Identifying the determinants of premature mortality in Russia: overcoming a methodological challenge

It is thought that excessive alcohol consumption is related to the high mortality among working age men in Russia. Specifically, it has been suggested that alcohol is a key proximate driver of the very sharp fluctuations in mortality seen in this group since the mid-1980s including a seven year period when, on average, male life expectancy at birth fell by more than one year for each calendar year [1‐4]. Most of the evidence comes from the analysis of routine data and from cross-sectional surveys of alcohol consumption, while in contrast there have been relatively few studies linking the drinking behaviour of individuals to mortality in Russia. Extrapolating the alcohol-mortality relationships found in research undertaken in Western countries to Russia is likely to be inappropriate because, along with many other parts of the former Soviet Union, it has a particular pattern of drinking characterised by binge-drinking of large volumes of spirits on one occasion, a pattern that is believed to be particularly dangerous [5].

Designing an individual-level study to investigate these issues raises many methodological challenges. The initial hypothesis is that the sharp fluctuations in working-age mortality that have characterised Russian demographic trends since the mid-1980s may be due to acute or very short-term effects of alcohol consumption. An individual's pattern of drinking may also change considerably over a short period of time. Thus, what is required is a design for collecting valid information about individual characteristics and drinking behaviours that can then be related to the risk of death in the following 12 or 18 months.

The two classic analytic study designs are cohort and case-control studies. However, in their conventional forms, neither design is ideal to address this problem. Cohort studies typically measure exposure at a base-line examination or interview and then follow up the study subjects. If mortality is the endpoint, follow-up is usually for years. This design is particularly suited to studying mortality effects of relatively stable patterns of exposure, such as smoking, or acute or episodic exposures which elevate mortality over an appreciable period of time such as exposure to radiation and subsequent risk of solid tumours. In the case of short-term mortality effects of acute and intrinsically unstable patterns of behaviour including binge drinking, a conventional cohort design is not optimal. As follow-up time accumulates, classification of people according to baseline reports of frequency and intensity of binge drinking becomes increasingly uninformative about exposures that may be occurring shortly before death. One possible solution to this would be to have a cohort study of such size that sufficient numbers of events would accrue within a short period of follow-up. In most instances the huge size of the required cohort would make this unfeasible. Another alternative would be to undertake regular resurveys of the cohort to update exposure information about drinking patterns, although this would be logistically difficult, expensive and likely to result in selective loss to follow-up of heavy drinkers as discussed below.

Some cohort studies suffer from another problem in terms of their suitability for studying the mortality effects of heavy drinking, or other outcomes associated with behavioural problems and social dysfunction. This is the selective exclusion of those at the ends of the spectrum, such as heavy or problem drinkers [6]. In a study which relied on regular resurveys, those individuals who became heavier/more problematic drinkers since being captured at baseline would be less likely to take part in resurveys than others. Additionally, studies for which recruitment requires subjects to travel from their home address, to an appointment in a clinic for examination for example, are also likely to exclude problem drinkers differentially. This is a well recognised phenomenon in cross-sectional studies, but may be particularly serious when cohort recruitment requires considerable commitment from the potential participants. In the Russian context, two of the larger and well known cohorts (the Lipid Research Clinics and the Novosibirsk cohorts) [7, 8] both required subjects to attend for a medical examination as part of the recruitment protocol. These studies are likely to have differentially excluded people who have serious alcohol problems at the time of recruitment.

In contrast, a case-control study in this context would focus upon obtaining information on the behaviours and characteristics of subjects in the most recent 12 month period, which for the cases (deaths) would be the year before death. From this perspective, the case-control design is more suitable than a cohort design. Certainly, retrospectively collected information about the immediate past might be regarded as more reliable and accurate than information about behaviours and characteristics much further back in time, as is often attempted in case-control studies.

If a case-control design is chosen it will require a departure from the usual approaches as, obviously, it must use proxy informants. Examples of such studies exist in the literature, particularly in investigations of risk factors for suicide [9, 10] and violent death [11, 12]. Other risk factors including drug use, smoking [13‐15]and dietary factors [16] have also been explored using case-control designs with proxy informants. There is less literature on differential response bias between cases and controls based on proxy interviews compared to when the index cases and controls are themselves interviewed [17‐19], and it is almost impossible to evaluate the extent of such bias when cases have died.

A case-control study in which the cases are dead does, however, have an advantage compared to the majority of studies where cases are of diagnosed disease. In a population with a well-functioning vital registration system, 100% case-ascertainment is feasible. Moreover even if detailed proxy-based information is not available for all, there will usually be sufficient routine data collected at death registration to assess the representativeness of the cases with full information. If the target group of cases comprises all deaths occurring in a defined population, identifying the appropriate control sampling frame is straightforward: it is the whole population of the area in which the deaths are from.

