This dataset provides a snapshot of global suicide rates by country, gender, and year. It offers insights into the prevalence of suicide across different regions and demographics. By analyzing this data, researchers and policymakers can identify trends, potential risk factors, and areas where interventions may be most effective. This information is crucial for developing targeted suicide prevention strategies and promoting mental health awareness.

Number of suicides and suicide rates by sex and age in England and Wales. Includes information on conclusion type, the proportion of suicides by method, and the median registration delay.

Effect of suicide rates on life expectancy dataset

Abstract
In 2015, approximately 55 million people died worldwide, of which 8 million committed suicide. In the USA, one of the main causes of death is the aforementioned suicide, therefore, this experiment is dealing with the question of how much suicide rates affects the statistics of average life expectancy.
The experiment takes two datasets, one with the number of suicides and life expectancy in the second one and combine data into one dataset. Subsequently, I try to find any patterns and correlations among the variables and perform statistical test using simple regression to confirm my assumptions.

Data

The experiment uses two datasets - WHO Suicide Statistics[1] and WHO Life Expectancy[2], which were firstly appropriately preprocessed. The final merged dataset to the experiment has 13 variables, where country and year are used as index: Country, Year, Suicides number, Life expectancy, Adult Mortality, which is probability of dying between 15 and 60 years per 1000 population, Infant deaths, which is number of Infant Deaths per 1000 population, Alcohol, which is alcohol, recorded per capita (15+) consumption, Under-five deaths, which is number of under-five deaths per 1000 population, HIV/AIDS, which is deaths per 1 000 live births HIV/AIDS, GDP, which is Gross Domestic Product per capita, Population, Income composition of resources, which is Human Development Index in terms of income composition of resources, and Schooling, which is number of years of schooling.

LICENSE

THE EXPERIMENT USES TWO DATASET - WHO SUICIDE STATISTICS AND WHO LIFE EXPECTANCY, WHICH WERE COLLEECTED FROM WHO AND UNITED NATIONS WEBSITE. THEREFORE, ALL DATASETS ARE UNDER THE LICENSE ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 3.0 IGO (https://creativecommons.org/licenses/by-nc-sa/3.0/igo/).

[1] https://www.kaggle.com/szamil/who-suicide-statistics

[2] https://www.kaggle.com/kumarajarshi/life-expectancy-who

Suicide Deaths in the United Kingdom by Age

The Age At Which Most People Are Dying By Suicide

By Andy Kriebel [source]

About this dataset

This dataset contains information on the age at which most people die by suicide in the United Kingdom

How to use the dataset

This dataset contains information on suicide deaths by age in the United Kingdom. The data is broken down by year, with the most recent year being 2018. The data includes both the number of suicides and the rate of suicides per 100,000 people.

To use this dataset, simply download it and then open it in your chosen software program. If you want to examine any patterns or trends, you can use the sorting and filtering options in your software to do so. You may also want to create graphs or charts to visualize the data in a more easily digestible format

Research Ideas

• To understand why middle-aged people are most likely to die by suicide and drug poisoning
• To develop interventions to reduce the rate of suicide and drug poisoning among middle-aged people
• To raise awareness of the issue of suicide and drug poisoning among middle-aged people

Acknowledgements

Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Suicide Deaths by Age.csv | Column name | Description | |:--------------|:-------------------------------------------------------| | Year | The year in which the suicide occurred. (Integer) | | Age | The age of the person who committed suicide. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit Andy Kriebel.

In 2015, approximately 55 million people died worldwide, of which 8 million committed suicide. In the USA, one of the main causes of death is the aforementioned suicide, therefore, this experiment is dealing with the question of how much suicide rates affects the statistics of average life expectancy.

Data

The experiment uses two datasets - WHO Suicide Statistics[1] and WHO Life Expectancy[2], which were firstly appropriately preprocessed. The final merged dataset to the experiment has 13 variables, where country and year are used as index: Country, Year, Suicides number, Life expectancy, Adult Mortality, which is probability of dying between 15 and 60 years per 1000 population, Infant deaths, which is number of Infant Deaths per 1000 population, Alcohol, which is alcohol, recorded per capita (15+) consumption, Under-five deaths, which is number of under-five deaths per 1000 population, HIV/AIDS, which is deaths per 1 000 live births HIV/AIDS, GDP, which is Gross Domestic Product per capita, Population, Income composition of resources, which is Human Development Index in terms of income composition of resources, and Schooling, which is number of years of schooling.

References

[1] https://www.kaggle.com/szamil/who-suicide-statistics [2] https://www.kaggle.com/kumarajarshi/life-expectancy-who

Acknowlegement

Foto von davide ragusa auf Unsplash

Context:

This dataset provides data on death rates for suicide categorized by selected population characteristics including sex, race, Hispanic origin, and age in the United States. It includes critical information about measures, definitions, and changes over time.

