Alzheimer’s disease (AD) is a progressive degenerating disease of complex etiology. A variety of risk factors contribute to the chance of developing AD. Lifestyle factors, such as physical, mental and social activity, education, and diet all affect the susceptibility to developing AD. These factors are in turn related to the level of personal income. Lower income usually coincides with lower level of education, lesser mental, leisure—social and physical activity, and poorer diet. In the present paper, we have analyzed the correlation of historical (1929–2011) per capita personal income (PCPI) for all states of the USA with corresponding age-adjusted AD death rates (AADR) for years 2000, 2005 and 2008. We found negative correlations in all cases, the highest one (R ≈ -0.65) for the PCPIs in the year 1970 correlated against the AADRs in 2005. From 1929 to 2005 the R value varies in an oscillatory manner, with the strongest correlations in 1929, 1970, 1990 and the weakest in 1950, 1980, 1998. Further analysis indicated that this oscillatory behavior of R is not artificially related to the economic factors but rather to delayed biological consequences associated with personal income. We conclude that the influence of the income level on the AD mortality in 2005 was the highest in the early years of life of the AD victims. Overall, the income had a significant, lifelong, albeit constantly decreasing, influence on the risk of developing AD. We postulate that the susceptibility of a population to late-onset AD (LOAD) is determined to a large extent by the history of income-related modifiable lifestyle risk factors. Among these risk factors, inappropriate diet has a significant contribution.

In 2021, COVID-19 caused about *** deaths per 100,000 population in high-income countries. This statistic displays the leading causes of death in high-income countries in 2021 by deaths per 100,000 population. Mortality from chronic diseases such as cancer and heart diseases are increasing around the world. Chronic deaths are especially prominent in Western countries, but have also recently began to increase in the developing world. Non-communicable disease burden This increase in chronic and degenerative non-communicable diseases globally stems from aging populations, modernization, and rapid urbanization. Though these are all signs of socioeconomic progress, the resulting shift in disease carries a heavy burden for societies. Health expenditure makes up around ** percent or more of the GDP in most high-income countries, and the global spending on medicines is expected to more than double from 2010 to 2027. Non-communicable disease risk factors and prevention In most OECD countries, over 30 percent of adults are overweight. Lack of exercise, poor nutrition, and generally unhealthy lifestyles can often lead to a cluster of symptoms including abnormal blood levels, high blood pressure, and excess body fat, which in turn pose an increased risk of heart disease, stroke, and diabetes. However, most non-communicable diseases are preventable, and their modifiable risk factors can be lowered through lifestyle and behavioral changes.

BackgroundThere is not enough evidence regarding how information obtained from general health check-ups can predict individual mortality based on long-term follow-ups and large sample sizes. This study evaluated the applicability of various health information and measurements, consisting of self-reported data, anthropometric measurements and laboratory test results, in predicting individual mortality.MethodsThe National Health Screening Cohort included 514,866 participants (aged 40–79 years) who were randomly selected from the overall database of the national health screening program in 2002–2003. Death was determined from causes of death statistics provided by Statistics Korea. We assessed variables that were collected at baseline and repeatedly measured for two consecutive years using traditional and time-variant Cox proportional hazards models in addition to random forest and boosting algorithms to identify predictors of 10-year all-cause mortality. Participants’ age at enrollment, lifestyle factors, anthropometric measurements and laboratory test results were included in the prediction models. We used c-statistics to assess the discriminatory ability of the models, their external validity and the ratio of expected to observed numbers to evaluate model calibration. Eligibility of Medicaid and household income levels were used as inequality indexes.ResultsAfter the follow-up by 2013, 38,031 deaths were identified. The risk score based on the selected health information and measurements achieved a higher discriminatory ability for mortality prediction (c-statistics = 0.832, 0.841, 0.893, and 0.712 for Cox model, time-variant Cox model, random forest and boosting, respectively) than that of the previous studies. The results were externally validated using the community-based cohort data (c-statistics = 0.814).ConclusionsIndividuals’ health information and measurements based on health screening can provide early indicators of their 10-year death risk, which can be useful for health monitoring and related policy decisions.

Central mortality rates by age and sex up to 2050, conditioned to the three risk factors under consideration (income, habitat size, and climate area), using georeferenced microdata from the population of Spain. This project contains two open-format files (please also read the Read me.xlsx).

