Dataset Information

Area-level socioeconomic deprivation and mortality differentials in Thailand: results from principal component analysis and cluster analysis.

ABSTRACT:

Background

Despite achievement of universal health coverage in Thailand, socioeconomic inequality in health has been a major policy concern. This study examined mortality patterns across different socioeconomic strata in Thailand.

Methods

We conducted a cross-sectional analysis of the 2010 Population and Housing Census on area-level socioeconomic deprivation against the 2010 mortality from the vital registration database at the super-district level. We used principal components analysis to construct a socioeconomic deprivation index and K-mean cluster analysis to group socioeconomic status and cause-specific mortality.

Results

Excess mortality rates from all diseases, except colorectal cancer, were observed among super-districts with low socioeconomic status. Spatial clustering was evident in the distribution of socioeconomic status and mortality rates. Cluster analysis revealed that super-districts which were predominantly urban tended to have low all-cause standardize mortality ratio but a high colorectal cancer-specific mortality rate. Deaths due to liver cancer, diabetes, and renal diseases were common in the low socioeconomic super-districts which hosted one third of the total Thai population.

Conclusion

Socially deprived areas have an excess of overall and cause specific deaths. Populations living in more affluent areas, despite low general mortality, still have many preventable deaths such as colorectal cancer. These findings warrant future epidemiological studies investigating various causes of excessive deaths in non-deprived areas and implementation of policies to reduce the mortality gap between rich and poor areas.

SUBMITTER: Aungkulanon S

PROVIDER: S-EPMC5496369 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Publications

Area-level socioeconomic deprivation and mortality differentials in Thailand: results from principal component analysis and cluster analysis.

Aungkulanon Suchunya S Tangcharoensathien Viroj V Shibuya Kenji K Bundhamcharoen Kanitta K Chongsuvivatwong Virasakdi V

International journal for equity in health 20170703 1

<h4>Background</h4>Despite achievement of universal health coverage in Thailand, socioeconomic inequality in health has been a major policy concern. This study examined mortality patterns across different socioeconomic strata in Thailand.<h4>Methods</h4>We conducted a cross-sectional analysis of the 2010 Population and Housing Census on area-level socioeconomic deprivation against the 2010 mortality from the vital registration database at the super-district level. We used principal components an ...[more]

PMID: 28673302

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Project description:BackgroundSocioeconomic conditions affect the dynamics of the Covid-19 pandemic. We analysed the association between area-level socioeconomic deprivation, proportion of non-nationals, and incidence of Covid-19 infections in Germany.MethodsUsing linked nationally representative data at the level of 401 German districts from three waves of infection (January-2020 to May-2021), we fitted Bayesian spatiotemporal models to assess the association between socioeconomic deprivation, and proportion of non-nationals with Covid-19 incidence, controlling for age, sex, vaccination coverage, settlement structure, and spatial and temporal effects. We estimated risk ratios (RR) and corresponding 95% credible intervals (95% CrI). We further examined the deprivation domains (education, income, occupation), interactions between deprivation, sex and the proportion of non-nationals, and explored potential pathways from deprivation to Covid-19 incidence.FindingsCovid-19 incidence risk was 15% higher (RR=1·15, 95%-CrI=1·06-1·24) in areas classified with the highest deprivation quintile (Q5) compared to the least deprived areas (Q1). Medium-low (Q2), medium (Q3), and medium-high (Q4) deprived districts showed 6% (1·06, 1·00-1·12), 8% (1·08, 1·01-1·15), and 5% (1·05, 0·98-1·13) higher risk, respectively, compared to the least deprived. Districts with higher proportion of non-nationals showed higher incidence risk compared to districts with lowest proportion, but the association weakened across the three waves. During the first wave, an inverse association was observed with highest incidence risk in least deprived areas (Q1). Deprivation interacted with sex, but not with the proportion of non-nationals.InterpretationSocioeconomic deprivation, and proportion of non-nationals are independently associated with the incidence of Covid-19. Regional planning of non-pharmaceutical interventions and vaccination strategies would benefit from consideration of area-level deprivation and non-national residency.FundingThe study was funded by the German Ministry of Health (ZMV I 1 - 25 20 COR 410).