Source: - NCHS, National Vital Statistics System (NVSS) - Grove RD, Hetzel AM. Vital statistics rates in the United States, 1940–1960. National Center for Health Statistics. 1968 - Numerator data from NVSS annual public-use Mortality Files - Denominator data from U.S. Census Bureau national population estimates - Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics. 2021

Source URLs:

Death rates for suicide by sex, race, Hispanic origin, and age: United States - HUS 2019 Data Finder - National Vital Statistics Reports - NVSS Appendix Entry

Dataset Details and Key Features

The dataset consists of data collected from the National Vital Statistics System (NVSS) and the U.S. Census Bureau, providing a comprehensive overview of suicide death rates across different demographics in the United States from 1950 to 2001.

Key Features:

• Historical Coverage: Data spans from 1950 to 2001, providing long-term trends.
• Demographic Breakdown: Includes data by sex, race, Hispanic origin, and age, facilitating targeted analysis.
• Yearly Data: Provides annual death rate estimates, enabling year-over-year comparison.
• Reliable Sources: Data collected from NVSS and U.S. Census Bureau, ensuring accuracy and reliability.

Usage:

Research and Analysis:

• Trend Analysis: Study long-term trends in suicide rates across different demographic groups.
• Impact Assessment: Analyze the impact of socio-economic factors on suicide rates over time.
• Health Disparities: Identify disparities in suicide rates among different demographic segments.

Policy Making:

• Intervention Development: Inform the creation of targeted interventions for high-risk groups.
• Resource Allocation: Aid in the effective allocation of resources to areas with higher suicide rates.
• Policy Evaluation: Evaluate the effectiveness of past policies and programs aimed at reducing suicide rates.

Public Health Initiatives:

• Awareness Campaigns: Develop awareness campaigns tailored to specific demographic groups.
• Prevention Programs: Design and implement suicide prevention programs based on demographic data.
• Community Outreach: Facilitate community outreach efforts by identifying high-risk areas.

Data Maintenance:

Updates:

• Periodic Updates: The dataset is periodically updated to incorporate the latest available data.
• Version Control: Maintains previous versions for reference and longitudinal studies.

Quality Assurance:

• Data Validation: Ensures data accuracy through rigorous validation processes.
• Consistency Checks: Regular consistency checks to maintain data integrity.

Additional Notes:

• For detailed definitions and explanations of measures, refer to the PDF or Excel version of this table in the HUS 2019 Data Finder.
• Numerator data is derived from NVSS annual public-use Mortality Files, while denominator data comes from U.S. Census Bureau national population estimates.
• The dataset also includes historical data, providing context and continuity for contemporary analysis.

Columns:

Abstract

Explore global statistics on a subject that claims 800,000 lives each year.

About this dataset

Context

Suicide is a major cause of death in the world, claiming around 800,000 lives each year. It is ranked as the 14th leading cause of death worldwide as of 2017 and on average men are twice as likely to fall victim to it. It also one of the leading causes of death on young people and older people are at a higher risk as well. Source

Notes

This dataset contains data from 200+ countries on the topic of suicide and mental health infrastructure. It was created by extracting the latest data from WHO and combining it into a single dataset. Variables available range from Country, Sex, Mental health infrastructure and personnel and finally Suicide Rate (amount of suicides per 100k people). Note that the suicide rate is age-standardized, as to not bias comparisons between countries with different age compositions.

How to use

• Explore Suicide rates and their associated trends, as well as the effects of infrastructure and personnel on the suicide rates.
• Forecast suicide rates

Acknowledgements

If you use this dataset in your research, please credit the authors.

Citation

@misc{Global Health Observatory data repository, title={Mental Health}, url={https://apps.who.int/gho/data/node.main.MENTALHEALTH?lang=en}, journal={WHO} }

License

CC BY NC SA IGO 3.0

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this project to realized in Power Bi:

Suicide rates vary around the world Suicide rates vary widely between countries. The map shows this.

For some countries in Southern Africa and Eastern Europe, the estimated rates of suicide are high, with over 15 annual deaths per 100,000 people.

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Meanwhile for other countries in Europe, South America and Asia, the estimated rates of suicide are lower, with under 10 annual deaths per 100,000 people.

The wide range in suicide rates around the world is likely the result of many factors. This includes differences in underlying mental health and treatment, personal and financial stress, restrictions on the means of suicide, recognition and awareness of suicide, and other factors.

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WHAT YOU SHOULD KNOW ABOUT THIS DATA Suicide estimates come from death certificate data, using deaths that were classified under death codes for 'intentional self-harm' in the International Classification of Diseases (ICD). This includes people who had self-harmed but had not intended to die, and they may not be considered suicides by the country's particular legal definition. In many countries, deaths due to self-harm are highly underreported due to social stigma, cultural and legal concerns. Instead, these deaths are often misclassified in reported data, especially as deaths due to "events of undetermined intent", accidents, homicides, or unknown causes. To account for this, the WHO's Global Health Observatory reclassifies a proportion of deaths reported with those causes as suicides, according to the fraction that are estimated to be deaths by suicide. As a result, data on suicide rates represent a better estimate of how many people die from suicide.

