The direct health care costs of obesity in the United States.

OBJECTIVES: Recent estimates suggest that obesity accounts for 5.7% of US total direct health care costs, but these estimates have not accounted for the increased death rate among obese people. This article examines whether the estimated direct health care costs attributable to obesity are offset by the increased mortality rate among obese individuals. METHODS: Data on death rates, relative risks of death with obesity, and health care costs at different ages were used to estimate direct health care costs of obesity from 20 to 85 years of age with and without accounting for increased death rates associated with obesity. Sensitivity analyses used different values of relative risk of death, given obesity, and allowed the relative costs due to obesity per unit of time to vary with age. RESULTS: Direct health care costs from 20 to 85 years of age were estimated to be approximately 25% lower when differential mortality was taken into account. Sensitivity analyses suggested that direct health care costs of obesity are unlikely to exceed 4.32% or to be lower than 0.89%. CONCLUSIONS: Increased mortality among obese people should be accounted for in order not to overestimate health care costs.     

Time to retire – Time to die? A prospective cohort study of the effects of early retirement on long-term survival

In a long-term prospective cohort study we try to assess selective and protective impacts of early retirement on life expectancy. The results are based on the members of a compulsory German health insurance fund (Gmünder Ersatzkasse). We analyzed 88,399 men and 41,276 women who retired between the ages of 50 and 65 from January 1990 to December 2004. Our main outcome measures are hazard ratios for death adjusted for age, sex, marital and socioeconomic status, year of observation, age at retirement, hospitalization, and form of retirement scheme. We found a significantly higher mortality risk among pensioners with reduced earning capacities than among old-age pensioners who either left the labor market between the ages of 56 and 60 or between 61 and 65. The youngest male and female pensioners who left the labor market between the ages of 51 and 55 because of their reduced earning capacity faced the highest mortality risk. But healthy people who retire early do not experience shorter long-term survival than those who retire late. On the contrary, if we take into consideration the amount of days spent in hospital during the last 2 years prior to retirement, early retirement in fact lowers mortality risks significantly by 12% for men and by 23% for women. Thus with respect to mortality, early retirement reflects both selective and protective processes. First of all, individuals with poor health and lower survival chances are filtered out of the labor market. However, healthy pensioners may be protected during retirement. For the former, early retirement is a necessity, for the latter it is an asset. Pension reformers should take health differentials into consideration when cutting back pension programs and increasing retirement age.     

1995 至 2009年北京协和医院住院糖尿病患者情况分析

目的分析不同年份、不同科室糖尿患者的住院率,比较糖尿病患者与非糖尿患者在住院费用、时间和死亡率方面的差异。方法回顾性分析1995至2009年在北京协和医院各科住院的糖尿病和非糖尿病患者的临床资料,按时间以5年为1段分为3段,按年龄分为4段。结果共有500523例患者纳入分析。1995至2009年,糖尿病患者占总住院人数的比率由2．85％增加至7．65％;各科糖尿病患者占科室住院人数比率以心内科、眼科和血管外科增加最明显,到2009年分别为29．36％、24．51％、21．25％。各时间段及年龄段糖尿病组患者的住院时间均明显长于非糖尿病组患者（P〈0．001）;总住院费用除2000至2004年及2005至2009年0～18岁年龄段差异无统计学意义外（P〉0．05）,其余各时间段及各年龄段均为糖尿病组患者明显高于非糖尿病组患者（P〈0．01或P〈0．001）;除1995至1999年65岁以上年龄段外（P〉0．05）,各时间段及年龄段糖尿病组患者的日均住院费用均明显低于非糖尿病组患者（P〈0．05、P〈0．01或P〈0．001）。1995至2004年0—18岁糖尿病患者的死亡率为0,2005至2009年19—44岁年龄段糖尿病与非糖尿病患者死亡率差异无统计学意义（P〉0．05）,其余各时间段及年龄段糖尿病组患者的死亡率均明显高于非糖尿病组患者（P〈0．01或P〈0．001）。结论糖尿病患者的住院时间较长,住院率、住院费用及死亡率较高,应制订全院范围内糖尿病管理模式,提高治疗水平。     

The European Community 'avoidable death indicators' in Sweden 1974-1985.

