How Do Geographical/Regional Factors Influence Breast Cancer Survival and Incidence among US Women - Free Essay Example

Sample details Pages: 9 Words: 2608 Downloads: 3 Date added: 2019/02/05 Category Medicine Essay Level High school Tags: Breast Cancer Essay Did you like this example? Background Breast Cancer is the second leading cancer among United States (US) women creating a burden of disease that demands research into etiology that can inform prevention and control (NIH National Cancer Institute, 2018). Large, population-based studies surveilling mortality and incidence data are able to identify trends and risk factors that exist among breast cancer cases in the US, and current studies have been providing greater resolution into a variety of these independent variables influencing breast cancer outcomes which makes them invaluable sources of information. While many of these studies have revealed genetic factors that are known risk factors for breast cancer, genetics often do not account for all of the observed variance in breast cancer incidence and survival. Don’t waste time! Our writers will create an original "How Do Geographical/Regional Factors Influence Breast Cancer Survival and Incidence among US Women" essay for you Create order This role of geography within the United States is especially evident given the incredible variation in the rate of new Breast Cancer cases observed in each state (CDC, 2015). In fact, research has identified many sociodemographic, environmental, and health access related risks which point to the importance of place in the story of breast cancer etiology (REFERENCES). Given that many of these place related risks, such as health access, mammographic screening, environment, etc. can be modified, understanding what factors are indicative of lower survival or increased incidence is a unique opportunity to paint a complete picture of breast cancer etiology and potentially identify opportunities for targeted evidenced-based interventions. For these reasons, considering geography and its relation to breast cancer outcomes is salient. This study seeks to summarize the existing literature on geography and its relation to breast cancer and what mediates that relationship by addressing the fol lowing question: Among US women, how do geographical/regional factors influence breast cancer survival and incidence? Methods A thorough search of the literature was performed in PubMed, search parameters were set only to include articles published within the last 5 years. Articles were included if they were: 1. Based on United States populations, 2. Directly related to geography/place and factors related to area of living, and 3. Based on incidence and mortality data. Articles were excluded if they were: 1. Based on a population in another country, 2. Were not clearly linked to geography, 3. Were exclusively studies looking at insurance and uptake (particularly among Medicare populations), and 3. Were Interventional studies as the focus of this paper is on epidemiological cross-sectional studies of population level data. The first search combined the terms â€Å"geographic*†, â€Å"breast cancer†, and â€Å"survival.† This search yielded 183 articles, of which 4 met the inclusion criteria. The next search combined the terms â€Å"geographic*†, â€Å"breast cancer†, â₠¬Å"mortality† which only yielded 82 articles, this provided 1 additional article that had not already been identified. The next search combined terms the following geographical terms one at a time â€Å"regional†, â€Å"county†, and â€Å"state† with â€Å"breast cancer†, â€Å"mortality†, â€Å"survival† and â€Å"united states† yielding 145 articles, 3 additional articles were added to the study. Multi-State Studies States: Atlanta, GA; Connecticut; Detroit, Michigan; Hawaii; Iowa; New Mexico; San Francisco-Oakland, California; Seattle, Washington; Utah; Los Angeles, California; San Jose-Monterey, California; Rural Georgia; Greater California; Kentucky; New Jersey. The study performed by Akinyemiju, Moore, Ojesina, Waterbor, and Altekruse (2016) â€Å"Racial disparities in individual breast cancer outcomes by hormone-receptor subtype, area-level socio-economic status and healthcare resources† explores the effect of race/ethnicity, healthcare resources, socioeconomic status, and hormone-receptor subtype on breast cancer survival. Each broad category was an aggregate of proxy variables listed in Table 1. These covariates were used to perform survival analysis, for consecutive multilevel regression modeling, and to calculate odds ratios and hazards ratios for the following outcomes: 1. Stage at Diagnosis; 2. Surgical Treatment; 3. Radiation Treatment; and 4. Breast Cancer Survival. The study