Small-area socioeconomic deprivation indices in Cyprus: development and association with premature mortality.
ABSTRACT: BACKGROUND:Area-level measures of socioeconomic deprivation are important for understanding and describing health inequalities. The aim of this study was the development and validation of a small-area index of socioeconomic deprivation for Cypriot communities and the investigation of its association with the spatial distribution of all-cause premature adult mortality. METHODS:Six area-level socioeconomic indicators were used from the 2011 national population census (low educational attainment, unemployment, not owner occupied household, single-person household, divorced or widowed and single-parent households). After normalization and standardization of the geographically smoothed indicators, Principal Component Analysis (PCA) was used to construct indicator weights. The association between deprivation indices and the spatial distribution of all-cause premature adult mortality was estimated in Poisson log-linear spatial models. RESULTS:PCA resulted in two principal components explaining the 65.7% of the total variance. The first principal component included four indicators (low educational attainment, single-person households, divorced or widowed and single-parent households, the latter however with a negative loading) and it thought more likely to capture rural-related aspects of deprivation. The second principal component included the other two indicators (unemployment and not owner occupied households) and it is more likely to capture urban-related aspects of material deprivation. Restricting the analysis in the metropolitan areas of the island resulted in a different set of indicators for the urban-specific deprivation index. All developed indices were linearly associated with all-cause premature adult mortality. The all-cause premature adult mortality increased by 17% per 1 standard deviation (SD) increase in rural-related socioeconomic deprivation (95% CrI: 8-27%) and 8% per 1 SD increase in urban-related aspects of material deprivation (95% CrI: 3-15%) in the nationwide analysis and 9% per 1 SD increase in urban-specific socioeconomic deprivation (95% CrI: 4-15%) across metropolitan areas. CONCLUSIONS:The results of this study demonstrate that a set of small-area indices of socioeconomic deprivation across Cypriot communities have good construct and predictive validity. However, the study indicates that different aspects of socioeconomic deprivation may be important in rural and urban areas in Cyprus. The developed socioeconomic deprivation indices could offer a valid new tool for Cypriot public health research and policy in terms of identifying areas in greatest need, guiding resource allocation and developing area-targeted public health programmes and policies.
Project description:Geographical investigations are a core function of public health monitoring, providing the foundation for resource allocation and policies for reducing health inequalities. The aim of this study was to develop geodemographic area classification based on several area-level indicators and to explore the extent of geographical inequalities in mortality. A series of 19 area-level socioeconomic indicators were used from the 2011 national population census. After normalization and standardization of the geographically smoothed indicators, the k-means cluster algorithm was implemented to classify communities into groups based on similar characteristics. The association between geodemographic area classification and the spatial distribution of mortality was estimated in Poisson log-linear spatial models. The k-means algorithm resulted in four distinct clusters of areas. The most characteristic distinction was between the ageing, socially isolated, and resource-scarce rural communities versus metropolitan areas with younger population, higher educational attainment, and professional occupations. By comparison to metropolitan areas, premature mortality appeared to be 44% (95% Credible Intervals [CrI] of Rate Ratio (RR): 1.06-1.91) higher in traditional rural areas and 36% (95% CrI of RR: 1.13-1.62) higher in young semi-rural areas. These findings warrant future epidemiological studies investigating various causes of the urban-rural differences in premature mortality and implementation policies to reduce the mortality gap between urban and rural areas.
Project description:Urbanisation brings with it rapid socio-economic change with volatile livelihoods and unstable ownership of assets. Yet, current measures of wealth are based predominantly on static livelihoods found in rural areas. We sought to assess the extent to which seven common measures of wealth appropriately capture vulnerability to poverty in urban areas. We then sought to develop a measure that captures the characteristics of one urban area in Nepal. We collected and analysed data from 1,180 households collected during a survey conducted between November 2017 and January 2018 and designed to be representative of the Kathmandu valley. A separate survey of a sub set of households was conducted using participatory qualitative methods in slum and non-slum neighbourhoods. A series of currently used indices of deprivation were calculated from questionnaire data. We used bivariate statistical methods to examine the association between each index and identify characteristics of poor and non-poor. Qualitative data was used to identify characteristics of poverty from the perspective of urban poor communities which were used to construct an Urban Poverty Index that combined asset and consumption focused context specific measures of poverty that could be proxied by easily measured indicators as assessed through multivariate modelling. We found a strong but not perfect association between each measure of poverty. There was disagreement when comparing the consumption and deprivation index on the classification of 19% of the sample. Choice of short-term monetary and longer-term capital approaches accounted for much of the difference. Those who reported migrating due to economic necessity were most likely to be categorised as poor. A combined index was developed to capture these dimension of poverty and understand urban vulnerability. A second version of the index was constructed that can be computed using a smaller range of variables to identify those in poverty. Current measures may hide important aspects of urban poverty. Those who migrate out of economic necessity are particularly vulnerable. A composite index of socioeconomic status helps to capture the complex nature of economic vulnerability.