Avoidable mortality in Sweden 1974-1985 was analysed using a European Community (EC) Working Group list of 'avoidable death indicators." The list includes causes of death that in certain age groups were defined as indicators of the outcome of medical care intervention or for some conditions, indicators of the national health policies. About 10 out of 14 medical health care indicators occurred in less than 50 cases per year. Death rates decreased over the 12-year period studied for most avoidable death indicators. For women, however, the death rate for malignant neoplasms of the trachea, bronchus and lung increased significantly. Swedish total mortality for ages 5-64 years was lower than the EC standards 1974-1978 and 1980-1984. Most of the avoidable causes of death had a relatively low standard mortality rate (SMR) when compared to both the EC standard and to the Swedish SMR for total mortality. For asthma, however, the Swedish SMR was higher. The development and implementation of the avoidable death concept and methodology is discussed.     

Health care costs in the last year of life--the Dutch experience

Health expenditure depends heavily on age. Common wisdom is that the age pattern is dominated by costs in the last year of life. Knowledge about these costs is important for the debate on the future development of health expenditure. According to the 'red herring' argument traditional projection methods overestimate the influence of ageing because improvements in life expectancy will postpone rather than raise health expenditure. This paper has four objectives: (1) to estimate health care costs in the last year of life in the Netherlands; (2) to describe age patterns and differences between causes of death for men and women; (3) to compare cost profiles of decedents and survivors; and (4) to use these figures in projections of future health expenditure. We used health insurance data of 2.1 million persons (13% of the Dutch population), linked at the individual level with data on the use of home care and nursing homes and causes of death in 1999. On average, health care costs amounted to 1100 Euro per person. Costs per decedent were 13.5 times higher and approximated 14,906 Euro in the last year of life. Most costs related to hospital care (54%) and nursing home care (19%). Among the major causes of death, costs were highest for cancer (19,000 Euro) and lowest for myocardial infarctions (8068 Euro). Between the other causes of death, however, cost differences were rather limited. On average costs for the younger decedents were higher than for people who died at higher ages. Ten per cent of total health expenditure was associated with the health care use of people in their last year of life. Increasing longevity will result in higher costs because people live longer. The decline of costs in the last year of life with increasing age will have a moderate lowering effect. Our projection demonstrated a 10% decline in the growth rate of future health expenditure compared to conventional projection methods.     

Life expectancy and health care expenditures: a new calculation for Germany using the costs of dying

Some people believe that the impact of population ageing on future health care expenditures will be quite moderate due to the high costs of dying. If not age per se but proximity to death determines the bulk of expenditures, a shift in the mortality risk to higher ages will not affect lifetime health care expenditures as death occurs only once in every life. We attempt to take this effect into account when we calculate the demographic impact on health care expenditures in Germany. From a Swiss data set, we derive age-expenditure profiles for both genders, separately for persons in their last 4 years of life and for survivors, which we apply to the projections of the age structure and mortality rates for the German population between 2002 and 2050 as published by the Statistische Bundesamt. In the extreme case, we assume that morbidity is compressed at the end of life in such a way that a 60-year old in 2050 is as healthy as a 56-year old today if his life expectancy is 4 years higher. We calculate that at constant prices, per-capita health expenditures of Social Health Insurance would rise from 2596 Euro in 2002 to between 2959 Euro and 3102 Euro in 2050 when only the age structure of the population changes and everything else remains constant at the present level, and to between 5232 Euro and 5485 Euro with a technology-driven exogenous cost increase of 1% per annum. A "na?ve" projection based only on the age distribution of health care expenditures, but not distinguishing between survivors and decedents, yields values of 3217 Euro and 5688 Euro for 2050, respectively. Thus, the error of excluding the "costs of dying" effect is small compared with the error of underestimating the financial consequences of expanding medical technology.     

