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.

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?

BackgroundIn Europe, men have lower rates of attempted suicide compared to women and at the same time a higher rate of completed suicides, indicating major gender differences in lethality of suicidal behaviour. The aim of this study was to analyse the extent to which these gender differences in lethality can be explained by factors such as choice of more lethal methods or lethality differences within the same suicide method or age. In addition, we explored gender differences in the intentionality of suicide attempts.Methods and FindingsMethods. Design: Epidemiological study using a combination of self-report and official data. Setting: Mental health care services in four European countries: Germany, Hungary, Ireland, and Portugal. Data basis: Completed suicides derived from official statistics for each country (767 acts, 74.4% male) and assessed suicide attempts excluding habitual intentional self-harm (8,175 acts, 43.2% male).Main Outcome Measures and Data Analysis. We collected data on suicidal acts in eight regions of four European countries participating in the EU-funded “OSPI-Europe”-project (www.ospi-europe.com). We calculated method-specific lethality using the number of completed suicides per method * 100 / (number of completed suicides per method + number of attempted suicides per method). We tested gender differences in the distribution of suicidal acts for significance by using the χ2-test for two-by-two tables. We assessed the effect sizes with phi coefficients (φ). We identified predictors of lethality with a binary logistic regression analysis. Poisson regression analysis examined the contribution of choice of methods and method-specific lethality to gender differences in the lethality of suicidal acts.Findings Main ResultsSuicidal acts (fatal and non-fatal) were 3.4 times more lethal in men than in women (lethality 13.91% (regarding 4106 suicidal acts) versus 4.05% (regarding 4836 suicidal acts)), the difference being significant for the methods hanging, jumping, moving objects, sharp objects and poisoning by substances other than drugs. Median age at time of suicidal behaviour (35–44 years) did not differ between males and females. The overall gender difference in lethality of suicidal behaviour was explained by males choosing more lethal suicide methods (odds ratio (OR) = 2.03; 95% CI = 1.65 to 2.50; p < 0.000001) and additionally, but to a lesser degree, by a higher lethality of suicidal acts for males even within the same method (OR = 1.64; 95% CI = 1.32 to 2.02; p = 0.000005). Results of a regression analysis revealed neither age nor country differences were significant predictors for gender differences in the lethality of suicidal acts. The proportion of serious suicide attempts among all non-fatal suicidal acts with known intentionality (NFSAi) was significantly higher in men (57.1%; 1,207 of 2,115 NFSAi) than in women (48.6%; 1,508 of 3,100 NFSAi) (χ2 = 35.74; p < 0.000001).Main limitations of the studyDue to restrictive data security regulations to ensure anonymity in Ireland, specific ages could not be provided because of the relatively low absolute numbers of suicide in the Irish intervention and control region. Therefore, analyses of the interaction between gender and age could only be conducted for three of the four countries. Attempted suicides were assessed for patients presenting to emergency departments or treated in hospitals. An unknown rate of attempted suicides remained undetected. This may have caused an overestimation of the lethality of certain methods. Moreover, the detection of attempted suicides and the registration of completed suicides might have differed across the four countries. Some suicides might be hidden and misclassified as undetermined deaths.ConclusionsMen more often used highly lethal methods in suicidal behaviour, but there was also a higher method-specific lethality which together explained the large gender differences in the lethality of suicidal acts. Gender differences in the lethality of suicidal acts were fairly consistent across all four European countries examined. Males and females did not differ in age at time of suicidal behaviour. Suicide attempts by males were rated as being more serious independent of the method used, with the exceptions of attempted hanging, suggesting gender differences in intentionality associated with suicidal behaviour. These findings contribute to understanding of the spectrum of reasons for gender differences in the lethality of suicidal behaviour and should inform the development of gender specific strategies for suicide prevention.

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:

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.

There're 2 datasets:

1. Life expectancy contains information about life expectancy for men and for women, happiness score and fertility rate.
2. Suicide Rate contains information about the suicide rate and GDP per capita on each country.

