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

Rural-urban differentials of premature mortality burden in south-west China

BACKGROUND: Yunnan province is located in south western China and is one of the poorest provinces of the country. This study examines the premature mortality burden from common causes of deaths among an urban region, suburban region and rural region of Kunming, the capital of Yunnan. METHODS: Years of life lost (YLL) rate per 1,000 and mortality rate per 100,000 were calculated from medical death certificates in 2003 and broken down by cause of death, age and gender among urban, suburban and rural regions. YLL was calculated without age-weighting and discounting rate. Rates were age-adjusted to the combined population of three regions. However, 3% discounting rate and a standard age-weighting function were included in the sensitivity analysis. RESULTS: Non-communicable diseases contributed the most YLL in all three regions. The rural region had about 50% higher premature mortality burden compared to the other two regions. YLL from infectious diseases and perinatal problems was still a major problem in the rural region. Among non-communicable diseases, YLL from stroke was the highest in the urban/suburban regions; COPD followed as the second and was the highest in the rural region. Mortality burden from injuries was however higher in the rural region than the other two regions, especially for men. Self-inflicted injuries were between 2–8 times more serious among women. The use of either mortality rate or YLL gives a similar conclusion regarding the order of priority. Reanalysis with age-weighting and 3% discounting rate gave similar results. CONCLUSION: Urban south western China has already engaged in epidemiological pattern of developed countries. The rural region is additionally burdened by diseases of poverty and injury on top of the non-communicable diseases

Epidemiology of hepatitis B, C and D in Malawi:systematic review

BACKGROUND:Viral hepatitis is an important public health issue in sub-Saharan Africa. Due to rising mortality from cirrhosis and hepatocellular carcinoma and limited implementation of screening and treatment programmes, it has been characterised as a neglected tropical disease. Synthesis of the existing evidence on the epidemiology of viral hepatitis B, C and D in Malawi is required to inform policy and identify research gaps. METHODS:We searched Pubmed, EMBASE and Scopus for studies reporting the epidemiology of viral hepatitis B, C and D in Malawi from 1990 to 2018. Articles reporting prevalence estimates were included provided they described details of participant selection, inclusion criteria and laboratory methods (detection of HBsAg, anti-HCV or anti-HDV antibody, HCV antigen or HCV RNA or HDV RNA). We assessed study quality using a prevalence assessment tool. Where appropriate, a pooled prevalence was calculated using a DerSimonian Laird random effects model. RESULTS:Searches identified 199 studies, 95 full text articles were reviewed and 19 articles were included. Hepatitis B surface antigen (HBsAg) seroprevalence was assessed in 14 general population cohorts. The pooled prevalence among adults was 8.1% (95% CI 6.1, 10.3). In 3 studies where HBsAg was stratified by HIV status, no effect of HIV on HBsAg prevalence was observed (OR 1.2 (95% CI: 0.8, 1.6, p = 0.80)). In a single study of HIV/HBV infected individuals, anti-hepatitis D antibody (anti-HDV) prevalence was low (1.5%). HCV antibody prevalence (anti-HCV) ranged from 0.7 to 18.0% among 12 cohorts in general populations. Among three studies which used PCR to confirm current infection, the pooled rate of HCV RNA confirmation among anti-HCV positive individuals was only 7.3% (95% CI: 0.0, 24.3). CONCLUSIONS:Hepatitis B is highly prevalent in Malawi. There is a paucity of epidemiological data from rural areas where 85% of the population reside, and the Northern region. Priority research needs include large-scale representative community studies of HBV, HDV and HCV seroprevalence, assessment of children following introduction of the HBV vaccine in 2002, prevalence estimates of viral hepatitis among individuals with cirrhosis and HCC and data on HCV prevalence using PCR confirmation, to support a viral hepatitis strategy for Malawi