Sample registration of vital events with verbal autopsy: a renewed commitment to measuring and monitoring vital statistics

Registration of births, recording deaths by age, sex and cause, and calculating mortality levels and differentials are fundamental to evidence-based health policy, monitoring and evaluation. Yet few of the countries with the greatest need for these data have functioning systems to produce them despite legislation providing for the establishment and maintenance of vital registration. Sample vital registration (SVR), when applied in conjunction with validated verbal autopsy, procedures and implemented in a nationally representative sample of population clusters represents an affordable, cost-effective, and sustainable short- and medium-term solution to this problem. SVR complements other information sources by producing age-, sex-, and cause-specific mortality data that are more complete and continuous than those currently available. The tools and methods employed in an SVR system, however, are imperfect and require rigorous validation and continuous quality assurance; sampling strategies for SVR are also still evolving. Nonetheless, interest in establishing SVR is rapidly growing in Africa and Asia. Better systems for reporting and recording data on vital events will be sustainable only if developed hand-in-hand with existing health information strategies at the national and district levels; governance structures; and agendas for social research and development monitoring. If the global community wishes to have mortality measurements 5 or 10 years hence, the foundation stones of SVR must be laid today.

Statistical modeling and projections of lung cancer mortality in 4 industrialized countries

The purpose of this work was to model lung cancer mortality as a function of past exposure to tobacco and to forecast age-sex-specific lung cancer mortality rates. A 3-factor age-period-cohort (APC) model, in which the period variable is replaced by the product of average tar content and adult tobacco consumption per capita, was estimated for the US, UK, Canada and Australia by the maximum likelihood method. Age- and sex-specific tobacco consumption was estimated from historical data on smoking prevalence and total tobacco consumption. Lung cancer mortality was derived from vital registration records. Future tobacco consumption, tar content and the cohort parameter were projected by autoregressive moving average (ARIMA) estimation. The optimal exposure variable was found to be the product of average tar content and adult cigarette consumption per capita, lagged for 2530 years for both males and females in all 4 countries. The coefficient of the product of average tar content and tobacco consumption per capita differs by age and sex. In all models, there was a statistically significant difference in the coefficient of the period variable by sex. In all countries, male age-standardized lung cancer mortality rates peaked in the 1980s and declined thereafter. Female mortality rates are projected to peak in the first decade of this century. The multiplicative models of age, tobacco exposure and cohort fit the observed data between 1950 and 1999 reasonably well, and time-series models yield plausible past trends of relevant variables. Despite a significant reduction in tobacco consumption and average tar content of cigarettes sold over the past few decades, the effect on lung cancer mortality is affected by the time lag between exposure and established disease. As a result, the burden of lung cancer among females is only just reaching, or soon will reach, its peak but has been declining for I to 2 decades in men. Future sex differences in lung cancer mortality are likely to be greater in North America than Australia and the UK due to differences in exposure patterns between the sexes. (c) 2005 Wiley-Liss, Inc.

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.

Validity of verbal autopsy procedures for determining cause of death in Tanzania

Objectives: To validate verbal autopsy (VA) procedures for use in sample vital registration. Verbal autopsy is an important method for deriving cause-specific mortality estimates where disease burdens are greatest and routine cause-specific mortality data do not exist. Methods: Verbal autopsies and medical records (MR) were collected for 3123 deaths in the perinatal/neonatal period, post-neonatal < 5 age group, and for ages of 5 years and over in Tanzania. Causes of death were assigned by physician panels using the International Classification of Disease, revision 10. Validity was measured by: cause-specific mortality fractions (CSMF); sensitivity; specificity and positive predictive value. Medical record diagnoses were scored for degree of uncertainty, and sensitivity and specificity adjusted. Criteria for evaluating VA performance in generating true proportional mortality were applied. Results: Verbal autopsy produced accurate CSMFs for nine causes in different age groups: birth asphyxia; intrauterine complications; pneumonia; HIV/AIDS; malaria (adults); tuberculosis; cerebrovascular diseases; injuries and direct maternal causes. Results for 20 other causes approached the threshold for good performance. Conclusions: Verbal autopsy reliably estimated CSMFs for diseases of public health importance in all age groups. Further validation is needed to assess reasons for lack of positive results for some conditions.