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Suicides may still be underestimated after this adjustment, especially if they are misclassified as other types of deaths.2 This can also be why some countries appear to have rising suicide rates, if the rates of misclassification decline.

Suicide Rate - This indicator shows the suicide rate per 100,000 population. Suicide is a serious public health problem that can have lasting effects on individuals, families, and communities. Mental disorders and/or substance abuse have been found in the great majority of people who have died by suicide. In Maryland, approximately 500 lives are lost each year to this preventable cause of death. Link to Data Details

For a summary of the case study, please go to "Portfolio Project".

Context

This data analysis was meant to show that men have their own issues in society that are being ignored. The mental health has been declining especially for men. This decline worldwide maybe due to a multitude of other variables that may correlate such as: internet usage/social media usage, social belonging, work hours, dating apps, and physical health. This data analysis was meant to show that men have their own issues in society that are being ignored. This decline worldwide maybe due to a multitude of other variables that may correlate such as: internet usage/social media usage, social belonging, work hours, dating apps, and physical health. These variables may require a separate dataset going into more detail about them.

A space dedicated just for men and another just for women to speak about their problems with help and constructive criticism for growth and for social belonging maybe required to improve the mental health of society (among other variables). This does not mean that the struggles of women are nonexistent. There are already a multitude of datasets and articles dedicated to some of the possible struggles of women from MSNBC, CNN, NBC, BBC, Netflix movies, and even popular secular music like recent songs WAP from Megan Thee Stallion, God is a Women by Arianna Grande, etc. This dataset's objective was not made to continue to light a flame between the already hostile relationships that modern men and women have with each other. Awareness without bias is the goal.

For the results, please read the portfolio project and leave comments.

Content

Where the data were obtained:

1. The first excel file was obtained from https://data.world/vizzup/mental-health-depression-disorder-data/workspace/file?filename=Mental+health+Depression+disorder+Data.xlsx

2. The second excel file was obtained from https://ourworldindata.org/grapher/male-vs-female-suicide

3. The third excel file was obtained from https://ourworldindata.org/suicide

4. The fourth excel file was obtained from https://ourworldindata.org/drug-use

Inspiration

I want to be the best data analyst ever, so criticism (regardless of the harshness), it will be greatly appreciated. What would you have added/improved on? Was it easy to understand? What else do you want me to make a dataset on?

This dataset provides comprehensive information on the total number of suicides in Mexico from 1990 to 2023, categorized by sex and state.The dataset adheres to the government methodology by using the year of registration and the state of residence of the deceased as key variables. It includes the following data points:The total male and female populations.Suicide counts for males and females.Suicide rates for each sex.Data SourcesSuicide Data: Extracted from the INEGI database of registered deaths.Source: INEGI - Microdata on DeathsPopulation Data: Sourced from Mexican government population projections for 2020-2070.Source: Gob.mx - Population ProjectionsThis dataset is a valuable resource for understanding trends in suicide across Mexico and offers insights into differences by sex and state-level demographics.

The dataset contains World Bank Suicide mortality rate WDI (world development indicator) (2000-2019) world-wide data in original and processed form. In addition to the statistical data this dataset also contains bibliographic records of articles published on the topic of suicide in relation to individual countries during (2000-2019) in original and processed form.

The data consists of six archives:

World development indicator suicide mortality rate SH.STA.SUIC.P5. This archive contains suicide mortality rate of 159 countries during the period of 2000-2019 per 100,000 population including males and females as of November, 2023.

Web of science records country and suicide. This archive contains bibliographic records organized by country on the topic of suicide related to that country published during 2000-2019 as of November, 2023.

Suicide mortality rate statistics and keywords. This archive contains processed data of 1 and 2 archives in three files. The 'Countries suicide rates and WOS records' contains organized temporal suicide mortality rate data for each country and each year for males and females including counts of articles on suicide related in that country. The 'words and countries matrix' file contains information about how many times author and paper keywords from suicide related publications were seen in articles associated with each country. This data is organized as matrix in which rows are keywords, columns are countries and cells are counts of the keyword. The 'words and countries pairs' file contains same information only organized as keyword country pairs.

Suicide mortality rate clusters countries keywords titles. This archive contains bibliographic data organized by country clusters. These clusters group countries with similar suicide mortality rate dynamics in males and females shown in two included figures. Each folder of the cluster contains a section with bibliographic records; a section with keywords associated with each country; and a section in which each publication associated with the country has a separate filecontaining its title and keywords.

