An adaptation of Charlson comorbidity index predicted subsequent mortality in a health survey

OBJECTIVE: The Catalan Health Interview Survey Follow-up Study analyzed survival differences according to comorbidity, using an adaptation of the Charlson's index. STUDY DESIGN AND SETTING: Vital status was ascertained by record linkage with death certificates 5 years after interview. Three thousand one hundred five men and 3,536 women aged 40-84 years old were included in the analysis. Proportional hazards models with age as time scale were used to calculate relative risk (RR) and 95% confidence interval adjusted for potential confounders. RESULTS: The adjusted RR of death in men was 1.02 (0.73-1.41) for a comorbidity index of 1-2; the RR was 1.51 (1-2.30) for an index of 3-4, and 2.64 (1.43-4.89) for an index of >4 composed to an index of 0. In women, for the same comorbidity index categorization, the RR of death were 0.83 (0.55-1.24), 1.71 (1.09-2.72) and 2.65 (1.47-4.77). CONCLUSION: This result confirms the relation between comorbidity and the risk of death based on a comorbidity index that takes into account severity and number of self-declared chronic diseases with mortality.     

Predictive validity of the total health index for all-cause mortality assessed in the Komo-Ise cohort

Background

The Total Health Index (THI), a self-administered questionnaire developed in Japan, is used for symptom assessment and stress management of employees and others; however, it has not been reported whether it can predict mortality risk.

Methods

The THI, with 12 primary and 5 secondary scales, was applied to a cohort consisting of middle-aged residents in Japan. This study, called the Komo-Ise cohort study, was started in 1993. The scale scores were related to 481 deaths from all causes among 10,816 residents over 93 months. The statistics were tested by the Cox hazard model and adjusted for three background variables (sex, age, and district where the subject resided).

Results

Five of the scales [depression and aggression (primary scales), and psychosomatics, neurotics, and schizophrenics (secondary scales)] indicated significant hazard ratios for mortality. The lowest quintile group of the aggression scale score had the largest hazard ratio of 2.58, compared with the middle quintile group (95% confidence interval: 1.88-3.52). The psychosomatics, neurotic scales and depression scales also had a minimum hazard ratio in the middle quintile group. One of the secondary scales, T1, which represents a somatoform disorder, had a significant linear relationship with the mortality risk, although its proportionality with the cumulative mortality rates was not satisfactory.

Conclusions

Five scales of the THI were significantly related to mortality risk in the Komo-Ise cohort, which could be used for score evaluation and in the personal health advice system of the THI.Key words: Komo-Ise Cohort, Mortality, Risk, Perceived Health, Prospective Studies, Total Health Index (THI)     

Child health and mortality

Bangladesh is currently one of the very few countries in the world, which is on target for achieving the Millennium Development Goal (MDG) 4 relating to child mortality. There have been very rapid reductions in mortality, especially in recent years and among children aged over one month. However, this rate of reduction may be difficult to sustain and may impede the achievement of MDG 4. Neonatal deaths now contribute substantially (57%) to overall mortality of children aged less than five years, and reductions in neonatal mortality are difficult to achieve and have been slow in Bangladesh. There are some interesting attributes of the mortality decline in Bangladesh. Mortality has declined faster among girls than among boys, but the poorest have not benefited from the reduction in mortality. There has also been a relative absence of a decline in mortality in urban areas. The age and cause of death pattern of under-five mortality indicate certain interventions that need to be scaled up rapidly and reach high coverage to achieve MDG 4 in Bangladesh. These include skilled attendance at delivery, postnatal care for the newborn, appropriate feeding of the young infant and child, and prevention and management of childhood infections. The latest (2007) Bangladesh Demographic and Health Survey shows that Bangladesh has made sustained and remarkable progress in many areas of child health. More than 80% of children are receiving all vaccines. The use of oral rehydration solution for diarrhoea is high, and the coverage of vitamin A among children aged 9-59 months has been consistently increasing. However, poor quality of care, misperceptions regarding the need for care, and other social barriers contribute to low levels of care-seeking for illnesses of the newborns and children. Improvements in the health system are essential for removing these barriers, as are effective strategies to reach families and communities with targeted messages and information. Finally, there are substantial health-system challenges relating to the design and implementation, at scale, of interventions to reduce neonatal mortality.     

The infant mortality rate, life expectancy at birth, and a linear index of mortality as measures of general health status

The infant mortality rate is not a good indicator of overall mortality or health status. Based on new empirical life tables from the UN Population Division, it can only predict life expectancy with 95% confidence to within a 14-year range. Two infant mortality rates must be nearly 80 units apart to be 95% confident that life expectancy in the two communities is different. Life expectancy itself is not an ideal general measure of mortality, because it implicitly weights deaths at different ages in an inconsistent fashion. A measure of potential years of life lost is preferable because it is ethically more consistent.     

