Ecological association between a deprivation index and mortality in France over the period 1997 – 2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death

Rey, Grégoire; Jougla, Éric; Fouillet, Anne; Hémon, Denis

doi:10.1186/1471-2458-9-33

Cited by 383 publications

(319 citation statements)

References 40 publications

(56 reference statements)

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“…Residual confounding cannot be excluded, in particular educational level, income, 17 obesity, 18 or inadequacy of prenatal care. 19 The regional environment, in particular the socio-economic context, such as the deprivation index, 20 working and commuting conditions, especially transportation to the different healthcare facilities where women might be seen according to their health status, have not been studied because this type of information was not available. A different study protocol would be required to take them into account.…”

Section: Discussionmentioning

confidence: 99%

Understanding regional differences in maternal mortality: a national case–control study in France

Saucedo

Deneux‐Tharaux

Bouvier‐Colle

2011

BJOG

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Objectives To assess the risk of postpartum maternal death associated with region, and to examine whether the quality of care received by the women who died differed by region.Design A national case-control study. Methods Crude and adjusted odds ratios (aOR) of maternal death associated with region were calculated with logistic regression, and the quality of care for women who died was compared according to region with chi-square tests or Fisher's exact tests.Main outcome measures Risk of postpartum maternal death associated with region, and quality of care.Results After adjustment for maternal age and nationality, the risk of maternal death was higher in the Ile-de-France region (aOR 1.6, 95% CI 1.2-2.0) and the overseas districts (aOR 3.5, 95% CI 2.4-5.0) than in the group for the rest of continental France. In both regions, the excess risk of death from haemorrhage, amniotic fluid embolism and hypertensive disorders was significant. In continental France, after further controlling for women's obstetric characteristics, the risk of maternal death in Ile-de-France remained higher (aOR 1.8. 95% CI 1.3-2.6). The women in the cases groups received suboptimal care more frequently in Ile-de-France than in the other continental regions (64% versus 43%, P = 0.01).Conclusions These results suggest that quality of care and organisation of health services may play a role in the differential risk of maternal mortality between regions in France. Research on severe maternal morbidity and its determinants is needed to clarify the mechanisms involved.

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Section: Discussionmentioning

confidence: 99%

Understanding regional differences in maternal mortality: a national case–control study in France

Saucedo

Deneux‐Tharaux

Bouvier‐Colle

2011

BJOG

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“…Perhaps a dozen or more schemes for assessing disparities have been developed. 19,[22][23][24][25][26][27][28][29] Of these, we have devolved on two measures of inequality, both of which derive from the distribution of the indicators (the I i S ) for a small area group. If we order the units by the size of the indicator (that is, by rank) on the abscissa and their Urban Health Index (the geometric mean of the proportions of the standardized indicators for each census tract) on the ordinate, we get a curve with roughly the shape shown in Fig.…”

Section: Index Constructionmentioning

confidence: 99%

“…Practitioners note the deficiencies of a composite statistic, [11][12][13][14][15][16][17][18][19] whose simplicity may conceal distortion. The factors making up a statistic may covary, and a change in the resulting metric may not be directly interpretable.…”

Section: Introductionmentioning

confidence: 99%

A Flexible Urban Health Index for Small Area Disparities

et al. 2014

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Available urban health metrics focus primarily on large area rankings. Less has been done to develop an index that provides information about level of health and health disparities for small geographic areas. Adopting a method used by the Human Development Index, we standardized indicators for small area units on a (0, 1) interval and combined them using their geometric mean to form an Urban Health Index (UHI). Disparities were assessed using the ratio of the highest to lowest decile and measurement of the slope of the eight middle deciles (middle; 80 %) of the data. We examined the sensitivity of the measure to weighting, to changes in the method, to correlation among indicators, and to substitution of indicators. Using seven health determinants and applying these methods to the 128 census tracts in the city of Atlanta, USA, we found a disparity ratio of 5.92 and a disparity slope of 0.54, suggesting substantial inequality and heterogeneity of risk. The component indicators were highly correlated; their systematic removal had a small effect on the results. Except in extreme cases, weighting had a little effect on the rankings. A map of Atlanta census tracts exposed a swath of high disparity. UHI rankings, ratio, and slope were resistant to alteration in composition and to non-extreme weighting schemes. This empirical evaluation was limited to a single realization, but suggests that a flexible tool, whose method rather than content is standardized, may be of use for local evaluation, for decision making, and for area comparison.

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“…Another problem that can arise is the spatial misalignment between potential risk factors and health data: in general, the former are available on a finer spatial resolution than the latter. For example, most deprivation indices 15 are built on the smallest possible geographical units of a certain region (see Rey et al, 2009;Salmond and Crampton, 2012) or even on a fine grid (Caudeville et al, 2012). Environmental agents (such as air pollution) constitute examples of risk factors that vary continuously in space.…”

Section: Introductionmentioning

confidence: 99%

Penalized composite link models for aggregated spatial count data: A mixed model approach

et al. 2016

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Mortality data provide valuable information for the study of the spatial distribution of mortality risk, in disciplines such as spatial epidemiology and public health. However, they are frequently available in an aggregated form over irregular geographical units, hindering the visualization of the underlying mortality risk. Also, it can be of interest to obtain mortality risk estimates on a finer spatial resolution, such that they can be linked to potential risk factors that are usually measured in a different spatial resolution. In this paper, we propose the use of the penalized composite link model and its mixed model representation. This model considers the nature of mortality rates by incorporating the population size at the finest resolution, and allows the creation of mortality maps at a finer scale, thus reducing the visual bias resulting from the spatial aggregation within original units. We also extend the model by considering individual random effects at the aggregated scale, in order to take into account the overdispersion. We illustrate our novel proposal using two datasets: female deaths by lung cancer in Indiana, USA, and male lip cancer incidence in Scotland counties. We also compare the performance of our proposal with the area-to-point Poisson kriging approach.

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Ecological association between a deprivation index and mortality in France over the period 1997 – 2001: variations with spatial scale, degree of urbanicity, age, gender and cause of death

Cited by 383 publications

References 40 publications

Understanding regional differences in maternal mortality: a national case–control study in France

Understanding regional differences in maternal mortality: a national case–control study in France

A Flexible Urban Health Index for Small Area Disparities

Penalized composite link models for aggregated spatial count data: A mixed model approach

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