used data from all Surveillance, Epidemiology, and End Results database (SEER) reporting registries. Non-Hispanic Black (NH-Black) and Hispanic women tended to live in areas with lower SES as measured by greater proportion unemployed and under the fed eral poverty level and also were less likely to live in rural areas. Interestingly, NH-Black women lived in areas with greater healthcare access, on average. Despite this, racial disparities were clear and apparent—NH-Black Women had 42% higher hazards of breast cancer mortality and both NH-Black and Hispanic women were more likely to have late-stage diagnosis. While the study found that Hormone-Receptor subtype explained the greatest amount of the variance in late stage diagnosis, survival, and treatment, even when this was controlled for geographical, socio-demographic, and socio-economic covariates did have a significant influence. The strength of this study was its thorough and rigorous models that allowed for the adjustment for multiple geographical, socioeconomic, and biological covariates in order to quantify the contribution of each covariate to the observed incidence and survival. However, the results found for healthcare access lacked clear rationale given that NH-Black women had the greatest access yet the worst outcomes. This is likely because healthcare access was defined by proxies that do not explain utilization. Additionally, county-level socio-economic covariates cannot be directly linked to the individual cancer cases. SEER also lacked data on Her2 status. States: Baltimore, MD; Chicago, IL; Dallas, TX; Detroit, MI; Houston, TX; Los Angeles, CA; Memphis, TN; New York City, NY; Philadelphia, PA; Washington D.C. Sighoko, Hunt, Irizarry, Watson, Ansell, Murphy (2018) â€Å"Disparity in breast cancer mortality by age and geography in 10 racially diverse US cities† explored the disparity in breast cancer mortality utilizing age-stratified Non-Hispanic Black to Non-Hispanic White rate ratio (RR) and Mortality Risk Differences (RD). In this descriptive analysis, the authors used National Center for Health Statistics mortality data from 1999-2013. The study found an interesting distribution of disparity, revealing that though the lowest mortality burden was among the younger age groups (under 40 and 40-49), the highest disparity exists in this age group while among the older age group, specifically the 65+ age group, had the lowest disparity and the highest burden of breast cancer mortality. Between cities, the same pattern of disparity was sustained however the magnitude of disparity differed. For instance, cities in the Eastern US tended to have lower disparity in breast cancer mortality . While this study is a useful source of descriptive evidence, it only utilizes descriptive epidemiological methods to observe the Non-Hispanic Black breast cancer disparities as compared to Non-Hispanic White in large metropolitan US cities with the top 10 largest black populations. While this study reveals the disparities that exist and how they differ from city to city, the study does not use methods or control for variables in order to describe why the disparities exist. In order to understand what drives that disparity, there is a need for more in-depth analysis to see what mediates the variation seen by geographic location between breast cancer mortality and race. States: California, Georgia, Iowa, Louisiana, Kentucky, New Jersey, New Mexico, and Utah Tatalovich, Zhu, Rolin, Lewis, Harlan, Winn (2015) â€Å"Geographic disparities in late stage breast cancer incidence: results from eight states in the United States† used descriptive analysis, ANOVA with Bonferroni correction, backward stepwise linear regression, and geospatial modeling to study geographical variation in age-adjusted late-stage breast cancer incidence based on SEER data from 2006-2010. The covariates studied included proxy variables which illustrated socio-demographic and economic characteristics, accessibility to health care, and availability of screening services in the given â€Å"Health Service Areas† (HSAs) defined by the National Center for Health Statistics and modified by the National Cancer Institute. New Jersey had the highest incidence of late stage breast cancer diagnosis while New Mexico had the lowest. Analysis of variance revealed statistically significant differences in the mean incidence rates of late stage breast cancer diagnosis between states, however further study with Bonferroni correction revealed that New Mexico had a significantly lower rate than NJ, GA, KY, and CA which explained that variance. Interestingly, the proportion of high, medium, and low incidence Health Service Areas varied dramatically. New Jersey