About Dataset

The dataset contains 2 .csv files This file contains various demographic and health-related data for different regions. Here's a brief description of each column:

File 1st

• avganncount: Average number of cancer cases diagnosed annually.

• avgdeathsperyear: Average number of deaths due to cancer per year.

• target_deathrate: Target death rate due to cancer.

• incidencerate: Incidence rate of cancer.

• medincome: Median income in the region.

• popest2015: Estimated population in 2015.

• povertypercent: Percentage of population below the poverty line.

• studypercap: Per capita number of cancer-related clinical trials conducted.

• binnedinc: Binned median income.

• medianage: Median age in the region.

• pctprivatecoveragealone: Percentage of population covered by private health insurance alone.

• pctempprivcoverage: Percentage of population covered by employee-provided private health insurance.

• pctpubliccoverage: Percentage of population covered by public health insurance.

• pctpubliccoveragealone: Percentage of population covered by public health insurance only.

• pctwhite: Percentage of White population.

• pctblack: Percentage of Black population.

• pctasian: Percentage of Asian population.

• pctotherrace: Percentage of population belonging to other races.

• pctmarriedhouseholds: Percentage of married households. birthrate: Birth rate in the region.

File 2nd

This file contains demographic information about different regions, including details about household size and geographical location. Here's a description of each column:

• statefips: The FIPS code representing the state.

• countyfips: The FIPS code representing the county or census area within the state.

• avghouseholdsize: The average household size in the region.

• geography: The geographical location, typically represented as the county or census area name followed by the state name.

Each row in the file represents a specific region, providing details about household size and geographical location. This information can be used for various demographic analyses and studies.

Cervical Cancer Risk Factors for Biopsy: This Dataset is Obtained from UCI Repository and kindly acknowledged! This file contains a List of Risk Factors for Cervical Cancer leading to a Biopsy Examination! About 11,000 new cases of invasive cervical cancer are diagnosed each year in the U.S. However, the number of new cervical cancer cases has been declining steadily over the past decades. Although it is the most preventable type of cancer, each year cervical cancer kills about 4,000 women in the U.S. and about 300,000 women worldwide. In the United States, cervical cancer mortality rates plunged by 74% from 1955 - 1992 thanks to increased screening and early detection with the Pap test. AGE Fifty percent of cervical cancer diagnoses occur in women ages 35 - 54, and about 20% occur in women over 65 years of age. The median age of diagnosis is 48 years. About 15% of women develop cervical cancer between the ages of 20 - 30. Cervical cancer is extremely rare in women younger than age 20. However, many young women become infected with multiple types of human papilloma virus, which then can increase their risk of getting cervical cancer in the future. Young women with early abnormal changes who do not have regular examinations are at high risk for localized cancer by the time they are age 40, and for invasive cancer by age 50. SOCIOECONOMIC AND ETHNIC FACTORS Although the rate of cervical cancer has declined among both Caucasian and African-American women over the past decades, it remains much more prevalent in African-Americans -- whose death rates are twice as high as Caucasian women. Hispanic American women have more than twice the risk of invasive cervical cancer as Caucasian women, also due to a lower rate of screening. These differences, however, are almost certainly due to social and economic differences. Numerous studies report that high poverty levels are linked with low screening rates. In addition, lack of health insurance, limited transportation, and language difficulties hinder a poor woman’s access to screening services. HIGH SEXUAL ACTIVITY Human papilloma virus (HPV) is the main risk factor for cervical cancer. In adults, the most important risk factor for HPV is sexual activity with an infected person. Women most at risk for cervical cancer are those with a history of multiple sexual partners, sexual intercourse at age 17 years or younger, or both. A woman who has never been sexually active has a very low risk for developing cervical cancer. Sexual activity with multiple partners increases the likelihood of many other sexually transmitted infections (chlamydia, gonorrhea, syphilis).Studies have found an association between chlamydia and cervical cancer risk, including the possibility that chlamydia may prolong HPV infection. FAMILY HISTORY Women have a higher risk of cervical cancer if they have a first-degree relative (mother, sister) who has had cervical cancer. USE OF ORAL CONTRACEPTIVES Studies have reported a strong association between cervical cancer and long-term use of oral contraception (OC). Women who take birth control pills for more than 5 - 10 years appear to have a much higher risk HPV infection (up to four times higher) than those who do not use OCs. (Women taking OCs for fewer than 5 years do not have a significantly higher risk.) The reasons for this risk from OC use are not entirely clear. Women who use OCs may be less likely to use a diaphragm, condoms, or other methods that offer some protection against sexual transmitted diseases, including HPV. Some research also suggests that the hormones in OCs might help the virus enter the genetic material of cervical cells. HAVING MANY CHILDREN Studies indicate that having many children increases the risk for developing cervical cancer, particularly in women infected with HPV. SMOKING Smoking is associated with a higher risk for precancerous changes (dysplasia) in the cervix and for progression to invasive cervical cancer, especially for women infected with HPV. IMMUNOSUPPRESSION Women with weak immune systems, (such as those with HIV / AIDS), are more susceptible to acquiring HPV. Immunocompromised patients are also at higher risk for having cervical precancer develop rapidly into invasive cancer. DIETHYLSTILBESTROL (DES) From 1938 - 1971, diethylstilbestrol (DES), an estrogen-related drug, was widely prescribed to pregnant women to help prevent miscarriages. The daughters of these women face a higher risk for cervical cancer. DES is no longer prsecribed.

