Emerging Themes in Epidemiology最新文献

Background: Hantavirus infection is an emerging zoonosis transmitted by wild rodents. In Brazil, high case-fatality rates among humans infected with hantavirus are of serious concern to public health authorities. Appropriate preventive measures partly depend on reliable knowledge about the geographical distribution of this disease.

Methods: Incidence of hantavirus infections in Brazil (1993-2013) was analyzed. Epidemiological, socioeconomic, and demographic indicators were also used to classify cities' vulnerability to disease by means of multi-criteria decision analysis (MCDA).

Results: From 1993 to 2013, 1752 cases of hantavirus were registered in 16 Brazilian states. The highest incidence of hantavirus was observed in the states of Mato Grosso (0.57/100,000) and Santa Catarina (0.13/100,000). Based on MCDA analysis, municipalities in the southern, southeastern, and midwestern regions of Brazil can be classified as highly vulnerable. Most municipalities in northern and northeastern Brazil were classified as having low vulnerability to hantavirus cardiopulmonary syndrome.

Conclusions: Although most human infections by hantavirus registered in Brazil occurred in the southern region of the country, a greater vulnerability to hantavirus was found in the Brazilian Midwest. This result reflects the need to strengthen surveillance where the disease has thus far gone unreported.

In 1965, Sir Austin Bradford Hill published nine "viewpoints" to help determine if observed epidemiologic associations are causal. Since then, the "Bradford Hill Criteria" have become the most frequently cited framework for causal inference in epidemiologic studies. However, when Hill published his causal guidelines-just 12 years after the double-helix model for DNA was first suggested and 25 years before the Human Genome Project began-disease causation was understood on a more elementary level than it is today. Advancements in genetics, molecular biology, toxicology, exposure science, and statistics have increased our analytical capabilities for exploring potential cause-and-effect relationships, and have resulted in a greater understanding of the complexity behind human disease onset and progression. These additional tools for causal inference necessitate a re-evaluation of how each Bradford Hill criterion should be interpreted when considering a variety of data types beyond classic epidemiology studies. Herein, we explore the implications of data integration on the interpretation and application of the criteria. Using examples of recently discovered exposure-response associations in human disease, we discuss novel ways by which researchers can apply and interpret the Bradford Hill criteria when considering data gathered using modern molecular techniques, such as epigenetics, biomarkers, mechanistic toxicology, and genotoxicology.

Background: The importance of studying associations between socio-economic position and health has often been highlighted. Previous studies have linked the prevalence and severity of lung disease with national wealth and with socio-economic position within some countries but there has been no systematic evaluation of the association between lung function and poverty at the individual level on a global scale. The BOLD study has collected data on lung function for individuals in a wide range of countries, however a barrier to relating this to personal socio-economic position is the need for a suitable measure to compare individuals within and between countries. In this paper we test a method for assessing socio-economic position based on the scalability of a set of durable assets (Mokken scaling), and compare its usefulness across countries of varying gross national income per capita.

Results: Ten out of 15 candidate asset questions included in the questionnaire were found to form a Mokken type scale closely associated with GNI per capita (Spearman's rank rs = 0.91, p = 0.002). The same set of assets conformed to a scale in 7 out of the 8 countries, the remaining country being Saudi Arabia where most respondents owned most of the assets. There was good consistency in the rank ordering of ownership of the assets in the different countries (Cronbach's alpha = 0.96). Scores on the Mokken scale were highly correlated with scores developed using principal component analysis (rs = 0.977).

Conclusions: Mokken scaling is a potentially valuable tool for uncovering links between disease and socio-economic position within and between countries. It provides an alternative to currently used methods such as principal component analysis for combining personal asset data to give an indication of individuals' relative wealth. Relative strengths of the Mokken scale method were considered to be ease of interpretation, adaptability for comparison with other datasets, and reliability of imputation for even quite large proportions of missing values.

Background: Specialised sexually transmitted infection (STI) clinics in the Netherlands provide STI care for high-risk groups, including female sex workers (FSW), at the clinic and by outreach visiting commercial sex workplaces with a permit. The objective was to investigate the STI positivity rate and determinants of an STI diagnosis among FSW tested by STI clinics in the Netherlands.

Methods: Sexually transmitted infection clinics report demographic, behavioural and diagnostic information of every consultation to the National Institute for Public Health and the Environment. We analysed all consultations of FSW between 2006 and 2013. Trends in STI positivity rate (chlamydia, gonorrhoea, infectious syphilis, HIV and hepatitis B) were analysed using χ(2) for trend and logistic regression was used to analyse determinants associated with an STI diagnosis. Differences between consultations at the STI clinic and consultations during outreach were analysed using χ(2) tests.

Results: The positivity rate for any STI (overall 9.5 %) was stable from 2006 to 2013. Chlamydia positivity rate (overall 7.1 %) decreased (p < 0.001) and gonorrhoea positivity rate (overall 2.6 %) increased (p < 0.001). For gonorrhoea, the highest positivity rate was found oropharyngeal (2.0 %). Characteristics associated with STI were a younger age [adjusted odds ratio (aOR) 0.96, 95 % confidence interval (CI) 0.95-0.97 per year], a previous STI diagnosis (aOR 1.63, 95 % CI 1.38-1.92) and being notified for an STI by partner notification (aOR 2.61, 95 % CI 2.0-3.40). The STI positivity rate was significantly lower among FSW tested at outreach locations (8.6 %) compared to FSW tested at the STI clinic (11.7 %, p < 0.001).

