The impact of social context on socio-demographic risk factors for suicide: a synthesis of data from case-control studies

2009 ◽  
Vol 64 (6) ◽  
pp. 530-534 ◽  
Author(s):  
M. J. Crawford ◽  
B. Kuforiji ◽  
P. Ghosh
Keyword(s):  
Risk Factors ◽  
Social Context ◽  
Case Control ◽  
Case Control Studies ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
The Impact ◽  
Risk Factors For Suicide

scholarly journals The case for case–control studies in the field of suicide prevention

2019 ◽  
Vol 29 ◽  
Author(s):  
Jane Pirkis ◽  
Angela Nicholas ◽  
David Gunnell
Keyword(s):  
Risk Factors ◽  
Stressful Life Events ◽  
Suicide Attempts ◽  
Hospital Admissions ◽  
Population Based ◽  
Case Control ◽  
Psychological Autopsy ◽  
Case Control Studies ◽  
Middle Income ◽  
Risk Factors For Suicide

Abstract Much of our knowledge about the risk factors for suicide comes from case–control studies that either use a psychological autopsy approach or are nested within large register-based cohort studies. We would argue that case–control studies are appropriate in the context of a rare outcome like suicide, but there are issues with using this design. Some of these issues are common in psychological autopsy studies and relate to the selection of controls (e.g. selection bias caused by the use of controls who have died by other causes, rather than live controls) and the reliance on interviewing informants (e.g. recall bias caused by the loved ones of cases having thought about the events leading up to the suicide in considerable detail). Register-based studies can overcome some of these problems because they draw upon contain information that is routinely collected for administrative purposes and gathered in the same way for cases and controls. However, they face issues that mean that psychological autopsy studies will still sometimes be the study design of choice for investigating risk factors for suicide. Some countries, particularly low and middle income countries, don't have sophisticated population-based registers. Even where they do exist, there will be variable of interest that are not captured by them (e.g. acute stressful life events that may immediately precede a suicide death), or not captured in a comprehensive way (e.g. suicide attempts and mental illness that do not result in hospital admissions). Future studies of risk factors should be designed to progress knowledge in the field and overcome the problems with the existing studies, particularly those using a case–control design. The priority should be pinning down the risk factors that are amenable to modification or mitigation through interventions that can successfully be rolled out at scale.

scholarly journals Sociocultural and Demographic Risk Factors for the Development of Multiple Sclerosis in Kuwait: A Case - Control Study

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0132106 ◽  
Author(s):  
Suhail N. Al-Shammri ◽  
Magdy G. Hanna ◽  
Arpita Chattopadhyay ◽  
Abayomi O. Akanji
Keyword(s):  
Risk Factors ◽  
Multiple Sclerosis ◽  
Case Control Study ◽  
Case Control ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
Control Study

scholarly journals Identifying socio-demographic risk factors for suicide using data on an individual level

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guus Berkelmans ◽  
Rob van der Mei ◽  
Sandjai Bhulai ◽  
Renske Gilissen
Keyword(s):  
Risk Factors ◽  
Low Income ◽  
Individual Level ◽  
Highly Educated ◽  
Aged People ◽  
Physical Health Problems ◽  
Using Data ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
Risk Factors For Suicide

Abstract Background Suicide is a complex issue. Due to the relative rarity of the event, studies into risk factors are regularly limited by sample size or biased samples. The aims of the study were to find risk factors for suicide that are robust to intercorrelation, and which were based on a large and unbiased sample. Methods Using a training set of 5854 suicides and 596,416 control cases, we fit a logistic regression model and then evaluate the performance on a test set of 1425 suicides and 594,893 control cases. The data used was micro-data of Statistics Netherlands (CBS) with data on each inhabitant of the Netherlands. Results Taking the effect of possible correlating risk factors into account, those with a higher risk for suicide are men, middle-aged people, people with low income, those living alone, the unemployed, and those with mental or physical health problems. People with a lower risk are the highly educated, those with a non-western immigration background, and those living with a partner. Conclusion We confirmed previously known risk factors such as male gender, middle-age, and low income and found that they are risk factors that are robust to intercorrelation. We found that debt and urbanicity were mostly insignificant and found that the regional differences found in raw frequencies are mostly explained away after correction of correlating risk factors, indicating that these differences were primarily caused due to the differences in the demographic makeup of the regions. We found an AUC of 0.77, which is high for a model predicting suicide death and comparable to the performance of deep learning models but with the benefit of remaining explainable.