had a staggering 80% of its HSAs in the â€Å"high† incidence category while New Mexico had 80% of its HSAs in the â€Å"low† incidence category. The other 6 states had varied proportions falling between these two extremes. The regression analysis revealed that of all the covariates tested, four in particular had significant relationships with late stage incidence. the number of mammography facilities per person, the percent of the population w ith bachelor’s degree or greater, and percent with English literacy were associated with lower incidence of late stage diagnosis. The percentage of Black population in a given area was associated with greater incidence of late stage diagnosis. The study effectively illustrated inter and intrastate differences in late stage breast cancer incidence. The geospatial mapping was particularly useful for visually representing the overlap between the independent geographic variables and the health service areas with high incidence. However, the conclusion that there is a significant relationship between college education and late stage breast cancer incidence is weak given that the p-value was 0.010. Additionally, the study acknowledges the difficulty in quantifying and representing these geographic independent covariates. Single State Studies State: Wisconsin, Southeastern Beyer, Zhou, Matthews, Hoormann, Bemanian, Laud, Nattinger (2016) â€Å"Breast and Colorectal Cancer Survival Disparities in Southeastern Wisconsin† focused on Southeastern Wisconsin counties (Milwaukee, Jefferson, Kenosha, Ozaukee, Racine, Walworth, Washington, Waukesha) to better understand the distribution of survival disparities. The study utilized Cox Proportional Hazards Model, Kaplan-Meier analysis, and Adaptive Spatial Filtering (mapping) in order to study cause-specific breast cancer mortality, all-cause breast cancer mortality. The study found significant survival disparities for race and ethnicity. Specifically, both Hispanic/Latino and Black/African American women had significantly poorer survival for both all cause and cause specific breast cancer than white women. Survival was also poorer for those with Late-Stage diagnosis and older age. Geography was analyzed using Adaptive Spatial Filtering which is essentially a univariate analysis of 5-year survival. These results found that the city of Milwaukee and several rural areas had lower survival rates. The methods of this study are intriguing; however, the spatial analysis does not allow for a thorough understanding of what factors are contributing to the observed survival disparities. This modeling method does not allow for the adjustment of covariates; thus, it is hard to tell even with the provided maps representing race/ethnicity and poverty what is truly driving the lower regional survivals. The survival analysis on race/ethnicity, late-stage diagnosis, marital status, and age is unique only because of the data set. Currently, more thorough analyses with greater resolution that observes intra-ethnic diversity exists. The state also has a relatively low number of minority populations represented in this registry. If anything, this study reveals a greater need for a thorough survival analysis with a model that allows for the adjustment of covariates. State: Nevada Callahan, Pinheiro, Cvijetic, Kelly, Ponce, Kovetz (2017) â€Å"Worse Breast Cancer Outcomes for Southern Nevadans, Filipina, and Black Women† observed Nevada by three regions: Northwestern, Southern, and Rural to analyze cause-specific breast cancer mortality and stage-specific survival and how it varied by region. The study utilized 5-year adjusted survival analysis, log rank test, and Cox proportional hazards regression modelling to describe the observed differences in survival between regions with data obtained from the Nevada Central Cancer Registry (NCCR) for the years 2003-2010. Three models were created, the first adjusted only for age; the second adjusted for age, race/ethnicity, insurance status, SES, and NV region; the third adjusted for age, race/ethnicity, insurance status, SES, NV Region, Stage, Estrogen-Receptor Status, and Grade of Tumor. Nevada as a state had a significantly lower survival rate (84.4%) than the US as a whole (89.2%). 