The file called "Estimates of death rates,Spain 2010-2019,by risk factor.csv" offers the results of converting nearly two billion microdata events into estimates of central mortality rates for each risk factor, categorised according to various variables. Spain 2010-2019.

The file called "Forecasts of death rates,Spain 2020-2050, by risk factor.csv" includes the projections of the death rates from 2020 to 2050.

BackgroundAdverse socioeconomic conditions at the individual and regional levels are associated with an increased risk of mortality. However, few studies have examined this relationship using multilevel analysis and, if so, only within a single country. This study aimed to examine this relationship using data from several European countries.MethodsIndividual-level data were obtained from Waves 5 to 9 of the Survey of Health, Ageing and Retirement in Europe, while regional-level data were obtained from the Luxembourg Income Study Database. Cox regression analysis with gamma-shared frailty and a random intercept for country of residence was used to examine the association between individual mortality from all causes, cancer, heart attack, and stroke and measures of socioeconomic deprivation at the individual level, including material and social deprivation indices, and at the area level, including the Gini index.ResultsThe risk of mortality from all causes was increased for respondents with material deprivation (hazard ratio (HR) = 1.77, 95% CI = [1.60, 1.96]) and social deprivation (HR = 7.63, 95% CI = [6.42, 9.07]) compared with those without. A similar association was observed between individual deprivation and the risk of mortality from cancer, heart attack, or stroke. Regional deprivation had a modest contextual effect on the individual risk of death from all causes and cancer. However, when individual-level deprivation was included in the models, no contextual effects were found.ConclusionThe results indicate that individual socioeconomic conditions significantly predict causes of death in older European adults, with those with material deprivation and social deprivation having a higher risk of death from all causes, including cancer, heart attack, and stroke, while the Gini index has a minimal effect, although the Gini index reflects regional disparities across Europe.

This statistic shows the share of occurrence and death tolls for weather-related disasters worldwide in the period from 1995 to 2015, by national income level. During the past 20 years, around ** percent of weather-related disasters affected lower-income countries.

Natural disasters and loss – additional information

The years 2014 and 2015 are two of the hottest years recorded since the 1880s. In 2014, there were ** deaths caused by extreme heat in the United States. The increased risk of extreme weather due to climate change has put pressure on countries to develop regulations to better protect infrastructure and human health. Between 1995 and 2015, about a third of the global weather-related disasters occurred in lower-middle income countries, however, almost half of the deaths due to these events affected these countries. The number of deaths caused by the Cyclone Nargis in Myanmar contributed significantly to these statistics. In high-income countries, weather-related deaths are largely due to heat waves. The actual number of casualties in low-income countries is estimated to be much higher and may reflect a lack of reporting.

China and India have been among the most severely impacted countries in the world in terms of weather catastrophes, accounting for some * billion people that have been affected between 1995 and 2015. Economic loss due to these events totaled some ** billion U.S. dollars in the Asia and Oceania regions. Millions of houses as well as public institutions such as schools, clinics, and hospitals have been damaged by weather-related disasters, primarily due to floods and storms. Over the last decades, countries have improved their preparedness as well as their response to natural disasters. Several countries in Asia have begun to follow the Hyogo Framework for Action, a guideline developed to help reduce disaster risk, in efforts to reduce the losses derived from these catastrophes.

Income Protection Insurance Market Outlook

The global income protection insurance market size was valued at USD 8.5 billion in 2023 and is projected to reach USD 13.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 5.2%. This notable growth is primarily driven by increasing awareness regarding financial security and the need for income sustainability during unforeseen events such as illness or job loss. The rising incidence of chronic diseases, coupled with the unpredictable economic environment, further fuels the demand for such insurance products.

The market is significantly propelled by the growing awareness among consumers about the importance of financial planning and risk management. As individuals become more cognizant of the financial risks posed by sudden income loss due to health issues or job instability, there is an increasing inclination towards income protection insurance. This trend is particularly strong among young professionals and the middle-aged working population who seek to safeguard their financial future. Additionally, the increasing penetration of digital platforms has made it easier for consumers to research and purchase income protection policies, thereby boosting the market's growth.