Project description:BackgroundAlthough measles is endemic throughout the World Health Organization European Region, few studies have analysed socioeconomic inequalities and spatiotemporal variations in the disease's incidence.AimTo study the association between socioeconomic deprivation and measles incidence in Germany, while considering relevant demographic, spatial and temporal factors.MethodsWe conducted a longitudinal small-area analysis using nationally representative linked data in 401 districts (2001-2017). We used spatiotemporal Bayesian regression models to assess the potential effect of area deprivation on measles incidence, adjusted for demographic and geographical factors, as well as spatial and temporal effects. We estimated risk ratios (RR) for deprivation quintiles (Q1-Q5), and district-specific adjusted relative risks (ARR) to assess the area-level risk profile of measles in Germany.ResultsThe risk of measles incidence in areas with lowest deprivation quintile (Q1) was 1.58 times higher (95% credible interval (CrI): 1.32-2.00) than in those with highest deprivation (Q5). Areas with medium-low (Q2), medium (Q3) and medium-high deprivation (Q4) had higher adjusted risks of measles relative to areas with highest deprivation (Q5) (RR: 1.23, 95%CrI: 0.99-1.51; 1.05, 95%CrI: 0.87-1.26 and 1.23, 95%CrI: 1.05-1.43, respectively). We identified 54 districts at medium-high risk for measles (ARR > 2) in Germany, of which 22 were at high risk (ARR > 3).ConclusionSocioeconomic deprivation in Germany, one of Europe's most populated countries, is inversely associated with measles incidence. This association persists after demographic and spatiotemporal factors are considered. The social, spatial and temporal patterns of elevated risk require targeted public health action and policy to address the complexity underlying measles epidemiology.
Project description:In contrast to area-based deprivation measures, commercial datasets remain infrequently used in health research and policy. Experian collates numerous commercial and administrative data sources to produce Mosaic groups which stratify households into 15 groups for marketing purposes. We assessed the potential utility of Mosaic groups for health research purposes by investigating their relationships with Indices of Multiple Deprivation (IMD) for the British population. Mosaic groups showed significant associations with IMD quintiles. Correspondence Analysis revealed variations in patterns of association, with Mosaic groups either showing increasing, decreasing, or some mixed trends with deprivation quintiles. These results suggest that Experian's Mosaics additionally measure other aspects of socioeconomic circumstances to those captured by deprivation measures. These commercial data may provide new insights into the social determinants of health at a small area level.
Project description:<h4>Background</h4>Monitoring health inequalities is an important task for health research and policy, to uncover who is being left behind - and where - and to inform effective and equitable policies and programmes to tackle existing inequities. The choice of which measure to use to monitor and analyse health inequalities is thereby not trivial. This article explores a new measure of socioeconomic deprivation status (SDS) to monitor health inequalities.<h4>Methods</h4>The SDS measure was constructed using the Alkire-Foster method. It includes eight indicators across two equally weighted dimensions (education and living standards) and specifies a four-level gradient of socioeconomic deprivation at the household-level. We conducted four exercises to examine the value-added of the proposed SDS measure, using Demographic and Health Surveys data. First, we examined the discriminatory power of the new measure when applied to outcomes in four select reproductive, maternal, neonatal, and child health (RMNCH) indicators across six countries: skilled birth attendance, stunting, U5MR, and DTP3 immunisation. Then, we analysed the behaviour and association of the new SDS measure vis-à-vis the DHS Wealth Index, including chi-squared test and Pearson correlation coefficient. Third, we analysed the robustness of the SDS measure results to changes in its structure, using pairwise comparisons and Kendal Tau-b rank correlation. Finally, we illustrated some of the advantageous properties of the new measure, disaggregation and decomposition, on Haitian data.<h4>Results</h4>1) Higher levels of socioeconomic deprivation are generally consistently associated with lower levels of achievements in the RMNCH indicators across countries. 2) 87% of all pairwise rank comparisons across a range of SDS measure structures were robust. 3) SDS and DHS Wealth Index are associated, but with considerable cross-country variation, highlighting their complementarity. 4) Haitian households in rural areas experienced, on average, more severe socioeconomic deprivation as well as lower levels of RMNCH achievement than urban households.<h4>Conclusions</h4>The proposed SDS measure adds analytical possibilities to the health inequality monitoring literature, in line with ethically and conceptually well-founded notions of absolute, multidimensional disadvantage. In addition, it allows for breakdown by its dimensions and components, which may facilitate nuanced analyses of health inequality, its correlates, and determinants.
