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

Data on death rates for suicide, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for 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; and 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. Available from: https://www.cdc.gov/nchs/products/nvsr.htm. For more information on the National Vital Statistics System, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

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 rather than unverifiable accident, neglect or abuse. The population denominators for rates are age 10 and over. Low numbers may result in zero values or missing data. Data source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator 41001 (E10). This data is updated annually.

This dataset shows the suicide rates for just over 100 countries. The data is compiled from the the World Health Organization from 2008 in which a country's rank is determined by its total rate deaths officially recorded as suicides. Rates are expressed as per 100,000 of population. Note - year is not consistant for all entries, please refer to the year column to determine what year the data represents. Data sourced from WHO website - Mental health. World Health Organization. 2009. http://www.who.int/mental_health/prevention/suicide/country_reports/en/index.html. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2011-01-31 and migrated to Edinburgh DataShare on 2017-02-21.

Number of suicides and suicide rates, by sex and age, in England and Wales. Information on conclusion type is provided, along with the proportion of suicides by method and the median registration delay.

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 rather than unverifiable accident, neglect or abuse. The population denominators for rates are age 10 and over. Low numbers may result in zero values or missing data.

Data source: Office for Health Improvement and Disparities (OHID), Public Health Outcomes Framework (PHOF) indicator 41001 (E10). This data is updated annually.

Over *** thousand deaths due to suicides were recorded in India in 2022. Furthermore, majority of suicides were reported in the state of Tamil Nadu, followed by Rajasthan. The number of suicides that year had increased from the previous year. Some of the causes for suicides in the country were due to professional problems, abuse, violence, family problems, financial loss, sense of isolation and mental disorders. Depressive disorders and suicide As of 2015, over ****** million people worldwide suffered from some kind of depressive disorder. Furthermore, over ** percent of the total population in India suffer from different forms of mental disorders as of 2017. There exists a positive correlation between the number of suicide mortality rates and people with select mental disorders as opposed to those without. Risk factors for mental disorders Every ******* person in India suffers from some form of mental disorder. Today, depressive disorders are regarded as the leading contributor not only to disease burden and morbidity worldwide, but even suicide if not addressed. In 2022, the leading cause for suicide deaths in India was due to family problems. The second leading cause was due to illness. Some of the risk factors, relative to developing mental disorders including depressive and anxiety disorders, include bullying victimization, poverty, unemployment, childhood sexual abuse and intimate partner violence.

We present 10 tables with different, related data. Table 1 is the result of an extensive narrative literature review depicting published national secular suicide trends extending by at least a century. Table 2 pinpoints all reforms in the statistical national system by year, period and political regimen since 1886. In Table 3, we relate different consecutive versions of international classification of diseases and causes of death, by year of international approval and periodic implementation in the national statistical system, also by period of political regimen, depicting periods when different data was made accessible (sex, age), when categories of causes of external death begun to be collected (total external, suicide, accidents, undetermined), and types of dates were apt to be estimated (eg., crude death rates, age-standardised death rates, age-specific death rates); Table 3 also shows a cumulative index of years and attributes bibliographic primary sources for each line of data since 1886. Table 4 presents economic cycles – recession, stagnation, expansion –, in Portugal, by year, political regimen, with indicated sources, since 1886. Tables 5 to 9 present yearly raw numbers, crude death rates of suicide, accidents, and undetermined deaths, by sex, since 1886 for suicide and 1971 for accidents and undetermined deaths; and age-standardised death rates for the population aged more than 15 years old, by sex, since 1913 for suicide, and 1971 both for accidents and undetermined deaths. Table 10 lists the reference sources for mortality primary data and nosology changes by yearly periods. Finally, Figures shows structural changes and breakpoints, from 1913-2018, by sex and group of cause of death, taking general mortality as a gold standard.

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.

