Mortality and socioeconomic deprivation in census tracts of an urban setting in southern Europe

Deep Learning to Unveil Correlations between Urban Landscape and Population Health

The global healthcare landscape is continuously changing throughout the world as technology advances, leading to a gradual change in lifestyle. Several diseases such as asthma and cardiovascular conditions are becoming more diffuse, due to a rise in pollution exposure and a more sedentary lifestyle. Healthcare providers deal with increasing new challenges, and thanks to fast-developing big data technologies, they can be faced with systems that provide direct support to citizens. In this context, within the EU-funded Participatory Urban Living for Sustainable Environments (PULSE) project, we are implementing a data analytic platform designed to provide public health decision makers with advanced approaches, to jointly analyze maps and geospatial information with healthcare and air pollution data. In this paper we describe a component of such platforms, which couples deep learning analysis of urban geospatial images with healthcare indexes collected by the 500 Cities project. By applying a pre-learned deep Neural Network architecture, satellite images of New York City are analyzed and latent feature variables are extracted. These features are used to derive clusters, which are correlated with healthcare indicators by means of a multivariate classification model. Thanks to this pipeline, it is possible to show that, in New York City, health care indexes are significantly correlated to the urban landscape. This pipeline can serve as a basis to ease urban planning, since the same interventions can be organized on similar areas, even if geographically distant.

[Effect of socioeconomic status on mortality in urban areas: a systematic critical review]

Socioeconomic inequalities cause more disease and death than most risk factors, especially in cities. This systematic review of the scientific evidence included articles in English, Spanish, Portuguese, and Italian and excluded studies with low levels of evidence and those that did not analyze associations between mortality and socioeconomic status in urban settings. Articles were selected by two independent reviewers, and data extraction used evidence tables. A total of 1,509 records were obtained, and 24 were included. All the studies showed higher mortality rates in poorer areas. Six studies showed an association with cardiovascular diseases, four with lung diseases, and three with AIDS, infectious and parasitic diseases, and cirrhosis. The selected studies showed low consistency in the results and important methodological limitations that prevented comparisons between studies or the extraction of relevant conclusions.

Linking of primary care records to census data to study the association between socioeconomic status and cancer incidence in Southern Europe: a nation-wide ecological study

BACKGROUND

Area-based measures of economic deprivation are seldom applied to large medical records databases to establish population-scale associations between deprivation and disease.

OBJECTIVE

To study the association between deprivation and incidence of common cancer types in a Southern European region.

METHODS

Retrospective ecological study using the SIDIAP (Information System for the Development of Research in Primary Care) database of longitudinal electronic medical records for a representative population of Catalonia (Spain) and the MEDEA index based on urban socioeconomic indicators in the Spanish census. Study outcomes were incident cervical, breast, colorectal, prostate, and lung cancer in 2009-2012. The completeness of SIDIAP cancer recording was evaluated through linkage of a geographic data subset to a hospital cancer registry. Associations between MEDEA quintiles and cancer incidence was evaluated using zero-inflated Poisson regression adjusted for sex, age, smoking, alcoholism, obesity, hypertension, and diabetes.

RESULTS

SIDIAP sensitivity was 63% to 92% for the five cancers studied. There was direct association between deprivation and lung, colorectal, and cervical cancer: incidence rate ratios (IRR) 1.82 [1.64-2.01], IRR 1.60 [1.34-1.90], IRR 1.22 [1.07-1.38], respectively, comparing the most deprived to most affluent areas. In wealthy areas, prostate and breast cancers were more common: IRR 0.92 [0.80-1.00], IRR 0.91 [0.78-1.06]. Adjustment for confounders attenuated the association with lung cancer risk (fully adjusted IRR 1.16 [1.08-1.25]), reversed the direction of the association with colorectal cancer (IRR 0.90 [0.84-0.95]), and did not modify the associations with cervical (IRR 1.27 [1.11-1.45]), prostate (0.74 [0.69-0.80]), and breast (0.76 [0.71-0.81]) cancer.

CONCLUSIONS

Deprivation is associated differently with the occurrence of various cancer types. These results provide evidence that MEDEA is a useful, area-based deprivation index for analyses of the SIDIAP database. This information will be useful to improve screening programs, cancer prevention and management strategies, to reach patients more effectively, particularly in deprived urban areas.

Deprivation and mortality at the town level in Busan, Korea: an ecological study

Objectives

Busan is reported to have the highest mortality rate among 16 provinces in Korea, as well as considerable health inequality across its districts. This study sought to examine overall and cause-specific mortality and deprivation at the town level in Busan, thereby identifying towns and causes of deaths to be targeted for improving overall health and alleviating health inequality.

Methods

Standardized mortality ratios (SMRs) for all-cause and four specific leading causes of death were calculated at the town level in Busan for the years 2005 through 2008. To construct a deprivation index, principal components and factor analysis were adopted, using 10% sample data from the 2005 census. Geographic information system (GIS) mapping techniques were applied to compare spatial distributions between the deprivation index and SMRs. We fitted the Gaussian conditional autoregressive model (CAR) to estimate the relative risks of mortality by deprivation level, controlling for both the heterogeneity effect and spatial autocorrelation.