68% of breast cancer mortality cases were localized in Southern NV. Survival was lowest in Southern and Rural Nevada regions. This observed elevation in risk of death (16%) observed in the Southern region remained even after adjusting for demographic, social, and pathological covariates. In Nevada, Black and Filipina women had higher hazards of cause specific mortality than white women. The pathological factor, stage at diagnosis, was the biggest factor for cause specific mortality. This study utilizes three Cox proportional hazards regression models which include many covariates to rigorously study what impacts breast cancer survival outcomes. Modelling that controlled for all demographic, social, and pathological factors specifically revealed the role of region in breast cancer survival outcomes. Despite variance being most significantly described by stage at diagnosis, the disparity i n the Southern Region of Nevada remained significant demonstrating the significant and important role of geography in breast cancer survival. This study did not include any covariates that served as a proxy for healthcare access. There may have been geographic disparities in access, thus it may describe the regional differences in survival that exist. State: Louisiana Carrol, Lawson, Jackson, Zhao (2017) â€Å"Assessment of spatial variation in breast cancer-specific mortality using Louisiana SEER data† studied cause-specific breast cancer mortality by Louisiana parish using SEER data from 2000-2013. The study used an accelerated failure time model with spatial frailty estimates, a complex model enabling a high-resolution analysis of Louisiana by parish. The study considered a multitude of covariates ranging from socio-demographic composition of parishes to environmental, industrial, and proximity to key geographical features of parishes. Overall, it was found that parishes with shorter survival time were lower income and positioned alongside either Red or Mississippi Rivers. There was heterogeneity between parishes, the best survival was in Orleans parish and the worst survival was in Terrebonne—those in Orleans Parish survived 1.5 times longer. Additional factors contributing to low survival in parishes included access and quality of care, food availability (fresh vs food desert), socioeconomic status, percent urban, percent farmland, and percent fishing mining, forestry, and agriculture. The study also included emissions as potential environmental risk factors and found that agriculture associated emissions such as ammonia and particulate matter were associated with shorter survival in parishes. The study paints a complete picture of place and its role in breast cancer survival. The model utilized is complicated but its scope and the number of covariates assessed provides a detailed evaluation. The study took a holistic approach in determining its risk factors and covered sociodemographic, socioeconomic, environmental, and occupational variables. The study reveals interesting and modifiable characteristics of areas that can be targeted and also environmental and occupational exposures that could be mitigated. State: Texas Pruitt, Lee, Tiro, Xuan, Ruiz, Inrig (2015) â€Å"Residential racial segregation and mortality among black, white, and Hispanic urban breast cancer patients in Texas, 1995 to 2009† sought to determine the role of segregation, as calculated by an LQ distribution that compares non-Hispanic Blacks to non-Hispanic whites in a given area, on cause-specific breast cancer mortality and all-cause breast cancer mortality. The data was derived from the Texas Cancer Registry for the years 1995-2009. The study utilized descriptive analyses, Chi-Square, ANOVA, Spearman Correlation Coefficients, and Cox Proportional Hazards to determine the significance of the following covariates with breast cancer mortality: 1. Age, 2. Summary Stage, 3. Diagnosis Year, 4. Tumor Grade, 5. Histology, 6. Neighborhood poverty (% of redisdents living in poverty by census tract), 7. # of Mammography Machines per 10,000 women aged 50 or older in county of residence, 8. Segregation: LQ distribution comparing NH Blacks to NH Whites and Hispanics to NH Whites. The study found that Non-Hispanic Blacks live in more segregated neighborhoods of Texas and Hispanics do as well, but to a lower extent. This study is unique amongst the other studies because it looks at neighborhood composition in the context of segregation for NH Blacks and Hispanics. The findings reveal the consistent finding of racial disparities in breast cancer survival. While there was weak univariate evidence to suggest that segregation is associated with poorer survival, segregation does not explain the disparities in survival for NH blacks. It is correlated; however, it does not explain it. The covariates included in the model allowed for appropriate adjustments to determine the relationships underlying the neighborhood differences between metropolitan areas. It is possible, as stated by the authors, that one of the other covariates is the mediator of segregation, such as poverty, and thus controlling for that covariate removed the relationship between segregation and breas t cancer mortality.