Another driving factor is the rising prevalence of lifestyle-related diseases and mental health issues, which contribute to an increased likelihood of prolonged work absences. With the growing burden of such diseases, there is a heightened awareness of the need for income protection to cover medical expenses and maintain household income. Furthermore, employers are increasingly offering income protection insurance as part of their employee benefits packages, recognizing its importance in attracting and retaining talent. This trend is particularly notable in industries with high-stress levels and health risks, such as IT, finance, and healthcare.

Economic uncertainties and the increasing volatility in job markets also play a vital role in the growth of the income protection insurance market. The COVID-19 pandemic has exemplified the critical need for financial protection, as many individuals faced unexpected job losses or reduced income. This has led to a surge in demand for income protection insurance as people seek to secure their livelihoods against future economic shocks. Moreover, regulatory changes and government initiatives aimed at promoting insurance penetration and financial literacy are likely to further support market growth.

Accidental Death and Dismemberment Insurance is another critical component of financial protection that complements income protection insurance. While income protection insurance primarily focuses on replacing lost income due to illness or injury, Accidental Death and Dismemberment Insurance provides financial compensation in the event of severe accidents leading to death or significant bodily harm. This type of insurance is particularly valuable for individuals in high-risk occupations or those who engage in activities with a higher likelihood of accidents. It offers peace of mind by ensuring that beneficiaries receive financial support to cover expenses such as medical bills, funeral costs, and ongoing living expenses, thereby safeguarding their financial stability during challenging times.

Regionally, North America and Europe have traditionally dominated the income protection insurance market, driven by high awareness levels and well-established insurance sectors. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. This can be attributed to the rapidly increasing middle-class population, rising disposable incomes, and growing awareness of insurance benefits in emerging economies such as China and India. Furthermore, digitalization and advancements in technology are making insurance products more accessible to the broader population in these regions.

Type Analysis

The income protection insurance market can be segmented by type into short-term and long-term income protection insurance. Short-term income protection insurance generally covers income loss for a period ranging from a few months to a couple of years. This type of insurance is typically sought by individuals who require temporary financial support during recovery from illness or injury. It is particularly popular

BackgroundThere has been substantial research on psychosocial and health care determinants of health disparities in the United States (US) but less on the role of modifiable risk factors. We estimated the effects of smoking, high blood pressure, elevated blood glucose, and adiposity on national life expectancy and on disparities in life expectancy and disease-specific mortality among eight subgroups of the US population (the “Eight Americas”) defined on the basis of race and the location and socioeconomic characteristics of county of residence, in 2005.Methods and FindingsWe combined data from the National Health and Nutrition Examination Survey and the Behavioral Risk Factor Surveillance System to estimate unbiased risk factor levels for the Eight Americas. We used data from the National Center for Health Statistics to estimate age–sex–disease-specific number of deaths in 2005. We used systematic reviews and meta-analyses of epidemiologic studies to obtain risk factor effect sizes for disease-specific mortality. We used epidemiologic methods for multiple risk factors to estimate the effects of current exposure to these risk factors on death rates, and life table methods to estimate effects on life expectancy. Asians had the lowest mean body mass index, fasting plasma glucose, and smoking; whites had the lowest systolic blood pressure (SBP). SBP was highest in blacks, especially in the rural South—5–7 mmHg higher than whites. The other three risk factors were highest in Western Native Americans, Southern low-income rural blacks, and/or low-income whites in Appalachia and the Mississippi Valley. Nationally, these four risk factors reduced life expectancy at birth in 2005 by an estimated 4.9 y in men and 4.1 y in women. Life expectancy effects were smallest in Asians (M, 4.1 y; F, 3.6 y) and largest in Southern rural blacks (M, 6.7 y; F, 5.7 y). Standard deviation of life expectancies in the Eight Americas would decline by 0.50 y (18%) in men and 0.45 y (21%) in women if these risks had been reduced to optimal levels. Disparities in the probabilities of dying from cardiovascular diseases and diabetes at different ages would decline by 69%–80%; the corresponding reduction for probabilities of dying from cancers would be 29%–50%. Individually, smoking and high blood pressure had the largest effect on life expectancy disparities.ConclusionsDisparities in smoking, blood pressure, blood glucose, and adiposity explain a significant proportion of disparities in mortality from cardiovascular diseases and cancers, and some of the life expectancy disparities in the US.Please see later in the article for the Editors' Summary