Conclusions: The STI positivity rate among FSW remained stable, but underlying this was a decreasing chlamydia trend and an increasing gonorrhoea trend, suggesting a shift in STI risks among FSW over time. Condom use during oral sex should be promoted since oropharyngeal gonorrhoea was frequently diagnosed and because of the potential spread of antimicrobial resistant gonococci.

Statistical inference is commonly said to be inapplicable to complete population studies, such as censuses, due to the absence of sampling variability. Nevertheless, in recent years, studies of whole populations, e.g., all cases of a certain cancer in a given country, have become more common, and often report p values and confidence intervals regardless of such concerns. With reference to the social science literature, the current paper explores the circumstances under which statistical inference can be meaningful for such studies. It concludes that its use implicitly requires a target population which is wider than the whole population studied - for example future cases, or a supranational geographic region - and that the validity of such statistical analysis depends on the generalizability of the whole to the target population.

Sedentary behaviour (too much sitting, as distinct from too little exercise) has emerged as a potentially significant public health issue. Analytically, researchers have reported 'independent' associations between sedentary behaviour (SB) and a number of health outcomes by adjusting for physical activity (PA) (and other confounders), and conclude that SB is associated with the outcome even in those who are physically active. However, the logical rationale for why adjustments for PA are required is often not delineated, and as a consequence, PA has been conceptualised as a confounder, an intermediary, and an effect measure modifier-sometimes simultaneously-in studies of SB and health outcomes. This paper discusses the analytical assumptions underlying adjustment for PA in studies of SB and a given outcome, and considers the implications for associations between SB and health.

Background: The case definition for traumatic brain injury (TBI) often includes 'unspecified injury to the head' diagnostic codes. However, research has shown that the inclusion of these codes leads to false positives. As such, it is important to determine the degree to which inclusion of these codes affect the overall numbers and profiles of the TBI population. The objective of this paper was to profile and compare the demographic and clinical characteristics, intention and mechanism of injury, and discharge disposition of hospitalized children and youth aged 19 years and under using (1) an inclusive TBI case definition that included 'unspecified injury to the head' diagnostic codes, (2) a restricted TBI case definition that excluded 'unspecified injury to the head 'diagnostic codes, and (3) the 'unspecified injury to the head' only case definition.

Methods: The National Ambulatory Care Reporting System and the Discharge Abstract Database from Ontario, Canada, were used to identify cases between fiscal years 2003/04 and 2009/10.

Results: The rate of TBI episodes of care using the inclusive case definition for TBI (2,667.2 per 100,000) was 1.65 times higher than that of the restricted case definition (1,613.3 per 100,000). 'Unspecified injury to the head' diagnostic codes made up of 39.5 % of all cases identified with the inclusive case definition. Exclusion of 'unspecified injury to the head' diagnostic code in the TBI case definition resulted in a significantly higher proportion of patients in the intensive care units (p < .0001; 18.5 % vs. 22.2 %) and discharged to a non-home setting (p < .0001; 9.9 % vs. 11.6 %).

Conclusion: Inclusion of 'unspecified injury to the head' diagnostic codes resulted in significant changes in numbers, healthcare use, and causes of TBI. Careful consideration of the inclusion of 'unspecified injury to the head' diagnostic codes in the case definition of TBI for the children and youth population is important, as it has implications for the numbers used for policy, resource allocation, prevention, and planning of healthcare services. This paper can inform future work on reaching consensus on the diagnostic codes for defining TBI in children and youth.

Background: Disadvantages have already been pointed out on the use of odds ratio (OR) as a measure of association for designs such as cohort and cross sectional studies, for which relative risk (RR) or prevalence ratio (PR) are preferable. The model that directly estimates RR or PR and correctly specifies the distribution of the outcome as binomial is the log-binomial model, however, convergence problems occur very often. Robust Poisson regression also estimates these measures but it can produce probabilities greater than 1.

Results: In this paper, the use of Bayesian approach to solve the problem of convergence of the log-binomial model is illustrated. Furthermore, the method is extended to incorporate dependent data, as in cluster clinical trials and studies with multilevel design, and also to analyse polytomous outcomes. Comparisons between methods are made by analysing four data sets.

Conclusions: In all cases analysed, it was observed that Bayesian methods are capable of estimating the measures of interest, always within the correct parametric space of probabilities.

The imposed limitations on what we can know about nature have been long recognized. Yet in the field of epidemiology a futile search for lifestyle-related risk factors for common chronic diseases continues unabated. This has led to the production of a growing body of evidence about potential lifestyle risk factors that tend to be marginal, contradictory, irreproducible, or hard to interpret. While epidemiologists are calling for a more refined methodology, I argue that our limitation in studying complex diseases is insurmountable. This is because the study of lifestyle-related small risks requires accurate measurement of multiple behaviors-exposures over a long period of time. It is also because in complex systems such as population's health, the effect of rich interactions between its parts cannot be predicted based on traditional causal models of epidemiology. Within complex systems, understanding the interactions between system components can be more important than the contribution of each to disease risk.