Correcting for numerator/denominator bias when assessing changing inequalites in occupational class mortality, Australia 1981-2002

Objective Comparisons of the changing patterns of inequalities in occupational mortality provide one way to monitor the achievement of equity goals. However, previous comparisons have not corrected for numerator/denominator bias, which is a consequence of the different ways in which occupational details are recorded on death certificates and on census forms. The objective of this study was to measure the impact of this bias on mortality rates and ratios over time. Methods Using data provided by the Australian Bureau of Statistics, we examined the evidence for bias over the period 1981-2002, and used imputation methods to adjust for this bias. We compared unadjusted with imputed rates of mortality for manual/non-manual workers. Findings Unadjusted data indicate increasing inequality in the age-adjusted rates of mortality for manual/non-manual workers during 1981-2002, Imputed data suggest that there have been modest fluctuations in the ratios of mortality for manual/non-manual workers during this time, but with evidence that inequalities have increased only in recent years and are now at historic highs. Conclusion We found that imputation for missing data leads to changes in estimates of inequalities related to social class in mortality for some years but not for others. Occupational class comparisons should be imputed or otherwise adjusted for missing data on census or death certificates.

Regional, disease specific patterns of smoking-attributable mortality in 2000

Background: Smoking has been causally associated with increased mortality from several diseases, and has increased considerably in many developing countries in the past few decades. Mortality attributable to smoking in the year 2000 was estimated for adult males and females, including estimates by age and for specific diseases in 14 epidemiological subregions of the world. Methods: Lung cancer mortality was used as an indirect marker of the accumulated hazard of smoking. Never-smoker lung cancer mortality was estimated based on the household use of coal with poor ventilation. Estimates of mortality caused by smoking were made for lung cancer, upper aerodigestive cancer, all other cancers, chronic obstructive pulmonary disease ( COPD), other respiratory diseases, cardiovascular diseases, and selected other medical causes. Estimates were limited to ages 30 years and above. Results: In 2000, an estimated 4.83 million premature deaths in the world were attributable to smoking, 2.41 million in developing countries and 2.43 million in industrialised countries. There were 3.84 million male deaths and 1.00 million female deaths attributable to smoking. 2.69 million smoking attributable deaths were between the ages of 30 - 69 years, and 2.14 million were 70 years of age and above. The leading causes of death from smoking in industrialised regions were cardiovascular diseases ( 1.02 million deaths), lung cancer (0.52 million deaths), and COPD (0.31 million deaths), and in the developing world cardiovascular diseases (0.67 million deaths), COPD (0.65 million deaths), and lung cancer (0.33 million deaths). The share of male and female deaths and younger and older adult deaths, and of various diseases in total smoking attributable deaths exhibited large inter-regional heterogeneity, especially in the developing world. Conclusions: Smoking was an important cause of global mortality in 2000, affecting a large number of diseases. Age, sex, and disease patterns of smoking-caused mortality varied greatly across regions, due to both historical and current smoking patterns, and the presence of other risk factors that affect background mortality from specific diseases.

Occupational and non-occupational risk factors in bladder cancer patients in an industrialized area located in former east-Germany

Purpose: Several occupational carcinogens are metabolized by polymorphic enzymes. The distribution of the polymorphic enzymes N-acetyltransferase 2 (NAT2; substrates: aromatic amines), glutathione S-transferase M1 (GSTM1; substrates: e.g., reactive metabolites of polycyclic aromatic hydrocarbons), and glutathione S-transferase T1 (GSTT1; substrates: small molecules with 1 - 2 carbon atoms) were investigated. Material and Methods: At the urological department in Lutherstadt Wittenberg, 136 patients with a histologically proven transitional cell cancer of the urinary bladder were investigated for all occupations performed for more than 6 months. Several occupational and non-occupational risk factors were asked. The genotypes of NAT2, GSTM1, and GSTT1 were determined from leucocyte DNA by PCR. Results: Compared to the general population in Middle Europe, the percentage of GSTT1 negative persons (22.1%) was ordinary; the percentage of slow acetylators (59.6%) was in the upper normal range, while the percentage of GSTM1 negative persons (58.8%) was elevated in the entire group. Shifts in the distribution of the genotypes were observed in subgroups who had been exposed to asbestos (6/6 GSTM1 negative, 5/6 slow acetylators), rubber manufacturing (8/10 GSTM1 negative), and chlorinated solvents (9/15 GSTM1 negative). Conclusions: The overrepresentation of GSTM1 negative bladder cancer patients also in this industrialized area and more pronounced in several occupationally exposed subgroups points to an impact of the GSTM1 negative genotype in bladder carcinogenesis.