Health care expenditures and the aging population

The impact of a longer life on future health care expenditures will be quite moderate because of the high costs of dying and the compression of mortality in old age. If not age per se but proximity to death determines the bulk of expenditures, a shift in the mortality risk to higher ages will not significantly affect lifetime health care expenditures, as death occurs only once in every life. A calculation of the demographic effect on health care expenditures in Germany up until 2050 that explicitly accounts for costs in the last years of life leads to a significantly lower demographic impact on per-capita expenditures than a calculation based on crude age-specific health expenditures.     

Gesundheitsausgaben und demografischer Wandel

The impact of a longer life on future health care expenditures will be quite moderate because of the high costs of dying and the compression of mortality in old age. If not age per se but proximity to death determines the bulk of expenditures, a shift in the mortality risk to higher ages will not significantly affect lifetime health care expenditures, as death occurs only once in every life. A calculation of the demographic effect on health care expenditures in Germany up until 2050 that explicitly accounts for costs in the last years of life leads to a significantly lower demographic impact on per-capita expenditures than a calculation based on crude age-specific health expenditures.     

Sex differences in health and mortality in Moscow and Denmark

In high income countries females outlive men, although they generally report worse health, the so-called male–female health-survival paradox. Russia has one of the world’s largest sex difference in life expectancy with a male disadvantage of more than 10 years. We compare components of the paradox between Denmark and Moscow by examining sex differences in mortality and several health measures. The Human Mortality Database and the Russian Fertility and Mortality Database were used to examine sex differences in all-cause death rates in Denmark, Russia, and Moscow in 2007–2008. Self-reported health data were obtained from the Study of Middle-Aged Danish Twins (n = 4,314), the Longitudinal Study of Aging Danish Twins (n = 4,731), and the study of Stress, Aging, and Health in Russia (n = 1,800). In both Moscow and Denmark there was a consistent female advantage at ages 55–89 years in survival and a male advantage in self-rated health, physical functioning, and depression symptomatology. Only on cognitive tests males performed similarly to or worse than women. Nevertheless, Muscovite males had more than twice higher mortality at ages 55–69 years compared to Muscovite women, almost double the ratio in Denmark. The present study showed that despite similar directions of sex differences in health and mortality in Moscow and Denmark, the male–female health-survival paradox is very pronounced in Moscow suggesting a stronger sex-specific disconnect between health indicators and mortality among middle-aged and young-old Muscovites.     

Sex differentials in health and mortality

Data on physical health and mortality in the US, centered near the 1980 Census year, are presented, focusing on sex differentials in mortality followed by sex differentials in health. The discussion covers possible explanations for these sex differentials and the apparent contradiction of why there is excess female morbidity but excess male mortality. In 1980, the estimated life expectancy at birth was 70.0 years for men and 77.5 years for women. Age-adjusted death rates in the US were 777 deaths/100,000 for men and 433 deaths/100,000 for women, yielding a sex ratio of 1.79. Thus, in 1980, men had nearly an 80% higher age-adjusted death rate than women. Further, for every 100,000 people, 200 more men than women died. The age-adjusted figure was 345. In the US in 1980 the age-adjusted mortality rate for each of the 12 leading causes of death was higher for men than women. The sex mortality ratios demonstrate that relative to women, men had higher mortality rates particularly between the ages of 15-34. The sex ratio of life expectation increases with age. A women over age 60 in 1980 could expect to live nearly 30% longer than a man her age. Accidents are the main contributor to the sex differential at young ages; heart disease is the primary contributor at older ages. Regardless of how health interviews word the questions, women consistently report worse health status than men. In interview data, females tend to have more acute conditions per year than males -- about 17% more in 1980, and with a similar excess in other years. The female excess appears for infective and parasitic diseases, respiratory conditions, digestive system conditions, and "all other acute conditions." The last group includes problems due to pregnancy and childbirth, yet, even when these are removed, female rates for "all other acute conditions" exceed male rates. Only for injuries do males have higher rates than females. The available data suggest that women have greater morbidity than men. After early childhood, females have both higher rates of acute conditions and more restricted activity per condition. Females are more likely to have a chronic condition, to have more doctor and dentist visits, and to use more drugs. These relationships remain even after pregnancy-related events are removed. Yet, men have higher prevalence for many "killer" chronic conditions, higher prevalence rates of heart disease at younger ages, and higher injury rates at all ages. Sex differences in 4 areas provide possible explanations as to why women tend to have poorer health but men tend to have shorter lives: inherited risks; acquired risks; illness and prevention orientations; and health and death reporting behavior.     

