The primary data source for this study is the Northern Ireland Longitudinal Study (NILS), which in 2001 defined a representative cohort of c.28% of the population. It is formed from the linkage of the universal Health Card registration system, 2001 Census returns, and vital statistics data. NILS contains a unique Health and Care Number that enables linkage to other health service databases. It is maintained by the Northern Ireland Statistics and Research Agency (NISRA). The 2001 Census records provided most of the attributes of the NILS cohort members, also contextual information relating to household composition and interpersonal relationships, and characteristics of the household and area of residence.

The vital events linked to NILS were used to determine whether a cohort member had been bereaved between April 2001 (the time of the Census) and the end of December 2009. The 2001 Census asked questions about relationship to other people living in the household, these questions were used to determine who a cohort member lived with, and the vital events records identified co-resident family members’ deaths. Approximately 96% of death records are routinely linked to the NILS dataset using a mixture of exact and probabilistic matching.

Data relating to medications that have been prescribed by a General Practitioner and dispensed from community pharmacies have been collated centrally in an Enhanced Prescribing Database (EPD) since 2009. Each prescription record contains the individual’s Health and Care Number, a General Practice (GP) identifier, the drug name and British National Formulary (BNF) category. Information was extracted for antidepressant and anxiolytic medications (BNF categories 4.1.2 and 4.3) for the period January 1st to February 28th 2010. Health and Care Number allowed exact matching between prescribing and NILS records. The linkage process was carried out by the EPD and NILS data custodians. The linked dataset was then anonymised before being supplied to the researchers, and was held in a secure setting (9). At no time were patient identifiable data available.

The data used for the Grief study is not publicly available, but researchers can make a request to link data for themselves by contacting the Northern Ireland Longitudinal Study Research Support Unit

Everybody will face bereavement at some stage; but for some people, this can be a more difficult process. There are many factors that can influence how people cope with the loss of a loved one, including level of family support, financial resources, stress, and the circumstances surrounding death.By studying use of prescription medications to help with mental health, we can get a better understanding of how factors such as age, gender, family support, employment and religion affect how people cope after bereavement. By looking at circumstances of bereavement this study will also discover if the factors that help people cope - such as family support - are more or less important depending on how they lost their loved ones.The Grief Study is based on data from the Northern Ireland Longitudinal Study, this holds information on around 500,000 people. By linking this data with the Northern Ireland Mortality Study and Health and Social care information on prescriptions, the Grief Study aims to learn more about bereavement, mental health, complicated grief, and longer term outcomes for people who have lost a loved one.

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.

Grief is a natural response to the death of a loved one. Grief may vary between individuals and across time. When grief reactions are so intense that they disrupt daily functioning, a prolonged grief disorder (PGD) may apply. Most studies on PGD rely on cross-sectional survey data, which provide insights into between-person differences but are impossible to examine within person moment-to-moment changes in grief reactions. The Grief in Daily Life (Grief-ID) archive addresses this gap by providing harmonized datasets from ecological momentary assessment (EMA) projects. The use of EMA captures time- and context-dependent changes, disentangles between-person from within-person effects, reduces recall bias, and offers a more ecologically valid assessment of grief reactions. The archive complies with Findable, Accessible, Interoperable, Reusable (FAIR) research guiding principles and provides extensive metadata corresponding to each principle. Researchers are encouraged to reuse and contribute data to the Grief-ID archive, thereby furthering our understanding of grief in daily life. Data Collection Version 1.0 of the archive includes 315 participants and 22,050 EMA measurement points. On average, participants responded to 43.77 ESM notifications in total, with the median being 50, on a scale from 1 to 70, which reflects an overall compliance rate of 71%. Individuals aged 18 years and above were eligible to participate. People diagnosed with a psychotic disorder or those reporting suicidal ideation, assessed at baseline, were excluded from participation. The studies included in Version 1.0 consisted of three distinct phases of data collection. First, the initial baseline measures included questions assessing sociodemographic, loss characteristics, measures of psychopathology, and other measures. Second, the ESM phase was conducted using the Avicenna application (Avicenna Research, 2024). Participants rated the intensity of PGD symptoms and contextual factors five times a day, for a period of 14 days. Third, the final phase of the study was conducted following the ESM phase. In this phase, psychopathology symptoms were assessed in a manner consistent with that employed in phase one. Differences in recruitment strategies and inclusion criteria between the three different projects are outlined in supporting information. Accessibility To receive the data file, you are required to pre-register your study for the use of the Grief-ID Archive. More details can be found in the Data Access Protocol. Please complete the Data Access Protocol and send it to the designated points of contact listed in the data accessibility instructions. All metadata is openly available. More Information A detailed description of the archive, methodology, and datasets can be found in the accompanying data note: https://doi.org/10.13140/RG.2.2.12452.80004

