Trends in mortality inequalities in an urban area: the influence of immigration

Abstract

Background Nearly 20% of the population in Barcelona is foreign-born and this percentage rises to up to 40% in some neighborhoods. Consequently, migration health patterns may play an important role in trends in socioeconomic geographical inequalities in mortality. The objective of this study was to analyze the trend in socioeconomic inequalities in mortality between neighborhoods in Barcelona during the period 2001–2012 in the foreign-born and Spanish-born population. Methods Repeated cross-sectional design of the population aged 25–64 years in Barcelona between 2001 and 2012. Hierarchical data consisted of yearly mortality linked-population. The variables analyzed were age, sex, education, and country of birth (Spanish-born, foreign-born), neighborhood of residence, and the socioeconomic level of the neighborhoods using quartiles of unemployment rates. Age-standardized mortality rates were estimated, and mixed Poisson regressions were applied using generalized linear mixed models, including two random effects to consider the intracorrelation within neighborhoods and across years. Results The number of foreign-born residents aged 25–64 increased notably in disadvantaged neighborhoods. Approximately 9% of premature deaths occurred in foreign-born individuals. Premature mortality rates were higher in disadvantaged neighborhoods and in the Spanish-born population in all periods. Despite the stabilized socioeconomic inequalities in mortality in the Spanish-born population, no inequalities were found between neighborhoods in foreign-born men and women. Conclusions Evidence of the ‘healthy migrant’ effect in mortality and socioeconomic inequalities in mortality was found in Barcelona, which seems to alter the distribution of mortality through time and space, related to the low levels of premature mortality and the selective residence of immigrants in socioeconomically disadvantaged neighborhoods.

Metropolitan age-specific mortality trends at borough and neighbourhood level: The case of Mexico City

“…The borough-level age-specific mortality rate data were modelled using Equations (1)(2)(3)(4). Interestingly, the ANOVA results presented in Table 1 show that the only not significant effect at borough level (p = 0.22), is the triple interaction that includes the time to the third power.…”

“…Identifying trends in Metropolitan Mortality (MM) is one of the most challenging problems nowadays. Systematic approaches to discriminate the relevance of social, economical, demographic, educational, environmental or criminal factors in MM are matters of intense current research [1,2,3]. The MM can be differentiated from rural mortality given the fact that causes and risk factors are substantially different, even when comparing their rates [3].…”

“…Systematic approaches to discriminate the relevance of social, economical, demographic, educational, environmental or criminal factors in MM are matters of intense current research [1,2,3]. The MM can be differentiated from rural mortality given the fact that causes and risk factors are substantially different, even when comparing their rates [3]. To develop a useful model that could explain the evolution in time and space of MM, it is crucial to have a comprehensive dataset with information regarding the aforementioned factors.…”

“…In all cases, capital letters stand for Fisher's LSD groups, where bars that share at least a single letter, are not statistically different after Bonferroni multiple test correction (p > 0.05). Results are presented as ordered mean ± standard error estimation according to model description of Equations(1)(2)(3)(4).Tables Additional FilesAdditional file 1 -Variogram modeling for age-specific mortality rates.…”

Spatial Variability of Heat-Related Mortality in Barcelona from 1992–2015: A Case Crossover Study Design

“…Recently, Barcelona has changed a lot and there has been an especially large immigration of young population since 2000. The migration in Barcelona is an additional factor influencing the mortality trend [41]. We did not incorporate air quality data into this study but encourage future study of the interactive effects of heat and air quality on summertime mortality as well as the potential for differential mortality over space as a result of local-scale air quality variability.…”