Mortality Burden and Socioeconomic Status in India
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{"title"=>"Mortality burden and socioeconomic status in India", "type"=>"journal", "authors"=>[{"first_name"=>"June Y.T.", "last_name"=>"Po", "scopus_author_id"=>"55161899700"}, {"first_name"=>"S. V.", "last_name"=>"Subramanian", "scopus_author_id"=>"55433328900"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"79951801670", "doi"=>"10.1371/journal.pone.0016844", "pui"=>"361298736", "issn"=>"19326203", "pmid"=>"21347373", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-79951801670"}, "id"=>"aee05538-1863-350a-a3f2-a3927d76f16c", "abstract"=>"The dimensions along which mortality is patterned in India remains unclear. We examined the specific contribution of social castes, household income, assets, and monthly per capita consumption to mortality differentials in India.", "link"=>"http://www.mendeley.com/research/mortality-burden-socioeconomic-status-india", "reader_count"=>39, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>3, "Student > Master"=>9, "Other"=>1, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>3, "Student > Master"=>9, "Other"=>1, "Student > Bachelor"=>3, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Engineering"=>1, "Environmental Science"=>1, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>8, "Agricultural and Biological Sciences"=>4, "Psychology"=>1, "Social Sciences"=>16, "Computer Science"=>1, "Economics, Econometrics and Finance"=>4}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Social Sciences"=>{"Social Sciences"=>16}, "Psychology"=>{"Psychology"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"India"=>2}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/799210"], "description"=>"<p>Predicted probabilities (PP) of death by age groups comparing monthly consumption per capita quintiles.</p>", "links"=>[], "tags"=>["probabilities", "groups", "comparing", "capita"], "article_id"=>469581, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0016844.g003", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_probabilities_PP_of_death_by_age_groups_comparing_monthly_consumption_per_capita_quintiles_/469581", "title"=>"Predicted probabilities (PP) of death by age groups comparing monthly consumption per capita quintiles.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-02-09 02:39:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/399741", "https://ndownloader.figshare.com/files/399748", "https://ndownloader.figshare.com/files/399755"], "description"=>"<div><h3>Background</h3><p>The dimensions along which mortality is patterned in India remains unclear. We examined the specific contribution of social castes, household income, assets, and monthly per capita consumption to mortality differentials in India.</p> <h3>Methods and Findings</h3><p>Cross-sectional data on 217 363 individuals from 41 554 households from the 2004–2005 India Human Development Survey was analyzed using multiple logistic regressions. Mortality differentials across social castes were attenuated after adjusting for household economic factors such as income and assets. Individuals living in the lowest income and assets quintiles had an increased risk of mortality with odds ratio (OR) of 1.66 (95% CI  = 1.23–2.24) in the bottom income quintile and OR of 2.94 (95% CI  = 1.66–5.22) in the bottom asset quintile. Counter-intuitively, individuals living in households with lowest monthly consumption per capita had significantly lower probability of death (OR  = 0.27, 95% CI  = 0.20–0.38).</p> <h3>Conclusions</h3><p>Mortality burden in India is largely patterned on economic dimensions as opposed to caste dimensions, though caste may play an important role in predicting economic opportunities.</p> </div>", "links"=>[], "tags"=>["socioeconomic", "india"], "article_id"=>138970, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0016844.s001", "https://dx.doi.org/10.1371/journal.pone.0016844.s002", "https://dx.doi.org/10.1371/journal.pone.0016844.s003"], "stats"=>{"downloads"=>16, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Mortality_Burden_and_Socioeconomic_Status_in_India/138970", "title"=>"Mortality Burden and Socioeconomic Status in India", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-02-09 02:29:30"}