Our interest in alcohol as the main exposure presents problems for case-control studies as it does for cohorts, particularly if, as is the case here, we wish to look at the role of heavy drinking. As already mentioned above cross-sectional surveys are likely to fail to interview people who drink heavily differentially. In terms of actual methods, a case-control study is very similar to a cross-sectional study in that one approaches people to be interviewed without a history of prior contact and engagement in the research. However, the obligatory use of proxies may actually help in one respect – in that the drinking behaviours of the cases and controls may be less strongly linked to the process of recruitment of proxies than they are to recruitment of the index subjects themselves.

In the rest of this paper we describe the design and implementation of an innovative study in Russia that illustrates how these challenges and issues can be addressed. Although some aspects of the design reflect the specific situation in Russia, we believe that it offers a set of principles that can usefully be adopted by epidemiologists studying sudden and unexpected deaths in other settings.

The Izhevsk Family Study was established to investigate whether patterns of alcohol consumption were linked to short-term risk of death among Russian men of working age in a typical, medium-sized Russian industrial town, Izhevsk. As already highlighted, the key challenge was to design a study which was able to capture information about exposures hypothesised to lead to mortality in the period immediately prior to death and to obtain a representative set of living controls with which to compare them.

Izhevsk has a population of 650 000 people and is located on the western side of the Ural mountains. It is the capital of the Udmurt Republic, one of the 89 territories that make up the Russian Federation. The leading causes of death among these men were cardiovascular disease, a high proportion of which were sudden, and external causes. While the focus was on alcohol, clearly it was important to be able to collect information on other factors that might act at different points on the causal pathway, such as unemployment, or act as confounders, such as smoking.

The Izhevsk Family study is not the first study to address the issue of premature mortality among Russian men of working age. The study benefited from an earlier study of 1998–99, also based in the Udmurt Republic, that attempted to address the same issue [4, 20]. The previous study used broadly the same design, and found an association between excessive alcohol consumption and premature mortality (below age 55 years) in Russian men. However, this previous study had several weaknesses which threw these findings into question. For example, despite including several questions about alcohol use, the information was limited and inadequate; it included too many subjective/evaluative questions, to which proxies could not reliably respond; no checks were made regarding whether the cases belonged to the sampling frame for the controls which could have causes selection bias; no data was collected from external, objective sources, nor were the controls themselves interviewed, so there was no opportunity to validate proxy-obtained data. In comparison, the Izhevsk Family study was strengthened in a number of important respects. Firstly, the questionnaire was improved, excluded subjective/evaluative questions and incorporated more questions on clearly observable behaviours, so as to obtain more valid responses from proxy respondents. Secondly, the questionnaire included an extended range of questions on alcohol consumption and alcohol-related behaviour, including questions about surrogates (manufactured alcohol-containing substances not intended for drinking), the consumption of which subsequently emerged as particularly important. Thirdly, the Izhevsk Family study carried out interviews with both controls and their proxies, and in addition previously collected administrative and clinical data on the subjects was obtained, providing opportunity for validation of responses obtained from proxy respondents. Finally, it was possible to identify which cases belonged to the sampling frame from which controls were drawn, and hence sensitivity analyses could be conducted.

To address the methodological challenge outlined in this paper, we adopted a population-based case-control design. We started with all deaths in men aged 25–54 (and a representative sample of live controls) from an entire defined population. We were therefore able to assess whether or not the cases and controls for whom we could not obtain an interview were representative of the target population. A great strength of this study was therefore that it was not subject to the same selection biases typically encountered by this type of research.

Although based on a conventional case control study, this study has three unusual features. First, although information could not be obtained from cases, it could be obtained from proxy informants providing certain precautions were taken. It was important to select proxies who had sufficient knowledge of the index to be able to report on their characteristics and behaviours, and to pose questions that addressed characteristics and behaviours that were observable. Second, given the need to ensure representativeness of controls and tackle recall bias, external sources of objective data relevant to the exposures being studied but blind to case/control status were used. Third, to overcome potential problems in defining outcomes, a detailed system of data collection to validate and extend information on causes of death was employed. Although adapted to the specific circumstances of Russia, we believe that the principles that we have set out here will be helpful to others seeking a better understanding of the causes of conditions associated with sudden and unexpected death in a range of situations, including deaths at young and middle ages, or deaths from certain causes such as violence or accidents, or tuberculosis. Moreover, the study illustrates that with sufficient attention given to issues of data quality and bias at the design stage, ancillary information can be collected which can be used to assess and demonstrate the validity of data collected using methods that might otherwise be regarded as questionable.