In 2022, Australia had the fourth-highest total number of skin cancer cases worldwide and the highest age-standardized rate, with roughly 37 cases of skin cancer per 100,000 population. The graph illustrates the rate of skin cancer in the countries with the highest skin cancer rates worldwide in 2022.

North America had the highest 12-month cancer prevalence rate in 2022. The 12-month prevalence rate for all cancers in North America as of this time was 595 per 100,000 population. This statistic displays 12-month cancer prevalence rates worldwide in 2022, by region.

Exploring County-Level Correlations in Cancer Rates and Trends

A Multivariate Ordinary Least Squares Regression Model

By Noah Rippner [source]

About this dataset

This dataset offers a unique opportunity to examine the pattern and trends of county-level cancer rates in the United States at the individual county level. Using data from cancer.gov and the US Census American Community Survey, this dataset allows us to gain insight into how age-adjusted death rate, average deaths per year, and recent trends vary between counties – along with other key metrics like average annual counts, met objectives of 45.5?, recent trends (2) in death rates, etc., captured within our deep multi-dimensional dataset. We are able to build linear regression models based on our data to determine correlations between variables that can help us better understand cancers prevalence levels across different counties over time - making it easier to target health initiatives and resources accurately when necessary or desired

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How to use the dataset

This kaggle dataset provides county-level datasets from the US Census American Community Survey and cancer.gov for exploring correlations between county-level cancer rates, trends, and mortality statistics. This dataset contains records from all U.S counties concerning the age-adjusted death rate, average deaths per year, recent trend (2) in death rates, average annual count of cases detected within 5 years, and whether or not an objective of 45.5 (1) was met in the county associated with each row in the table.

To use this dataset to its fullest potential you need to understand how to perform simple descriptive analytics which includes calculating summary statistics such as mean, median or other numerical values; summarizing categorical variables using frequency tables; creating data visualizations such as charts and histograms; applying linear regression or other machine learning techniques such as support vector machines (SVMs), random forests or neural networks etc.; differentiating between supervised vs unsupervised learning techniques etc.; reviewing diagnostics tests to evaluate your models; interpreting your findings; hypothesizing possible reasons and patterns discovered during exploration made through data visualizations ; Communicating and conveying results found via effective presentation slides/documents etc.. Having this understanding will enable you apply different methods of analysis on this data set accurately ad effectively.

Once these concepts are understood you are ready start exploring this data set by first importing it into your visualization software either tableau public/ desktop version/Qlikview / SAS Analytical suite/Python notebooks for building predictive models by loading specified packages based on usage like Scikit Learn if Python is used among others depending on what tool is used . Secondly a brief description of the entire table's column structure has been provided above . Statistical operations can be carried out with simple queries after proper knowledge of basic SQL commands is attained just like queries using sub sets can also be performed with good command over selecting columns while specifying conditions applicable along with sorting operations being done based on specific attributes as required leading up towards writing python codes needed when parsing specific portion of data desired grouping / aggregating different categories before performing any kind of predictions / models can also activated create post joining few tables possible , when ever necessary once again varying across tools being used Thereby diving deep into analyzing available features determined randomly thus creating correlation matrices figures showing distribution relationships using correlation & covariance matrixes , thus making evaluations deducing informative facts since revealing trends identified through corresponding scatter plots from a given metric gathered from appropriate fields!

Research Ideas

• Building a predictive cancer incidence model based on county-level demographic data to identify high-risk areas and target public health interventions.
• Analyzing correlations between age-adjusted death rate, average annual count, and recent trends in order to develop more effective policy initiatives for cancer prevention and healthcare access.
• Utilizing the dataset to construct a machine learning algorithm that can predict county-level mortality rates based on socio-economic factors such as poverty levels and educational attainment rates

Acknowledgements

If you use this dataset i...

Number and rate of new cancer cases diagnosed annually from 1992 to the most recent diagnosis year available. Included are all invasive cancers and in situ bladder cancer with cases defined using the Surveillance, Epidemiology and End Results (SEER) Groups for Primary Site based on the World Health Organization International Classification of Diseases for Oncology, Third Edition (ICD-O-3). Random rounding of case counts to the nearest multiple of 5 is used to prevent inappropriate disclosure of health-related information.

This dataset provides a detailed view of global cancer trends across the 50 most populated countries. With 160,000 records, it encompasses a wide range of variables including cancer types, risk factors, healthcare expenditure, and environmental factors. The data is designed to assist researchers, healthcare policymakers, and data scientists in identifying patterns, predicting future trends, and crafting effective cancer control strategies.