The dataset contains 2 .csv files

This file contains various demographic and health-related data for different regions. Here's a brief description of each column:

File 1st

avganncount: Average number of cancer cases diagnosed annually.

avgdeathsperyear: Average number of deaths due to cancer per year.

target_deathrate: Target death rate due to cancer.

incidencerate: Incidence rate of cancer.

medincome: Median income in the region.

popest2015: Estimated population in 2015.

povertypercent: Percentage of population below the poverty line.

studypercap: Per capita number of cancer-related clinical trials conducted.

binnedinc: Binned median income.

medianage: Median age in the region.

pctprivatecoveragealone: Percentage of population covered by private health insurance alone.

pctempprivcoverage: Percentage of population covered by employee-provided private health insurance.

pctpubliccoverage: Percentage of population covered by public health insurance.

pctpubliccoveragealone: Percentage of population covered by public health insurance only.

pctwhite: Percentage of White population.

pctblack: Percentage of Black population.

pctasian: Percentage of Asian population.

pctotherrace: Percentage of population belonging to other races.

pctmarriedhouseholds: Percentage of married households. birthrate: Birth rate in the region.

File 2nd

This file contains demographic information about different regions, including details about household size and geographical location. Here's a description of each column:

statefips: The FIPS code representing the state.

countyfips: The FIPS code representing the county or census area within the state.

avghouseholdsize: The average household size in the region.

geography: The geographical location, typically represented as the county or census area name followed by the state name.

Each row in the file represents a specific region, providing details about household size and geographical location. This information can be used for various demographic analyses and studies.

ObjectiveReal-world data characterizing differences between African American (AA) and White women with metastatic triple-negative breast cancer (mTNBC) are limited. Using 9 years of data collected from community practices throughout the United States, we assessed racial differences in the proportion of patients with mTNBC, and their characteristics, treatment, and overall survival (OS).MethodsThis retrospective study analyzed de-identified data from 2,116 patients with mTNBC in the Flatiron Health database (January 2011 to March 2020). Characteristics and treatment patterns between AA and White patients with mTNBC were compared using descriptive statistics. OS was examined using Kaplan-Meier analysis and a multivariate Cox proportional hazards regression model.ResultsAmong patients with metastatic breast cancer, more AA patients (23%) had mTNBC than White patients (12%). This difference was particularly pronounced in patients who lived in the Northeast, were aged 45–65, had commercial insurance, and had initial diagnosis at stage II. AA patients were younger and more likely to have Medicaid. Clinical characteristics and first-line treatments were similar between AA and White patients. Unadjusted median OS (months) was shorter in AA (10.3; 95% confidence interval [CI]: 9.1, 11.7) vs. White patients (11.9; 95% CI: 10.9, 12.8) but not significantly different. After adjusting for potential confounders, the hazard ratio for OS was 1.09 (95% CI: 0.95, 1.25) for AA vs. White patients.ConclusionsThe proportion of patients with mTNBC was higher in AA than White mBC patients treated in community practices. Race did not show an association with OS. Both AA and White patients with mTNBC received similar treatments. OS was similarly poor in both groups, particularly in patients who had not received any documented anti-cancer treatment. Effective treatment remains a substantial unmet need for all patients with mTNBC.

