch et al., 2011). Therefore, control programs in concert with community-based approaches as a strategic asset from inception that requires a timely, professional response to every notification, benefiting from a strengthened focus on community empowerment. According to Schofield (1978), when bug population density is low, vector detection failures are unavoidable. Decision-making will be dependent upon the accurate estimation of infestation rates (World Health Organization, 2002), and imperfect detection can seriously misguide Chagas disease control management program. Continued attentiveness from governmental and health organizations are warranted, as this disease continue to be a globalized public health issue. Improved diagnostic tools, expanded surveillance and increased research funding will be required in maintaining existing effective public health strategies and in preventing the spread of the disease to new areas and populations (Bonney, 2014). To improve outbreak control, and improve Chagas disease response, it is essential to discuss the gaps in the scientific knowledge of the disease. Moreover,  crucial in improving the morbidity in the state of Texas and neighboring states is the recommendation of the needed steps to enhance the understanding of T. cruzi.

References

Abad-Franch, F., Vega, M. C., Rolón, M. S., Santos, W. S., & de Arias, A. R. (2011). Community participation in Chagas disease vector surveillance: systematic review. PLoS Negl Trop Dis, 5(6), e1207.

Bonney, K. M. (2014). Chagas disease in the 21st century: a public health success or an emerging threat?. Parasite, 21, 11.

Cantey, P. T., Stramer, S. L., Townsend, R. L., Kamel, H., Ofafa, K., Todd, C. W., … & Hall, C. (2012). The United States Trypanosoma cruzi Infection Study: evidence for vector‐borne transmission of the parasite that causes Chagas disease among United States blood donors. Transfusion, 52(9), 1922-1930.

Centers for disease control and prevention. (2013). Parasites-American Trypanosomiasis (also known as Chagas Disease). Retrieved 21 July, 2016, from http://www.cdc.gov/parasites/chagas/gen_info/detailed.html

Garcia, M. N., Woc-Colburn, L., Aguilar, D., Hotez, P. J., & Murray, K. O. (2015). Historical perspectives on the epidemiology of human chagas disease in Texas and recommendations for enhanced understanding of clinical chagas disease in the Southern United States. PLOS Negl Trop Dis, 9(11), e0003981.

Hotez, P. J., Bottazzi, M. E., Franco-Paredes, C., Ault, S. K., & Periago, M. R. (2008). The neglected tropical diseases of Latin America and the Caribbean: a review of disease burden and distribution and a roadmap for control and elimination. PLoS Negl Trop Dis, 2(9), e300.

Hotez, P. J., Alvarado, M., Basáñez, M. G., Bolliger, I., Bourne, R., Boussinesq, M., … & Carabin, H. (2014). The global burden of disease study 2010: interpretation and implications for the neglected tropical diseases. PLoS Negl Trop Dis, 8(7), e2865.

Schofield, C. J. (1978). A comparison of sampling techniques for domestic populations of Triatominae. Transactions of the Royal Society of Tropical Medicine and Hygiene, 72(5), 449-455.

Stimpert, K. K., & Montgomery, S. P. (2010). Physician awareness of Chagas disease, USA. Emerging infectious diseases, 16(5), 871.

Tarleton, R. L., Reithinger, R., Urbina, J. A., Kitron, U., & Gürtler, R. E. (2007). The challenges of Chagas disease—Grim outlook or glimmer of hope?. PLoS Med, 4(12), e332.

World Health Organization. (2002). Control of Chagas disease: second report of the WHO expert committee.

Ethical Concepts of the New Public Health

I am currently working on two essays that I needed to submit with my fellowship application, but the event in Paris made me stop for a few minutes and reflect on the scorching reminder that terrorism has no religion, a brand of madness, not faith. Such event amplified the urgency to stress the significance of New Public Health that carries a high potential for healthy less aggressive societies.  The main principles of living together in healthy communities were summarized by Laaser et al. (2002) as four ethical concepts of the New Public Health essential to violence reduction – equity, participation, subsidiarity, and sustainability. The coupling of current economic, demographic, and social issues will play a role in guiding future policy revisions. While my fellowship of interest is in epidemiology and infectious diseases, increased understanding of the interrelated dimensions of deracination or forced migration using the modern concept of public health is warranted. It is critical to understand the determinants of violence: the type of stigmatization; the process of urbanization; religious, ethnic, and racial prejudices; women’s status; the level of education; employment status; socialization of the family; availability of firearms;  alcohol and drug consumption;  and poverty.

