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{"title"=>"Socioeconomic factors and all cause and cause-specific mortality among older people in Latin America, India, and China: A population-based cohort study", "type"=>"journal", "authors"=>[{"first_name"=>"Cleusa P.", "last_name"=>"Ferri", "scopus_author_id"=>"7103090584"}, {"first_name"=>"Daisy", "last_name"=>"Acosta", "scopus_author_id"=>"7103004631"}, {"first_name"=>"Mariella", "last_name"=>"Guerra", "scopus_author_id"=>"7102971517"}, {"first_name"=>"Yueqin", "last_name"=>"Huang", "scopus_author_id"=>"22953692700"}, {"first_name"=>"Juan J.", "last_name"=>"Llibre-Rodriguez", "scopus_author_id"=>"6508242689"}, {"first_name"=>"Aquiles", "last_name"=>"Salas", "scopus_author_id"=>"21233821200"}, {"first_name"=>"Ana Luisa", "last_name"=>"Sosa", "scopus_author_id"=>"7006027348"}, {"first_name"=>"Joseph D.", "last_name"=>"Williams", "scopus_author_id"=>"55543972100"}, {"first_name"=>"Ciro", "last_name"=>"Gaona", "scopus_author_id"=>"24474501000"}, {"first_name"=>"Zhaorui", "last_name"=>"Liu", "scopus_author_id"=>"7406676208"}, {"first_name"=>"Lisseth", "last_name"=>"Noriega-Fernandez", "scopus_author_id"=>"55053517800"}, {"first_name"=>"A. T.", "last_name"=>"Jotheeswaran", "scopus_author_id"=>"55405927400"}, {"first_name"=>"Martin J.", "last_name"=>"Prince", "scopus_author_id"=>"55507271700"}], "year"=>2012, "source"=>"PLoS Medicine", "identifiers"=>{"doi"=>"10.1371/journal.pmed.1001179", "sgr"=>"84857699507", "issn"=>"15491277", "pui"=>"364370614", "pmid"=>"22389633", "scopus"=>"2-s2.0-84857699507"}, "id"=>"c0d0f147-20c0-3a5c-b5f8-380eef788386", "abstract"=>"BACKGROUND Even in low and middle income countries most deaths occur in older adults. In Europe, the effects of better education and home ownership upon mortality seem to persist into old age, but these effects may not generalise to LMICs. Reliable data on causes and determinants of mortality are lacking. METHODS AND FINDINGS The vital status of 12,373 people aged 65 y and over was determined 3-5 y after baseline survey in sites in Latin America, India, and China. We report crude and standardised mortality rates, standardized mortality ratios comparing mortality experience with that in the United States, and estimated associations with socioeconomic factors using Cox's proportional hazards regression. Cause-specific mortality fractions were estimated using the InterVA algorithm. Crude mortality rates varied from 27.3 to 70.0 per 1,000 person-years, a 3-fold variation persisting after standardisation for demographic and economic factors. Compared with the US, mortality was much higher in urban India and rural China, much lower in Peru, Venezuela, and urban Mexico, and similar in other sites. Mortality rates were higher among men, and increased with age. Adjusting for these effects, it was found that education, occupational attainment, assets, and pension receipt were all inversely associated with mortality, and food insecurity positively associated. Mutually adjusted, only education remained protective (pooled hazard ratio 0.93, 95% CI 0.89-0.98). Most deaths occurred at home, but, except in India, most individuals received medical attention during their final illness. Chronic diseases were the main causes of death, together with tuberculosis and liver disease, with stroke the leading cause in nearly all sites. CONCLUSIONS Education seems to have an important latent effect on mortality into late life. However, compositional differences in socioeconomic position do not explain differences in mortality between sites. Social protection for older people, and the effectiveness of health systems in preventing and treating chronic disease, may be as important as economic and human development.", "link"=>"http://www.mendeley.com/research/socioeconomic-factors-cause-causespecific-mortality-among-older-people-latin-america-india-china-pop-11", "reader_count"=>61, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>1, "Researcher"=>17, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>4, "Student > Master"=>15, "Other"=>5, "Student > Bachelor"=>2, "Professor"=>3}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>1, "Researcher"=>17, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>4, "Student > Master"=>15, "Other"=>5, "Student > Bachelor"=>2, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>1, "Nursing and Health Professions"=>2, "Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>33, "Agricultural and Biological Sciences"=>4, "Neuroscience"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Psychology"=>4, "Social Sciences"=>12, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>33}, "Neuroscience"=>{"Neuroscience"=>1}, "Social Sciences"=>{"Social Sciences"=>12}, "Psychology"=>{"Psychology"=>4}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"United States"=>3, "Japan"=>1, "Brazil"=>2, "Mexico"=>3, "Malaysia"=>1, "Chile"=>1, "Kenya"=>1, "Nigeria"=>1, "Spain"=>1}, "group_count"=>0}