Olympic athletes: the epitome of health and fitness, role models for their communities, and competing on the world stage. Is there a cost incurred by highlighting the achievements of these elite athletes? Suicide, as defined by the Centers for Disease Control and Prevention, is death by injuring oneself whereby death was the intent (Suicide Prevention: Facts, 2022). A person harming themselves with death as the intention but not the outcome is classified as a suicide attempt (Suicide Prevention: Facts, 2022). In the general population, suicide is one of the leading causes of death, especially amongst younger people where it is the fourth leading cause of death (Suicide Prevention: Risk, 2022). In 2019, the global age-standardized suicide rate was 9 deaths per 100,000 people (World Health Organization (WHO), 2021). The risk factors for suicide are multifaceted and complex, ranging from a history of mental health issues, serious illnesses, chronic pain, financial stress, substance use, adverse childhood experiences, and difficulties in relationships (Suicide Prevention: Risk, 2022). Differences in sociodemographic variables have been linked with suicide rates (Suicide Prevention: Risk, 2022). For example, the suicide rate for males (~12.6 per 100,000) is typically higher than females (5.4 per 100,000) (Suicide Prevention: Risk, 2022). Economic factors may also play a role given the largest portion of deaths by suicide occur in lower-income and middle-income countries (Suicide Prevention: Risk, 2022), yet high-income countries report higher age-standardized rates of suicide (10.9 per 100,000) (Suicide Prevention: Risk, 2022). More than half (58%) of global suicides occur in persons less than 50 years of age (Suicide Prevention: Risk, 2022) implicating stage of life as a plausible risk factor linked with death by suicide. Overall, suicide rates have been declining since 2000 with a 36% reduction noted in 2019 compared with 20 years earlier (Suicide Prevention: Risk, 2022).

Sports and athletes can be ‘newsworthy’, so there is heightened media attention when high-profile athletes die from suicide. Research examining suicide and athletes has focused primarily on collegiate (or university-level) athletes. In the National Collegiate Athletic Association (NCAA) over a nine-year period, the rate of death by suicide in athletes was 1.35 per 100,000 in males, and 0.37 per 100,000 in females, both of which are lower than suicide rates for age-matched students (Rao et al., 2015). NCAA football had the highest relative rates of suicide at 2.25 per 100,000 yet this rate is still lower compared against other students matched for age and sex (Rao et al., 2015). In football, chronic traumatic encephalopathy (or CTE) has been gaining traction as one risk factor leading to death by suicide (Rao, 2018). To date, studies of suicide and athletes competing at other levels of sport (e.g., Olympics, etc.) appear sparse. One study of US Olympians compared mental disorders, substance abuse, and self-harm reported by athletes with the public noting athletes had a lower risk of death by suicide from these factors (Rao, 2018). Suicidal ideation was reported by 1 in 6 Swedish athletes competing at the international level (Timpka et al., 2019). Finally, retirement may be a factor to consider in suicide prevention initiatives given that male athletes competing in power sports (e.g., wrestling, Olympic lifting, etc.) retiring between 30 and 50 years of age were 2 to 4 times more likely to die by suicide than non-athletes of the same ages (Lindqvist et al., 2014).

To date, limited research has been reported on Olympic athletes and suicide. Further research is warranted to determine the frequency of suicide rates in Olympians plus identifiable risk factors for death by suicide reported by this cohort of elite athletes.

Background: Child malnutrition is not only common in developing countries but also an important issue faced by developed countries. This study aimed to explore the influence and degree of childhood starvation on the health of the elderly, which provides a reference for formulating health-related policies under the concept of full lifecycle health.Methods: Based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2008, 2011, and 2014, this study took a total of 13,185 elderly people aged 65–99 years as the target population. By IMaCH software, with gender and income level as the control variables, the average life expectancy and healthy life expectancy of the elderly were measured. The x2test was used to explore the differences in the socioeconomic status of elderly people with or without starvation in childhood. Statistical differences between average life expectancy and healthy life expectancy were analyzed by rank tests.Results: (1) The results showed that there was a statistically significant difference in age, gender, residency, education level, and income level between the groups with or without starvation (P < 0.05). (2) Transition probabilities in health–disability, health–death, and disability–death all showed an upward trend with age (P < 0.05), where the elderly who experienced starvation in childhood were higher than those without such an experience (P < 0.05). However, the probability of disability–health recovery showed a downward trend with age (P < 0.05), in which the elderly who experienced starvation in childhood were lower than those without starvation (P < 0.05). (3) For the elderly who experienced starvation in childhood, the health indicators of the average life expectancy, healthy life expectancy, and healthy life expectancy proportion accounted for the remaining life were lower than those of the elderly without childhood starvation (P < 0.05).Conclusions: The average life expectancy and healthy life expectancy of the elderly with childhood starvation are lower than those without childhood starvation. It shows that the negative impact of childhood starvation on health through the life course till old age has a persistent negative cumulative effect on the quantity and quality of life. Therefore, it is important to pay attention to the nutritional status of children in poor families from the perspective of social policymaking.