Reference

Laaser, U., Donev, D., Bjegovic, V., & Sarolli, Y. (2002). Public health and peace. Croatian medical journal, 43(2), 107-113.

A Promise to a Dying Brother

When I was inducted into the Honor Society in winter 2013, I thought that being on top of my batch will be enough to get me through my journey as a Public Health Ph.D. candidate. Recruiting a dissertation chair is the most challenging so far, especially getting a response from them. What if I do not get a dissertation chair who will be a good match with my dissertation topic? Can I submit my premise and finish my dissertation to another university? A night before my youngest brother passed away; I was on the phone with him. He told me that he is too tired, and I responded that it is okay to let go. He asked me to promise him to go back to school and take on a graduate degree to make a difference. “Promise me that at some point to be involved in a research project that could make a difference to individuals diagnosed with pancreatic cancer.” He passed away in 2007, a few weeks before his 40th birthday, and three months before his only daughter’s first birthday.

Focusing on the impact of cigarette smoking as a factor that promotes pancreatic cancer rather than initiates it will amplify the importance of behavioral change, and enhance the quality of life. The outcome of pancreatic cancer remains dismal, even with treatment combinations of surgery, radiotherapy and chemotherapy with an estimated annual economic burden of $4.9 billion annually (Pandol, Apte, Wilson, Gukovskaya, and Edderkaoui, 2012). Advances in patient management and understanding the biology of pancreatic cancer has taken substantial progress over the years. Herman, Schulick, Hruban and Goggins (2011) found that screening first-degree relatives of individuals with family members affected by pancreatic cancer can identify non-invasive precursors of the disease. In this 2011 study shows the gradual rise in the incidence and number of deaths caused by pancreatic tumors, even with the decline in incidence and mortality of other common cancers. Furthermore, Vincent et al. found that despite developments in detection and management of pancreatic cancer, only about 4% of patients will live five years after diagnosis. Moreover, Vincent et al. (2011) found that present surgical resectioning offers the only chance of cure and improve the survival rate for those with malignant disease localized to the pancreas. Statistical analysis in 2012 study shows 80–85% of patients with advanced unresectable disease responds poorly to most chemotherapeutic agents. Therefore, it is warranted to have continued understanding of the biological mechanisms contributory to the development and progression of pancreatic tumors. On the other hand, Klein et al. (2004) emphasized the significance of quantification of the risk of individuals with a family history of pancreatic cancer as a rational basis for cancer risk screening and counseling. In a prospective registry-based approach of this 2004 study, the risk of these individuals showed an increased risk of developing the disease. Klein et al. (2004) performed standardized incidence ratios and compared the number of incident pancreatic cancers observed with those expected using Surveillance, Epidemiology and End Results (SEER) rates. It was quantified in this registry-based study the pancreatic cancer risk in kindreds with a family member who was diagnosed with the disease, supporting the hypothesis of increased risk in association with family history. While Blackford et al. (2009) failed to identify the signature tobacco-related mutation in cigarette smokers that could have strong implication to the development of pancreatic cancer; this 2009 study found the nonspecific DNA damage caused by tobacco carcinogens. Furthermore, the combined causality of non-tobacco-related mutagenic risk factors such as inherited predisposition to cancer may share mutagenic properties with the tobacco mutagens active in pancreatic tissues (Ding et al., 2008; Prokopczyk et al., 2002). The types and patterns of these mutations provide insight into the mechanisms by which cigarette smoking causes pancreatic cancer (Blackford et al., 2009). Porta et al. (2009) and Blackford et al. (2009) suggested that smoking enhances the risk for pancreatic cancer through mechanisms other than genetic mutation. The development of pancreatic cancer may have a non-significant association to pipe smoking and smokeless tobacco use, but in a large collaborative pooled analysis of non-cigarette tobacco use in 11 studies within the International Pancreatic Cancer Case-Control Consortium (PanC4) found that cigar smoking is associated with an excess risk of the disease (Bertuccio et al., 2011). Cigarette smoking was found to be an established risk factors— both exposure to environmental tobacco smoke (ETS), and active cigarette smoking (Vrieling et al., 2010). Over 40,000 individuals are diagnosed with pancreatic cancer, and less than 5% of patients diagnosed has a survival rate of five years. The component of the smoke of cigarettes that produced in the body as a metabolite of nicotine and the most abundant carcinogens in tobacco smoke is 4-(methyl nitrosamine)-1-(3-pyridyl)-1-butanone (NNK). Vary widely in nicotine content and carcinogenic nicotine metabolites, cigarettes, cigars, and other tobacco products—nicotine reaches the lungs and is quickly absorbed into the bloodstream during smoking. A cigar containing as many as 20 grams of tobacco can have nicotine between 5.9 and 335.2 mg per gram of tobacco (Henningfield, Fant, Radzius, & Frost, 1999). Prokopczyk et al. (2002) noted that the nicotine levels in pancreatic juice in smokers is seven times higher than non-smokers. Blackford et al. (2009) concluded that smokers diagnosed with pancreatic carcinomas harbors more mutations than the non-smoker, therefore, doubles the risk, accounting for 20 to 25% of pancreatic cancers.