This dataset contains real-world information about colorectal cancer cases from different countries. It includes patient demographics, lifestyle risks, medical history, cancer stage, treatment types, survival chances, and healthcare costs. The dataset follows global trends in colorectal cancer incidence, mortality, and prevention.

Use this dataset to build models for cancer prediction, survival analysis, healthcare cost estimation, and disease risk factors.

Dataset Structure Each row represents an individual case, and the columns include:

Patient_ID (Unique identifier) Country (Based on incidence distribution) Age (Following colorectal cancer age trends) Gender (M/F, considering men have 30-40% higher risk) Cancer_Stage (Localized, Regional, Metastatic) Tumor_Size_mm (Randomized within medical limits) Family_History (Yes/No) Smoking_History (Yes/No) Alcohol_Consumption (Yes/No) Obesity_BMI (Normal/Overweight/Obese) Diet_Risk (Low/Moderate/High) Physical_Activity (Low/Moderate/High) Diabetes (Yes/No) Inflammatory_Bowel_Disease (Yes/No) Genetic_Mutation (Yes/No) Screening_History (Regular/Irregular/Never) Early_Detection (Yes/No) Treatment_Type (Surgery/Chemotherapy/Radiotherapy/Combination) Survival_5_years (Yes/No) Mortality (Yes/No) Healthcare_Costs (Country-dependent, $25K-$100K+) Incidence_Rate_per_100K (Country-level prevalence) Mortality_Rate_per_100K (Country-level mortality) Urban_or_Rural (Urban/Rural) Economic_Classification (Developed/Developing) Healthcare_Access (Low/Moderate/High) Insurance_Status (Insured/Uninsured) Survival_Prediction (Yes/No, based on factors)

In 2022, the highest cancer rate for men and women among European countries was in Denmark with 728.5 cancer cases per 100,000 population. Ireland and the Netherlands followed, with 641.6 and 641.4 people diagnosed with cancer per 100,000 population, respectively.
Lung cancer Lung cancer is the deadliest type of cancer worldwide, and in Europe, Germany was the country with the highest number of lung cancer deaths in 2022, with 47.7 thousand deaths. However, when looking at the incidence rate of lung cancer, Hungary had the highest for both males and females, with 138.4 and 72.3 cases per 100,000 population, respectively.
Breast cancer Breast cancer is the most common type of cancer among women with an incidence rate of 83.3 cases per 100,000 population in Europe in 2022. Cyprus was the country with the highest incidence of breast cancer, followed by Belgium and France. The mortality rate due to breast cancer was 34.8 deaths per 100,000 population across Europe, and Cyprus was again the country with the highest figure.

BackgroundBreast cancer is a leading global health challenge, exhibiting significant regional disparities in incidence, mortality, and survival outcomes. This study analyzed the burden of breast cancer in 2022 and projects its future impact by 2050 using GLOBOCAN data.MethodsIncidence and mortality data for breast cancer from 2022 were analyzed across continents, age group, HDI and countries categories. The Average Annual Percent Change (AAPC) from 2018 to 2022 was calculated to project cases and deaths for 2050. Mortality-to-Incidence Ratios (MIR) were computed to assess survival disparities.ResultsIn 2022, Asia accounted for the highest breast cancer incidence (985,817 cases), followed by Europe (557,532) and Northern America (306,307). Africa recorded the highest mortality-to-incidence ratio (MIR) of 0.510, highlighting challenges in early detection and treatment. By 2050, global breast cancer cases are projected to exceed 6 million, with Asia, experiencing the most significant rise (2.0 million cases) followed by Africa (1.118 million cases), followed by. Mortality is expected to rise proportionally, with Asia (484,468) and Africa (390,695 deaths) and bearing the largest burden. The MIR for 2050 shows marked disparities, with Africa (0.35) and Asia (0.25) remaining elevated compared to Europe (0.20) and Northern America (0.13).ConclusionThe projected rise in breast cancer incidence and mortality highlights the urgent need for region-specific interventions. Targeted strategies focusing on early detection, improved access to treatment, and reduction of modifiable risk factors are essential, particularly in transitioning economies where disparities remain stark.

