Health and life insurance-related problems in very long-term cancer survivors in Germany: a population-based study.

PURPOSE: Limited research suggests that cancer survivors have problems with insurance. Our study aimed to gain insight into the proportion of very long-term (14-24 years post-diagnosis) survivors of breast, colorectal, and prostate cancers who had problems with health (HI) and life (LI) insurance. METHODS: We used data from CAESAR (CAncEr Survivorship-A multi-Regional population-based study). Participants completed questions on change in insurance providers since cancer diagnosis, problems with requesting (additional) HI or LI, and how potential problems were resolved. We conducted logistic regression to determine factors associated with change in statutory HI. RESULTS: Of the 2714 respondents, 174 (6%) reported having changed HI providers. Most switched between different statutory HI providers (86%), 9% from statutory to private, and 5% from private to statutory. Respondents who changed statutory HI providers were more likely to be prostate cancer survivors (OR 2.79, 95% CI 1.01-7.68) while being ≥ 65 years at time of diagnosis (OR 0.58, 95% CI 0.35-0.96) and having ≥ 2 comorbid conditions (OR 0.61, 95% CI 0.40-0.92) were associated with reduced odds for change. Problems in changing HI were minimal and were resolved with additional contribution. Of the 310 respondents who tried to get LI, 25 respondents reported having difficulties, of whom the majority had their request rejected. CONCLUSION: Most cancer survivors did not change their HI nor tried to buy LI after cancer diagnosis. Problems with changing statutory HI were generally resolved with additional contribution while the main problem encountered when buying LI was rejection of request.

Effect of air pollution on household insurance purchases. Evidence from China household finance survey data.

In recent years, the health and economic effects of air pollution have attracted considerable attention, and health and insurance services have been closely related to residents' welfare. However, there are few studies on the influence of pollution on household purchases of insurance. Using data from the 2013 and 2015 China Household Finance Surveys, this study investigates the effect of air pollution on insurance purchases using Logit and Poisson regression models. It is found that air pollution significantly increases the probability of household insurance purchases and the level of premium expenditure, although the impact of air pollution on insurance purchases shows a degree of heterogeneity. Health insurance is more sensitive to air pollution than life insurance and other types of insurance. In areas where NO2 and O3 are the main types of pollutants, air pollution has a greater impact on household insurance purchases.

Predictors of Health Insurance, Life Insurance, and Retirement Savings Among NYC's Immigrant Taxi and For-Hire Vehicle Drivers.

Taxi and for-hire vehicle (FHV) drivers are a predominantly immigrant population facing a range of occupational stressors, including lack of workplace benefits and increasing financial strain from tumultuous industry changes and now COVID-19's devastating impact. Bilingual research staff surveyed 422 New York City taxi/FHV drivers using a stratified sampling approach in driver-frequented locations to examine drivers' health and financial planning behaviors for the first time. Drivers lacked health insurance at double the NYC rate (20% vs. 10%). Life insurance and retirement savings rates were lower than U.S. averages (20% vs. 60%, 25% vs. 58%, respectively). Vehicle ownership was a significant predictor of health insurance, life insurance, and retirement savings. Compared to South Asian drivers, Sub-Saharan African drivers were significantly less likely to have health insurance and North African, and Middle Eastern drivers were significantly less likely to have retirement savings. Although most drivers indicated the importance of insurance and benefits, < 50% understood how to use them. Drivers felt primary care coverage to be most important followed by other health-related coverage, retirement benefits, and life insurance. Results reveal compelling addressable gaps in insurance and benefits coverage and the need to implement accessible financial literacy with navigation and advising services and programs.

A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients.

OBJECTIVE: Many cancer survivors are facing difficulties in getting a life insurance; raised premiums and declinatures are common. We generated a prediction model estimating the conditional extra mortality risk of breast cancer patients in the Netherlands. This model can be used by life insurers to accurately estimate the additional risk of an individual patient, conditional on the years survived. METHODOLOGY: All women diagnosed with stage I-III breast cancer in 2005-2006, treated with surgery, were selected from the Netherlands Cancer Registry. For all stages separately, multivariable logistic regression was used to estimate annual mortality risks, conditional on the years survived, until 10 years after diagnosis, resulting in 30 models. The conditional extra mortality risk was calculated by subtracting mortality rates of the general Dutch population from the patient mortality rates, matched by age, gender and year. The final model was internally and externally validated, and tested by life insurers. RESULTS: We included 23,234 patients: 10,101 stage I, 9,868 stage II and 3,265 stage III. The final models included age, tumor stage, nodal stage, lateralization, location within the breast, grade, multifocality, hormonal receptor status, HER2 status, type of surgery, axillary lymph node dissection, radiotherapy, (neo)adjuvant systemic therapy and targeted therapy. All models showed good calibration and discrimination. Testing of the model by life insurers showed that insurability using the newly-developed model increased with 13%, ranging from 0%-24% among subgroups. CONCLUSION: The final model provides accurate conditional extra mortality risks of breast cancer patients, which can be used by life insurers to make more reliable calculations. The model is expected to increase breast cancer patients' insurability and transparency among life insurers.