Pandol et al. (2012) stated that the pro-carcinogenic effects of smoking on the pancreas are inadequately studied, confirming that tobacco smoking is the strongest avoidable risk and the major environmental factor for pancreatic cancer. Pandol et al. provided valuable insights into the pathogenesis of pancreatic cancer, particularly in the initiation and progression of the disease. Determining the mechanisms underlying the effect of smoking compounds on fibrosis and inflammation will improve our limited knowledge of pancreatic biology. Pancreatic cancer can be classified as genetic, environmental, or both; as well as a disease caused by inherited DNA mutation or mutation by chance. While advances in Genomics gives the promise to early pancreatic cancer detection through better understanding of pancreatic biology, it is paramount to embrace the significance of lifestyle habits that can be modified to evidence-based healthier concepts that translates to reduced cancer risk. Applying lessons learned from the outcome of my proposed study, and existing body of knowledge will prevent the emergence of pancreatic cancer, reduce cancer risk and advance population health. Early behavioral change and interventions will improve the survival rate and quality of life during the time course of pancreatic cancer progression.

References

Bayraktar, S., Bayraktar, U. D., & Rocha-Lima, C. M. (2010). Recent developments in palliative chemotherapy for locally advanced and metastatic pancreas cancer. World journal of gastroenterology: WJG16(6), 673.

Bertuccio, P., La Vecchia, C., Silverman, D. T., Petersen, G. M., Bracci, P. M., Negri, E., … & Boffetta, P. (2011). Cigar and pipe smoking, smokeless tobacco use and pancreatic cancer: an analysis from the International Pancreatic Cancer Case-Control Consortium (PanC4). Annals of Oncology, mdq613.

Blackford, A., Parmigiani, G., Kensler, T. W., Wolfgang, C., Jones, S., Zhang, X., … & Hruban, R. H. (2009). Genetic mutations associated with cigarette smoking in pancreatic cancer. Cancer research69(8), 3681-3688.

Bosetti, C., Lucenteforte, E., Silverman, D. T., Petersen, G., Bracci, P. M., Ji, B. T., … & La Vecchia, C. (2012). Cigarette smoking and pancreatic cancer: an analysis from the International Pancreatic Cancer Case-Control Consortium (Panc4). Annals of oncology23(7), 1880-1888.

Bouvier, A. M., David, M., Jooste, V., Chauvenet, M., Lepage, C., & Faivre, J. (2010). Rising incidence of pancreatic cancer in France. Pancreas39(8), 1243-1246.

Breslow, N. E., Day, N. E., & Davis, W. (1980). The analysis of case-control studies. International Agency for Research on Cancer.