Project description:<h4>Introduction</h4>Severe undernutrition among under-5 children is usually assessed using single or conventional indicators (i.e., severe stunting, severe wasting, and/or severe underweight). But these conventional indicators partly overlap, thus not providing a comprehensive estimate of the proportion of malnourished children in the population. Incorporating all these conventional nutritional indicators, the Composite Index of Severe Anthropometric Failure (CSIAF) provides six different undernutrition measurements and estimates the overall burden of severe undernutrition with a more comprehensive view. This study applied the CISAF indicators to investigate the prevalence of severe under-5 child undernutrition in Bangladesh and its associated socioeconomic factors in the rural-urban context.<h4>Methods</h4>This study extracted the children dataset from the 2017-18 Bangladesh Demographic Health Survey (BDHS), and the data of 7661 children aged under-5 were used for further analyses. CISAF was used to define severe undernutrition by aggregating conventional nutritional indicators. Bivariate analysis was applied to examine the proportional differences of variables between non-severe undernutrition and severe undernutrition group. The potential associated socioeconomic factors for severe undernutrition were identified using the adjusted model of logistic regression analysis.<h4>Results</h4>The overall prevalence of severe undernutrition measured by CISAF among the children under-5 was 11.0% in Bangladesh (rural 11.5% vs urban 9.6%). The significant associated socioeconomic factors of severe undernutrition in rural areas were children born with small birth weight (AOR: 2.84), children from poorest households (AOR: 2.44), and children aged < 36 months, and children of uneducated mothers (AOR: 2.15). Similarly, in urban areas, factors like- children with small birth weight (AOR: 3.99), children of uneducated parents (AOR: 2.34), poorest households (APR: 2.40), underweight mothers (AOR: 1.58), mothers without postnatal care (AOR: 2.13), and children's birth order ≥4 (AOR: 1.75), showed positive and significant association with severe under-5 undernutrition.<h4>Conclusion</h4>Severe undernutrition among the under-5 children dominates in Bangladesh, especially in rural areas and the poorest urban families. More research should be conducted using such composite indices (like- CISAF) to depict the comprehensive scenario of severe undernutrition among the under-5 children and to address multi-sectoral intervening programs for eradicating severe child undernutrition.
Project description:Life expectancy inequalities are an established indicator of health inequalities. More recent attention has been given to lifespan variation, which measures the amount of heterogeneity in age at death across all individuals in a population. International studies have documented diverging socioeconomic trends in lifespan variation using individual level measures of income, education and occupation. Despite using different socioeconomic indicators and different indices of lifespan variation, studies reached the same conclusion: the most deprived experience the lowest life expectancy and highest lifespan variation, a double burden of mortality inequality. A finding of even greater concern is that relative differences in lifespan variation between socioeconomic group were growing at a faster rate than life expectancy differences. The magnitude of lifespan variation inequalities by area-level deprivation has received limited attention. Area-level measures of deprivation are actively used by governments for allocating resources to tackle health inequalities. Establishing if the same lifespan variation inequalities emerge for area-level deprivation will help to better inform governments about which dimension of mortality inequality should be targeted. We measure lifespan variation trends (1981-2011) stratified by an area-level measure of socioeconomic deprivation that is applicable to the entire population of Scotland, the country with the highest level of variation and one of the longest, sustained stagnating trends in Western Europe. We measure the gradient in variation using the slope and relative indices of inequality. The deprivation, age and cause specific components driving the increasing gradient are identified by decomposing the change in the slope index between 1981 and 2011. Our results support the finding that the most advantaged are dying within an ever narrower age range while the most deprived are facing greater and increasing uncertainty. The least deprived group show an increasing advantage, over the national average, in terms of deaths from circulatory disease and external causes.