This dataset shows the Canadian Armed Forces (CAF) rate for suicide per 100,000 for Regular Force males. As the number of events was less than 20 in most years, rates were not calculated annually as these would not have been statistically reliable. Regular Force female rates were not calculated because female suicides were uncommon. This dataset is taken from the yearly Report on Suicide Mortality in the Canadian Armed Forces released on the Canada.ca platform at the homepage link provided down below.

Data from Heuer (1979) on suicide rates in West Germany classified by age, sex, and method of suicide.
A data frame with 306 observations and 6 variables.

This dataset contains data about obesity, suicides and unemployment segregated by Country. The sources of data are wikipedia tables as updated on 11/04/2022. More information can be found in project's github: https://github.com/martinsanc/wikipedia_scraper

Países (List of countries by population (United Nations) - Wikipedia)

Country

UN continental region

UN statistical subregion

Population 1 July 2018

Population 1 July 2019

Change

Desempleo (List of countries by unemployment rate - Wikipedia)

Unemployment Rate

Sourcedate of information

Suicidios (List of countries by suicide rate - Wikipedia)

All

Male

Female

Tasa de obesidad por país (List of countries by suicide rate - Wikipedia)

Rank

Obesity rate

Age-adjusted suicide rates (per 100,000 per year) inside and outside of Wayne county as well as relative risk of suicide in Wayne county relative to all other counties among non-ethnic white males and females aged 10 and older in Michigan, 1990–2007.

Background: Despite most suicides occurring in low-and-middle-income countries (LAMICs), limited reports on suicide rates in older adults among LAMICs are available. In Ecuador, high suicide rates have been reported among adolescents. Little is known about the epidemiology of suicides among older adults in Ecuador.Aim: To examine the sociodemographic characteristics of suicides among older adults living in Ecuador from 1997 to 2019.Methods: An observational study was conducted using Ecuador's National Institute of Census and Statistics database from 1997 to 2019 in Ecuadorians aged 60 and older. International Classification of Diseases 10th Revision (ICD-10) (X60-X84)-reported suicide deaths were included in addition to deaths of events of undetermined intent (Y21-Y33). Sex, age, ethnicity, educational level, and method of suicide were analyzed. Annual suicide rates were calculated per 100,000 by age, sex, and method. To examine the trends in rates of suicide, Joinpoint analysis using Poisson log-linear regression was used.Results: Suicide rates of female older adults remained relatively stable between 1997 and 2019 with an average annual percentage increase of 2.4%, while the male rates increased between 2002 and 2009, 2014 and 2016, and maintained relatively stable within the past 3 years (2017–2019). The annual age-adjusted male suicide rate was 29.8 per 100,000, while the female suicide rate was 5.26 per 100,000 during the study period. When adding deaths of undetermined intent, the annual male rate was 60.5 per 100,000, while the same rate was 14.3 for women. The most common suicide method was hanging (55.7%) followed by self-poisoning (26.0%). The highest suicide numbers were reported in urban districts, men, and those with lower education status.Conclusion: This study contributes to building the baseline for further studies on suicide rates of older adults in Ecuador. Results highlight priority areas of suicide prevention. By examining suicide trends over 23 years, findings can help inform policy and future interventions targeting suicide prevention.

This group of datasets describe the suicides in Scotland for the period 1982-2009. There are 4 separate datasets: All Suicides/Male Suicides/Female Suicides/All Suicide Rate (expressed per 100,000 people). The data is broken down into Local Authority Areas making it easier to investigate any spatial disparity in the suicide figures. A couple of points are worth noting are that it is unclear if the suicide data shows all suicides or just those of Adults. A recent Scottish Government report(http://www.scotland.gov.uk/Publications/2007/03/01145422/20) used deaths of people over 15 years old. Differences in the rates between this data and the results presented in the Scottish Government report may also be due to different population datasets being used. Suicide data sources form the Scottish Public Health Observatory (http://www.scotpho.org.uk/home/Healthwell-beinganddisease/suicide/suicide_data/suicide_la.asp) and the population data used to calculate the rates was sourced from ShareGeo Open (http://hdl.handle.net/10672/95) which uses mid-year estimates downloaded from Nomis (www.nomisweb.co.uk/. Datasets were joined to Local Authority (district, unitary authority and borough) boundaries downloaded from Ordnance Survey OpenData Boundary Line dataset. All spatial analysis was carried out in ArcGIS. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2011-01-13 and migrated to Edinburgh DataShare on 2017-02-21.