Chowdhury, P., Chang, L. W., & Rayford, P. L. (1993). Tissue distribution of [3H]-nicotine in rats. Biomedical and environmental sciences: BES6(1), 59-64.

Chowdhury, P., Doi, R., Tangoku, A., & Rayford, P. L. (1995). Structural and functional changes of rat exocrine pancreas exposed to nicotine. International journal of pancreatology, 18(3), 257-264.

Colby, S. M., Clark, M. A., Rogers, M. L., Ramsey, S., Graham, A. L., Boergers, J., … & Abrams, D. B. (2012). Development and reliability of the lifetime interview on smoking trajectories. Nicotine & Tobacco Research14(3), 290-298.

Colditz, G. A., Wolin, K. Y., & Gehlert, S. (2012). Applying what we know to accelerate cancer prevention. Science translational medicine4(127), 127rv4-127rv4.

DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled clinical trials7(3), 177-188.

Ding, L., Getz, G., Wheeler, D. A., Mardis, E. R., McLellan, M. D., Cibulskis, K., … & Sawyer, C. S. (2008). Somatic mutations affect key pathways in lung adenocarcinoma. Nature, 455(7216), 1069-1075. Chicago.

Edderkaoui, M., Park, C., Lee, I., Nitsche, C., Gerloff, A., Grippo, P. J., … & Gukovskaya, A. S. (2011, November). Novel model of pancreatic neoplastic lesions induced by smoking compound NNK. In Pancreas (Vol. 40, No. 8, pp. 1321-1321). 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA: LIPPINCOTT WILLIAMS & WILKINS.

Feuer, E. J., & Wun, L. M. DEVCAN: probability of developing or dying of cancer software, version 4.1.[internet]. Bethesda (MD): National Cancer Institute (NCI); 1999 [accessed 2002 May 28].[1 p].

Gould, G. S., Watt, K., Cadet-James, Y., & Clough, A. R. (2015). Using the risk behaviour diagnosis scale to understand Australian Aboriginal smoking—a cross-sectional validation survey in regional New South Wales. Preventive Medicine Reports2, 4-9.

Greenland, S. (1987). Quantitative methods in the review of epidemiologic literature. Epidemiologic reviews9(1), 1-30.

Henningfield, J. E., Fant, R. V., Radzius, A., & Frost, S. (1999). Nicotine concentration, smoke pH and whole tobacco aqueous pH of some cigar brands and types popular in the United States. Nicotine & Tobacco Research1(2), 163-168.

Hoffmann, D., Hoffmann, I., & El-Bayoumy, K. (2001). The less harmful cigarette: a controversial issue. A tribute to Ernst L. Wynder. Chemical research in toxicology14(7), 767-790.

Hruban, R. H., Iacobuzio-Donahue, C., Wilentz, R. E., Goggins, M., & Kern, S. E. (2000). Molecular pathology of pancreatic cancer. Cancer journal (Sudbury, Mass.)7(4), 251-258.

Institute for Health Metrics and Evaluation. (2015). US County Profile: Dallas County, Texas. 2301 Fifth Ave., Suite 600 Seattle, WA 98121 USA.

Jiao, L., Mitrou, P. N., Reedy, J., Graubard, B. I., Hollenbeck, A. R., Schatzkin, A., & Stolzenberg-Solomon, R. (2009). A combined healthy lifestyle score and risk of pancreatic cancer in a large cohort study. Archives of internal medicine, 169(8), 764-770.

Kadam, P., & Bhalerao, S. (2010). Sample size calculation. International journal of Ayurveda research1(1), 55.

Kirby, A., Gebski, V., & Keech, A. C. (2002). Determining the sample size in a clinical trial. Medical journal of Australia177(5), 256-257.

Klein, A. P., Brune, K. A., Petersen, G. M., Goggins, M., Tersmette, A. C., Offerhaus, G. J. A., … & Hruban, R. H. (2004). Prospective risk of pancreatic cancer in familial pancreatic cancer kindreds. Cancer Research, 64(7), 2634-2638. Chicago

Janghorban, R., Roudsari, R. L., & Taghipour, A. (2014). Skype interviewing: the new generation of online synchronous interview in qualitative research. International journal of qualitative studies on health and well-being9.