Self rated health: Is it as good a predictor of subsequent mortality among adults in lower as well as in higher social classes?

STUDY OBJECTIVE: To analyse the predictive power of self rated health for mortality in different socioeconomic groups. DESIGN, SETTING, PARTICIPANTS: Analysis of mortality rates and risk ratios of death during follow up among 170 223 respondents aged 16 years and above in the Swedish Survey of Living Conditions 1975-1997, in relation to self rated health stated at the interview, by age, sex, socioeconomic group, chronic illness and over time. MAIN RESULTS: There was a strong relation between poor self rated health and mortality, greater at younger ages, similar among men and women and among persons with and without a chronic illness. The relative relation between self rated health and subsequent death was stronger in higher than in lower socioeconomic groups, possibly because of the lower base mortality of these groups. However, the absolute mortality risk differences between persons reporting poor and good self rated health were similar across socioeconomic groups within each sex. The mortality risk difference between persons reporting poor and good self rated health was considerably higher among persons with a chronic illness than among persons without a chronic illness. The mortality risk among persons reporting poor health was increased for shorter (<2 years) as well as longer (10+ years) periods of follow up. CONCLUSIONS: The results suggest that poor self rated health is a strong predictor of subsequent mortality in all subgroups studied, and that self rated health therefore may be a useful outcome measure.     

Formal and Informal Costs of Care for People With Dementia Who Experience a Transition to Hospital at the End of Life: A Secondary Data Analysis

ObjectivesTo explore formal and informal care costs in the last 3 months of life for people with dementia, and to evaluate the association between transitions to hospital and usual place of care with costs.DesignCross-sectional study using pooled data from 3 mortality follow-back surveys.Setting and ParticipantsPeople who died with dementia.MethodsThe Client Service Receipt Inventory survey was used to derive formal (health, social) and informal care costs in the last 3 months of life. Generalized linear models were used to explore the association between transitions to hospital and usual place of care with formal and informal care costs.ResultsA total of 146 people who died with dementia were included. The mean age was 88.1 years (SD 6.0), and 98 (67.1%) were female. The usual place of care was care home for 85 (58.2%). Sixty-five individuals (44.5%) died in a care home, and 85 (58.2%) experienced a transition to hospital in the last 3 months. The mean total costs of care in the last 3 months of life were £31,224.7 (SD 23,536.6). People with a transition to hospital had higher total costs (£33,239.2, 95% CI 28,301.8-39,037.8) than people without transition (£21,522.0, 95% CI 17,784.0-26,045.8), mainly explained by hospital costs. People whose usual place of care was care homes had lower total costs (£23,801.3, 95% CI 20,172.0-28,083.6) compared to home (£34,331.4, 95% CI 27,824.7-42,359.5), mainly explained by lower informal care costs.Conclusions and ImplicationsTotal care costs are high among people dying with dementia, and informal care costs represent an important component of end-of-life care costs. Transitions to hospital have a large impact on total costs; preventing these transitions might reduce costs from the health care perspective, but not from patients' and families' perspectives. Access to care homes could help reduce transitions to hospital as well as reduce formal and informal care costs.     