Contribution of major risk factors of all-cause of death risk score in the National Health Insurance Service—National Health Screening Cohort (NHIS-HEALS) from 2002 to 2013.

Social vulnerability is defined as the disproportionate susceptibility of some social groups to the impacts of hazards, including death, injury, loss, or disruption of livelihood. In this dataset from Climate Ready Boston, groups identified as being more vulnerable are older adults, children, people of color, people with limited English proficiency, people with low or no incomes, people with disabilities, and people with medical illnesses. Source:The analysis and definitions used in Climate Ready Boston (2016) are based on "A framework to understand the relationship between social factors that reduce resilience in cities: Application to the City of Boston." Published 2015 in the International Journal of Disaster Risk Reduction by Atyia Martin, Northeastern University.Population Definitions:Older Adults:Older adults (those over age 65) have physical vulnerabilities in a climate event; they suffer from higher rates of medical illness than the rest of the population and can have some functional limitations in an evacuation scenario, as well as when preparing for and recovering from a disaster. Furthermore, older adults are physically more vulnerable to the impacts of extreme heat. Beyond the physical risk, older adults are more likely to be socially isolated. Without an appropriate support network, an initially small risk could be exacerbated if an older adult is not able to get help.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for population over 65 years of age.Attribute label: OlderAdultChildren: Families with children require additional resources in a climate event. When school is cancelled, parents need alternative childcare options, which can mean missing work. Children are especially vulnerable to extreme heat and stress following a natural disaster.Data source: 2010 American Community Survey 5-year Estimates (ACS) data by census tract for population under 5 years of age.Attribute label: TotChildPeople of Color: People of color make up a majority (53 percent) of Boston’s population. People of color are more likely to fall into multiple vulnerable groups aswell. People of color statistically have lower levels of income and higher levels of poverty than the population at large. People of color, many of whom also have limited English proficiency, may not have ready access in their primary language to information about the dangers of extreme heat or about cooling center resources. This risk to extreme heat can be compounded by the fact that people of color often live in more densely populated urban areas that are at higher risk for heat exposure due to the urban heat island effect.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract: Black, Native American, Asian, Island, Other, Multi, Non-white Hispanics.Attribute label: POC2Limited English Proficiency: Without adequate English skills, residents can miss crucial information on how to preparefor hazards. Cultural practices for information sharing, for example, may focus on word-of-mouth communication. In a flood event, residents can also face challenges communicating with emergency response personnel. If residents are more sociallyisolated, they may be less likely to hear about upcoming events. Finally, immigrants, especially ones who are undocumented, may be reluctant to use government services out of fear of deportation or general distrust of the government or emergency personnel.Data Source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract, defined as speaks English only or speaks English “very well”.Attribute label: LEPLow to no Income: A lack of financial resources impacts a household’s ability to prepare for a disaster event and to support friends and neighborhoods. For example, residents without televisions, computers, or data-driven mobile phones may face challenges getting news about hazards or recovery resources. Renters may have trouble finding and paying deposits for replacement housing if their residence is impacted by flooding. Homeowners may be less able to afford insurance that will cover flood damage. Having low or no income can create difficulty evacuating in a disaster event because of a higher reliance on public transportation. If unable to evacuate, residents may be more at risk without supplies to stay in their homes for an extended period of time. Low- and no-income residents can also be more vulnerable to hot weather if running air conditioning or fans puts utility costs out of reach.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for low-to- no income populations. The data represents a calculated field that combines people who were 100% below the poverty level and those who were 100–149% of the poverty level.Attribute label: Low_to_NoPeople with Disabilities: People with disabilities are among the most vulnerable in an emergency; they sustain disproportionate rates of illness, injury, and death in disaster events.46 People with disabilities can find it difficult to adequately prepare for a disaster event, including moving to a safer place. They are more likely to be left behind or abandoned during evacuations. Rescue and relief resources—like emergency transportation or shelters, for example— may not be universally accessible. Research has revealed a historic pattern of discrimination against people with disabilities in times of resource scarcity, like after a major storm and flood.Data source: 2008-2012 American Community Survey 5-year Estimates (ACS) data by census tract for total civilian non-institutionalized population, including: hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty. Attribute label: TotDisMedical Illness: Symptoms of existing medical illnesses are often exacerbated by hot temperatures. For example, heat can trigger asthma attacks or increase already high blood pressure due to the stress of high temperatures put on the body. Climate events can interrupt access to normal sources of healthcare and even life-sustaining medication. Special planning is required for people experiencing medical illness. For example, people dependent on dialysis will have different evacuation and care needs than other Boston residents in a climate event.Data source: Medical illness is a proxy measure which is based on EASI data accessed through Simply Map. Health data at the local level in Massachusetts is not available beyond zip codes. EASI modeled the health statistics for the U.S. population based upon age, sex, and race probabilities using U.S. Census Bureau data. The probabilities are modeled against the census and current year and five year forecasts. Medical illness is the sum of asthma in children, asthma in adults, heart disease, emphysema, bronchitis, cancer, diabetes, kidney disease, and liver disease. A limitation is that these numbers may be over-counted as the result of people potentially having more than one medical illness. Therefore, the analysis may have greater numbers of people with medical illness within census tracts than actually present. Overall, the analysis was based on the relationship between social factors.Attribute label: MedIllnesOther attribute definitions:GEOID10: Geographic identifier: State Code (25), Country Code (025), 2010 Census TractAREA_SQFT: Tract area (in square feet)AREA_ACRES: Tract area (in acres)POP100_RE: Tract population countHU100_RE: Tract housing unit countName: Boston Neighborhood