All-Cause Mortality for Life Insurance Applicants with a Family History of Coronary Artery Disease Before 60.

OBJECTIVE: -To determine the all-cause mortality of life insurance applicants having a family history of coronary artery disease (CAD) before age 60. BACKGROUND: -Epidemiological studies have shown that a family history of premature CAD is an independent risk factor for CAD events. The strength of the association between family history and CAD is greatest with earlier age of presentation of CAD in the family member and when multiple family members are affected. Despite earlier insurance studies on this relationship, there is sparse current data on the association between family history of CAD and all-cause mortality in life insurance applicants. METHODOLOGY: -Life insurance applicants with reported family history of Coronary Artery Disease (CAD) were extracted from data covering United States residents between October 2009 and October 2016. Information about these applicants was matched to the Social Security Death Master (SSDMF) file for deaths occurring from 2009 to 2012 and to another commercially available death source file (Other Death Source, ODS) for deaths occurring from 2009 to 2016 to determine vital status. Actual to Expected (A/E) mortality ratios were calculated using the Society of Actuaries 2015 Valuation Basic Table (2015VBT), select and ultimate table (age last birthday). All expected bases were not smoker distinct. Confidence bands around these mortality ratios were calculated. The variables of interest were applicant age, gender, number of family members with CAD before age 60, and the presence of cardiac or cardiovascular conditions. RESULTS: -Overall, the mortality of applicants with family members with a history of CAD before age 60 was slightly lower than expected mortality based on the 2015 VBT. Applicants with a cardiac or cardiovascular comorbid condition had a significantly higher mortality ratio. For applicants aged 25-54 and 65-75 with cardiac comorbid conditions, the mortality ratio was 2 times that of those without a cardiac comorbid condition. For those aged 55-64 with cardiovascular comorbid conditions, the mortality ratio was 2.9 times that of those without a cardiovascular comorbid condition. Females had a slightly higher mortality ratio for all age groups, number of family members with CAD before age 60, and cardiovascular conditions. CONCLUSION: -A family history of CAD before the age of 60 in an insurance applicant may be associated with increased all-cause mortality. Overall in this study, life insurance applicants had a mortality slightly lower than the expected mortality based on the 2015 VBT. However, applicants with a positive family history and a cardiac or cardiovascular comorbid condition had a significantly higher mortality ratio.

How are genetic test results being used by Australian life insurers?

In Australia, the USA and many Asian countries the life insurance industry is self-regulated. Individuals must disclose genetic test results known to them in applications for new or updated policies including cover for critical care, income protection and death. There is limited information regarding how underwriting decisions are made for policies with such disclosures. The Australian Financial Services Council (FSC) provided de-identified data collected on applications with genetic test result disclosure from its life insurance member companies 2010-2013 to enable repetition of an independent examination undertaken of applications 1999-2003: age; gender; genetic condition; testing result; decision-maker; and insurance cover. Data was classified as to test result alone or additional other factors relevant to risk and decision. Where necessary, the FSC facilitated clarification by insurers. 345/548 applications related to adult-onset conditions. The genetic test result solely influenced the decision in 165/345 applications: positive (n = 23), negative (n = 139) and pending (n = 3). Detailed analyses of the decisions in each of these result categories are presented with specific details of 11 test cases. Policies with standard decisions were provided for all negative test results with evidence of reassessment of previous non-standard decisions and 20/23 positive results with recognition of risk reduction strategies. Disclosure of positive results for breast/ovarian cancer, Lynch syndrome and hereditary spastic paraplegia, and three pending results, generated non-standard decisions. The examination demonstrates some progress in addressing concerns in regard to utilisation of genetic test information but the self-regulatory system in Australia only goes some way in meeting internationally recommended best practice.

A diagnosis of eosinophilic esophagitis is associated with increased life insurance premiums.