Project description:Area-based deprivation indices (ABDIs) have become a common tool with which to investigate the patterns and magnitude of socioeconomic inequalities in health. ABDIs are also used as a proxy for individual socioeconomic status. Despite their widespread use, comparably less attention has been focused on their geographic variability and practical concerns surrounding the Modifiable Area Unit Problem (MAUP) than on the individual attributes that make up the indices. Although scale is increasingly recognized as an important factor in interpreting mapped results among population health researchers, less attention has been paid specifically to ABDI and scale. In this paper, we highlight the effect of scale on indices by mapping ABDIs at multiple census scales in an urban area. In addition, we compare self-rated health data from the Canadian Community Health Survey with ABDIs at two census scales. The results of our analysis confirm the influence of spatial extent and scale on mapping population health-with potential implications for health policy implementation and resource distribution.
Project description:<h4>Objective</h4>Countries in sub-Saharan Africa suffer the highest rates of child mortality worldwide. Urban areas tend to have lower mortality than rural areas, but these comparisons likely mask large within-city inequalities. We aimed to estimate rates of under-five mortality (U5M) at the neighbourhood level for Ghana's Greater Accra Metropolitan Area (GAMA) and measure the extent of intraurban inequalities.<h4>Methods</h4>We accessed data on >700 000 women aged 25-49 years living in GAMA using the most recent Ghana census (2010). We summarised counts of child births and deaths by five-year age group of women and neighbourhood (n=406) and applied indirect demographic methods to convert the summaries to yearly probabilities of death before age five years. We fitted a Bayesian spatiotemporal model to the neighbourhood U5M probabilities to obtain estimates for the year 2010 and examined their correlations with indicators of neighbourhood living and socioeconomic conditions.<h4>Results</h4>U5M varied almost five-fold across neighbourhoods in GAMA in 2010, ranging from 28 (95% credible interval (CrI) 8 to 63) to 138 (95% CrI 111 to 167) deaths per 1000 live births. U5M was highest in neighbourhoods of the central urban core and industrial areas, with an average of 95 deaths per 1000 live births across these neighbourhoods. Peri-urban neighbourhoods performed better, on average, but rates varied more across neighbourhoods compared with neighbourhoods in the central urban areas. U5M was negatively correlated with multiple indicators of improved living and socioeconomic conditions among peri-urban neighbourhoods. Among urban neighbourhoods, correlations with these factors were weaker or, in some cases, reversed, including with median household consumption and women's schooling.<h4>Conclusion</h4>Reducing child mortality in high-burden urban neighbourhoods in GAMA, where a substantial portion of the urban population resides, should be prioritised as part of continued efforts to meet the Sustainable Development Goal national target of less than 25 deaths per 1000 live births.
Project description:<h4>Background</h4>This study aimed to characterize trends in absolute and relative socioeconomic inequalities in adult premature mortality between 1992 and 2017, in the context of declining population-wide mortality rates. We conducted a population-based cohort study of all adult premature deaths in Ontario, Canada using provincial vital statistics data linked to census-based, area-level deprivation indices for socioeconomic status.<h4>Methods</h4>The cohort included all individuals eligible for Ontario's single-payer health insurance system at any time between January 1, 1992 and December 31, 2017 with a recorded Ontario place of residence and valid socioeconomic status information (N = 820,370). Deaths between ages 18 and 74 were used to calculate adult premature mortality rates per 1000, stratified by provincial quintile of material deprivation. Relative inequalities were measured using Relative Index of Inequality (RII) measures. Absolute inequalities were estimated using Slope Index of Inequality (SII) measures. All outcome measures were calculated as sex-specific, annual measures for each year from 1992 to 2017.<h4>Results</h4>Premature mortality rates declined in all socioeconomic groups between 1992 and 2017. Relative inequalities in premature mortality increased over the same period. Absolute inequalities were mostly stable between 1992 and 2007, but increased dramatically between 2008 and 2017, with larger increases to absolute inequalities seen in females than in males.<h4>Conclusions</h4>As in other developed countries, long-term downward trends in all-cause premature mortality in Ontario, Canada have shifted to a plateau pattern in recent years, especially in lower- socioeconomic status subpopulations. Determinants of this may differ by setting. Regular monitoring of mortality by socioeconomic status is the only way that this phenomenon can be detected sensitively and early, for public health attention and possible corrective action.