Labilles, U. (2015). Reevaluating the Impact of Cigarette Smoking on Pancreatic Cancer (Unpublished, Advanced Quantitative Reasoning and Analysis (RSCH – 8250H – 3), 2015 Summer Qtr. Wk11Assgn3LabillesU) Walden University, Minneapolis.

Larsson, S. C., Permert, J., Håkansson, N., Näslund, I., Bergkvist, L., & Wolk, A. (2005). Overall obesity, abdominal adiposity, diabetes and cigarette smoking in relation to the risk of pancreatic cancer in two Swedish population-based cohorts. British journal of cancer93(11), 1310-1315.

Lau, P. P., Dubick, M. A., Gloria, S. M., Morrill, P. R., & Geokas, M. C. (1990). Dynamic changes of pancreatic structure and function in rats treated chronically with nicotine. Toxicology and applied pharmacology, 104(3), 457-465.

Le Houezec, J. (2003). Role of nicotine pharmacokinetics in nicotine addiction and nicotine replacement therapy: a review. The International Journal of Tuberculosis and Lung Disease7(9), 811-819.

Lowenfels, A. B., & Maisonneuve, P. (2003). Environmental factors and risk of pancreatic cancer. Pancreatology3(1), 1-8.

Lynch, S. M., & Rebbeck, T. R. (2013). Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach. Cancer Epidemiology Biomarkers & Prevention22(4), 485-495.

Lynch, S. M., Vrieling, A., Lubin, J. H., Kraft, P., Mendelsohn, J. B., Hartge, P., … & Stolzenberg-Solomon, R. Z. (2009). Cigarette smoking and pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium. American journal of epidemiology170(4), 403-413.

Miller, T. Q. (1997). Statistical methods for describing temporal order in longitudinal research. Journal of clinical epidemiology50(10), 1155-1168.

NHIS – Adult Tobacco Use – Smoking Status Recodes. (n.d.). Retrieved from http://www.cdc.gov/nchs/nhis/tobacco/tobacco_recodes.htm

Pancreatic Expression Database. (n.d.). Retrieved from http://pancreasexpression.org/

Pandol, S. J., Apte, M. V., Wilson, J. S., Gukovskaya, A. S., & Edderkaoui, M. (2012). The burning question: why is smoking a risk factor for pancreatic cancer? Pancreatology12(4), 344-349.

Philip, P. A. (2008). Targeted therapies for pancreatic cancer. Gastrointestinal cancer research: GCR2(4 Suppl 2), S16.

Prokopczyk, B., Hoffmann, D., Bologna, M., Cunningham, A. J., Trushin, N., Akerkar, S., … & El-Bayoumy, K. (2002). Identification of tobacco-derived compounds in human pancreatic juice. Chemical research in toxicology, 15(5), 677-685. Chicago.

Porta, M., Crous-Bou, M., Wark, P. A., Vineis, P., Real, F. X., Malats, N., & Kampman, E. (2009). Cigarette smoking and K-ras mutations in pancreas, lung and colorectal adenocarcinomas: etiopathogenic similarities, differences and paradoxes. Mutation Research/Reviews in Mutation Research682(2), 83-93.

Prospective Ascertainment for Late Effects among Cancer … (n.d.). Retrieved from http://www.mskcc.org/cancer-care/trial/12-143

Raimondi, S., Maisonneuve, P., Löhr, J. M., & Lowenfels, A. B. (2007). Early onset pancreatic cancer: evidence of a major role for smoking and genetic factors. Cancer Epidemiology Biomarkers & Prevention16(9), 1894-1897.

Schottenfeld, D., & Fraumeni Jr, J. F. (1982). Cancer epidemiology and prevention. Eastbourne, UK; WB Saunders Co.

Silverman, D. T., Dunn, J. A., Hoover, R. N., Schiffiman, M., Lillemoe, K. D., Schoenberg, J. B., … & Pottern, L. M. (1994). Cigarette Smoking and Pancreas Cancer: a Case—Control Study Based on Direct Interviews. Journal of the National Cancer Institute86(20), 1510-1516.