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• http://doi.org/10.1016/j.vhri.2014.02.002
• http://doi.org/10.1038/srep39820
• http://doi.org/10.1093/ije/dyw056
• http://doi.org/10.3928/00989134-20130604-01
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• http://doi.org/10.1590/S1980-57642014DN84000002
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• http://doi.org/10.1186/s12939-016-0341-9
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• {"files"=>["https://ndownloader.figshare.com/files/674280"], "description"=>"<p>Rate and ratio data are given as percent (95% CI).</p>a<p>Standardized by age group, sex, education, occupational attainment, household assets, and food insecurity, using the whole sample as the standard population.</p>b<p>Standardized for age group and sex to US national rates for 2005.</p>", "links"=>[], "tags"=>["sex-specific", "rates", "aged", "65", "standardized"], "article_id"=>344748, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001179.t003", "stats"=>{"downloads"=>4, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Total_and_sex_specific_mortality_rates_per_1_000_person_years_among_people_aged_65_and_over_and_standardized_mortality_ratio_/344748", "title"=>"Total and sex-specific mortality rates (per 1,000 person-years) among people aged 65 and over and standardized mortality ratio.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-28 01:19:08"}
• {"files"=>["https://ndownloader.figshare.com/files/674140"], "description"=>"<p>DR, Dominican Republic.</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>344617, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001179.g002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mortality_rate_per_1_000_person_years_by_age_group_for_each_site_among_men_/344617", "title"=>"Mortality rate (per 1,000 person-years) by age group for each site among men.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-28 01:16:57"}
• {"files"=>["https://ndownloader.figshare.com/files/674366"], "description"=>"<p>Cohort characteristics.</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>344845, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001179.t001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cohort_characteristics_/344845", "title"=>"Cohort characteristics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-28 01:20:45"}
• {"files"=>["https://ndownloader.figshare.com/files/674417"], "description"=>"<p>Five leading causes of death by site, using cause of death as interpreted probabilistically by the InterVA model.</p>", "links"=>[], "tags"=>["causes", "interpreted", "probabilistically", "interva"], "article_id"=>344885, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001179.t007", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Five_leading_causes_of_death_by_site_using_cause_of_death_as_interpreted_probabilistically_by_the_InterVA_model_/344885", "title"=>"Five leading causes of death by site, using cause of death as interpreted probabilistically by the InterVA model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-28 01:21:25"}
• {"files"=>["https://ndownloader.figshare.com/files/344744", "https://ndownloader.figshare.com/files/344814", "https://ndownloader.figshare.com/files/344875", "https://ndownloader.figshare.com/files/344924"], "description"=>"<div><h3>Background</h3><p>Even in low and middle income countries most deaths occur in older adults. In Europe, the effects of better education and home ownership upon mortality seem to persist into old age, but these effects may not generalise to LMICs. Reliable data on causes and determinants of mortality are lacking.