Consideration of Marital Status in a Mortality Model and its Application for Mortality Risk Management

2016 ◽  
Vol 10 (2) ◽  
Author(s):  
Hyuk-Sung Kwon
Keyword(s):  
Risk Factors ◽  
Marital Status ◽  
Mortality Risk ◽  
Life Insurance ◽  
Pension Plans ◽  
Never Married ◽  
Mortality Model ◽  
Logistic Regression Method ◽  
Mortality Table ◽  
Actuarial Model

AbstractAs a variety of mortality risk factors have been identified by previous studies, it is desirable that these factors are reflected in mortality (longevity) risk assessments for life insurance, individual annuities, and pension plans. In this study, an extended traditional mortality table that accommodates marital status, which is one of the important risk factors in terms of mortality, is considered. A logistic regression method is used to model the mortality of groups of people with four different marital statuses–never married, married, widowed, and divorced. The analyses are based on data regarding mortality and changes of marital status in Korea. The results of the analyses that are based on the developed mortality model suggest that the information on risk factors must be reflected in an actuarial model to improve the evaluations and monitoring of risk for the portfolios of relevant insurance products.

Assessment of the Risk Factors of MDD Recurrence Based on Deep Learning Approaches

2021 ◽  
Vol 6 (3) ◽  
Author(s):  
Wu Q ◽  
◽  
Zhao W ◽  
Yang X ◽  
Tan H ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Marital Status ◽  
Prediction Accuracy ◽  
Learning Approaches ◽  
Never Married ◽  
Factors Associated ◽  
Diagnosis Codes ◽  
Icd 10 ◽  
And Control

Objective: Explore the risk factors related to the recurrence of MDD and provide a basis for the prevention and control of MDD. Methods: Patients with MDD were extracted from two large, multi-center clinical datasets. The inpatients and outpatients between January 2000 and December 2015 were collected. Eligible patients were 18-90 years-old and had a diagnosis of MDD. The MDD were identified based on the MDD-related ICD-9- CM diagnosis codes; and MDD-related ICD-10-CM diagnosis codes. Eventually, 140,497 patients were qualified for further analysis, including 69.2% female patients. Among of 140,497, 20, 078 patients (14.3%) had no comorbidities. Logistic regression, SVM, and LSTM were employed to predict the key risk factors associated with MDD recurrence. Results: The MDD patients with married /life partners had a lower prevalence rate (9.2%) of MDD recurrence than the patients with single marital status (11.8%). The primary MDD patients had a higher MDD recurrent rate (11.7%) than secondary MDD patients (10.5%). Primary MDD was associated with MDD recurrence (OR 2.49, 95% CI 1.53-3.96) via logistic regression analysis. Insomnia, anxiety and single marital status were also top-ranked risk factors for the MDD recurrence. The prediction accuracy of logistic regression, SVM and LSTM were 0.736, 0.791 and 0.834, respectively. Conclusions: Building statistical models by mining existing EHR data can explore the risk factors associated with MDD recurrence. Our results indicated that primary MDD, never married, anxiety symptoms, and insomnia were risk factors for MDD recurrence. The prediction accuracy of the LSTM model was higher than the other two approaches.

scholarly journals Protective and Risk Factors of Depression Among Older Adults During the COVID-19 Pandemic

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 726-727
Author(s):  
Yeonjung Lee ◽  
Tyran Terada
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Depressive Symptoms ◽  
Marital Status ◽  
Protective Factor ◽  
Well Being ◽  
Never Married ◽  
Married People ◽  
Status Data ◽  
Retirement Study

Abstract The coronavirus disease 2019 (COVID-19) pandemic adversely impacted the mental health of older adults. This study aims to explore the associations between protective/risk factors of depression during the pandemic and to examine the differences in these associations by marital status. Data from the Health and Retirement Study 2020 COVID-19 module, released in February, 2021, were used. The level of resilience during the pandemic was selected as a protective factor. The level of COVID-19 pandemic concern was selected as a risk factor. Among older adults aged 51 years and older, the weighted regression model found that higher levels of COVID-19 concern were associated with higher levels of depressive symptoms (p<0.05), whereas higher levels of resilience were associated with lower levels of depressive symptoms (p<0.05). Marital status moderated the association between COVID-19 concern and depressive symptoms. Never-married people were at higher risk of depressive symptoms than married people when COVID-19 concerns increased. It is important to enhance support for never-married people during the pandemic to protect their psychological well-being.