Results

The SMRs of towns in Busan averaged 100.3, ranging from 70.7 to 139.8. In old inner cities and towns reclaimed for replaced households, the deprivation index and SMRs were relatively high. CAR modeling showed that gaps in SMRs for heart disease, cerebrovascular disease, and physical injury were particularly high.

Conclusions

Our findings indicate that more deprived towns are likely to have higher mortality, in particular from cardiovascular disease and physical injury. To improve overall health status and address health inequality, such deprived towns should be targeted.

Socio-economic inequalities in mortality due to injuries in small areas of ten cities in Spain (MEDEA Project)

OBJECTIVES

To analyse socio-economic inequalities in mortality due to injuries among census tracts of ten Spanish cities by sex and age in the period 1996-2003.

METHODS

This is a cross-sectional ecological study where the units of analysis are census tracts. The study population consisted of people residing in the cities during the period 1996-2003. For each census tract we obtained an index of socio-economic deprivation, and estimated standardized mortality ratios using hierarchical Bayesian models which take into account the spatial structure of the data.

RESULTS

In the majority of the cities, the geographical pattern of total mortality from injuries is similar to that of the socio-economic deprivation index. There is an association between mortality due to injuries and the deprivation index in the majority of the cities which is more important among men and among those younger than 45 years. In these groups, traffic injuries and overdoses are the causes most often associated with deprivation in the cities. The percentage of excess mortality from injuries related to socio-economic deprivation is higher than 20% in the majority of the cities, the cause with the highest percentage being drug overdose.

CONCLUSIONS

In most cities, there are socio-economic inequalities in mortality due to overdose and traffic injuries. In contrast, few cities have found association between suicide mortality and deprivation. Finally, no association was found between deprivation and deaths due to falls. Inequalities are higher in men and those under 45 years of age. These results highlight the importance of intra-urban inequalities in mortality due to injuries.

Inequalities in mortality in small areas of eleven Spanish cities (the multicenter MEDEA project)

The objectives of this study are to identify inequalities in mortality among census tracts of 11 Spanish cities in the period 1996-2003 and to analyse the relationship between these geographical inequalities and socioeconomic deprivation. It is a cross-sectional ecological study where the units of analysis are census tracts. We obtained an index of socioeconomic deprivation and estimated SMR by each census tract using hierarchical Bayesian models which take into account the spatial structure. In the majority of the cities geographical patterns in total mortality were found in both sexes, which were similar to those for the index of socioeconomic deprivation. Among men, four specific causes of death (lung cancer, ischemic heart diseases, respiratory diseases and cirrhosis) were positively associated with deprivation in the majority of cities. Among women the specific causes diabetes and cirrhosis were positively associated, while lung cancer was negatively associated with deprivation. The excess of mortality related with deprivation was 59,445 deaths among men and 23,292 among women. These results highlight the importance of intra-urban inequalities in health.

[Socioeconomic inequalities in mortality in the Basque Country [Spain]]

OBJECTIVES

To describe socioeconomic inequalities in mortality in the Basque Country, using mortality and socioeconomic data by census sections.

METHODS

Mortality and population data were obtained from the Basque Institute of Statistics. Socioeconomic characteristics of the census sections were assigned to each death and a deprivation index combining information from four socioeconomic indicators was computed. Age-adjusted mortality rates by sex, age group (0-64 > or = 65) and cause of death were calculated for each quintile of the deprivation index. Poisson regression models were fitted to estimate age-adjusted rate ratios and excess mortality attributable to inequalities.

RESULTS

Mortality showed a gradient according to the deprivation index in men and women. Mortality was greater in the most deprived sections. Mortality inequalities were observed in men younger than 65 years. A total of 9.3% of deaths in men and 4.9% of those in women were attributable to socioeconomic inequalities. The relative importance of the cause of death differed according to the inequality measure used. Lifestyle-related causes of death were notable.

CONCLUSION

This study illustrates the potential utility of census section socioeconomic indicators both to describe socioeconomic inequalities in mortality and to identify priorities for interventions.

Mortalidad y privación socioeconómica en las secciones censales y los distritos de Barcelona

OBJECTIVES

To analyze the association between socioeconomic deprivation and mortality in the census tracts of Barcelona and the distinct patterns of this association in the districts.

METHODS

We performed an ecological, cross sectional study based on the 1,812 census tracts and the 10 districts of Barcelona, using socioeconomic variables obtained from the 1991 census and mortality data for 1987-1995. A deprivation index was created through component analysis. Descriptive analyses were performed and multivariate Poisson regression models were adjusted.

RESULTS

The greater the socioeconomic deprivation in the census tracts, the higher the mortality. The quartile with the greatest deprivation had a relative risk (RR) of mortality of 1.24 (95% confidence interval [CI], 1.22-1.27) in males and an RR of 1.05 (95% CI, 1.02-1.07) in females (compared with the quartile of census tracts with the lowest deprivation). This association varied according to district: in the old inner-city district (district 1), which had the highest mortality and the greatest deprivation, the RR was 1.57 (95% CI, 1.21-2.05) for males, while in district 8, which also has considerable deprivation, mortality was lower.

CONCLUSIONS

Analysis of socioeconomic inequalities in mortality in census tracts in an urban area highlights special areas of risk not observed in analysis of districts.