Smith-Warner, S. A., Spiegelman, D., Ritz, J., Albanes, D., Beeson, W. L., Bernstein, L., … & Hunter, D. J. (2006). Methods for Pooling Results of Epidemiologic Studies the Pooling Project of Prospective Studies of Diet and Cancer. American journal of epidemiology163(11), 1053-1064.

Special Section: Pancreatic Cancer. (n.d.). Retrieved from http://www.cancer.org/acs/groups/content/@research/documents/document/acspc-0388

Thomas, J. K., Kim, M. S., Balakrishnan, L., Nanjappa, V., Raju, R., Marimuthu, A., … & Pandey, A. (2014). Pancreatic cancer database: an integrative resource for pancreatic cancer. Cancer biology & therapy15(8), 963-967.

Validation of risk assessment scales and predictors of … (n.d.). Retrieved from http://europepmc.org/articles/PMC4054635

Vincent, A., Herman, J., Schulick, R., Hruban, R. H., & Goggins, M. (2011). Pancreatic cancer. The Lancet, 378(9791), 607-620. Chicago

Vrieling, A., Bueno‐de‐Mesquita, H. B., Boshuizen, H. C., Michaud, D. S., Severinsen, M. T., Overvad, K., … & Riboli, E. (2010). Cigarette smoking, environmental tobacco smoke exposure and pancreatic cancer risk in the European Prospective Investigation into Cancer and Nutrition. International journal of cancer126(10), 2394-2403.

Wen, K. Y., & Gustafson, D. H. (2004). Needs assessment for cancer patients and their families. Health and quality of life outcomes2(1), 11.

Wilson, L. S., & Lightwood, J. M. (1999). Pancreatic cancer: total costs and utilization of health services. Journal of surgical oncology71(3), 171-181.

Witte, K. (1996). Predicting risk behaviors: Development and validation of a diagnostic scale. Journal of health communication1(4), 317-342.

Witte, K., & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public health campaigns. Health Education & Behavior27(5), 591-615.

Wittel, U. A., Pandey, K. K., Andrianifahanana, M., Johansson, S. L., Cullen, D. M., Akhter, M. P., … & Batra, S. K. (2006). Chronic pancreatic inflammation induced by environmental tobacco smoke inhalation in rats. The American journal of gastroenterology101(1), 148-159.

In Texas, Everything is Bigger: In the context of data collection—is bigger better?