Cost inefficiency and mortality rates in Florida hospitals

This study examines the relationship between health outcomes and cost inefficiency in Florida hospitals over the period 1999-2001, with health outcomes measured by risk-adjusted in-hospital mortality rates. Previous research has come to conflicting conclusions regarding the relationship between costs and health outcomes. We hypothesize that these seemingly conflicting findings are due to the fact that total cost has two components--cost that reflects the best use of resources under current circumstances and cost associated with waste or inefficiency. By isolating costs due to inefficiency, we can examine directly their relationship, if any, to hospital mortality rates, and begin to assess whether policies that create incentives for hospitals to increase efficiency have adverse effects on health outcomes. We regress an in-hospital mortality index for each hospital on a measure of the hospital's cost inefficiency, obtained from a stochastic cost frontier estimation, as well as on predicted mortality and a set of variables linked to mortality performance. Our results indicate a positive and significant relationship between a hospital's mortality performance and its inefficiency: on average, a one percentage point reduction in cost inefficiency would be associated with one fewer in-hospital death per 10,000 discharges, holding patient risk and other factors constant.     

The intention to switch health insurer and actual switching behaviour: are there differences between groups of people?

Background Several western countries have introduced managed competition in their health care system. In the Netherlands, a new health insurance law was introduced in January 2006 making it easier to switch health insurer each year. Objective The objective was to measure people’s intention to switch health insurer and actual switching behaviour. We also examined whether some groups were less inclined to switch health insurer and/or had more difficulty to exert their intention to switch. Design In October 2006, members of three Dutch panels indicated whether they intended to switch health insurer during that year’s open enrolment period. In the beginning of 2007, the same people were asked whether they indeed switched health insurer. Results Only 1% intended to switch health insurer. Women, older people, lower educated people, people who were insured for a longer period and people who reported a bad or moderate health were less inclined to switch health insurer. The amount of switching was higher among individuals who intended to switch (31%) than among individuals who did not know whether they would switch (7%) and individuals with no intention to switch (2%). Among those who intended to switch health insurer, women and people who reported a good health switched health insurer more often. The years of enrolment were also associated with actual switching behaviour. Discussion and Conclusions We might have to temper the optimistic expectations on enhanced choice. Future research should determine why people do not switch health insurer when they intend to and which barriers they experience.     

Policy relevant determinants of health: an international perspective

BACKGROUND: International comparisons can provide clues to understanding some of the important policy-related determinants of health, including those related to the provision of health care services. An earlier study indicated that the strength of the primary care infrastructure of a health services system might be related to overall costs of health services. The purpose of the current research was to determine the robustness of the findings in the light of the passage of 5-10 years, the addition of two more countries, and the findings of other research on the possible importance of other determinants of country health levels. METHODS: Thirteen industrialized countries, all with populations of at least 5 million, were characterized by the relative strength of their primary care infrastructure, the degree of national income inequality, and a major manifestation of a behavioral determinant of health that is amenable to policy intervention (smoking), using international data sets and national informants. Health system and primary care practice characteristics were judged according to pre-set criteria. Major indicators of health were used as dependent variables, as were health care costs. FINDINGS: The stronger the primary care, the lower the costs. Countries with very weak primary care infrastructures have poorer performance on major aspects of health. Although countries that are intermediate in the strength of their primary care generally have levels of health at least as good as those with high levels of primary care, this is not the case in early life, when the impact of strong primary care is greatest. A subset of characteristics (equitable distribution of resources, publicly accountable universal financial coverage, low cost sharing, comprehensive services, and family-oriented services) distinguishes countries with overall good health from those with poor health at all ages. Neither income inequality nor smoking status accurately identified those countries with either consistently high or consistently poor performance on the health indicators. Interpretation: A certain level of health care expenditures may be required to achieve overall good health levels, even in the presence of strong primary care infrastructures. Very low costs may interfere with achievement of good health, particularly at older ages, although very high levels of costs may signal excessive and potentially health-compromising care. Five policy-relevant characteristics appear to be related to better population health levels. There is no consistent relationship between income inequality, smoking, and health levels as measured by various indicators of health in different age groups.     