Eosinophilic esophagitis (EoE) is a chronic disease that can be diagnosed at any age, but is not associated with malignancy and does not shorten lifespan. It remains unknown whether an EoE diagnosis affects insurability or insurance premium costs. We therefore aimed to determine whether a diagnosis of EoE affects the costs of life insurance. Our investigation was a secret shopper audit study whereby we contacted national insurance companies in the United States to evaluate the effect of a diagnosis of EoE on life insurance premiums. We constructed standardized case scenarios for males and females, including a 25-year-old and a 48-year-old without other comorbid conditions, who either had or did not have a diagnosis of EoE. Companies were asked for their best estimate for a $100,000 whole life insurance policy. Comparisons between median premiums were made using the Mann-Whitney U test. There were 20 national life insurance companies contacted and a total of 73 quotes were obtained. The median premium rate was similar for EoE and non-EoE cases at the younger age ($828 [IQR $576-1,020] vs. $756 [IQR $504-$804]; P = 0.10). However, the premium for the older case without EoE was 19% less expensive compared to a case with EoE ($1990 [IQR $1,248-2,350] vs. $2,375 [IQR $2,100-2568; P = 0.02]. This finding was not explained by sex or state of residence. Based on these findings, we conclude that life insurance premiums are significantly more expensive in the older patient case with EoE when compared to the same case without EoE. Patients with EoE and their providers should be aware of the additional cost associated with this diagnosis.

Employment and insurance outcomes and factors associated with employment among long-term thyroid cancer survivors: a population-based study from the PROFILES registry.

PURPOSE: To obtain insight into employment and insurance outcomes of thyroid cancer survivors and to examine the association between not having employment and other factors including quality of life. METHODS: In this cross-sectional population-based study, long-term thyroid cancer survivors from the Netherlands participated. Clinical data were collected from the cancer registry. Information on employment, insurance, socio-demographic characteristics, long-term side effects, and quality of life was collected with questionnaires. RESULTS: Of the 223 cancer survivors (response rate 87 %), 71 % were employed. Of the cancer survivors who tried to obtain insurance, 6 % reported problems with obtaining health care insurance, 62 % with life insurance, and 16 % with a mortgage. In a multivariate logistic regression analysis, higher age (OR 1.07, CI 1.02-1.11), higher level of fatigue (OR 1.07, CI 1.01-1.14), and lower educational level (OR 3.22, CI 1.46-7.09) were associated with not having employment. Employment was associated with higher quality of life. CONCLUSIONS: Many thyroid cancer survivors face problems when obtaining a life insurance, and older, fatigued, and lower educated thyroid cancer survivors may be at risk for not having employment.

The Added Value of Medical Testing in Underwriting Life Insurance.

BACKGROUND: In present-day life-insurance medical underwriting practice the risk assessment starts with a standard health declaration (SHD). Indication for additional medical screening depends predominantly on age and amount of insured capital. From a medical perspective it is questionable whether there is an association between the level of insured capital and medical risk in terms of mortality. The aim of the study is to examine the prognostic value of parameters from the health declaration and application form on extra mortality based on results from additional medical testing. METHODS: A history register-based cohort study was conducted including about 15.000 application files accepted between 2007 and 2010. Blood pressure, lipids, cotinine and glucose levels were used as dependent variables in logistic regression models. Resampling validation was applied using 250 bootstrap samples to calculate area under the curves (AUC's). The AUC was used to discriminate between persons with and without at least 25% extra mortality. RESULTS: BMI and the overall assessment of the health declaration by an insurance physician or medical underwriter showed the strongest discrimination in multivariable analysis. Including all variables at minimum cut-off levels resulted in an AUC of 0.710 while by using a model with BMI, the assessment of the health declaration and gender, the AUC was 0.708. Including all variables at maximum cut-off levels lead to an AUC of 0.743 while a model with BMI, the assessment of the health declaration and age resulted in an AUC of 0.741. CONCLUSIONS: The outcome of this study shows that BMI and the overall assessment of the health declaration were the dominant variables to discriminate between applicants for life-insurance with and without at least 25 percent extra mortality. The variable insured capital set by insurers as factor for additional medical testing could not be established in this study population. The indication for additional medical testing at underwriting life-insurance can possibly be done on limited variables instead of the obligatory medical testing based on age and the amount of insured capital.

Incidence of and mortality from kidney disease in over 600,000 insured Swedish dogs.