Design options for sample-based mortality surveillance

Background Reliable information on causes of death is a fundamental component of health development strategies, yet globally only about one-third of countries have access to such information. For countries currently without adequate mortality reporting systems there are useful models other than resource-intensive population-wide medical certification. Sample-based mortality surveillance is one such approach. This paper provides methods for addressing appropriate sample size considerations in relation to mortality surveillance, with particular reference to situations in which prior information on mortality is lacking. Methods The feasibility of model-based approaches for predicting the expected mortality structure and cause composition is demonstrated for populations in which only limited empirical data is available. An algorithm approach is then provided to derive the minimum person-years of observation needed to generate robust estimates for the rarest cause of interest in three hypothetical populations, each representing different levels of health development. Results Modelled life expectancies at birth and cause of death structures were within expected ranges based on published estimates for countries at comparable levels of health development. Total person-years of observation required in each population could be more than halved by limiting the set of age, sex, and cause groups regarded as 'of interest'. Discussion The methods proposed are consistent with the philosophy of establishing priorities across broad clusters of causes for which the public health response implications are similar. The examples provided illustrate the options available when considering the design of mortality surveillance for population health monitoring purposes.

Lifestyle still predicts mortality in older men with established vascular disease

Background. It is uncertain whether accepted associations between health behaviors and mortality are pertinent to elderly people. No previous studies have examined the patterns of lifestyle in elderly men with and without clinically evident vascular disease by using a lifestyle score to predict survival. Methods. We measured prevalence of a healthy lifestyle (four or more healthy behaviors out of eight) and examined survival in 11,745 men aged 65-83 years participating in a randomized population-based trial of screening for abdominal aortic aneurysm in Perth, Western Australia. After stratifying participants into five groups according to history and symptoms of vascular disease, we compared survival of men in each subgroup with that of 'healthy' men with no history or symptoms of vascular disease. Results. Invitations to screening produced a corrected response of 70.5%. After adjusting for age and place of birth, having an unhealthy lifestyle was associated with an increase of 20% in the likelihood of death from any cause within 5 years (95% CI: 10-30%). This pattern was consistently evident across subgroups defined by history of vascular disease, but was less evident for deaths from vascular disease. Conclusions. Our results highlight the importance of maintaining a healthy lifestyle through to old age, regardless of history of vascular disease. (c) 2005 Elsevier Inc. All rights reserved.

The short-term effects of air pollution on daily mortality in four Australian cities

Objective: To examine the short-term health effects of air pollution on daily mortality in four Australian cities (Brisbane, Melbourne, Perth and Sydney), where more than 50% of Australians reside. Methods: The study used a similar protocol to APHEA2 (Air Pollution and Health: A European Approach) study and derived single-city and pooled estimates. Results: The results derived from the different approaches for the 1996-99 period showed consistent results for different statistical models used. There were significant effects on total mortality, (RR=1.0284 per 1 unit increase in nelphelometry [10(-4).m(-1)], RR=1.0011 per 1ppb increase in NO2), and on respiratory mortality (RR=1.0022 per 1ppb increase in O-2). No significant differences between cities were found, but the NO2 and particle effects may refer to the same impacts. Meta-analyses carried out for three cities yielded estimates for the increase in the daily total number of deaths of 0.2% (-0.8% to 1.2%) for a 10 mu g/m(3) increase in PM, concentration, and 0.9% (-0.7% to 2.5%) for a 10 mu g/m(3) increase in PM2.5 concentration. Conclusions: Air pollutants in Australian cities have significant effects on mortality.

Effect of conditional release from hospitalization on mortality risk

Objectives: This study considered the protective value provided by conditional release. It assessed the contribution of conditional release to mortality risk among patients with mental disorders severe enough to require psychiatric hospitalization during a mental health treatment span of 13.5 years in Victoria, Australia. Methods: Death records were obtained from the Australian National Death Index for a sample of 24,973 Victorian Psychiatric Case Register patients with a history of psychiatric hospitalizations: 8,879 had experienced at least one conditional release during community care intervals and 16,094 had not. Risk of death was assessed with standardized mortality ratios of the general population of Victoria. Relative risk of death among patients with and without past experience of conditional release was computed with risk and odds ratios. The contribution of conditional release to mortality, taking into account use of community care services, age, gender, inpatient experience, and diagnosis, as well as other controls, was assessed with logistic regression. Results: Patients who had been hospitalized showed higher mortality risk than the general population. Sixteen percent ( 4,034) died. Patients exposed to conditional release, however, had a 14 percent reduction in probability of noninjury-related death and a 24 percent reduction per day on orders in the probability of death from injury compared with those not offered such oversight throughout their mental health treatment, all other factors taken into account. Conclusions: Conditional release can offer protective oversight for those considered dangerous to self or others and appears to reduce mortality risk among those with disorders severe enough to require psychiatric hospitalization.