BackgroundThe rise of depression, anxiety, and suicide rates has led to increased demand for telemedicine-based mental health screening and remote patient monitoring (RPM) solutions to alleviate the burden on, and enhance the efficiency of, mental health practitioners. Multimodal dialog systems (MDS) that conduct on-demand, structured interviews offer a scalable and cost-effective solution to address this need.ObjectiveThis study evaluates the feasibility of a cloud based MDS agent, Tina, for mental state characterization in participants with depression, anxiety, and suicide risk.MethodSixty-eight participants were recruited through an online health registry and completed 73 sessions, with 15 (20.6%), 21 (28.8%), and 26 (35.6%) sessions screening positive for depression, anxiety, and suicide risk, respectively using conventional screening instruments. Participants then interacted with Tina as they completed a structured interview designed to elicit calibrated, open-ended responses regarding the participants' feelings and emotional state. Simultaneously, the platform streamed their speech and video recordings in real-time to a HIPAA-compliant cloud server, to compute speech, language, and facial movement-based biomarkers. After their sessions, participants completed user experience surveys. Machine learning models were developed using extracted features and evaluated with the area under the receiver operating characteristic curve (AUC).ResultsFor both depression and suicide risk, affected individuals tended to have a higher percent pause time, while those positive for anxiety showed reduced lip movement relative to healthy controls. In terms of single-modality classification models, speech features performed best for depression (AUC = 0.64; 95% CI = 0.51–0.78), facial features for anxiety (AUC = 0.57; 95% CI = 0.43–0.71), and text features for suicide risk (AUC = 0.65; 95% CI = 0.52–0.78). Best overall performance was achieved by decision fusion of all models in identifying suicide risk (AUC = 0.76; 95% CI = 0.65–0.87). Participants reported the experience comfortable and shared their feelings.ConclusionMDS is a feasible, useful, effective, and interpretable solution for RPM in real-world clinical depression, anxiety, and suicidal populations. Facial information is more informative for anxiety classification, while speech and language are more discriminative of depression and suicidality markers. In general, combining speech, language, and facial information improved model performance on all classification tasks.

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.