IntroductionDespite advancements in cervical cancer screening and HPV vaccines, demographic disparities perpetuate the burden of cervical cancer. The aim of this study is to utilize the most up-to-date CDC WONDER data of cervical cancer mortality to provide a comprehensive temporal analysis of demographic variables and account for patients missed in other database studies. In doing so, temporal trends found in this study may be used to guide future efforts and studies to understand nuanced barriers to cervical cancer screening and prevention.MethodsWith CDC WONDER Data, cervical cancer-related mortality was assessed in the U.S. from 1999 to 2023. Using age-adjusted mortality rates (AAMR), temporal trends were analyzed using the Joinpoint Regression Program for women 25 years and older across race, census regions, urban/rural residence, and states. Annual percentage change (APC) and average annual percentage change (AAPC) were calculated with 95% confidence intervals.ResultsCervical cancer-related mortality declined over the study period with an AAPC of –1.043*. Between 2015 and 2023, there was a concerning positive change in AAMR [APC of 0.1272 (95% CI –0.3393 to 1.7502)], though not statistically significant. Black or African American patients experienced the highest AAMR across races but maintained a decrease in mortality rate over the study period [AAPC of -2.670* (95% CI -2.931 to -2.356)]. Region and race analysis demonstrated Black or African American patients in the Northeast held the largest decline in AAMR [AAPC of –3.218* (95% CI –3.708 to –2.390)], while Hispanic or Latino and Black or African American patients in the South closely followed AAPC of –1.347* (–1.898 to –0.824) and –2.656* (95% CI –2.939 to -2.350), respectively]. Rural areas (NonCore and Micropolitan) and the Southern region displayed a concerning positive trend after 2009 and 2010, though not statistically significant [APC values of 0.772 (95% CI -0.328 to 4.888), 0.986 (95% CI –0.252 to 4.887), and 0.286 (95% CI –0.061 to 0.772), respectively].ConclusionThese findings underscore the need for targeted interventions with consideration of regional and racial temporal disparities in cervical cancer-related mortality.

Medical Service Study Areas (MSSAs)As defined by California's Office of Statewide Health Planning and Development (OSHPD) in 2013, "MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data" (Source). Each census tract in CA is assigned to a given MSSA. The most recent MSSA dataset (2014) was used. Spatial data are available via OSHPD at the California Open Data Portal. This information may be useful in studying health equity.Definitions:Race/Ethnicity: Race/ethnicity is categorized as: All races/ethnicities, Non-Hispanic (NH) White, NH Black, Asian/Pacific Islander, or Hispanic. "All races" includes all of the above, as well as other and unknown race/ethnicity and American Indian/Alaska Native. The latter two groups are not reported separately due to small numbers for many cancer sites.Racial/Ethnic Composition: Distribution of residents' race/ethnicity (e.g., % Hispanic, % non-Hispanic White, % non-Hispanic Black, % non-Hispanic Asian/Pacific Islander). (Source: US Census, 2010.)Rural: Percent of residents who reside in blocks that are designated as rural. (Source: US Census, 2010.)Foreign Born: Percent of residents who were born outside the United States. (Source: American Community Survey, 2008-2012.)Socioeconomic Status (Neighborhood Level): A composite measure of seven indicator variables created by principal component analysis; indicators include: education, blue-collar job, unemployment, household income, poverty, rent, and house value. Quintiles based on state distribution, with quintile 1 being the lowest SES and 5 being the highest. (Source: American Community Survey, 2008-2012.)Spatial extent: CaliforniaSpatial Unit: MSSACreated: n/aUpdated: n/aSource: California Health MapsContact Email: gbacr@ucsf.eduSource Link: https://www.californiahealthmaps.org/?areatype=mssa&address=&sex=Both&site=AllSite&race=&year=05yr&overlays=none&choropleth=Obesity