In 2010, cancer deaths accounted for more than 15% of all deaths worldwide, and this fraction is estimated to rise in the coming years. Increased cancer mortality has been observed in immigrant populations, but a comprehensive analysis by country of birth has not been conducted. We followed all individuals living in Sweden between 1961 and 2009 (7,109,327 men and 6,958,714 women), and calculated crude cancer mortality rates and age-standardized rates (ASRs) using the world population for standardization. We observed a downward trend in all-site ASRs over the past two decades in men regardless of country of birth but no such trend was found in women. All-site cancer mortality increased with decreasing levels of education regardless of sex and country of birth (p for trend <0.001). We also compared cancer mortality rates among foreign-born (13.9%) and Sweden-born (86.1%) individuals and determined the effect of education level and sex estimated by mortality rate ratios (MRRs) using multivariable Poisson regression. All-site cancer mortality was slightly higher among foreign-born than Sweden-born men (MRR = 1.05, 95% confidence interval 1.04–1.07), but similar mortality risks was found among foreign-born and Sweden-born women. Men born in Angola, Laos, and Cambodia had the highest cancer mortality risk. Women born in all countries except Iceland, Denmark, and Mexico had a similar or smaller risk than women born in Sweden. Cancer-specific mortality analysis showed an increased risk for cervical and lung cancer in both sexes but a decreased risk for colon, breast, and prostate cancer mortality among foreign-born compared with Sweden-born individuals. Further studies are required to fully understand the causes of the observed inequalities in mortality across levels of education and countries of birth.

According to Cognitive Market Research, the global Cancer Diagnosis market size was USD 109614.5 million in 2024. It will expand at a compound annual growth rate (CAGR) of 6.50% from 2024 to 2031.

North America held the major market share for more than 40% of the global revenue with a market size of USD 43845.80 million in 2024 and will grow at a compound annual growth rate (CAGR) of 4.7% from 2024 to 2031.
Europe accounted for a market share of over 30% of the global revenue with a market size of USD 32884.35 million.
Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 25211.34 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.5% from 2024 to 2031.
Latin America had a market share of more than 5% of the global revenue with a market size of USD 5480.73 million in 2024 and will grow at a compound annual growth rate (CAGR) of 5.9% from 2024 to 2031.
Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 2192.29 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.2% from 2024 to 2031.
The consumables category is the fastest growing segment of the Cancer Diagnosis industry

Market Dynamics of Cancer Diagnosis Market

Key Drivers for Cancer Diagnosis Market

Increasing Rate of Cancer Diagnostics to Boost Market Growth

The rising global incidence of cancer, which affects millions of people a year, is a primary driver of the need for diagnostic testing. Numerous factors contribute to this tendency, such as the aging population, which increases the risk of developing some cancers in older adults. Changes in lifestyle, including poor eating habits, inactivity, and increased use of alcohol and tobacco, have also contributed to an increase in cancer incidence. Environmental factors, such as exposure to chemicals and hazardous compounds, exacerbate the problem and increase the risk of developing cancer. Therefore, as early detection and diagnosis are becoming more and more important to patients and healthcare professionals, effective cancer diagnostics are essential. The market for cancer diagnostics is expanding as a result of the increased emphasis on prompt and precise cancer detection, which highlights the value of novel diagnostic procedures. For Instance, in 2023, the Pan American Health Organization (PAHO) projects that there will be 20 million new cases and 10 million deaths, and by 2040, nearly 30 million cases will be reported annually.

Innovations in Diagnostic Technologies to Drive Market Growth

The market for cancer diagnostics is expanding as a result of advancements in diagnostic technologies that have greatly improved the precision and effectiveness of cancer detection. For example, non-invasive cancer biomarker identification in physiological fluids is made possible by liquid biopsies, which offer vital insights into tumor dynamics and therapy response. In a similar vein, molecular diagnostics has transformed the detection of particular genetic abnormalities and changes linked to different types of cancer, allowing for more individualized treatment strategies. High-resolution images of tumors are provided by advanced imaging methods like MRI and PET scans, which help with accurate staging and localization. Better patient outcomes result from these technical developments because they increase overall diagnosis accuracy and enable early intervention. The ongoing development of these cutting-edge diagnostic instruments is propelling market expansion and revolutionizing cancer treatment.