This dataset contains counts of deaths for California as a whole 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 California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California 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.

Death statistics (i) Number of Deaths for Different Sexes and Crude Death Rate for the Period from 1981 to 2023 (ii) Age-standardised Death Rate (Overall and by Sex) for the Period from 1981 to 2023 (iii) Age-specific Death Rate for Year 2013 and 2023 (iv) Death Rates by Leading Causes of Death for the Period from 2001 to 2023 (v) Number of Deaths by Leading Causes of Death for the Period from 2001 to 2023 (vi) Age-standardised Death Rates by Leading Causes of Death for the Period from 2001 to 2023 (vii) Late Foetal Mortality Rate for the Period from 1981 to 2023 (viii) Perinatal Mortality Rate for the Period from 1981 to 2023 (ix) Neonatal Mortality Rate for the Period from 1981 to 2023 (x) Infant Mortality Rate for the Period from 1981 to 2023 (xi) Number of Maternal Deaths for the Period from 1981 to 2023 (xii) Maternal Mortality Ratio for the Period from 1981 to 2023

This dataset presents the age-adjusted death rates for the 10 leading causes of death in the United States beginning in 1999. Data are based on information from all resident death certificates filed in the 50 states and the District of Columbia using demographic and medical characteristics. Age-adjusted death rates (per 100,000 population) are based on the 2000 U.S. standard population. Populations used for computing death rates after 2010 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for non-census years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Causes of death classified by the International Classification of Diseases, Tenth Revision (ICD–10) are ranked according to the number of deaths assigned to rankable causes. Cause of death statistics are based on the underlying cause of death. SOURCES CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Murphy SL, Xu JQ, Kochanek KD, Curtin SC, and Arias E. Deaths: Final data for 2015. National vital statistics reports; vol 66. no. 6. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_06.pdf.

Financial overview and grant giving statistics of Life Grief Support Ministry

Financial overview and grant giving statistics of Global Grief Support Inc

In the United States in 2021, the death rate was highest among those aged 85 and over, with about 17,190.5 men and 14,914.5 women per 100,000 of the population passing away. For all ages, the death rate was at 1,118.2 per 100,000 of the population for males, and 970.8 per 100,000 of the population for women. The death rate Death rates generally are counted as the number of deaths per 1,000 or 100,000 of the population and include both deaths of natural and unnatural causes. The death rate in the United States had pretty much held steady since 1990 until it started to increase over the last decade, with the highest death rates recorded in recent years. While the birth rate in the United States has been decreasing, it is still currently higher than the death rate. Causes of death There are a myriad number of causes of death in the United States, but the most recent data shows the top three leading causes of death to be heart disease, cancers, and accidents. Heart disease was also the leading cause of death worldwide.

Explore Grief therapy-Case studies through data from visualizations to datasets, all based on diverse sources.