Kidney disease is an important cause of morbidity and mortality in dogs. Knowledge about the epidemiology of kidney disease in the dog population is valuable and large-scale epidemiological studies are needed. The aim of the present study was to use insurance data to estimate kidney-related morbidity and mortality in the Swedish dog population. Insurance company data from insured dogs during the years 1995-2006 were studied retrospectively. Incidence and mortality were calculated for the whole group of dogs as well as divided by sex and breed. The total number of veterinary care insured dogs was 665,245. The total incidence of kidney disease in this group of dogs was 15.8 (15.3-16.2) cases/10,000 dog-years at risk. The number of dogs in the life insurance was 548,346 and in this group the total kidney-related mortality was 9.7 (9.3-10.2) deaths/10,000 dog-years at risk. The three breeds with the highest incidence of kidney disease were the Bernese mountain dog, miniature schnauzer and boxer. The three breeds with the highest mortality caused by kidney disease were the Bernese mountain dog, Shetland sheepdog and flat-coated retriever. In conclusion, the epidemiological information provided in this study concerning kidney disease in dogs can provide valuable information for future research.

[Rare diseases from a life insurance perspective]. / Seltene Erkrankungen aus Sicht der Lebensversicherungswirtschaft.

A rare disease is defined as a disease that affects a maximum of 5 in 10,000 people. As of today there are roughly 7000 different rare diseases known. On account of this one can say that "rare diseases are rare, but people affected by them are common". For Germany this amounts to: 4 million people that are affected by a rare disease. Diagnosis, therapeutic options and prognosis have substantially improved for some of the rare diseases. Besides the general medical advances--especially in the area of genetics--this is also due to networking and sharing information by so-called Centres of Competence on a national and international scale. This results in a better medical care for the corresponding group of patients. Against this backdrop, the number of people applying for life assurance who are suffering from a complex or rare disease has risen steadily in the last years. Due to the scarce availability of data regarding long-term prognosis of many rare diseases, a biomathematical, medical and actuarial expertise on the part of the insurer is necessary in order to adequately assess the risk of mortality and morbidity. Furthermore there is quite a focus on the issue of rare diseases from not only politics but society as well. Therefore evidence based medical assessment by insurers is especially important in this group of applicants--thinking of legal compliance and reputational risk.

NT-proBNP as a predictor of all-cause mortality in a population of insurance applicants.

OBJECTIVE: Quantify the independent value of NT-proBNP in predicting all-cause mortality for individual life insurance applicants and establish risk-based reference ranges. METHOD: By use of the Social Security Death Master File and multivariate analysis, relative mortality was determined for 144,027 life insurance applicants tested (almost all routinely rather than for cause) for NT-proBNP along with other laboratory testing and measurement of BP and BMI. RESULTS: Risk increased substantially for NT-proBNP values > 300 pg/mL in women and > 200 pg/mL in men after age, smoking status and other cardiovascular risk factors were accounted for. The relative risk reached > 10 fold at NT-proBNP levels > 1000 pg/mL. For those age 50 to 89 and denying a history of heart disease, this level occurred in only 0.5% of applicants but was present in 7% of all deaths. CONCLUSION: NT-proBNP is a strong independent predictor of all-cause mortality but values associated with increased risk vary by sex.

A study on the effect of exclusion period on the suicidal risk among the insured.

An exclusion period (usually from 12 months to 2 years) is usually found in life insurance policies as a precautionary measure to prohibit people from insuring their lives with the intent to kill themselves shortly thereafter. Several studies have been conducted to investigate the effect of exclusion periods on the risk of suicide among the insured in the US and Australia. However, while Hong Kong has experienced an increase in the number of suicides among the insured, little is known about the dynamic between the exclusion period and suicide in Asia. Here we make use of death claims data from one of the major life insurance companies in Hong Kong to ascertain the impact of a 12-month exclusion period on suicide risk. We also use utility functions derived from economic theory to better understand individual choices regarding suicide among the insured. More specifically, we sought to determine whether there is a greater risk of suicide immediately following the 12-month exclusion period. We also examined whether the risk of suicide claims was higher than that of other non-suicidal claims. The study period for this investigation was from January 1, 1997 to December 31, 2011, during which time there were 1935 claims based on 1243 deaths. Of these, 197 were suicide-related claims for 106 suicide deaths. The mean number of life policies held by suicidal claimants and non-suicidal claimants was 1.6 and 1.4, respectively. The average/median size of the claims (total payment made on all policies held by the insured life) was HK$665,800/426,600 and HK$497,700/276,200 for suicidal and non-suicidal deaths, respectively. The policy lifetime of the claims, or the number of days from policy issuance to suicide occurrence, ranged from 38 to 7561 days, with a mean of 2209 days, a median of 1941 days, and a standard deviation of 1544 days. The peak density of suicide claims occurred on day 1039 of the policy. Our results revealed that suicide claims tend to occur earlier than other claims and that there is a greater risk of suicide observed following the 12-month exclusion period. Some suggestions are made in terms of extending the exclusion period, which is anticipated to significantly reduce suicide at the global level.

Actual to expected studies--Part 2.