The traditional researcher concept that big data equates statistical significance could always eclipse the importance of understanding the interrelationship between the effect size, power, and sample size that could translate to both practical and statistical significance. In Texas, everything is bigger, everything a Texan do is bigger, but in the context of data collection—is bigger better? Current big data opportunities facing science, technology communities, and the health community is facing a tsunami of health- and healthcare-related content generated from numerous patient care points of contact, sophisticated medical instruments, and web-based health communities (Chen, Chiang & Storey, 2012). Two primary sources of health big data are payer–provider big data (electronic health records, insurance records, pharmacy prescription, patient feedback and responses), and data from my favorite field-genomics. I cannot help to imagine how many interesting research studies I could do with genomics-driven big data (genotyping, gene expression, sequencing data). Extracting knowledge from health big data poses significant research and practical challenges, especially considering the HIPAA (Health Insurance Portability and Accountability Act) and IRB (Institutional Review Board) requirements for building a privacy-preserving and trust-worthy health infrastructure and conducting ethical health-related research (Gelfand, 2011). Setting aside these challenges, can big data provide both practical and statistical significance? Just think about terabytes of expected raw sequencing data that associate variants that affect variation in two common highly heritable measures of obesity, weight and body mass index (BMI). For this discussion, let me broach the 2012 study of Hutchinson and Wilson in improving nutrition and physical activity in the workplace. The cumulative knowledge found in the meta-analysis of Hutchinson & Wilson (2012) found the extant results of 29 intervention studies examining physical activity or nutrition interventions in the workplace, published between 1999 and March 2009. The results from these 29 intervention studies were synthesized using meta-analyses in terms of the effectiveness of workplace health promotion programs to resolve inconsistent findings. The challenge of extant results that are sometimes discordant, Hutchinson & Wilson (2012) took into consideration the limitations in the methodology of some of the studies reviewed that demonstrated modest success in achieving long-term change. The importance of interventions’ association with successful outcomes that includes behavior maintenance and generalization was also considered in this study. Weighted Cohen’s d effect sizes, percentage overlap statistics, confidence intervals and failsafe Ns were calculated. The increased prevalence of obesity and its association with increased risk for chronic diseases including cancer, diabetes, cancer and cardiovascular disease warrants the needs for innovative and efficient interventions. Green (1988), stated that the workplace is a valuable intervention site for a number of reasons including the amount of time people spend at work, access to populations that may be difficult to engage in different settings and the opportunity to utilize peer networks and employer incentives. These reasons justify the practical significance of the study. Moreover, the statistical significance was established by the methodology of Hutchinson & Wilson (2012) developing inclusion criteria of the 29 identified studies. The inclusion criteria are published studies on workplace intervention; a control group, not receiving the intervention, health, and in particular diet, nutrition or physical activity as outcome measures; and statistical information for the calculation of effect sizes, (e.g. means and standard deviations, the results of t-tests or one-way F tests).Change over time (mean and standard deviation) data were requisite to calculate effect sizes for interventions. Studies that did not provide this data, the means and standard deviations at the end of the intervention of controls and interventions groups were compared. Statistical analyses was performed such as Cohen’s d to calculate effect sizes for the difference between the intervention and control groups on each outcome measure (diet measures: fruit, vegetables, fat; physical activity measures: activity, fitness; health measures: weight, cholesterol, blood pressure, heart rate or glucose). Based on outcome measures and the form of intervention, effect sizes were aggregated. Mean effect size, standard deviation and 95% confidence interval were calculated for each grouping (Zakzanis, 2001). Fail safe Ns (Nfs) were calculated to address the potential for studies with statistically significant results. The conclusion of this 2012 meta-analysis in terms of study design—randomized controlled trials were associated with larger effects; therefore, long-term maintenance of changes should be evaluated in order to determine the extent to which workplace interventions can make sustainable changes to individuals’ health.

References

Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly36(4), 1165-1188. Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Academic press. Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press. Forthofer, R.N., Lee, E.S. & Hernandez, M. (2006). Biostatistics: A Guide to Design, Analysis and Discovery. 2nd Edition [Vital Source Bookshelf version]. Retrieved from http://online.vitalsource.com/books/9780123694928 Gelfand, A. (2011). Privacy and biomedical research: building a trust infrastructure: an exploration of data-driven and process-driven approaches to data privacy. Biomed Comput Rev2012, 23-28. Green, K. L. (1988). Issues of control and responsibility in workers’ health. Health Education & Behavior15(4), 473-486. Hutchinson, A. D., & Wilson, C. (2012). Improving nutrition and physical activity in the workplace: a meta-analysis of intervention studies. Health promotion international27(2), 238-249. Labilles, U. (2015). Big Data: Does it matter? Can it give a practical significance? Is bigger better? (Unpublished, Advanced Biostatistics (PUBH – 8500 – 1), 2015 Spring Qtr. Wk2DiscLabillesU) Walden University, Minneapolis. Thorleifsson, G., Walters, G. B., Gudbjartsson, D. F., Steinthorsdottir, V., Sulem, P., Helgadottir, A., … & Stefansson, K. (2009). Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nature genetics41(1), 18-24. Zakzanis, K. K. (2001). Statistics to tell the truth, the whole truth, and nothing but the truth: formulae, illustrative numerical examples, and heuristic interpretation of effect size analyses for neuropsychological researchers. Archives of clinical neuropsychology16(7), 653-667.