Restraint Factor for the Cancer Diagnosis Market

The High Price of Cutting-Edge Diagnostic Technology Will Limit Market Growth

The market for cancer diagnostics is severely hampered by the high price of sophisticated diagnostic tools. Advanced diagnostic instruments, such as molecular tests and imaging technologies, are frequently expensive, which limits healthcare facilities' access to them, especially in settings with limited resources. These institutions' capacity to provide thorough cancer screening and diagnostic services is restricted by this financial barrier, which eventually affects patient outcomes. These financial difficulties are further exacerbated by the costs associated with the development, research, and regulatory approval of new diagnostic instruments. Companies have to spend a lot of money to comply with...

Lung cancer is the deadliest cancer worldwide, accounting for 1.82 million deaths in 2022. The second most deadly form of cancer is colorectum cancer, followed by liver cancer. However, lung cancer is only the sixth leading cause of death worldwide, with heart disease and stroke accounting for the highest share of deaths. Male vs. female cases Given that lung cancer causes the highest number of cancer deaths worldwide, it may be unsurprising to learn that lung cancer is the most common form of new cancer cases among males. However, among females, breast cancer is by far the most common form of new cancer cases. In fact, breast cancer is the most prevalent cancer worldwide, followed by prostate cancer. Prostate cancer is a very close second to lung cancer among the cancers with the highest rates of new cases among men. Male vs. female deaths Lung cancer is by far the deadliest form of cancer among males but is the second deadliest form of cancer among females. Breast cancer, the most prevalent form of cancer among females worldwide, is also the deadliest form of cancer among females. Although prostate cancer is the second most prevalent cancer among men, it is the fifth deadliest cancer. Lung, liver, stomach, colorectum, and oesophagus cancers all have higher deaths rates among males.

This database encompasses several files related to cancer data. The first file is an Excel spreadsheet, containing information on newly diagnosed cancer cases from 2014 to 2017. It provides demographic details and specific characteristics of 482,229 cancer patients. We categorized this data according to the International Agency for Research on Cancer (IARC) reporting rules, and cancers with greater incidence rates were identified. To create a geodatabase, individual data was integrated at the county level and combined with population data. Files 2 and 3 contain gender-specific spatial data for the top cancer types and non-melanoma skin cancer. Each file includes county identifications, the number of cancer cases for each cancer type per year, and gender-specific population information. Lastly, there is a user's guide file to help navigate through the data files.

Editor’s Choice

• Global Breast Cancer Market size is expected to be worth around USD 49.2 Bn by 2032 from USD 19.8 Bn in 2022, growing at a CAGR of 9.8% during the forecast period from 2022 to 2032.
• Breast cancer is the most common cancer among women worldwide. In 2020, there were about 2.3 million new cases of breast cancer diagnosed globally.
• Breast cancer is the leading cause of cancer-related deaths in women. In 2020, it was responsible for approximately 685,000 deaths worldwide.
• The survival rate of breast cancer has improved over the years. In the United States, the overall five-year survival rate of breast cancer is around 90%.
• The American Cancer Society recommends annual mammograms starting at age 40 for women at average risk.
• Although rare, breast cancer also occurs in men. Less than 1% of breast cancer cases are diagnosed in males.

(Source: WHO, American Cancer Society)

BackgroundThe incidence of kidney, bladder, and prostate cancer ranked ninth, sixth, and third in male cancers respectively, meanwhile, the incidence of testicular cancer also increased gradually in the past 30 years.ObjectiveTo study and present estimates of the incidence, mortality, and disability of kidney, bladder, prostate, and testicular cancer by location and age from 1990 to 2019 and reveal the mortality risk factors of them.MaterialsThe Global Burden of Diseases Study 2019 was used to obtain data for this research. The prediction of cancer mortality and incidence was based on mortality-to-incidence ratios (MIRs). The MIR data was processed by logistic regression and adjusted by Gaussian process regression. The association between the socio-demographic index and the incidence or disease burden was determined by Spearman's rank order correlation.ResultsGlobally in 2019, there were 371,700 kidney cancer cases with an age-standardized incidence rate (ASIR) of 4.6 per 100,000, 524,300 bladder cancer cases, with an ASIR of 6.5 per 100,000, 1,410,500 prostate cancer cases with an ASIR of 4.6 per 100,000 and 109,300 testicular cancer incident cases with an ASIR of 1.4 per 100,000, the ASIR of these four cancers increased by 29.1, 4, 22, and 45.5% respectively. The incidence rate of the four cancers and the burden of kidney cancer were positively correlated with the socio-demographic index (SDI), regions with a higher SDI faced more of a burden attributable to these four cancers. High body-mass index has surpassed smoking to be the leading risk factor in the past thirty years for kidney cancer mortality. Smoking remained the leading risk factor for cancer-related mortality for bladder cancer and prostate cancer and the only risk factor for prostate cancer. However, the contribution of high fasting plasma glucose to bladder cancer mortality has been increasing.ConclusionThe incidence of bladder, kidney, prostate, and testicular cancer is ever-increasing. High-income regions face a greater burden attributable to the four cancers. In addition to smoking, metabolic risk factors may need more attention.