Project description:Numerous studies have linked air pollution with adverse birth outcomes, but relatively few have examined differential associations across the socioeconomic gradient. To evaluate interaction effects of gestational nitrogen dioxide (NO2) and area-level socioeconomic deprivation on fetal growth, we used: (1) highly spatially-resolved air pollution data from the New York City Community Air Survey (NYCCAS); and (2) spatially-stratified principle component analysis of census variables previously associated with birth outcomes to define area-level deprivation. New York City (NYC) hospital birth records for years 2008-2010 were restricted to full-term, singleton births to non-smoking mothers (n=243,853). We used generalized additive mixed models to examine the potentially non-linear interaction of nitrogen dioxide (NO2) and deprivation categories on birth weight (and estimated linear associations, for comparison), adjusting for individual-level socio-demographic characteristics and sensitivity testing adjustment for co-pollutant exposures. Estimated NO2 exposures were highest, and most varying, among mothers residing in the most-affluent census tracts, and lowest among mothers residing in mid-range deprivation tracts. In non-linear models, we found an inverse association between NO2 and birth weight in the least-deprived and most-deprived areas (p-values<0.001 and 0.05, respectively) but no association in the mid-range of deprivation (p=0.8). Likewise, in linear models, a 10 ppb increase in NO2 was associated with a decrease in birth weight among mothers in the least-deprived and most-deprived areas of -16.2g (95% CI: -21.9 to -10.5) and -11.0 g (95% CI: -22.8 to 0.9), respectively, and a non-significant change in the mid-range areas [?=0.5 g (95% CI: -7.7 to 8.7)]. Linear slopes in the most- and least-deprived quartiles differed from the mid-range (reference group) (p-values<0.001 and 0.09, respectively). The complex patterning in air pollution exposure and deprivation in NYC, however, precludes simple interpretation of interactive effects on birth weight, and highlights the importance of considering differential distributions of air pollution concentrations, and potential differences in susceptibility, across deprivation levels.

Project description:ImportanceDiabetes management operates under a complex interrelationship between behavioral, social, and economic factors that affect a patient's ability to self-manage and access care.ObjectiveTo examine the association between 2 complementary area-based metrics, area deprivation index (ADI) score and rurality, and optimal diabetes care.Design, setting, and participantsThis cross-sectional study analyzed the electronic health records of patients who were receiving care at any of the 75 Mayo Clinic or Mayo Clinic Health System primary care practices in Minnesota, Iowa, and Wisconsin in 2019. Participants were adults with diabetes aged 18 to 75 years. All data were abstracted and analyzed between June 1 and November 30, 2020.Main outcomes and measuresThe primary outcome was the attainment of all 5 components of the D5 metric of optimal diabetes care: glycemic control (hemoglobin A1c <8.0%), blood pressure (BP) control (systolic BP <140 mm Hg and diastolic BP <90 mm Hg), lipid control (use of statin therapy according to recommended guidelines), aspirin use (for patients with ischemic vascular disease), and no tobacco use. The proportion of patients receiving optimal diabetes care was calculated as a function of block group-level ADI score (a composite measure of 17 US Census indicators) and zip code-level rurality (calculated using Rural-Urban Commuting Area codes). Odds of achieving the D5 metric and its components were assessed using logistic regression that was adjusted for demographic characteristics, coronary artery disease history, and primary care team specialty.ResultsAmong the 31 934 patients included in the study (mean [SD] age, 59 [11.7] years; 17 645 men [55.3%]), 13 138 (41.1%) achieved the D5 metric of optimal diabetes care. Overall, 4090 patients (12.8%) resided in the least deprived quintile (quintile 1) of block groups and 1614 (5.1%) lived in the most deprived quintile (quintile 5), while 9193 patients (28.8%) lived in rural areas and 2299 (7.2%) in highly rural areas. The odds of meeting the D5 metric were lower for individuals residing in quintile 5 vs quintile 1 block groups (odds ratio [OR], 0.72; 95% CI, 0.67-0.78). Patients residing in rural (OR, 0.84; 95% CI, 0.73-0.97) and highly rural (OR, 0.81; 95% CI, 0.72-0.91) zip codes were also less likely to attain the D5 metric compared with those in urban areas.Conclusions and relevanceThis cross-sectional study found that patients living in more deprived and rural areas were significantly less likely to attain high-quality diabetes care compared with those living in less deprived and urban areas. The results call for geographically targeted population health management efforts by health systems, public health agencies, and payers.