BackgroundOur current understanding of Asian American mortality patterns has been distorted by the historical aggregation of diverse Asian subgroups on death certificates, masking important differences in the leading causes of death across subgroups. In this analysis, we aim to fill an important knowledge gap in Asian American health by reporting leading causes of mortality by disaggregated Asian American subgroups.Methods and FindingsWe examined national mortality records for the six largest Asian subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese) and non-Hispanic Whites (NHWs) from 2003-2011, and ranked the leading causes of death. We calculated all-cause and cause-specific age-adjusted rates, temporal trends with annual percent changes, and rate ratios by race/ethnicity and sex. Rankings revealed that as an aggregated group, cancer was the leading cause of death for Asian Americans. When disaggregated, there was notable heterogeneity. Among women, cancer was the leading cause of death for every group except Asian Indians. In men, cancer was the leading cause of death among Chinese, Korean, and Vietnamese men, while heart disease was the leading cause of death among Asian Indians, Filipino and Japanese men. The proportion of death due to heart disease for Asian Indian males was nearly double that of cancer (31% vs. 18%). Temporal trends showed increased mortality of cancer and diabetes in Asian Indians and Vietnamese; increased stroke mortality in Asian Indians; increased suicide mortality in Koreans; and increased mortality from Alzheimer’s disease for all racial/ethnic groups from 2003-2011. All-cause rate ratios revealed that overall mortality is lower in Asian Americans compared to NHWs.ConclusionsOur findings show heterogeneity in the leading causes of death among Asian American subgroups. Additional research should focus on culturally competent and cost-effective approaches to prevent and treat specific diseases among these growing diverse populations.

BackgroundGastric cancer (GC) is a significant public health concern in the USA, and its burden is on the rise.MethodsThis study utilized the latest data from the Global Burden of Disease (GBD) study. We provided descriptive statistics on the incidence, prevalence, mortality, disability-adjusted life years (DALYs), and age-standardized rates (ASRs) of GC across the USA and states. By calculating percentage changes and average annual percentage changes (AAPC), along with conducting age-period-cohort analysis, we assessed the trends in the burden of GC. Decomposition analysis was then performed, followed by the application of an autoregressive integrated moving average (ARIMA) model to forecast changes in ASRs through 2036.ResultsFrom 1990 to 2021, the number of incidence and prevalence of GC in the USA increased, but age-standardized incidence rates (ASIR) trended downward (AAPC = -0.73, 95% confidence interval [CI]: -0.77 to -0.68) and age-standardized prevalence rates (ASPR) (AAPC = -0.99, 95% CI: -1.08 to -0.9) showed a decreasing trend. In addition, the number of deaths, DALYs, age-standardized mortality rates (ASMR) and age-standardized DALYs rates (ASDR) in GC showed a decreasing trend. The burden of GC was significantly higher in males compared to females. In addition, we found that the highest incidence and prevalence in females was in the age group of 75-79 years, whereas the highest incidence and prevalence in males was in the age group of 70-74 years.ConclusionGC is a major public health issue in the USA. Although ASIR, ASPR, ASMR, and ASDR for GC are decreasing, the number of incidence and prevalence of GC in the USA remains high, and the disease burden of GC in the USA remains high. Strengthening preventive interventions, particularly for men and patients over the age of 60, will be crucial in the future.

International Classification of Diseases for Oncology version 3 (ICDO-3) histology and topography codes and percentage distribution among all pancreatic carcinoma diagnoses in Australia between 2018 and 2020.

Notes: c - the generalized scale parameter of age dimension which characterizes the age of maximal incidence; m (m-stages) - the number of stages occurring during individual’s life and leading to the cancer diagnosis; n - the parameter running over different types of frailty distributions (e.g., n = 1 and n = 2 correspond to gamma-distribution and inverse Gaussian distribution); σ - characterizes the standard deviation of the frailty distribution (the distribution of cancer predisposition in population); Rsex and Rrace describe the relative risks of cancer incidence in females and in African-American population, respectively; and characterizes the percent change in cancer incidence rates for a 10-year period.