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

Trends in socioeconomic inequalities in cancer mortality in Barcelona: 1992–2003

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to assess trends in cancer mortality by educational level in Barcelona from 1992 to 2003.</p> <p>Methods</p> <p>The study population comprised Barcelona inhabitants aged 20 years or older. Data on cancer deaths were supplied by the system of information on mortality. Educational level was obtained from the municipal census. Age-standardized rates by educational level were calculated. We also fitted Poisson regression models to estimate the relative index of inequality (RII) and the Slope Index of Inequalities (SII). All were calculated for each sex and period (1992–1994, 1995–1997, 1998–2000, and 2001–2003).</p> <p>Results</p> <p>Cancer mortality was higher in men and women with lower educational level throughout the study period. Less-schooled men had higher mortality by stomach, mouth and pharynx, oesophagus, larynx and lung cancer. In women, there were educational inequalities for cervix uteri, liver and colon cancer. Inequalities of overall and specific types of cancer mortality remained stable in Barcelona; although a slight reduction was observed for some cancers.</p> <p>Conclusion</p> <p>This study has identified those cancer types presenting the greatest inequalities between men and women in recent years and shown that in Barcelona there is a stable trend in inequalities in the burden of cancer.</p

Explaining Ethnic Differences in Late Antenatal Care Entry by Predisposing, Enabling and Need Factors in the Netherlands. The Generation R Study

Despite compulsory health insurance in Europe, ethnic differences in access to health care exist. The objective of this study is to investigate how ethnic differences between Dutch and non-Dutch women with respect to late entry into antenatal care provided by community midwifes can be explained by need, predisposing and enabling factors. Data were obtained from the Generation R Study. The Generation R Study is a multi-ethnic population-based prospective cohort study conducted in the city of Rotterdam. In total, 2,093 pregnant women with a Dutch, Moroccan, Turkish, Cape Verdean, Antillean, Surinamese Creole and Surinamese Hindustani background were included in this study. We examined whether ethnic differences in late antenatal care entry could be explained by need, predisposing and enabling factors. Subsequently, logistic regression analysis was used to assess the independent role of explanatory variables in the timing of antenatal care entry. The main outcome measure was late entry into antenatal care (gestational age at first visit after 14 weeks). With the exception of Surinamese-Hindustani women, the percentage of mothers entering antenatal care late was higher in all non-Dutch compared to Dutch mothers. We could explain differences between Turkish (OR = 0.95, CI: 0.57–1.58), Cape Verdean (OR = 1.65. CI: 0.96–2.82) and Dutch women. Other differences diminished but remained significant (Moroccan: OR = 1,74, CI: 1.07–2.85; Dutch Antillean OR 1.80, CI: 1.04–3.13). We found that non-Dutch mothers were more likely to enter antenatal care later than Dutch mothers. Because we are unable to explain fully the differences regarding Moroccan, Surinamese-Creole and Antillean women, future research should focus on differences between 1st and 2nd generation migrants, as well as on language barriers that may hinder access to adequate information about the Dutch obstetric system

Do socioeconomic inequalities in mortality vary between different Spanish cities? a pooled cross-sectional analysis

Background: The relationship between deprivation and mortality in urban settings is well established. This relationship has been found for several causes of death in Spanish cities in independent analyses (the MEDEA project). However, no joint analysis which pools the strength of this relationship across several cities has ever been undertaken. Such an analysis would determine, if appropriate, a joint relationship by linking the associations found. Methods: A pooled cross-sectional analysis of the data from the MEDEA project has been carried out for each of the causes of death studied. Specifically, a meta-analysis has been carried out to pool the relative risks in eleven Spanish cities. Different deprivation-mortality relationships across the cities are considered in the analysis (fixed and random effects models). The size of the cities is also considered as a possible factor explaining differences between cities. Results: Twenty studies have been carried out for different combinations of sex and causes of death. For nine of them (men: prostate cancer, diabetes, mental illnesses, Alzheimer’s disease, cerebrovascular disease; women: diabetes, mental illnesses, respiratory diseases, cirrhosis) no differences were found between cities in the effect of deprivation on mortality; in four cases (men: respiratory diseases, all causes of mortality; women: breast cancer, Alzheimer’s disease) differences not associated with the size of the city have been determined; in two cases (men: cirrhosis; women: lung cancer) differences strictly linked to the size of the city have been determined, and in five cases (men: lung cancer, ischaemic heart disease; women: ischaemic heart disease, cerebrovascular diseases, all causes of mortality) both kinds of differences have been found. Except for lung cancer in women, every significant relationship between deprivation and mortality goes in the same direction: deprivation increases mortality. Variability in the relative risks across cities was found for general mortality for both sexes. Conclusions: This study provides a general overview of the relationship between deprivation and mortality for a sample of large Spanish cities combined. This joint study allows the exploration of and, if appropriate, the quantification of the variability in that relationship for the set of cities considered.This article was partially funded by Ministerio de Economia y Competitividad via the research grant MTM2010-19528 (jointly financed with European Regional Development Fund), the FIS-FEDER projects: PI042013, PI040041, PI040170, PI040069, PI042602, PI040388, PI040489, PI042098, PI041260, PI040399, PI08/1488, PI08/0330 and by the CIBER Epidemiología y Salud Publica (CIBERESP), Spain

Trends in Inequalities in Induced Abortion According to Educational Level among Urban Women

This study aims to describe trends in inequalities by women’s socioeconomic position and age in induced abortion in Barcelona (Spain) over 1992–1996 and 2000–2004. Induced abortions occurring in residents in Barcelona aged 20 and 44 years in the study period are included. Variables are age, educational level, and time periods. Induced abortion rates per 1,000 women and absolute differences for educational level, age, and time period are calculated. Poisson regression models are fitted to obtain the relative risk (RR) for trends. Induced abortion rates increased from 10.1 to 14.6 per 1,000 women aged 20–44 (RR = 1.44; 95% confidence interval (CI) 1.41–1.47) between 1992–1996 and 2000–2004. The abortion rate was highest among women aged 20–24 and 25–34 and changed little among women aged 35–44. Among women aged 20–24 and 25–34, those with a primary education or less had higher rates of induced abortion in the second period. Induced abortion rates also grew in those women with secondary education. In the 35–44 age group, the induced abortion rate declined among women with a secondary education (RR = 0.66; 95% CI 0.60–0.73) and slightly among those with a greater level of education. Induced abortion is rising most among women in poor socioeconomic positions. This study reveals deep inequalities in induced abortion in Barcelona, Spain. The trends identified in this study suggest that policy efforts to reduce unintended pregnancies are failing in Spain. Our study fills an important gap in literature on recent trends in Southern Europe