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.

Benchmarking of performance of Mexican states with effective coverage

Benchmarking of the performance of states, provinces, or districts in a decentralised health system is important for fostering of accountability, monitoring of progress, identification of determinants of success and failure, and creation of a culture of evidence. The Mexican Ministry of Health has, since 2001, used a benchmarking approach based on the World Health Organization (WHO) concept of effective coverage of an intervention, which is defined as the proportion of potential health gain that could be delivered by the health system to that which is actually delivered. Using data collection systems, including state representative examination surveys, vital registration, and hospital discharge registries, we have monitored the delivery of 14 interventions for 2005-06. Overall effective coverage ranges from 54.0% in Chiapas, a poor state, to 65.1% in the Federal District. Effective coverage for maternal and child health interventions is substantially higher than that for interventions that target other health problems. Effective coverage for the lowest wealth quintile is 52% compared with 61% for the highest quintile. Effective coverage is closely related to public-health spending per head across states; this relation is stronger for interventions that are not related to maternal and child health than those for maternal and child health. Considerable variation also exists in effective coverage at similar amounts of spending. We discuss the implications of these issues for the further development of the Mexican health-information system. Benchmarking of performance by measuring effective coverage encourages decision-makers to focus on quality service provision, not only service availability. The effective coverage calculation is an important device for health-system stewardship. In adopting this approach, other countries should select interventions to be measured on the basis of the criteria of affordability, effect on population health, effect on health inequalities, and capacity to measure the effects of the intervention. The national institutions undertaking this benchmarking must have the mandate, skills, resources, and independence to succeed.

Age-at-first-registration and heterogeneity in affective psychoses

Background: Previous research into age of onset in affective disorders has produced conflicting results. This paper examines the influence of heterogeneity on the age-at-first-registration distribution for the ICD-9 diagnostic group 'affective psychosis'. Method: For 1979-1991, data for age-at-first-registration for 4985 individuals diagnosed with affective psychosis (ICD-9 296.x) were extracted from a name-linked mental health register. These data were divided into (i) '296.1 only', a category used to code unipolar depression (males = 700; females = 1321); and (ii) '296 other', all 296 cases other than 296.1 (males = 1280; females = 1684). Inception rates for each 5-year age division were adjusted for the background population age-structure as a rate per 100 000 population. Results: The age-at-first-registration distribution for affective psychosis has a wide age range, with women outnumbering men. There is a near-linear increase in inception rates for both men and women with 296.1 only, while the bulk of those with affective psychoses (296 other) have an inverted U-shaped age distribution. Males have an earlier modal age-at-first-registration for 296 other compared to females. Conclusion: The heterogeneity in terms of subtypes and sex in affective psychosis clouds the interpretation of age-at-first-registration. Separating those with unipolar psychotic depression from other subclassifications and differentiating by sex may provide clues to factors that precipitate the onset of affective psychosis.

Dynamic breast MRI: Image registration and its impact on enhancement curve estimation

A novel algorithm for performing registration of dynamic contrast-enhanced (DCE) MRI data of the breast is presented. It is based on an algorithm known as iterated dynamic programming originally devised to solve the stereo matching problem. Using artificially distorted DCE-MRI breast images it is shown that the proposed algorithm is able to correct for movement and distortions over a larger range than is likely to occur during routine clinical examination. In addition, using a clinical DCE-MRI data set with an expertly labeled suspicious region, it is shown that the proposed algorithm significantly reduces the variability of the enhancement curves at the pixel level yielding more pronounced uptake and washout phases.