This data package contains: Document describing data cleaning (in Dutch), Anonymized data for SPSS. Syntaxes and outputs belonging to the published article: 2 SPSS syntaxes. One for general analyses and one for creating Mplus data file. Mplus output files ((per analysis) output files contain the syntaxes). Abstract from paper: Prolonged grief disorder, characterized by severe, persistent and disabling grief, has recently been added to the DSM-5-TR and ICD-11. Treatment for prolonged grief symptoms shows limited effectiveness. It has been suggested that prolonged grief symptoms exacerbate insomnia symptoms, whereas insomnia symptoms, in turn, may fuel prolonged grief symptoms. To help clarify if treating sleep disturbances may be a viable treatment option for prolonged grief disorder, we examined the proposed reciprocal relationship between symptoms of prolonged grief and insomnia. On three time points across six-month intervals, 343 bereaved adults (88% female) completed questionnaires to assess prolonged grief, depression, and insomnia symptoms. We applied random intercept cross-lagged panel models (RICLPMs) to assess reciprocal within-person effects between prolonged grief and insomnia symptoms and, as a secondary aim, between depression and insomnia symptoms. Changes in insomnia symptoms predicted changes in prolonged grief symptoms but not vice versa. Additionally, changes in depression and insomnia symptoms showed a reciprocal relationship. Our results suggest that targeting insomnia symptoms after bereavement is a viable option for improving current treatments for prolonged grief disorder.

This data collection consists of three data files, which can be used to determine infant mortality rates. The first file provides linked records of live births and deaths of children born in the United States in 1990 (residents and nonresidents). This file is referred to as the "Numerator" file. The second file consists of live births in the United States in 1990 and is referred to as the "Denominator-Plus" file. Variables include year of birth, state and county of birth, characteristics of the infant (age, sex, race, birth weight, gestation), characteristics of the mother (origin, race, age, education, marital status, state of birth), characteristics of the father (origin, race, age, education), pregnancy items (prenatal care, live births), and medical data. Beginning in 1989, a number of items were added to the U.S. Standard Certificate of Birth. These changes and/or additions led to the redesign of the linked file record layout for this series and to other changes in the linked file. In addition, variables from the numerator file have been added to the denominator file to facilitate processing, and this file is now called the "Denominator-Plus" file. The additional variables include age at death, underlying cause of death, autopsy, and place of accident. Other new variables added are infant death identification number, exact age at death, day of birth and death, and month of birth and death. The third file, the "Unlinked" file, consists of infant death records that could not be linked to their corresponding birth records.

Data for deaths by leading cause of death categories are now available in the death profiles dataset for each geographic granularity.

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.

Cause of death categories for years 1999 and later are based on tenth revision of International Classification of Diseases (ICD-10) codes. Comparable categories are provided for years 1979 through 1998 based on ninth revision (ICD-9) codes. For more information on the comparability of cause of death classification between ICD revisions see Comparability of Cause-of-death Between ICD Revisions.

The dataset contains longitudinal survey data that was used to examine the reciprocal associations between prolonged grief symptoms and state anger levels. In addition, the data were used to explore whether aspects related to the criminal justice system were related to prolonged grief symptoms and state anger levels. In our paper titled "Reciprocal relations between prolonged grief and anger in homicidally bereaved people involved in a criminal trial: A four-wave cross-lagged panel model", 237 MH17 bereaved people are included. Here in DANS, the dataset contains data from 225 MH17 bereaved people, because 12 people did not provide consent to any of their data being shared. Participants were eligible to participate if they were 18 years old or older, could understand either Dutch or English, and lost one or more loved ones during the MH17 plane disaster that took place on July 17 2014. The data were collected 67, 79, 88, and 103 months after the MH17 plane disaster. During each wave of the study, prolonged grief symptoms and state anger levels were assessed, using the Traumatic Grief Inventory Self-Report Plus (TGI-SR+) and the State-Trait Anger Expression Inventory 2 (STAXI-II), respectively. The first wave took place before, the second and third during, and the fourth after the criminal trial. Various characteristics of the criminal trial were assessed at different waves, including whether the participant received monetary compensation and delivered a victim impact statement, how satisfied the participant was with different professionals and the verdict, and the number of statements the participant listened to. Accessibility Due to the sensitive nature of the dataset, the data can be viewed upon reasonable request.