BackgroundThe exponential growth of the cancer burden attributable to metabolic factors deserves global attention. We investigated the trends of cancer mortality attributable to metabolic factors in 204 countries and regions between 1990 and 2019.MethodsWe extracted data from the Global Burden of Disease Study (GBD) 2019 and assessed the mortality, age-standardized death rate (ASDR), and population attributable fractions (PAFs) of cancers attributable to metabolic factors. Average annual percentage changes (AAPCs) were calculated to assess the changes in the ASDR. The cancer mortality burden was evaluated according to geographic location, SDI quintiles, age, sex, and changes over time.ResultsCancer attributable to metabolic factors contributed 865,440 (95% UI, 447,970-140,590) deaths in 2019, a 167.45% increase over 1990. In the past 30 years, the increase in the number of deaths and ASDR in lower SDI regions have been significantly higher than in higher SDI regions (from high to low SDIs: the changes in death numbers were 108.72%, 135.7%, 288.26%, 375.34%, and 288.26%, and the AAPCs were 0.42%, 0.58%, 1.51%, 2.36%, and 1.96%). Equatorial Guinea (AAPC= 5.71%), Cabo Verde (AAPC=4.54%), and Lesotho (AAPC=4.42%) had the largest increase in ASDR. Large differences were observed in the ASDRs by sex across different SDIs, and the male-to-female ratios of ASDR were 1.42, 1.50, 1.32, 0.93, and 0.86 in 2019. The core population of death in higher SDI regions is the age group of 70 years and above, and the lower SDI regions are concentrated in the age group of 50-69 years. The proportion of premature deaths in lower SDI regions is significantly higher than that in higher SDI regions (from high to low SDIs: 2%, 4%, 7%, 7%, and 9%). Gastrointestinal cancers were the core burden, accounting for 50.11% of cancer deaths attributable to metabolic factors, among which the top three cancers were tracheal, bronchus, and lung cancer, followed by colon and rectum cancer and breast cancer.ConclusionsThe cancer mortality burden attributable to metabolic factors is shifting from higher SDI regions to lower SDI regions. Sex differences show regional heterogeneity, with men having a significantly higher burden than women in higher SDI regions but the opposite is observed in lower SDI regions. Lower SDI regions have a heavier premature death burden. Gastrointestinal cancers are the core of the burden of cancer attributable to metabolic factors.

Ecuador EC: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 12.200 NA in 2016. This records a decrease from the previous number of 12.400 NA for 2015. Ecuador EC: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 13.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 15.600 NA in 2000 and a record low of 12.200 NA in 2016. Ecuador EC: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ecuador – Table EC.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

BACKGROUND Comprehensive analyses of statistical data on breast cancer incidence, mortality, and associated risk factors are of great value for decision-making related to reducing the disease burden of breast cancer. METHODS: Based on data from the Annual Report of China Tumour Registry and the Global Burden of Disease (GBD), we conducted summary and trend analyses of incidence and mortality rates of breast cancer in Chinese women from 2014 to 2018 for urban and rural areas in the whole, eastern, central, and western parts of the country, and projected the incidence and mortality rates of breast cancer for 2019 in comparison with the GBD 2019 estimates. And the comparative risk assessment framework estimated risk factors contributing to breast cancer deaths and disability-adjusted life years (DALYs) from GBD. RESULTS: The Annual Report of the Chinese Tumour Registry showed that showed that the mortality rate of breast cancer declined and the incidence rate remained largely unchanged from 2014 to 2018. There was a significant increasing trend in incidence rates among urban and rural women in eastern China and rural women in central China, whereas there was a significant decreasing trend in mortality rates among rural women in China. The two data sources have some differences in their predictions of breast cancer in China in 2019. The GBD data estimated the age-standard DALYs rates of high body-mass index, high fasting plasma glucose and diet high in red meat, which are the top three risk factors attributable to breast cancer in Chinese women, to be 29.99/100,000, 13.66/100,000 and 13.44/100,000, respectively. Conclusion: The trend of breast cancer incidence and mortality rates shown in the Annual Report of China Tumour Registry indicates that China has achieved remarkable results in reducing the burden of breast cancer, but there is still a need to further improve breast cancer screening and early diagnosis and treatment, and to improve the system of primary prevention. The GBD database provides risk factors for breast cancer in the world, Asia, and China, and lays the foundation for research on effective measures to reduce the burden of breast cancer.