A Critique of Todays Process of Ijtihad - 814 Words

A Critique of Today’s Process of Ijtihad Recent achievements in Islamic banking do not indicate an advance in the jurists interpretation of riba. Writings on riba have been extensively concerned with the expositions of riba, but with disquisitions about riba. Thought about riba, and any other Qur’anic penetrative codes, must be a story of movements in outlook and ever-changing ideas, and developments taking place in contemporary social sciences. Its province is destined by God, may he be exalted, in a way to be determined and re-determined in the course of time by drawing insights from different branches of human science. The subject of riba, and other divine codes in Qur’an regarding dealings and transactions is such that no cohesive delineation of the scope can be regarded as final. Some of needless difficulties that have arisen in a proper interpretation of riba are of linguistic origin. The jurist’s business is with words. Words are not only tools of thought, but also control it. Accordingly, to think profitably about riba will be assisted by a sharpened awareness of possibilities of language, not only to lead thought but also to mislead it. This paves the ground on which the Islamic jurists’ adherence to their predecessors’ grasp of riba is questioned. This should not be deemed a denial of the rich legacy handed down from the predecessors. A modern society cannot but build upon the foundations laid in the past. However, this must be carried out with dueShow MoreRelatedThe True Face of Islam: Essays on Islam and Modernity in Indonesia1950 Words   |  8 Pagesinto account the myriad challenges that Indonesia is today faced with. They reflect Madjid’s quest for developing a contextually relevant interpretation of Islam that, departing from traditional notions in some significant respects, can help in the process of building a pluralist and more democratic society based on social justice. Madjid’s search for a contextual Indonesian Islamic theology draws upon his understanding of what he calls the underlying ‘spirit’ of Islam. Like other Muslim liberals

Permit and Opening Portion Free Essays

For this activity, please construct a series of questions that you would ask In the opening portion of the following types of interviews: 1 . To obtain information from a county official about building permits for a report you have been assigned to deliver to senior management 2. To write a biography of a long-time employee for a special presentation at her retirement party 3. We will write a custom essay sample on Permit and Opening Portion or any similar topic only for you Order Now To counsel a subordinate about a problem he or she is having keeping his or her business expenses within budget deadlines Activity 1 . Construct a series of questions that you would ask in the opening portion of the following types of interviews: a. To obtain information from a county official about building permits for a report you have been assigned to deliver to senior management What will we need for the permission to begin our project In this area? How long does It take to get the permit after we submit everything? Do we have an allotted time to finish the project, or do we have indefinite time to complete this? B. To write a biography of a long-time employee for a special presentation at her detriment party Brenda Mason, the dedication of a woman who has been working to supply for her children all these years, now gets the opportunity to celebrate her retirement and we are thankfully here to celebrate with her. She started working here 35 years ago, when her kids were Just 2 and 3, with the dream of becoming a decanter admit, and all the experience she ever had was witnessing. Her hard work got her into the entry level tech department with all the guys, and everyone treated her as she were a kindergarten, helped her with all the basics. She reemploy became the go-to to other people, and she was known for her charisma, and drive, we even tried to convince her to go to management, we wanted more people like her. She declined, and with that, still holding a positive attitude, she’d decline and said management was only â€Å"baby sitting adults†, she wanted to do a man’s job, she stuck to her dream. With absolute certainty we all knew she was going to be someone, with her two kids, and her job, working an additional 20 hours a week when her daughters began school, she got ahead of the whole department, raced the est. sales people, and learned all the server administrative tasks she ever could. She was getting to her dream, she applied to server support, and kept narrowing down her dream, spiraled Into It, till 3 years later, faster than anyone, she got It. Unbounded to us, this whole time, working the additional 20 hours, and she was In school, after the 3rd year she’d graduated, and qualified for those positions she qualified for. From there to now, she has brought that girl feel every tech department needed, the nagging and the whining, that got us all off our seat to get to work. We absolutely love her, and wish her the best, and to give her time to use up all the paid time off she earned. Equines expenses within budget guidelines We’ve noticed a few draw backs in your business, is everything okay with