A Dataset exploring suicide counts in South American Prisons. The set contains suicide and population counts divided by female and male gender between 2000 and 2017 in the federal prisons of Argentina, the Palmasola prison in Bolivia, all public prisons in Brazil, Chile, Colombia, Ecuador, Guyana, Paraguay, Perú, and Uruguay. The set also contains rates of occupancy, rates of incarceration, and suicide and population counts for the general population of the same countries.

ABSTRACT Objective To describe the epidemiological profile and analyze the time trend of suicide mortality among adolescents (10-19 years old) from the Brazilian Northeast, from 2001 to 2015. Methods This is an observational study, which took place in the Northeast region, Brazil. The study period was from 2001 to 2015. Deaths from intentional self-harm (X60 to X84). exogenous poisoning of undetermined intent (Y10 to Y19) and intentional self-harm (Y87.0) were considered, according to the 10th Review of the International Classification of Diseases (ICD-10), for adolescents aged 10 to 19 years. The variables analyzed were: sex, age group, race / color, specific ICD, state of residence and suicide mortality rate/100,000 inhabitants. Results There were 3,194 deaths due to suicide in the age group studied, with a male predominance (62.1%; n = 1,984), age group 15 to 19 years (84.8%; n = 2,707), race/brown color (65.4%; n = 2,090); between 4 and 7 years of schooling (31.7%; n = 1,011) and at CID X70 (47.8%; n = 1,528). The time trend of mortality was increasing from 2001 to 2015 (APC: 2.4%; p < 0.01), with higher rates in males. There was an increasing trend in the suicide rate, among men, throughout the period (AAPC: 2.9%; p < 0.01). In women, a decreasing trend was identified as of 2004 (APC: -2.2%; p < 0.01). Conclusion The epidemiological profile was characterized by male gender, age group 15-19 years, color/brown race and average schooling. The trend showed a growth pattern in males and a decline in females. It is recommended that public policies are aimed at the adolescent population.

BackgroundAbout 1 million people worldwide commit suicide each year, and college students with suicidal ideation are at high risk of suicide. The prevalence of suicidal ideation in college students has been estimated extensively, but quantitative syntheses of overall prevalence are scarce, especially in China. Accurate estimates of prevalence are important for making public policy. In this paper, we aimed to determine the prevalence of suicidal ideation in Chinese college students.Objective and MethodsDatabases including PubMed, Web of Knowledge, Chinese Web of Knowledge, Wangfang (Chinese database) and Weipu (Chinese database) were systematically reviewed to identify articles published between 2004 to July 2013, in either English or Chinese, reporting prevalence estimates of suicidal ideation among Chinese college students. The strategy also included a secondary search of reference lists of records retrieved from databases. Then the prevalence estimates were summarized using a random effects model. The effects of moderator variables on the prevalence estimates were assessed using a meta-regression model.ResultsA total of 41 studies involving 160339 college students were identified, and the prevalence ranged from 1.24% to 26.00%. The overall pooled prevalence of suicidal ideation among Chinese college students was 10.72% (95%CI: 8.41% to 13.28%). We noted substantial heterogeneity in prevalence estimates. Subgroup analyses showed that prevalence of suicidal ideation in females is higher than in males.ConclusionsThe prevalence of suicidal ideation in Chinese college students is relatively high, although the suicide rate is lower compared with the entire society, suggesting the need for local surveys to inform the development of health services for college students.

Age-adjusted rate of suicide deaths for Santa Clara County residents. The data are provided for the total county population and by sex and race/ethnicity. Data trends are presented from 2007 to 2016. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau, 2010 Census.METADATA:Notes (String): Lists table title, notes and sourceYear (String): Year of death Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only) and Asian/Pacific Islander subgroups: Asian Indian, Chinese. Filipino, Korean and Vietnamese.Age adjusted rate per 100,000 people (Numeric): The Tenth Revision of the International Classification of Diseases codes (ICD-10) are used for coding causes of death. Age-adjusted rate is calculated using 2000 U.S. Standard Population. Suicide rate is number of suicide deaths in a year per 100,000 people in the same time period.