Is mortality from heart failure increasing in Australia? An analysis of official data on mortality for 1997-2003

Objective To assess whether trends in mortality from heart failure(HF) in Australia are due to a change in awareness of the condition or real changes in its epidemiology. Methods We carried out a retrospective analysis of official data on national mortality data between 1997 and 2003. A death was attributed to HF if the death certificate mentioned HF as either the underlying cause of death (UCD) or among the contributory factors. Findings From a total of 907 242 deaths, heart failure was coded as the UCD for 29 341 (3.2%) and was mentioned anywhere on the death certificate in 135 268 (14.9%). Between 1997 and 2003, there were decreases in the absolute numbers of deaths and in the age-specific and age-standardized mortality rates for HF either as UCD or mentioned anywhere for both sexes. HF was mentioned for 24.6% and 17.8% of deaths attributed to ischaemic heart disease and circulatory disease, respectively, and these proportions remained unchanged over the period of study. In addition, HF as UCD accounted for 8.3% of deaths attributed to circulatory disease and this did not change materially from 1997 to 2003. Conclusion The decline in mortality from HF measured as either number of deaths or rate probably reflects a real change in the epidemiology of HF. Population-based studies are required to determine accurately the contributions of changes in incidence, survival and demographic factors to the evolving epidemiology of HF.

Estimating cause-specfic mortality from community- and facility-based data sources in the United Republic of Tanzania: options and implications for mortality burden estimates

Objective To compare mortality burden estimates based on direct measurement of levels and causes in communities with indirect estimates based on combining health facility cause-specific mortality structures with community measurement of mortality levels. Methods. Data from sentinel vital registration (SVR) with verbal autopsy (VA) were used to determine the cause-specific mortality burden at the community level in two areas of the United Republic of Tanzania. Proportional cause-specific mortality structures from health facilities were applied to counts of deaths obtained by SVR to produce modelled estimates. The burden was expressed in years of life lost. Findings. A total of 2884 deaths were recorded from health facilities and 2167 recorded from SVR/VAs. In the perinatal and neonatal age group cause-specific mortality rates were dominated by perinatal conditions and stillbirths in both the community and the facility data. The modelled estimates for chronic causes were very similar to those from SVR/VA. Acute febrile illnesses were coded more specifically in the facility data than in the VA. Injuries were more prevalent in the SVR/VA data than in that from the facilities. Conclusion. In this setting, improved International classification of diseases and health related problems, tenth revision (ICD-10) coding practices and applying facility-based cause structures to counts of deaths from communities, derived from SVR, appears to produce reasonable estimates of the cause-specific mortality burden in those aged 5 years and older determined directly from VA. For the perinatal and neonatal age group, VA appears to be required. Use of this approach in a nationally representative sample of facilities may produce reliable national estimates of the cause-specific mortality burden for leading causes of death in adults.

Maternal health during pregnancy and perinatal mortality in Bangladesh: evidence form a large-scale community-based clinical trial

Perinatal mortality is very high in Bangladesh. In this setting, few community-level studies have assessed the influence of underlying maternal health factors on perinatal outcomes. We used the data from a community-based clinical controlled trial conducted between 1994 and 1997 in the catchment areas of a large MCH/FP hospital located in Mirpur, a suburban area of Dhaka in Bangladesh, to investigate the levels of perinatal mortality and its associated maternal health factors during pregnancy. A total of 2007 women were followed after recruitment up to delivery, maternal death, or until they dropped out of the study. Of these, 1584 who gave birth formed our study subjects. The stillbirth rate was 39.1 per 1000 births [95% confidence interval (CI) 39.0, 39.3] and the perinatal mortality rate (up to 3 days) was 54.3 per 1000 births [95% CI 54.0, 54.6] among the study population. In the fully adjusted logistic regression model, the risk of perinatal mortality was as high as 2.7 times [95% CI 1.5, 4.9] more likely for women with hypertensive disorders, 5.0 times [95% CI 2.3, 10.8] as high for women who had antepartum haemorrhage and 2.6 times [95% CI 1.2, 5.8] as high for women who had higher haemoglobin levels in pregnancy when compared with their counterparts. The inclusion of potential confounding variables such as poor obstetric history, sociodemographic characteristics and preterm delivery influenced only marginally the net effect of important maternal health factors associated with perinatal mortality. Perinatal mortality in the study setting was significantly associated with poor maternal health conditions during pregnancy. The results of this study point towards the urgent need for monitoring complications in high-risk pregnancies, calling for the specific components of the safe motherhood programme interventions that are designed to manage these complications of pregnancy.