Perceived general health and mortality

Many international studies underline the importance of the health indicator "perceived general health" (PGH). For Germany, only few Longitudinal studies are available from recent years, dealing with the question whether PGH is a predictor for overall mortality. Based on a Mortality-Follow-up Study (n = 7212) under the auspices of the Federal Institute for Population Research the importance of the indicator PGH for the prediction of the mortality experience in the general population has been analysed for the period 1984 - 1998. The age-adjusted relative risk of "less than good health" for overall mortality is 2.11 (p <0.001) for males and 2.05 (p <0.001) for females (reference category: "good/very good health"). The relative risks for "poor health" are 4.32 (p <0,001) in males and 3.07 (p <0.001) in females. An inclusion of several control variables remarkably reduces these relative risks. The results indicate that the indicator "perceived general health" is an important predictor of overall mortality in Germany.     

Jarman index related to post-perinatal mortality.

Post-perinatal infant deaths in North and Southern Derbyshire District Health Authorities were calculated by electoral ward over a period of two years and related to Jarman scores of deprivation. The deaths were categorised into clinical-pathological groupings after full confidential enquiry. The post-perinatal death rates were significantly related to Jarman score of deprivation.     

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.     

健康指数的构建方法

当前在健康指数构建方面存在的瓶颈,一方面是缺乏构建健康指数的一般性、普适性的理论模型或理论范式;二是缺乏全栈式健康指数技术流程,致使健康指数转化应用难以实现规模化、权威化适时发布。为此,本文在已构建的健康指数的普适性概念模型及理论范式指导下,制定了贯穿“数据平台→数据采集→健康测量→理论模型→循证指标→指标体系→加权综合→指数可视化→指数发布→转化服务”的全栈式健康指数技术流程,实现了健康指数转化应用的规模化、权威化适时发布和服务。     

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.     

Body shape index and mortality in hemodialysis patients

ObjectiveThe relationship between various anthropometric parameters and mortality in hemodialysis (HD) patients is conflicting. Recently a new anthropometric parameter emerged, namely, body shape index (BSI). BSI is based on waist circumference (WC) but is independent of height, weight, and body mass index in predicting mortality in the general population. The aim of this study was to determine the relationship between BSI and mortality in HD patients.MethodsThis retrospective study evaluated the demographic characteristics and anthropometric measures including BSI, laboratory parameters, and mortality data in HD patients in a single center.ResultsThere were 142 HD patients enrolled in the study. The median BSI was 0.0816. Because no normal value was defined for BSI, the patients were divided into two groups based on the median BSI: group 1 BSI < 0.0816 and group 2 BSI > 0.0816. During an average follow-up period of 40.1 ± 19.2 mo (range 12–88 mo), 36 (25.4%) patients had died. The Cox regression analysis of independence showed that increased age (hazard ratio [HR], 1.077, 95% confidence interval [CI],1.031–1.125; P = 0.001), presence of diabetes (HR, 2.855, 95% CI, 1.258–6.481; P = 0.012), hemoglobin (HR, 0.629, 95% CI, 0.452–0.875; P = 0.006), and albumin (HR, 0.442, 95% CI, 0.204–0.955; P = 0.038) were independently related with mortality. None of the anthropometric parameters including BSI were related with mortality. Kaplan-Meier analysis showed that there were no differences with respect to mortality among patients in group 1 and group 2 based on median BSI (P = 0.332, log-rank test).ConclusionIn conclusion, BSI is not independently associated with mortality in HD patients.     

Relationship of health practices and mortality

This paper explores the relationship of a number of personal health practices and mortality in the $\text{5}\text{1}\text{2}$ years after a survey made in Alameda County, California in 1965. Age-adjusted mortality rates were higher for men, for persons reporting disability, and for those with inadequate incomes.The individual health practices, smoking, weight in relation to desirable standards for height, drinking, hours of sleep, regularity of meals, and physical activity, were related to mortality in the expected direction. When accumulated to form a health practice score from 0 to 7, the number of health practices showed a striking inverse relationship with mortality rates, especially for men. This relationship was independent of income level and physical health status.The age-specific death rates by number of health practices were used to develop a life table. The average life expectancy of men aged 45 who reported six or seven “good” practices was more than 11 years more than that of men reporting fewer than four. For women the relationship between health practices and mortality was less strong, and the difference between the life expectancy at age 45 for those who reported six or seven, and those who reported fewer than four, was 7 years.     

健康指数逻辑框架

本研究旨在构建健康指数逻辑框架,服务健康大数据背景下健康指数的构建和“评改结合”的政策应用。以健康指数目标和问题为导向,在已有研究的基础上,明晰健康指数的内涵和外延,并将其概念化,这是逻辑框架的基础环节。其后,围绕关键目标,按照“投入-产出-结果-影响”逻辑总结归纳健康指数全过程影响因素并梳理各个因素间的交互作用,最终形成健康指数的逻辑框架。概念框架有助于抽象复杂的健康问题,反映问题的本质特征,引领健康指数定量化评估,并提出切实有效的改进政策。