Macedonia MK: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data was reported at 11.400 % in 2011. This records a decrease from the previous number of 15.800 % for 2005. Macedonia MK: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data is updated yearly, averaging 10.100 % from Dec 1999 (Median) to 2011, with 4 observations. The data reached an all-time high of 15.800 % in 2005 and a record low of 7.600 % in 2004. Macedonia MK: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Macedonia – Table MK.World Bank: Health Statistics. Prevalence of overweight, female, is the percentage of girls under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues

BackgroundCaregiving to lung cancer patients is distressing, isolating, and associated with a high burden of anxiety and depression. However, few population-based studies in the U.S. have examined the risk of mental health conditions (MHCs) among spouses of lung cancer patients after the death of their partner. Guided by Anderson’s Behavioral Health Utilization model, we examined the role of sex, pre-bereavement MHC, and decedents’ healthcare utilization on the risk of having a diagnosed MHC after the death of a lung cancer patient.MethodsThis retrospective cohort study linked state-wide health facility records of 1,224 dyads—deceased lung cancer patients and their bereaved spouses (824 female, 400 male)—in Utah between 2013 and 2021. Bereavement-related mood/stress-related conditions were identified for spouses using diagnostic codes (starting from day 1 following the patients’ deaths). The Kaplan–Meier curves and Cox proportional hazard models were used to estimate the risk for a composite outcome of MHC/death and the risk of MHC, after adjusting for censorship due to death and controlling for covariates.ResultsThe majority of spouses were aged 65+ (female: 67%; male: 33%), white/non-Hispanic (female: 89%; male: 90%), and urban-dwelling (female: 69%; male: 71%). Spouses experienced 374 events (MHCs/death) across the follow-up period. Adjusting for census-tract level income, cancer stage, insurance, censoring due to death, and the interaction between sex and MHC, spouses with preexisting MHCs had 4.09 times higher risk of developing MHCs during bereavement (95% CI: 2.70, 6.19) compared to spouses without pre-existing MHCs. Spouses of decedents with some college education (aHR: 0.68, 95% CI = 0.48–0.97) and longer survival (aHR: 0.85, 95% CI = 0.74–0.99) had a lower risk of MHCs compared to those of decedents with high school education and shorter survival.DiscussionThis population-based study supports evidence for multi-level risk factors associated with having MHC after the death of a spouse with lung cancer. Findings suggest the need for targeted bereavement support for subgroups of spouses at greater risk of MHCs.