Suicide keywords embedding data. This archive contains word embedding vectors and metadata learned by recurrent neural network trained to classify countries from suicide related keywords of articles associated with those countries. Folder 'trained with keywords' contains embeddings learned in classifying countries in which training samples are keyword strings of publications. Folder 'trained with titles' contains embeddings learned in classifying countries in which training samples are strings containing titles of publication plus keywords.

Suicide keywords association rule mining. This archive contains files of subsets of keywords frequently mentioned together in suicide related publications. Folder 'Mining in clusters' has frequent keyword itemsets in country clusters. Folder 'Mining in individual countries' has frequent keyword itemsets in countries. Examples of keyword networks connecting clusters and networks connecting countries in individual clusters are included which helps to identify specific and shared keywords by country clusters and by countries in the individual clusters.

These datasets support a data availability statements for upcoming articles.

Demographic characteristics of New South Wales men diagnosed with prostate cancer in 1997 to 2007, comparing those who committed suicide with all men diagnosed with prostate cancer, number, percent, person years at risk and crude rate per 100,000 person years at risk.

This data shows deaths (of people age 10 and over) from Suicide and Undetermined Injury, numbers and rates by gender, as 3-year moving-averages.

Suicide is a significant cause of premature deaths occurring generally at younger ages than other common causes of premature mortality. It may also be seen as an indicator of underlying rates of mental ill-health.

Directly Age-Standardised Rates (DASR) are shown in the data, where numbers are sufficient, so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates.

The figures in this dataset include deaths recorded as suicide (people age 10 and over) and undetermined injury (age 15 and over) as those are mostly likely also to have been caused by self-harm. The population denominators for rates are age 10 and over.

Data source: Public Health England, Public Health Outcomes Framework (PHOF) indicator 4.10. This data is updated annually.

India IN: Suicide Mortality Rate: Male data was reported at 17.800 NA in 2016. This records a decrease from the previous number of 18.000 NA for 2015. India IN: Suicide Mortality Rate: Male data is updated yearly, averaging 18.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 18.600 NA in 2000 and a record low of 17.700 NA in 2010. India IN: Suicide Mortality Rate: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Accidental Deaths and Suicides in India (ADSI) 2022 is an annual report published by the National Crime Records Bureau of the Ministry of Home. It details statistics on accidental deaths - road, railway etc and deaths by suicide in India in the past year.

this graph was created in code R :

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Reported annual death rate from suicide per 100,000 people. Suicide deaths are underreported in many countries due to social stigma and cultural or legal concerns. This data has not been adjusted for underreporting, and comparisons may be affected by differences in measurement. To guide decisions in public health – whether that’s by governments, organizations, or individuals – it’s vital to know what people are dying from. This helps us understand which conditions are going untreated, or how much investment is needed to address diseases; to see how much progress we’re making, and whether new challenges are emerging. The ideal way to find out is by aggregating knowledge of the causes of death from medical professionals who know about each patient, their medical conditions and risk factors, and the circumstances in which they died. But officially registering a death, and attributing a cause to it, can be difficult and complex. The process is affected by legal and cultural norms, access to healthcare, and advances in medical knowledge. Because of this, in many countries a large share of deaths are not registered at all.

This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

Background: In 2011, depression was added to the product labeling of finasteride in the USA. The US Food and Drug Administration’s Adverse Event Reporting System database contains at least 36 death cases for finasteride. The aim of this study is to characterize the clinical histories and symptoms reported by a series of 6 suicide victims who took finasteride for treatment of androgenic alopecia. Methods: Medical records and autopsy reports were provided by family members of the cases. Relevant information was extracted according to guidelines for submitting adverse event reports. Results: An important pattern of symptoms was common among all cases who committed suicide in the setting of finasteride use – insomnia and persistent sexual dysfunction after medication discontinuation. Insomnia and fatigue/tiredness were some of the most debilitating symptoms. Apart from 1 case who had hyperlipidemia, there was no documentation of concomitant medication use with finasteride or any baseline medical or psychiatric diagnoses prior to starting finasteride. The findings of this postmarketing series may not be generalizable to the population of men who committed suicide in the setting of finasteride use due to small sample size and bias. Associations between medication use and symptoms cannot prove causality. Conclusion: Men under the age of 40 who use finasteride for alopecia are at risk for suicide if they develop persistent sexual adverse effects and insomnia. Further research is needed to establish whether finasteride has a causal relationship to suicide.

Canada CA: Suicide Mortality Rate: Male data was reported at 18.100 NA in 2016. This records a decrease from the previous number of 18.200 NA for 2015. Canada CA: Suicide Mortality Rate: Male data is updated yearly, averaging 19.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 19.600 NA in 2000 and a record low of 18.100 NA in 2016. Canada CA: Suicide Mortality Rate: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Health Statistics. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;