  • {"files"=>["https://ndownloader.figshare.com/files/799341"], "description"=>"1<p>PP: Predicted probabilities of mortality per 1000 persons given the individual is a male living in the city, who belongs in the High Caste and living in the top quintile of household income, assets ownership and monthly consumption per capita.</p><p>*significance with <i>p</i>-value <0.10,</p><p>**significance with <i>p</i>-value <0.05.</p>", "links"=>[], "tags"=>["probabilities", "socioeconomic", "factors", "modified", "adjusted", "urban-rural", "indian"], "article_id"=>469709, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0016844.t003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_Probabilities_95_Confidence_Intervals_of_Mortality_by_Socioeconomic_Factors_Modified_by_Age_Adjusted_for_Gender_Urban_Rural_Status_Religion_Fixed_Effects_on_States_Indian_Human_Development_Survey_2004_2005_/469709", "title"=>"Predicted Probabilities (95% Confidence Intervals) of Mortality by Socioeconomic Factors Modified by Age, Adjusted for Gender, Urban-Rural Status, Religion, Fixed Effects on States: Indian Human Development Survey, 2004-2005.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-02-09 02:41:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/799088"], "description"=>"<p>Predicted probabilities (PP) of death by age groups comparing asset quintiles.</p>", "links"=>[], "tags"=>["probabilities", "groups", "comparing"], "article_id"=>469461, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0016844.g002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_probabilities_PP_of_death_by_age_groups_comparing_asset_quintiles_/469461", "title"=>"Predicted probabilities (PP) of death by age groups comparing asset quintiles.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-02-09 02:37:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/799309"], "description"=>"<p>Number and Percentage of Deaths during One Year Before the Survey, by Descriptive Characteristics of the Sample: India Human Development Survey, 2004-2005.</p>", "links"=>[], "tags"=>["deaths", "descriptive", "characteristics", "india"], "article_id"=>469681, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0016844.t001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Number_and_Percentage_of_Deaths_during_One_Year_Before_the_Survey_by_Descriptive_Characteristics_of_the_Sample_India_Human_Development_Survey_2004_2005_/469681", "title"=>"Number and Percentage of Deaths during One Year Before the Survey, by Descriptive Characteristics of the Sample: India Human Development Survey, 2004-2005.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-02-09 02:41:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/799281"], "description"=>"<p>*significance with <i>p</i>-value <0.05.</p>", "links"=>[], "tags"=>["ratios", "quartiles", "stratified", "adjusted", "urban-rural", "indian"], "article_id"=>469648, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0016844.t004", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Odds_Ratios_of_Mortality_in_Asset_Quartiles_Stratified_by_Social_Castes_Adjusted_for_Gender_Urban_Rural_Status_Fixed_Effects_on_States_Indian_Human_Development_Survey_2004_2005_/469648", "title"=>"Odds Ratios of Mortality in Asset Quartiles Stratified by Social Castes, Adjusted for Gender, Urban-Rural Status, Fixed Effects on States: Indian Human Development Survey, 2004-2005.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-02-09 02:40:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/798995"], "description"=>"<p>Predicted probabilities (PP) of death by age groups comparing income quintiles.</p>", "links"=>[], "tags"=>["probabilities", "groups", "comparing"], "article_id"=>469369, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0016844.g001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_probabilities_PP_of_death_by_age_groups_comparing_income_quintiles_/469369", "title"=>"Predicted probabilities (PP) of death by age groups comparing income quintiles.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-02-09 02:36:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/799370"], "description"=>"<p>*significance with <i>p</i>-value <0.05.</p>", "links"=>[], "tags"=>["ratios", "socioeconomic", "adjusted", "urban-rural", "indian"], "article_id"=>469746, "categories"=>["Biotechnology"], "users"=>["June Y. T. Po", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0016844.t002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Odds_Ratios_of_Mortality_by_Socioeconomic_Factors_Adjusted_for_Gender_Age_Urban_Rural_Status_Religion_Fixed_Effects_on_States_Indian_Human_Development_Survey_2004_2005_/469746", "title"=>"Odds Ratios of Mortality by Socioeconomic Factors, Adjusted for Gender, Age, Urban-Rural Status, Religion, Fixed Effects on States: Indian Human Development Survey, 2004-2005.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-02-09 02:42:26"}

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Relative Metric

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