Crude suicide rates (per 100 000 population)

  Dataset Description

This dataset provides information on 'Crude suicide rates' for countries in the WHO African Region. The data is disaggregated by the 'Sex' dimension, allowing for analysis of health inequalities across different population subgroups. Units: per 100 000 population

  Dimensions and Subgroups

Dimension: Sex Available Subgroups: Female, Male

  Data Structure

The dataset is in a wide format.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/crude-suicide-ratesby-sex-for-african-countries.

Abstract Objective: to perform spatiotemporal analysis of suicide mortality in the elderly in Brazil. Methods: a mixed ecological study was carried out in which deaths from suicide among the elderly were analyzed using data from the Mortality Information System (MIS) and socio-demographic variables, from 2000 to 2014, with a trend analysis of this period. Univariate and bivariate spatial analysis was performed using the Moran Global and Moran Map index to evaluate the intensity and significance of spatial clusters. Results: there were 19,806 deaths due to suicide among the elderly in Brazil between 2000 and 2014. The ratio of male and female mortality rates was 4:1, with increasing trends for both genders (R2>0.8), but with greater intensity among men (p=0.0293). There was a moderate autocorrelation for men (I>0.40), with clusters forming for both genders in the south of Brazil. Bivariate analysis showed the formation of clusters in the southern region with the Human Development Index and aging variables and in the north and northeast regions based on dependence and illiteracy ratio. Conclusions: mortality due to suicide among the elderly has a tendency to increase and is unequally distributed in Brazil.

1. Database contents The Russian Short-Term Mortality Fluctuations database (RusSTMF) contains a series of standardized and crude death rates for men, women and both sexes for Russia as a whole and its regions for the period from 2000 to 2021. All the output indicators presented in the database are calculated based on data of deaths registered by the Vital Registry Office. The weekly death counts are calculated based on depersonalized individual data provided by the Russian Federal State Statistics Service (Rosstat) at the request of the HSE. Time coverage: 03.01.2000 (Week 1) – 31.12.2021 (Week 1148)
2. A brief description of the input data on deaths Date of death: date of occurrence Unit of time: week First and last days of the week: Monday – Sunday First and last week of the year: The weeks are organized according to ISO 8601:2004 guidelines. Each week of the year, including the first and last, contains 7 days. In order to get 7-day weeks, the days of previous years are included in this first week (if January 1 fell on Tuesday, Wednesday or Thursday) or in the last calendar week (if December 31 fell on Thursday, Friday or Saturday). Age groups: the entire population Sex: men, women, both sexes (men and women combined) Restrictions and data changes: data on deaths in the Pskov region were excluded for weeks 9-13 of 2012 Note: Deaths with an unknown date of occurrence (unknown year, month, or day) account for about 0.3% of all deaths and are excluded from the calculation of week-age-specific and standardized death rates.
3. Description of the week-specific mortality rates data file Week-specific standardized death rates for Russia as a whole and its regions are contained in a single data file presented in .csv format. The format of data allows its uploading into any system for statistical analysis. Each record (row) in the data file contains data for one calendar year, one week, one territory, one sex. The decimal point is dot (.) The first element of the row is the territory code ("PopCode" column), the second element is the year ("Year" column), the third element ("Week" column) is the week of the year, the fourth element ("Sex" column) is sex (F – female, M – male, B – both sexes combined). This is followed by a column "CDR" with the value of the crude death rate and "SDR" with the value of the standardized death rate. If the indicator cannot be calculated for some combination of year, sex, and territory, then the corresponding meaningful data elements in the data file are replaced with ".".

This dataset documents rates and trends in local hypertension-related cardiovascular disease (CVD) death rates. Specifically, this report presents county (or county equivalent) estimates of hypertension-related CVD death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (female, male). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.