The effects of income, education and age on health

We use the core interviews of the US Health Interview Survey for the years 1987-1994, to study the effects of socioeconomic status (SES) on mortality and self-reported health. We find, consistent with previous studies, that the relationship between mortality and indicators such as education and income diminishes with age. We consider new explanations for this result and conclude that general biological deterioration at old age is probably the principal one. One important piece of evidence for this conclusion is the finding that there is no relationship at all between mortality and SES for people whose self-reported health status at baseline is either fair or poor.     

Health Care Utilization and Costs Associated with Physical and Nonphysical-Only Intimate Partner Violence

Objective. To estimate health care utilization and costs associated with the type of intimate partner violence (IPV) women experience by the timing of their abuse.
Methods. A total of 3,333 women (ages 18–64) were randomly sampled from the membership files of a large health plan located in a metropolitan area and participated in a telephone survey to assess IPV history, including the type of IPV (physical IPV or nonphysical abuse only) and the timing of the abuse (ongoing; recent, not ongoing but occurring in the past 5 years; remote, ending at least 5 years prior). Automated annual health care utilization and costs were assembled over 7.4 years for women with physical IPV and nonphysical abuse only by the time period during which their abuse occurred (ongoing, recent, remote), and compared with those of never-abused women (reference group).
Results. Mental health utilization was significantly higher for women with physical or nonphysical abuse only compared with never-abused women—with the highest use among women with ongoing abuse (relative risk for those with ongoing abuse: physical, 2.61; nonphysical, 2.18). Physically abused women also used more emergency department, hospital outpatient, primary care, pharmacy, and specialty services; for emergency department, pharmacy, and specialty care, utilization was the highest for women with ongoing abuse. Total annual health care costs were higher for physically abused women, with the highest costs for ongoing abuse (42 percent higher compared with nonabused women), followed by recent (24 percent higher) and remote abuse (19 percent higher). Women with recent nonphysical abuse only had annual costs that were 33 percent higher than nonabused women.
Conclusion. Physical and nonphysical abuse contributed to higher health care utilization, particularly mental health services utilization.     

Subjective health as predictor for mortality

In the last two decades self-rated health has received growing interest in international studies because of its consistent prediction for mortality. However, for Germany there are no studies confirming a long-term effect independent from objective health indicators in comparison of different follow-up. On the basis of the Life-Expectancy-Study (1984/86 - 1998) from the Federal Institute for Population Research it was possible to analyze the association between subjective health and mortality in relation to the length of observation. A stronger correlation between bad self-rated health and objective health status could be indicated because of a better prediction for mortality in a short-term follow-up. The evidence of a significant effect between self-rated health and mortality in the long-term follow-up not including the deaths from the short-term follow-up indicates that the mechanisms between subjective health and mortality are more complex than those between objective health status and death.     

Conjugal bereavement effects on health and mortality at advanced ages

Spousal bereavement at old ages may lead to dramatic changes in health. This paper investigates whether spousal bereavement has a causal effect on health and on mortality of the surviving spouse. We advance on the literature in two main ways. First, we model survivals of both spouses and the dynamic evolution of health jointly, allowing for potential endogeneity of timing of bereavement and health in explaining mortality of the surviving spouse. Second, we use a flexible non-parametric data dimensionality reduction method to thoroughly characterize health (using 22 health indicators) by a limited number of latent health indicators. This allows us to investigate the causal effect of spousal bereavement on mortality and on all aspects of health simultaneously. Our analyses are based on an ongoing longitudinal survey that follows a random sample of older individuals from 1992. We find strong instantaneous effects of bereavement on mortality and on certain aspects of health. Individuals lose on average 12% of residual life expectancy after conjugal bereavement. Conjugal bereavement affects the share of healthy years in residual lifetime, primarily because healthy years are replaced by years with chronic diseases. The strong direct effects of bereavement suggest that monitoring and/or interventions just after spousal bereavement are important for the length and quality of life of older bereaved individuals.