Demographic risk factors for suicide and depression among Serbian medical school students

2014 ◽  
Vol 50 (4) ◽  
pp. 633-638 ◽  
Author(s):  
Vladimir Miletic ◽  
Jasminka Adzic Lukovic ◽  
Nevena Ratkovic ◽  
Danijela Aleksic ◽  
Anita Grgurevic
Keyword(s):  
Risk Factors ◽  
Medical School ◽  
School Students ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
Risk Factors For Suicide ◽  
Medical School Students

scholarly journals Behavioral, health- related and demographic risk factors of death in floods: A case-control study

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0262005
Author(s):  
Arezoo Yari ◽  
Homa Yousefi Khoshsabegheh ◽  
Yadolah Zarezadeh ◽  
Ali Ardalan ◽  
Mohsen Soufi Boubakran ◽  
...  
Keyword(s):  
Risk Factors ◽  
Behavioral Health ◽  
Case Control Study ◽  
Case Control ◽  
Control Group ◽  
Case Group ◽  
Health Related ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
Control Study

During the first half of 2019, many provinces of Iran were affected by floods, which claimed the lives of 82 people. The present study aimed to investigate the behavioral, health related and demographic risk factors associated with deaths due to floods. We measured the odds ratio and investigated the contribution and significance of the factors in relation to mortality. This case-control study was conducted in the cities affected by flood in Iran. Data were collected on the flood victims using a questionnaire. Survivors, a member of the flood victim’s family, were interviewed. In total, 77 subjects completed the survey in the case group, and 310 subjects completed the survey in the control group. The findings indicated that factors such as the age of less than 18 years, low literacy, being trapped in buildings/cars, and risky behaviors increased the risk of flood deaths. Regarding the behavioral factors, perceived/real swimming skills increased the risk of flood deaths although it may seem paradoxical. This increment is due to increased self confidence in time of flood. On the other hand, skills and abilities such as evacuation, requesting help, and escape decreased the risk of flood deaths. According to the results, the adoption of support strategies, protecting vulnerable groups, and improving the socioeconomic status of flood-prone areas could prevent and reduce the risk of flood deaths.

scholarly journals Distribution of the environmental and socioeconomic risk factors on COVID-19 death rate across continental United States: A spatial nonlinear analysis

2020 ◽  
Author(s):  
Yaowen Luo ◽  
Jianguo Yan ◽  
Stephen McClure
Keyword(s):  
Risk Factors ◽  
Random Forest ◽  
Regression Model ◽  
Environmental Protection Agency ◽  
Death Rate ◽  
Linear Models ◽  
Global Regression ◽  
Demographic Risk ◽  
Demographic Risk Factors ◽  
The Impact

Abstract The COVID-19 outbreak has become a global pandemic. Spatial variation in the environmental, health, socioeconomic, and demographic risk factors of COVID-19 death rate is not well understood. Global models and local linear models were used to estimate the impact of risk factors of the COVID-19, but these do not account for the nonlinear relationships between the risk factors and the COVID-19 death rate at various geographical locations. We proposed a local nonlinear nonparametric regression model named geographically weighted random forest (GW-RF) to estimate the nonlinear relationship between COVID-19 death rate and 47 risk factors derived from US Environmental Protection Agency, National Center for Environmental Information, Centers for Disease Control and the US census. The COVID-19 data were employed to a global regression model random forest (RF) and a local model GW-RF. The adjusted R2 of the RF is 0.69. The adjusted R2 of the proposed GW-RF is 0.78. The result of GW-RF showed that the risk factors (i.e. going to work by walking, airborne benzene concentration, householder with a mortgage, unemployment, airborne PM2.5 concentration and percent of the black or African American) have a high correlation with the spatial distribution of the COVID-19 death rate and these key factors driven from the GW-RF were mapped, which could provide useful implications for controlling the spread of COVID-19 pandemic.

Sign in / Sign up

Export Citation Format

Share Document