Estimating health-adjusted life expectancy conditional on risk factors: results for smoking and obesity

BACKGROUND: Smoking and obesity are risk factors causing a large burden of disease. To help formulate and prioritize among smoking and obesity prevention activities, estimations of health-adjusted life expectancy (HALE) for cohorts that differ solely in their lifestyle (e.g. smoking vs. non smoking) can provide valuable information. Furthermore, in combination with estimates of life expectancy (LE), it can be tested whether prevention of obesity and smoking results in compression of morbidity. METHODS: Using a dynamic population model that calculates the incidence of chronic disease conditional on epidemiological risk factors, we estimated LE and HALE at age 20 for a cohort of smokers with a normal weight (BMI < 25), a cohort of non-smoking obese people (BMI>30) and a cohort of 'healthy living' people (i.e. non smoking with a BMI < 25). Health state valuations for the different cohorts were calculated using the estimated disease prevalence rates in combination with data from the Dutch Burden of Disease study. Health state valuations are multiplied with life years to estimate HALE. Absolute compression of morbidity is defined as a reduction in unhealthy life expectancy (LE-HALE) and relative compression as a reduction in the proportion of life lived in good health (LE-HALE)/LE. RESULTS: Estimates of HALE are highest for a 'healthy living' cohort (54.8 years for men and 55.4 years for women at age 20). Differences in HALE compared to 'healthy living' men at age 20 are 7.8 and 4.6 for respectively smoking and obese men. Differences in HALE compared to 'healthy living' women at age 20 are 6.0 and 4.5 for respectively smoking and obese women. Unhealthy life expectancy is about equal for all cohorts, meaning that successful prevention would not result in absolute compression of morbidity. Sensitivity analyses demonstrate that although estimates of LE and HALE are sensitive to changes in disease epidemiology, differences in LE and HALE between the different cohorts are fairly robust. In most cases, elimination of smoking or obesity does not result in absolute compression of morbidity but slightly increases the part of life lived in good health. CONCLUSION: Differences in HALE between smoking, obese and 'healthy living' cohorts are substantial and similar to differences in LE. However, our results do not indicate that substantial compression of morbidity is to be expected as a result of successful smoking or obesity prevention

Relative contribution of various chronic diseases and multi-morbidity to potential disability among Dutch elderly

BACKGROUND: The amount of time spent living with disease greatly influences elderly people’s wellbeing, disability and healthcare costs, but differs by disease, age and sex. METHODS: We assessed how various single and combined diseases differentially affect life years spent living with disease in Dutch elderly men and women (65+) over their remaining life course. Multistate life table calculations were applied to age and sex-specific disease prevalence, incidence and death rates for the Netherlands in 2007. We distinguished congestive heart failure, coronary heart disease (CHD), breast and prostate cancer, colon cancer, lung cancer, diabetes, COPD, stroke, dementia and osteoarthritis. RESULTS: Across ages 65, 70, 75, 80 and 85, CHD caused the most time spent living with disease for Dutch men (from 7.6 years at age 65 to 3.7 years at age 85) and osteoarthritis for Dutch women (from 11.7 years at age 65 to 4. 8 years at age 85). Of the various co-occurrences of disease, the combination of diabetes and osteoarthritis led to the most time spent living with disease, for both men (from 11.2 years at age 65 to 4.9 -years at age 85) and women (from 14.2 years at age 65 to 6.0 years at age 85). CONCLUSIONS: Specific single and multi-morbid diseases affect men and women differently at different phases in the life course in terms of the time spent living with disease, and consequently, their potential disability. Timely sex and age-specific interventions targeting prevention of the single and combined diseases identified could reduce healthcare costs and increase wellbeing in elderly people

Particulate air pollutants, APOE alleles and their contributions to cognitive impairment in older women and to amyloidogenesis in experimental models

Exposure to particulate matter (PM) in the ambient air and its interactions with APOE alleles may contribute to the acceleration of brain aging and the pathogenesis of Alzheimer's disease (AD). Neurodegenerative effects of particulate air pollutants were examined in a US-wide cohort of older women from the Women's Health Initiative Memory Study (WHIMS) and in experimental mouse models. Residing in places with fine PM exceeding EPA standards increased the risks for global cognitive decline and all-cause dementia respectively by 81 and 92%, with stronger adverse effects in APOE ɛ4/4 carriers. Female EFAD transgenic mice (5xFAD(+/−)/human APOE ɛ3 or ɛ4(+/+)) with 225 h exposure to urban nanosized PM (nPM) over 15 weeks showed increased cerebral β-amyloid by thioflavin S for fibrillary amyloid and by immunocytochemistry for Aβ deposits, both exacerbated by APOE ɛ4. Moreover, nPM exposure increased Aβ oligomers, caused selective atrophy of hippocampal CA1 neurites, and decreased the glutamate GluR1 subunit. Wildtype C57BL/6 female mice also showed nPM-induced CA1 atrophy and GluR1 decrease. In vitro nPM exposure of neuroblastoma cells (N2a-APP/swe) increased the pro-amyloidogenic processing of the amyloid precursor protein (APP). We suggest that airborne PM exposure promotes pathological brain aging in older women, with potentially a greater impact in ɛ4 carriers. The underlying mechanisms may involve increased cerebral Aβ production and selective changes in hippocampal CA1 neurons and glutamate receptor subunits