It is estimated that around 280,000 new cases of cancer will be diagnosed in Spain during 2023, of which 160,000 are expected in men and 120,000 in women. Breast cancer is expected to be the type with the highest incidence in the country, with more than 35,000 new cases estimated for 2023, followed by lung and prostate cancer with 31,282 and 29,002 cases, respectively.

Cancer-related deaths

In 2021, cancer was responsible for approximately 114,000 deaths in Spain. Lung and bronchial cancer caused the highest number of cancer deaths in the country, accounting for approximately 22,400 terminal cases. In fact, it was the fourth main cause of death overall, only after COVID-19, coronary artery disease (CAD), and cerebrovascular disease. Lung cancer is highly associated with smoking and is therefore among the most preventable diseases.

Most common types of cancer worldwide

Breast cancer is the most common type of cancer among women in the world. In 2020, around a quarter of all new cancer cases within this group was attributed to breast cancer. Colorectum and lung cancer followed, accounting for 9.4 and 8.4 percent of all new cancer cases among women that year, respectively. In comparison, lung cancer was the most common type of cancer among men, with a share of 14.3 percent. Prostate cancer followed closely, with 14.1 percent.

In 2022, the incidence of lung cancer among men in Europe was highest in Hungary at ***** per 100,000, while Sweden had the lowest incidence. The incidence of lung cancer recorded among women in Denmark was over ** per 100,000 population. Across the European Union overall, the rate of lung cancer diagnoses was **** per 100,000 among men and **** per 100,000 among women. Smoking and lung cancer risk The connection between smoking and the increased risk of health problems is well established. As of 2021, Hungary had one of the highest daily smoking rates in Europe, with over a quarter of adults smoking daily in the Central European country. The only other countries with a higher share of smoking adults were Bulgaria and Turkey. A positive development though, is the share of adults smoking every day has decreased in almost every European country since 2011. The rise of vaping Originally marketed as a device to help smokers quit, e-cigarettes or vapes have seen increased popularity among people who never smoked cigarettes, especially young people. The use of vapes among young people was reported to be highest in Estonia, Czechia, and Ireland. The dangers of vaping have not been examined over the long term. In the EU there have been attempts to make ‘vapes’ less accessible and appealing for young people, which would include such things as banning flavors and stopping the sale of disposable e-cigarettes.

BackgroundHigh fasting plasma glucose (HFPG) has been identified as one of the risk factors associated with the development of breast cancer. The worldwide distribution of breast cancer attributable to HFPG was not comprehensively investigated.MethodsWe utilized the data from the Global Burden of Disease Study 2021 to explore HFPG-related breast cancer deaths, disability adjusted life years (DALYs) and corresponding age-standardized rates (ASRs). The average annual percentage change (AAPC) and the estimated annual percentage change (EAPC) were employed to evaluate the temporal trend.ResultsThe global effect of HFPG resulted in nearly 30,570 breast cancer deaths and 819,550 DALYs in 2021, representing an age-standardized deaths rate (ASMR) of 0.66 (95% UI -0.19-1.57) and an age-standardized DALYs rate (ASDR) of 18.05 (95% UI -5.31-42.71). In the regions with low, low-middle, and middle SDI, the ASRs of HFPG-related breast cancer increased significantly over time. The highest ASMR and ASDR were observed in several countries, such as Palau, American Samoa, Cook Islands, Marshall Islands, and United Arab Emirates. There was a positive correlation between ASRs and Socio-Demographic Index (SDI) in countries where SDI was below 0.75. The escalation in death and DALYs was primarily driven by epidemiological change and population growth in low, low-middle, middle SDI regions.ConclusionsSubstantial disparities exist across diverse regions in breast cancer burden attributed to HFPG. It is urgent to regulate glycemic levels, improve healthcare infrastructures, and provide cost-effective care in less developed and developing countries that endure a disproportionately heavier health burden.