</p> <h3>Methods and Findings</h3><p>The vital status of 12,373 people aged 65 y and over was determined 3–5 y after baseline survey in sites in Latin America, India, and China. We report crude and standardised mortality rates, standardized mortality ratios comparing mortality experience with that in the United States, and estimated associations with socioeconomic factors using Cox's proportional hazards regression. Cause-specific mortality fractions were estimated using the InterVA algorithm. Crude mortality rates varied from 27.3 to 70.0 per 1,000 person-years, a 3-fold variation persisting after standardisation for demographic and economic factors. Compared with the US, mortality was much higher in urban India and rural China, much lower in Peru, Venezuela, and urban Mexico, and similar in other sites. Mortality rates were higher among men, and increased with age. Adjusting for these effects, it was found that education, occupational attainment, assets, and pension receipt were all inversely associated with mortality, and food insecurity positively associated. Mutually adjusted, only education remained protective (pooled hazard ratio 0.93, 95% CI 0.89–0.98). Most deaths occurred at home, but, except in India, most individuals received medical attention during their final illness. Chronic diseases were the main causes of death, together with tuberculosis and liver disease, with stroke the leading cause in nearly all sites.</p> <h3>Conclusions</h3><p>Education seems to have an important latent effect on mortality into late life. However, compositional differences in socioeconomic position do not explain differences in mortality between sites. Social protection for older people, and the effectiveness of health systems in preventing and treating chronic disease, may be as important as economic and human development.</p> <h3></h3><p> <em>Please see later in the article for the Editors' Summary</em></p> </div>", "links"=>[], "tags"=>["socioeconomic", "factors", "cause-specific", "older", "latin", "population-based", "cohort"], "article_id"=>128142, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001179.s001", "https://dx.doi.org/10.1371/journal.pmed.1001179.s002", "https://dx.doi.org/10.1371/journal.pmed.1001179.s003", "https://dx.doi.org/10.1371/journal.pmed.1001179.s004"], "stats"=>{"downloads"=>10, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Socioeconomic_Factors_and_All_Cause_and_Cause_Specific_Mortality_among_Older_People_in_Latin_America_India_and_China_A_Population_Based_Cohort_Study/128142", "title"=>"Socioeconomic Factors and All Cause and Cause-Specific Mortality among Older People in Latin America, India, and China: A Population-Based Cohort Study", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-02-28 02:15:42"}
• {"files"=>["https://ndownloader.figshare.com/files/674022"], "description"=>"<p>DR, Dominican Republic.</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>344503, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001179.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mortality_rate_per_1_000_person_years_by_age_group_for_each_site_among_women_/344503", "title"=>"Mortality rate (per 1,000 person-years) by age group for each site among women.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-28 01:15:03"}
• {"files"=>["https://ndownloader.figshare.com/files/674577"], "description"=>"<p>Site-specific values are HR (95% CI).</p><p>df, degrees of freedom.</p>", "links"=>[], "tags"=>["sex-adjusted", "ratios", "associations", "sociodemographic", "factors"], "article_id"=>345043, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001179.t004", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Age_and_sex_adjusted_hazard_ratios_for_the_associations_between_sociodemographic_factors_and_mortality_by_site_/345043", "title"=>"Age- and sex-adjusted hazard ratios for the associations between sociodemographic factors and mortality, by site.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-28 01:24:03"}
• {"files"=>["https://ndownloader.figshare.com/files/674519"], "description"=>"<p>Site-specific values are HR (95% CI).</p><p>df, degrees of freedom.</p>", "links"=>[], "tags"=>["adjusted", "ratios", "associations", "sociodemographic", "factors"], "article_id"=>344991, "categories"=>["Biotechnology"], "users"=>["Cleusa P. Ferri", "Daisy Acosta", "Mariella Guerra", "Yueqin Huang", "Juan J. Llibre-Rodriguez", "Aquiles Salas", "Ana Luisa Sosa", "Joseph D. Williams", "Ciro Gaona", "Zhaorui Liu", "Lisseth Noriega-Fernandez", "A. T. Jotheeswaran", "Martin J. Prince"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001179.t005", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mutually_adjusted_hazard_ratios_for_the_associations_between_sociodemographic_factors_and_mortality_by_site_/344991", "title"=>"Mutually adjusted hazard ratios for the associations between sociodemographic factors and mortality, by site.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-28 01:23:11"}

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Relative Metric

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F1000Prime