Socioeconomic Status and Public Health Financing

Health financing is the cornerstone of strategy development based on both in terms of raising resources and of ways to manage resources. It is critical to emphasize the need for greater evaluation of the distributional impact of policies and programs. Socioeconomic status could affect public health financing such as people with insurance or money, creating higher expenditures. On the other hand, medically underserved, uninsured and underinsured create greater expenses because they enter the health system at the advanced stages of diseases and in weakened conditions (Laureate Education, Inc., 2012). In addition to socioeconomic status, other social determinants that affects both average and distribution of health includes physical environment, lifestyle or behavior, working conditions, social network, family, demographics, political, legal, institutional and cultural factors. Since funding is considered as a scarce resource, it is paramount to allocate resources based on the identified gaps in care. The significance of socioeconomic data in US public health surveillance systems should be emphasized in order to monitor socio-economic gradients in health. Socioeconomic data is important in determining the allocation of resources for public health financing. Krieger et al. (2003) stated that the use of multilevel frameworks and area-based socioeconomic measures (ABSMs) for public health monitoring can potentially overcome the absence of socioeconomic data in most US public health surveillance systems. Moreover, political will is essential to bridging public health and action that will help in the development and implementation of public health policy based on scientific evidence and community participation. Epstein, Stern and Weissman (1990) found that hospitalized patients with lower socioeconomic status have longer stays and require more resources. It was suggested in this study that supplementary payments allocated to the poor merits further consideration. Strategies for more efficient provision of care for patients with low socioeconomic status can be developed at the managerial and clinical levels.

Inequality or disparity is defined as the difference in health status, inequalities in access to and quality of health care services. Additional disparities are attributed to factors such as discrimination in relation to health care system and the regulatory climate. The Institute of Medicine (IOM) found that disparities continue to dwell even when socio-demographic factors, insurance status, and clinical needs were controlled for racial and ethnic health care. Disparities dictate funding requirements for public health initiatives for the underserved populations. Furthering social justice and maximizing individual liberties will advance traditional public health goals. Socioeconomic status of communities drives the financing needs for public health initiatives; therefore, burdens of the program must be minimized and identified to reduce pre-existing social injustices. Social benefits, public health programs that stimulate dignified employment, and strengthening of communities are important benefits that should be given high consideration. Public health professionals and health department leaders may not have the capacity to implement all programs that could be beneficial to a target population or community, but advocacy is paramount to improving health. Sufficient data is critical to justify the necessity of the program. I believe that it is our duty as healthcare and public health leaders to remove from policy debates and decision-making any discriminatory procedures or unjustified limitations on personal liberties. Public policy should be based on an ethics perspective and multiple considerations.

References

Bleich, S. N., Jarlenski, M. P., Bell, C. N., & LaVeist, T. A. (2012). Health inequalities: trends, progress, and policy. Annual review of public health33, 7.

Carter-Pokras, O. & Baquet, C. (2002). What is a” health disparity”? Public health reports117(5), 426.

Epstein, A. M., Stern, R. S., & Weissman, J. S. (1990). Do the poor cost more? A multihospital study of patients’ socioeconomic status and use of hospital resources. New England Journal of Medicine322(16), 1122-1128.

Getzen, T. E. (2013). Health economics and financing (5th ed.). Hoboken, NJ: John Wiley and Sons.

Kass, N. E. (2001). An ethics framework for public health. American Journal of Public Health91(11), 1776-1782.

Krieger, N., Chen, J. T., Waterman, P. D., Rehkopf, D. H., & Subramanian, S. V. (2003). Race/ethnicity, gender, and monitoring socioeconomic gradients in health: a comparison of area-based socioeconomic measures-the public health disparities geocoding project. American journal of public health93(10), 1655-1671.

Laureate Education, Inc. (Executive Producer). (2012). Multi-media PowerPoint: Financing public health. Baltimore, MD: Author.

Palmer, N., Mueller, D. H., Gilson, L., Mills, A., & Haines, A. (2004). Health financing to promote access in low income settings—how much do we know? The Lancet364(9442), 1365-1370.

Patrick, D. L., & Erickson, P. (1993). Health status and health policy. Quality of life in health care evaluation and resource.

Shi, L., & Singh, D. A. (2011). The nation’s health (8th ed.). Sudbury, MA: Jones & Bartlett Learning.