This table contains 2394 series, with data for years 1991 -1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 3;Income adequacy quintile 2 ...), Age (14 items: At 25 years; At 30 years; At 35 years; At 40 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Probability of survival; Low 95% confidence interval; life expectancy; High 95% confidence interval; life expectancy ...).

CR: Prevalence of Overweight: Weight for Height: Male: % of Children Under 5 data was reported at 8.200 % in 2018. This records a decrease from the previous number of 8.300 % for 2008. CR: Prevalence of Overweight: Weight for Height: Male: % of Children Under 5 data is updated yearly, averaging 8.250 % from Dec 2008 (Median) to 2018, with 2 observations. The data reached an all-time high of 8.300 % in 2008 and a record low of 8.200 % in 2018. CR: Prevalence of Overweight: Weight for Height: Male: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Costa Rica – Table CR.World Bank.WDI: Social: Health Statistics. Prevalence of overweight, male, is the percentage of boys under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.;;Estimates of overweight children are from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues.

The industry has grown over the five years to 2024 due to the growth of global demand for insurance products. The industry provides essential risk management services to downstream consumers and is a vital part of the financial sector, particularly concerning the industry's massive asset holdings. Industry operators protect individuals from current, immediate and long-term illness, injury and death costs. By merging various risks, life and health insurers protect a fraction of the potential loss. The role of life and health insurers has become increasingly important as the global population has aged. Although the industry provides essential products and services, operators are highly susceptible to macroeconomic shocks. Industry revenue is expected to grow at a CAGR of 0.6% to $5.5 trillion over the five years to 2024, including a decrease of 0.3% in 2024 alone. In addition to premiums from insurance underwriting, operators also obtain revenue from financial instruments, such as stocks and bonds, which generate income and capital gains. However, this exposure to financial markets, particularly for life insurers, means that revenue and profit can exhibit significant volatility. The decline in global interest rates has been the primary obstacle to the industry's expansion. Nevertheless, given the immediacy of health concerns, health insurance largely tempers revenue fluctuations for the industry. Market conditions are expected to recover moving forward. Thus, revenue is expected to increase at a CAGR of 0.9% to $5.8 trillion over the five years to 2029. Moreover, increasing employment levels globally are expected to drive demand for insurance. Meanwhile, demand for insurance is growing in emerging markets. As the wealth of these regions continues to grow, individuals will likely become more interested in ensuring their wealth and income against a range of risks. Additionally, the threat of volatile financial markets is anticipated to persist during the period and could hurt investment income, particularly if interest rates are forced to remain low.

Key Person Income Insurance Market Outlook

The global key person income insurance market size is expected to reach $XX billion by 2032, up from $XX billion in 2023, growing at a compound annual growth rate (CAGR) of XX% from 2024 to 2032. The growth of this market is significantly influenced by the increasing awareness of business continuity risks and the rising adoption of key person insurance policies by businesses of all sizes.

One of the primary growth factors driving the key person income insurance market is the increasing recognition of the financial risks associated with the loss of a critical employee or executive. Companies, especially those heavily reliant on specific individuals for their revenue generation and strategic direction, are beginning to understand the catastrophic impact that losing a key person can have on their operations. This realization is spurring a higher demand for key person insurance policies as a means to mitigate these risks and ensure business continuity. Additionally, the rise of small and medium enterprises (SMEs) which are more vulnerable to the loss of critical personnel is further boosting the market growth.

Another significant factor contributing to the market's expansion is the growing complexity of corporate structures and the heightened focus on strategic risk management. Businesses are now more intertwined and operationally dependent on the expertise and leadership of specific individuals. This has led to an increased demand for insurance products that can provide financial support during the unexpected absence of these key individuals. Moreover, key person insurance is also becoming an integral part of the risk management strategies of large enterprises, further driving the market growth.