United States US: Death Rate: Crude: per 1000 People data was reported at 8.400 Ratio in 2016. This records a decrease from the previous number of 8.440 Ratio for 2015. United States US: Death Rate: Crude: per 1000 People data is updated yearly, averaging 8.700 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 9.800 Ratio in 1968 and a record low of 7.900 Ratio in 2009. United States US: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A word on the flaws of numbers like this

People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

This data collection presents information about the causes of deaths occurring in the United States during 1959 to 1967. Data are provided concerning underlying causes of death, place of death, whether there were multiple conditions that caused the death, and what those conditions were. In addition, data are provided on date of death, and on sex, race, age, marital status, and origin or descent of the deceased. Also included is information on residence of the deceased (state, county, city, region, and whether the county was a metropolitan or nonmetropolitan area). The 1967 data file does not match the PDF documentation. This file was created by comparing means and frequencies to 1967 VSUS tables and/or the 1966 file.

This data collection consists of three data files, which can be used to determine infant mortality rates. The first file provides linked records of live births and deaths of children born in the United States in 1989 (residents and nonresidents). This file is referred to as the "Numerator" file. The second file consists of live births in the United States in 1989 and is referred to as the "Denominator-Plus" file. Variables include year of birth, state and county of birth, characteristics of the infant (age, sex, race, birth weight, gestation), characteristics of the mother (origin, race, age, education, marital status, state of birth), characteristics of the father (origin, race, age, education), pregnancy items (prenatal care, live births), and medical data. Beginning in 1989, a number of items were added to the U.S. Standard Certificate of Birth. These changes and/or additions led to the redesign of the linked file record layout for this series and to other changes in the linked file. In addition, variables from the numerator file have been added to the denominator file to facilitate processing, and this file is now called the "Denominator-Plus" file. The additional variables include age at death, underlying cause of death, autopsy, and place of accident. Other new variables added are infant death identification number, exact age at death, day of birth and death, and month of birth and death. The third file, the "Unlinked" file, consists of infant death records that could not be linked to their corresponding birth records.

The COVID-19 pandemic resulted in an increase in the global death rate, but had little to no significant impact on birth rates, causing population growth to dip slightly. On a global level, population growth is determined by the difference between the birth and death rate, and this is known as the rate of natural change - on a national or regional level, population change is also affected by migration. Ongoing trends Since the middle of the 20th century, the global birth rate has been well above the global death rate, however, the gap between these figures has grown closer in recent years. The death rate is projected to overtake the birth rate in the 2080s, which means that the world's population will then go into decline. In the future, death rates will increase due to ageing populations across the world and a plateau in life expectancy. Why does this change? There are many reasons for falling death and birth rates in recent decades. Falling death rates have been driven by a reduction in infant and child mortality, as well as increased life expectancy. Falling birth rates were also driven by the reduction in child mortality, whereby mothers would have fewer children as survival rates rose - other factors include the drop in child marriage, improved contraception access and efficacy, and women choosing to have children later in life.

Net Birth & Death Adj: Post Benchmark Estimates: Total Nonfarm data was reported at -23.000 Unit th in Dec 2017. This records a decrease from the previous number of 8.000 Unit th for Nov 2017. Net Birth & Death Adj: Post Benchmark Estimates: Total Nonfarm data is updated monthly, averaging 94.000 Unit th from Apr 2002 (Median) to Dec 2017, with 147 observations. The data reached an all-time high of 271.000 Unit th in Apr 2006 and a record low of -391.000 Unit th in Jan 2003. Net Birth & Death Adj: Post Benchmark Estimates: Total Nonfarm data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G042: Current Employment Statistics: Birth-Death Adjustment.