you and your family? We need to make sure you succeed here for them, if there is anything you need to do we will list it, but we are going over the goals you have failed to med, and re-structure the plan. You will report to us, the customers need to be served the right portions, you are busy, you have clientele, but you are allowing your employees to run your business and they re handing things off to their friends and family. This is coming out of your family resources, they depend on you, and you need to make sure that everyone is accountable for their actions. Your employees must get their receipts reviewed every night, and if I were you, I’d be having their submitted orders reviewed before the client checks out for the moment in order to have them understand how important this is. If they aren’t willing to comply, you have the right to fire them, you have to feed your family, they are not the right fit for the restaurant if that is the way they are behaving while they are clocked in. How to cite Permit and Opening Portion, Papers

Variable Pay for Variable Work Free Samples †MyAssignmenthe

Question: Discuss about the Variable Pay for Variable Work. Answer: Wisdom behind variable pays for variable works: The management of companies like RS2 Software PLc, Malta enforce variable payment structures for variable work areas but do not necessarily implement the system for all the departments. This is because different departments in an organisation fulfil different responsibilities and as a result come under different levels of professional pressures. The management bodies use variable pay as an effective way for motivating people to perform better which also means taking up more pressure. For example, the sales department plays the tremendously important role of selling products and earning revenue (rs2.com 2018). They are under continuous pressure to sell more products to generate higher revenue. This mounting stress often results in diminishing motivation which requires the management to implement motivation-enhancement measures. Thus variable pay structures enable the sales force to earn higher compensations in form of incentives. These factors boost their motivation and urge them to a chieve higher sales target. However, departments like administration are involved in internal operations of companies and do not come under direct impact of the market. Thus, they require less motivation compared to the sales departments to achieve high performances. These differences of work pressure acting on different departments necessitate the management bodies to decide different types of pay packages to motivate them (Bennett et al. 2017). Thus, it can be reinstated once again, that it is a prudent management decision to offer variable pay packages to different job roles to motivate them. Factors behind variable pays for variable works: The following are the factors which impact the variable payments for variable works in the organisations: Performance: The performance parameters of different teams constitute the first factor which decides the application of variable payment system. The roles, responsibilities, work pressure and motivation level required to counteract it play significant roles in deciding the application of variable pay programmes. As pointed out, the sales team experience high job pressure to achieve their targets and require higher motivation. The employers thus, use variable pay programme to motivate the sales personnel which is absent in case of back-office departments like administration department since they experience almost no external pressure and consequently, need lesser motivation (Cooper, Gulen and Rau 2016). Seniority and potential: The level of seniority and potential are important factors determining the application of variable payment system. For example, the senior sales managers of RS2 Software have the potential to handle larger teams compared to junior managers. As a result, they come under more professional pressure to over-achieve their targets and require more motivation to handle it. Thus, the company pays these senior managers more incentives than junior managers (Deysel and Kruger 2015). Thus, seniority and potential forms important factors while deciding the variable payment systems in business organisations. Conclusion: Thus, it can be concluded that variable pay system has emerged as a new motivating tool to motivate employees who work under excess tress. This helps employers to motivate these employees to over achieve their targets. This high employee performance ultimately translates into the high performances of the business organisations thus enabling them to earn high revenue. References: Bennett, B., Bettis, J.C., Gopalan, R. and Milbourn, T., 2017. Compensation goals and firm performance. Journal of Financial Economics, 124(2), pp.307-330. Cooper, M., Gulen, H. and Rau, P.R., 2016. Performance for pay? The relation between CEO incentive compensation and future stock price performance. Deysel, B. and Kruger, J., 2015. The relationship between South African CEO compensation and company performance in the banking industry. Southern African Business Review, 19(1), pp.137-169. rs2.com. 2018. Contact Us. [online] Available at: https://ps://www.rs2.com/contact-us/ [Accessed 2 Feb. 2018].