Cause-specific mortality time series analysis: a general method to detect and correct for abrupt data production changes

<p>Abstract</p> <p>Background</p> <p>Monitoring the time course of mortality by cause is a key public health issue. However, several mortality data production changes may affect cause-specific time trends, thus altering the interpretation. This paper proposes a statistical method that detects abrupt changes ("jumps") and estimates correction factors that may be used for further analysis.</p> <p>Methods</p> <p>The method was applied to a subset of the AMIEHS (Avoidable Mortality in the European Union, toward better Indicators for the Effectiveness of Health Systems) project mortality database and considered for six European countries and 13 selected causes of deaths. For each country and cause of death, an automated jump detection method called Polydect was applied to the log mortality rate time series. The plausibility of a data production change associated with each detected jump was evaluated through literature search or feedback obtained from the national data producers.</p> <p>For each plausible jump position, the statistical significance of the between-age and between-gender jump amplitude heterogeneity was evaluated by means of a generalized additive regression model, and correction factors were deduced from the results.</p> <p>Results</p> <p>Forty-nine jumps were detected by the Polydect method from 1970 to 2005. Most of the detected jumps were found to be plausible. The age- and gender-specific amplitudes of the jumps were estimated when they were statistically heterogeneous, and they showed greater by-age heterogeneity than by-gender heterogeneity.</p> <p>Conclusion</p> <p>The method presented in this paper was successfully applied to a large set of causes of death and countries. The method appears to be an alternative to bridge coding methods when the latter are not systematically implemented because they are time- and resource-consuming.</p

Using vital statistics to estimate the population-level impact of osteoporotic fractures on mortality based on death certificates, with an application to France (2000-2004)

Abstract Background We developed a methodology using vital statistics to estimate the impact of osteoporotic fractures on the mortality of an entire population, and applied it to France for the period 2000-2004. Methods Current definitions of osteoporotic fractures were reviewed and their components identified. We used the International Classification of Diseases with national vital statistics data for the French adult population and performed cross-classifications between various components: age, sex, I-code (site) and E-code (mechanism of fracture). This methodology allowed identification of appropriate thresholds and categorization for each pertinent component. Results 2,625,743 death certificates were analyzed, 2.2% of which carried a mention of fracture. Hip fractures represented 55% of all deaths from fracture. Both sexes showed a similar pattern of mortality rates for all fracture sites, the rate increased with age from the age of 70 years. The E-high-energy code (present in 12% of death certificates with fractures) was found to be useful to rule-out non-osteoporotic fractures, and to correct the overestimation of mortality rates. Using this methodology, the crude number of deaths associated with fractures was estimated to be 57,753 and the number associated with osteoporotic fractures 46,849 (1.85% and 1.78% of all deaths, respectively). Conclusion Osteoporotic fractures have a significant impact on overall population mortality.</p

Mortality and LC50Values for Several Stages of the Marine CopepodTigriopus brevicornis(Müller) Exposed to the Metals Arsenic and Cadmium and the Pesticides Atrazine, Carbofuran, Dichlorvos, and Malathion

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