English: The data set contains 503 variables and 624 observations on suicides and suicide rates as well as on demographic, socio-structural, infrastructure and crime statistics on the canton and national level for the years 1952 to 1990. The information was recorded and processed by GDR’s Central Bureau of Statistics on a yearly basis. The statistical yearbooks of the GDR and various files of the Federal Archive were used as the sources of this data. The demographic statistics include the population distribution by gender and age-groups, the incidence of deaths, homicides, births, stillbirths, as well as infant mortality and domestic migration rates by year and administrative district. The socio-structural information includes marriage and divorce rates, population distribution by education, employment and religious denomination, as well as the number of members and candidates of the Socialist Unity Party of Germany by year and district. The infrastructure data contains information on population density, residential housing construction and retail sales by year and administrative canton. The annual numbers of offenders of criminally liable age and convicted persons in the districts that come from the GDR crime statistics were included in the data set from the GDR crime statistics. Missing values indicate that no information could be found for the given year or region. However, the missing information on the distribution by gender and age-groups, as well as suicide rates by age-group can be estimated using the attached do-files. A detailed description of how the missing values have been determined can be found in the document “Imputation und Standardisierung.pdf”. The do-files and the description are available in a zip file below. Deutsch: Dieser Datensatz umfasst 503 Variablen und 624 Beobachtungen. Er beinhaltet Informationen zu Suizidzahlen sowie demographische, sozialstrukturelle, infrastrukturelle Statistiken und Kriminalstatistiken in den Bezirken der DDR sowie des gesamten Landes von 1952 bis 1990. In der DDR war die Staatliche Zentralverwaltung für Statistik (SZS) für die Sammlung und Aufbereitung der verschiedenen Jahresstatistiken zuständig, weshalb die langen Zeitreihen größtenteils aus dem Primärbestand der SZS ermittelt und anschließend vergleichbar über die Bezirke und den Zeitverlauf berechnet wurden. Als Recherchequellen dienen die statistischen Jahrbücher der DDR sowie verschiedene Akten des Bundesarchivs. Die demographischen Statistiken umfassen die jährlichen bezirksspezifischen Verteilungen der Geschlechter, Altersgruppen, Verstorbenen, Ermordeten, Lebendgeborenen, Totgeborenen, gestorbenen Säuglinge und Binnenmigration. Die sozialstrukturellen Informationen umfassen Angaben zu regionalen Verteilungen der Eheschließung, Ehescheidung, Bildung, Beschäftigung und Konfession sowie Statistiken über die Mitgliedschaft und Kandidatur für eine Mitgliedschaft bei der SED. Die verschiedenen infrastrukturellen Daten umfassen jährliche Statistiken der Bevölkerungsdichte, des Wohnungsbaus und des Einzelhandelsumsatzes in den Bezirken der DDR. Zudem wurden aus der Kriminalstatistik der DDR die jährliche Anzahl der strafmündigen Täter und der Verurteilten in den Bezirken in den Datensatz aufgenommen. Missings werden in dem Datensatz ausgewiesen, wenn für bestimmte Jahre oder Regionen keine Zahlen recherchiert werden konnten bzw. die Informationen nicht erhoben wurden. Fehlende Suizidzahlen und fehlende Bevölkerungszahlen in bestimmten Altersgruppen können mittels der beigefügten Do-Files geschätzt und importiert werden. Eine ausführliche Beschreibung der Bestimmung der fehlenden Zahlen lassen sich dem Dokument „Imputation und Standardisierung.pdf“ entnehmen. Zudem ist ein unverzerrter Vergleich der Suizidraten über Regionen und Zeit nur anhand von standardisierten Suizidraten möglich. Auch dieses Vorgehen der indirekten Standardisierung ist im genannten Dokument beschrieben und kann anhand der Do-Files repliziert werden. Sie sind unten in einer Zip-Datei verfügbar.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Death by suicide is a major public health problem. People living with human immunodeficiency virus (PLHIV) have higher risk of suicidal behavior than the general population. The aim of this review is to summarize suicidal behavior, associated risk factors, and risk populations among PLHIV. Research studies in six databases from January 1, 1988, to July 8, 2021, were searched using keywords that included “HIV,” “suicide,” and “risk factors.” The study design, suicide measurement techniques, risk factors, and study findings were extracted. A total of 193 studies were included. We found that the Americas, Europe, and Asia have the highest rates of suicidal behavior. Suicide risk factors include demographic factors, mental illness, and physiological, psychological, and social support. Depression is the most common risk factor for PLHIV, with suicidal ideation and attempt risk. Drug overdosage is the main cause of suicide death. In conclusion, the current study found that PLHIV had experienced a high level of suicidal status. This review provides an overview of suicidal behavior and its risk factors in PLHIV with the goal of better managing these factors and thus preventing death due to suicide.

Questionnaire includes: Patient Health Questionnaire-2, The Depressive Symptom Index-Suicidality Subscale (DSI-SS), Interpersonal Needs Questionnaire (IPTS), Suicide Capacity Scale-3 (SCS-3), Suicide attempt:, Adverse childhood experiences (ACEs) , General Anxiety Disorder Questionnaire, The Suicide Behaviors Questionnaire- Revised (SBQ-R).

The indicator measures the number of deaths that result from suicide per 100 000 inhabitants. The World Health Organization defines suicide as an act deliberately initiated and performed by a person in the full knowledge or expectation of its fatal outcome. Data on causes of death (COD) refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of a standard European population. The number of suicides in certain countries may be under-reported because of the stigma associated with the act for religious, cultural or other reasons. The comparability of suicide data between countries is also affected by a number of reporting criteria, including how a person’s intention of killing him- or herself is ascertained or who is responsible for completing the death certificate. The product has been discontinued since: 29 Nov 2018.

Characteristics of four included reviews.