Non-Spousal Support, Marital Status, and Mortality Risk

2021 ◽  
pp. 089826432110253
Author(s):  
Adam R. Roth ◽  
Siyun Peng
Keyword(s):  
Older Adults ◽  
Marital Status ◽  
Mortality Risk ◽  
Social Life ◽  
Spousal Support ◽  
Later Life ◽  
Future Research ◽  
Never Married ◽  
Logistic Regression Models ◽  
Using Data

Objective To investigate whether the association between non-spousal support and mortality risk differs by marital status. Methods Using data from the National Social Life, Health, and Aging Project (N = 2460), we estimate a series of logistic regression models to assess how non-spousal support moderates the relationship between marital status and mortality across a 5-year period. Results Never married respondents who had minimal perceived access to non-spousal support had a greater probability of death compared to married respondents with similar levels of non-spousal support. The disparity in mortality risk between these two groups disappeared when non-spousal support was high. Discussion Although family and friends play an important role in mortality risk in later life, these findings suggest that never married older adults exhibit a heightened dependence on support from non-spousal sources. Future research and policies should explore ways in which never married older adults can be integrated into a supportive social environment.

Age and marital status predictors of binge alcohol use among adults with major depressive episode

2020 ◽  
Author(s):  
Areen Omary
Keyword(s):  
At Risk ◽  
Alcohol Use ◽  
Marital Status ◽  
Depressive Episode ◽  
Major Depressive Episode ◽  
Age Groups ◽  
Future Research ◽  
Major Depressive ◽  
Never Married ◽  
At Risk Populations

Aims: This study aims to examine if age and marital status can predict the risk for binge alcohol use (BAU) among adults with a major depressive episode (MDE). Methods: Data from the Substance Abuse and Mental Health Services Administration’s (SAMHSA) 2018 National Survey for Drug Use and Health (NSDUH) were analyzed. The unweighted sample included 6,999 adults representing a weighted population size of 33,900,452.122 in the US. Results and Conclusions: The findings of this retrospective research confirmed that age and marital status significantly predicted BAU in the past month among adults with MDE. Adults with MDE at higher risk for BAU were adults under the age of 50, adults who were never married, and adults who were divorced/separated. Special attention must be paid to those in age groups under 50, never married, and have been separated/divorced who are particularly at-risk for future alcohol abuse. Future research should consider examining additional potential confounders for BAU among other at-risk populations.

scholarly journals Burden of Respiratory Syncytial Virus Disease and Mortality Risk Factors in Argentina

2019 ◽  
Vol 38 (6) ◽  
pp. 589-594 ◽  
Author(s):  
Angela Gentile ◽  
María Florencia Lucion ◽  
María del Valle Juarez ◽  
María Soledad Areso ◽  
Julia Bakir ◽  
...  
Keyword(s):  
Risk Factors ◽  
Respiratory Syncytial Virus ◽  
Mortality Risk ◽  
Virus Disease ◽  
Respiratory Syncytial Virus Disease ◽  
Syncytial Virus

Mortality Risk Factors in Chronic Renal Failure Patients after Coronary Artery Bypass Grafting

Renal Failure ◽  
2007 ◽  
Vol 29 (7) ◽  
pp. 823-828 ◽  
Author(s):  
Beril Akman ◽  
Ayse Bilgic ◽  
Gulsah Sasak ◽  
Siren Sezer ◽  
Atilla Sezgin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Renal Failure ◽  
Coronary Artery ◽  
Chronic Renal Failure ◽  
Coronary Artery Bypass Grafting ◽  
Coronary Artery Bypass ◽  
Mortality Risk ◽  
Artery Bypass ◽  
Bypass Grafting ◽  
Artery Bypass Grafting

scholarly journals 699 Sleep Health Traits and COVID-19: Mortality Risk from the UK Biobank

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A273-A273
Author(s):  
Xi Zheng ◽  
Ma Cherrysse Ulsa ◽  
Peng Li ◽  
Lei Gao ◽  
Kun Hu
Keyword(s):  
Risk Factors ◽  
Sleep Apnea ◽  
Sleep Duration ◽  
Sex Education ◽  
Mortality Risk ◽  
Self Report ◽  
Severe Illness ◽  
Uk Biobank ◽  
Sleep Health ◽  
The Uk

Abstract Introduction While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3; range 50.2–84.6). Self-reported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/”intermediate”/”evening”), daytime dozing (often/rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (>9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%); OR 2.09, 95% 1.19–3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04–2.72, p=0.03), and nappers (OR 1.52, 95% 1.04–2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25–3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19. Support (if any) NIH [T32GM007592 and R03AG067985 to L.G. RF1AG059867, RF1AG064312, to K.H.], the BrightFocus Foundation A2020886S to P.L. and the Foundation of Anesthesia Education and Research MRTG-02-15-2020 to L.G.

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