In Part I of this two-part series, we used a synthetic dataset which we called the "Health Risk Appraisal" dataset. Using this dataset, we performed an actual/expected mortality study using one and only one health assessment per individual. This synthetic dataset is actually more realistic in that many persons were evaluated more than once. Our previous study assessed predicted mortality based on the "first" HRA evaluation. There are three other alternatives: "last", "every", and "weighted-every" aka, "fractional". In this Part 2, we will briefly describe the "last" and "every" scenarios" and compare their results with those from the "first". We will then describe the fractional method in detail because our experience has shown this method provides the most desirable results.

Age dependent decline of relative risks in life insurance medical underwriting.

UNLABELLED: INTRODUCTORY: Life insurance medicine focuses on mortality hazards. People are free to insure themselves for small or large amounts and for short or long-terms. This freedom makes it necessary for life insurers to assess and select the mortality risks in a medical underwriting process. Medical underwriting guidelines are based on company statistics, population surveys following (clinical) epidemiological principles and clinical studies. Mortality of potential life insurance applicants is compared to life tables of insured populations, or to adjusted life tables of the general population. Because many risk determinants have higher normal values at higher ages, it is reasonably to assume that the relative hazards (RHs) or mortality ratios calculated for these risk determinants should be age dependent. This is also common use in underwriting guidelines, and can have much influence on the accessibility of life insurances for (chronically) diseased people. A proof of principle is therefor warranted. METHODS: This population-based cohort study uses NHANES- datafiles from the Third National Health and Nutrition Examination Survey (NHANES III) and the NHANES Linked Mortality Files 2010. Only participants aged 20 to 69 that were examined in mobile examination centers, without a history of some prevalent high risk diseases were included. The observed mortality was compared to the expected mortality in a Generalized Linear Model (GLM) with Poisson error structure with two reference populations, which theoretically both can serve as preferred reference for life insurers: The United States Life Tables 2008 and the 2008 Valuation Basic Tables based on the insured population of 35 US life insurers. The age dependency was assessed of the values and the RH s of the systolic blood Pressure (SBP), aspartate aminotranseferase (ASAT), lactate dehydrogenase (LDH), serum albumin and albuminuria, with correction for ethnicity, household income, history of diabetes mellitus, BMI and serum cholesterol. RESULTS: All 5 continuous risk determinants had age dependent values in the comparison between ages 20-54 and 55-69 (Mann-Whitney U P < 0.001). Graphical inspections using age at time of interview revealed only for the SBP an increase with age. In the GLM again only SBP had a significant interaction term with age at time of interview. It made no difference which life tables were used for the calculation of the expected mortality. DISCUSSION: Age dependency of RHs of risk determinants can be assumed if the risk determinants themselves are age dependent on statistical and graphical inspection. In other cases age dependency might not be significant, or cannot be modelled with some form of linear function as customary in many underwriting guidelines. The RHs or mortality ratios in current medical underwriting guidelines for life insurances should be checked for age dependency by analysing the underlying data statistically and graphically and by using GLM and appropriate life tables.

Feasibility and usefulness of troponin I testing in insurance medicine.

OBJECTIVE: Ascertain the prevalence of elevated Troponin I levels in applicants for insurance to assess the utility of routine measurement of Troponin I in this population. BACKGROUND: Patients presenting with chest pain, who are determined not to be experiencing an acute coronary event, but are noted to have increased levels of Troponin have higher mortality rates than a control population. Elevated levels of Tropoins in the general population are also associated with increase in all cause mortality. Therefore elevated Troponin levels in asymptomatic individuals could be considered a cardiac risk marker. METHODS: Blood samples from Insurance applicants and Health & Wellness participants were analyzed for Troponin I by the Siemens ADVIA Centaur immunoanalyzer. Since such samples are in transit for a day, we determined the rate of degradation of Troponin I on 24-hour storage at room temperature and extrapolated the time-zero values. RESULTS: About 1.5% (10 of 697) of the patients had Troponin levels above 0.04 ng/mL. This rate is higher than would be expected in a healthy general population. Three samples (0.43%) had levels > 0.06 ng/mL, which would be considered elevated and indicative of myocardial injury. CONCLUSIONS: Given the low percentage Troponin I elevations in the general population applying for life insurance, it may not be cost effective to routinely measure Troponin I levels in blood specimens submitted for insurance purposes, except for high value policies. It may be prudent collect data on Troponin I levels in Insurance applicants for better defining the risk models of cardiovascular disease.

Actual to expected studies--Part 1.

In this Part 1 of a two-part series, pivot tables are used to analyze mortality and then a step-by-step process is demonstrated of converting seriatim data that is suitable for pivot table analysis.