Project description:BackgroundSocioeconomic deprivation (SED) is known to influence cardiovascular health. However, studies analyzing the relationship between deprivation and circulatory system diseases (CSD) in Central and Eastern Europe are limited. This study aimed to assess the relationship between SED and mortality due to CSD at a population level in 66 sub-regions of Poland.MethodsThe 2010-2014 data regarding mortality and SED components were obtained from the Central Statistical Office. An area-based SED index was calculated based on the higher education rates, employment structure, wages, unemployment, and poverty. The dynamics of changes in mortality due to CSD was expressed by the number of deaths prevented or postponed (DPP) in terciles of the SED index. The associations between the mortality from CSD and SED index were analyzed using multivariate Poisson regression models and generalized estimating equations.ResultsAmong men, the percentage of DPP in 2014 was 13.1% for CSD, 23.4% for ischemic heart disease (IHD), and 21.4% for cerebrovascular diseases (CeVD). In the case of women, the proportion of DPP was 12.8, 25.6, and 21.6%, respectively. More deprived sub-regions experienced a greater decrease in CSD-related mortality than less deprived sub-regions. The disparity in mortality reduction between more deprived and less deprived sub-regions was even more pronounced for women. After adjusting for smoking prevalence, average BMI, population density, and changes in mortality over time, it was found that the SED index over the 2010-2014 time period was significantly associated with CSD- and IHD-related mortality for men (respectively 5.3 and 19.5% expected mortality increase per 1-unit increase of SED index), and with IHD- and CeVD-related mortality for women (respectively 30.3 and 23.0% expected mortality increase per 1-unit increase of SED index).ConclusionsSignificant differences in mortality changes due to CSD in Poland could be observed in relation to socioeconomic deprivation, resulting in reduced health inequalities. To reduce CSD mortality, more comprehensive preventive measures, including approaches addressing the socioeconomic factors, mainly poverty, education and employment, are needed, particularly in less urbanized areas.

Project description:ImportanceSocial determinants of health play a role in diabetes management and outcomes, including potentially life-threatening complications of severe hypoglycemia and diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar state (HHS). Although several person-level socioeconomic factors have been associated with these complications, the implications of area-level socioeconomic deprivation are unknown.ObjectiveTo examine the association between area-level deprivation and the risks of experiencing emergency department visits or hospitalizations for hypoglycemic and hyperglycemic crises (ie, DKA or HHS).Design, setting, and participantsThis cohort study used deidentified administrative claims data for privately insured individuals and Medicare Advantage beneficiaries across the US. The analysis included adults with diabetes who met the claims criteria for diabetes between January 1, 2016, and December 31, 2017. Data analyses were performed from November 17, 2020, to November 11, 2021.ExposuresArea deprivation index (ADI) was derived for each county for 2016 and 2017 using 17 county-level indicators from the American Community Survey. ADI values were applied to patients who were living in each county based on their index dates and were categorized according to county-level ADI quintile (with quintile 1 having the least deprivation and quintile 5 having the most deprivation).Main outcomes and measuresThe numbers of emergency department visits or hospitalizations related to the primary diagnoses of hypoglycemia and DKA or HHS (ascertained using validated diagnosis codes in the first or primary position of emergency department or hospital claims) between 2016 and 2019 were calculated for each ADI quintile using negative binomial regression models and adjusted for patient age, sex, health plan type, comorbidities, glucose-lowering medication type, and percentage of White residents in the county.ResultsThe study population included 1 116 361 individuals (563 943 women [50.5%]), with a mean (SD) age of 64.9 (13.2) years. Of these patients, 343 726 (30.8%) resided in counties with the least deprivation (quintile 1) and 121 810 (10.9%) lived in counties with the most deprivation (quintile 5). Adjusted rates of severe hypoglycemia increased from 13.54 (95% CI, 12.91-14.17) per 1000 person-years in quintile 1 counties to 19.13 (95% CI, 17.62-20.63) per 1000 person-years in quintile 5 counties, corresponding to an incidence rate ratio of 1.41 (95% CI, 1.29-1.54; P < .001). Adjusted rates of DKA or HHS increased from 7.49 (95% CI, 6.96-8.02) per 1000 person-years in quintile 1 counties to 8.37 (95% CI, 7.50-9.23) per 1000 person-years in quintile 5 counties, corresponding to an incidence rate ratio of 1.12 (95% CI, 1.00-1.25; P = .049).Conclusions and relevanceThis study found that living in counties with a high area-level deprivation was associated with an increased risk of severe hypoglycemia and DKA or HHS. The concentration of these preventable events in areas of high deprivation signals the need for interventions that target the structural barriers to optimal diabetes management and health.

Dataset Information

Area-level socioeconomic deprivation and mortality differentials in Thailand: results from principal component analysis and cluster analysis.

Background

Methods

Results

Conclusion

Publications

Area-level socioeconomic deprivation and mortality differentials in Thailand: results from principal component analysis and cluster analysis.

Similar Datasets

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