The increasing global economic uncertainties and the unpredictable nature of business environments are also augmenting the demand for key person income insurance. Companies are looking for ways to safeguard their financial stability against unforeseen challenges. Key person insurance offers a financial cushion that helps businesses navigate the turbulence caused by the sudden loss of a pivotal team member. This insurance is not only seen as a protective measure but also as a vital component of a comprehensive business continuity plan.

Endowment Insurances are another form of financial protection that businesses and individuals can consider alongside key person income insurance. Unlike key person insurance, which is designed to protect against the loss of a critical employee, endowment insurances provide a lump sum payment after a specified term or upon the policyholder's death. This type of insurance is particularly beneficial for businesses looking to secure funds for future investments or for individuals planning for retirement or significant life events. The dual benefit of savings and protection makes endowment insurances an attractive option for those seeking a comprehensive financial strategy. As businesses and individuals become more aware of their financial planning needs, the integration of endowment insurances into their portfolios is expected to rise, complementing the coverage provided by key person insurance.

Regionally, North America is anticipated to hold the largest market share due to the high adoption rate of key person insurance policies and the presence of a large number of SMEs and multinational corporations. Europe follows closely with a steady demand driven by stringent corporate governance norms and risk management practices. The Asia Pacific region is expected to witness the highest growth rate, fueled by the rapid economic development, increasing number of SMEs, and growing awareness about business risk management. Latin America and the Middle East & Africa are also showing promising growth potential, albeit from a relatively smaller base.

Type Analysis

The key person income insurance market is segmented by type into permanent and term insurance. Permanent key person income insurance provides coverage for the entire life of the insured individual, offering both a death benefit and a cash value component that can accumulate over time. This type of insurance is particularly attractive to large enterprises seeking long-term financial security and stability. The permanent insurance segment is anticipated to witness robust growth as more companies look to lock in long-term coverage for their key personnel. The rising cost of replacing high-level executives and the need for s

Results from cross validation with bootstrapping and external validation of risk prediction models to estimate 10-year mortality risk by the combination of major risk factors of all-cause of death in the National Health Insurance Service—National Health Screening Cohort (NHIS-HEALS) from 2002 to 2013.

BackgroundColorectal cancer is a high-burden disease that requires comprehensive multidisciplinary management. In Colombia, despite a healthcare system covering 97% of the population, socioeconomic disparities persist. Lower income levels are associated with decreased survival, potentially due to delays in diagnosis or treatment and a higher probability of advanced staging at diagnosis, These inequities persist even among relatively advantaged populations, such as formal employee who are assumed to have fewer barriers to accessing healthcare services compared to informal workers.ObjectiveThis study aimed to assess the association monthly minimum wages (MMW) as a measure of socioeconomic status in three-year survival among formal employees diagnosed with colorectal cancer in Colombia from 2012 to 2019.MethodsA retrospective cohort study was conducted using administrative databases that included healthcare and mortality records. Formal employees newly diagnosed with colorectal cancer were identified through diagnostic and oncological procedure codes and were followed for three years from the date of diagnosis or until death. The exposure variable was the legal monthly minimum wage (MMW) at the time of diagnosis, used as a proxy for socioeconomic status, while the outcome variable was three-year survival. Patients were stratified into quartiles based on their MMW. The three-year mortality proportion was calculated for each quartile. To assess survival differences, Cox proportional hazards regression models were applied to estimate adjusted hazard ratios (HRs). Socioeconomic gradients in survival were quantified using the Relative Index of Inequality (RII) and the Slope Index of Inequality (SII).ResultsThe cohort included 1,913 formal employees (mean age: 49.9 years), with 660 deaths (34.5%) recorded over the follow-up period. Patients in the lowest MMW quartile experienced the highest three-year mortality (39.5%) compared to those in the highest quartile (30.7%). After adjusting for confounders, individuals in the highest quartile had a 25% lower risk of death than those in the lowest quartile (aHR: 0.74; 95% CI: 0.59–0.92). The RII indicated a 50% higher risk of death in the lowest income group (RII: 1.50; 95% CI: 1.13–1.99), while the SII revealed an absolute difference of 0.16 deaths per 1,000 individuals (p=0.01).ConclusionSignificant income-based disparities in colorectal cancer survival were observed among formal employees in Colombia despite the theoretically equitable healthcare system. These findings underscore the persistent influence of socioeconomic factors on health outcomes, even within populations assumed to have better access to care.