Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race-Counties in the United States
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{"title"=>"Eight Americas: Investigating mortality disparities across races, counties, and race-counties in the United States", "type"=>"journal", "authors"=>[{"first_name"=>"Christopher J.L.", "last_name"=>"Murray", "scopus_author_id"=>"55481130700"}, {"first_name"=>"Sandeep C.", "last_name"=>"Kulkarni", "scopus_author_id"=>"36004905600"}, {"first_name"=>"Catherine", "last_name"=>"Michaud", "scopus_author_id"=>"56888864500"}, {"first_name"=>"Niels", "last_name"=>"Tomijima", "scopus_author_id"=>"7801575104"}, {"first_name"=>"Maria T.", "last_name"=>"Bulzacchelli", "scopus_author_id"=>"14119447100"}, {"first_name"=>"Terrell J.", "last_name"=>"Iandiorio", "scopus_author_id"=>"6507310752"}, {"first_name"=>"Majid", "last_name"=>"Ezzati", "scopus_author_id"=>"6701418638"}], "year"=>2006, "source"=>"PLoS Medicine", "identifiers"=>{"issn"=>"15491277", "isbn"=>"1549-1277", "pui"=>"44455262", "sgr"=>"33749020857", "doi"=>"10.1371/journal.pmed.0030260", "scopus"=>"2-s2.0-33749020857", "pmid"=>"16968116"}, "id"=>"b77568f8-076b-3c7c-9438-6b3af4e03213", "abstract"=>"BACKGROUND: The gap between the highest and lowest life expectancies for race-county combinations in the United States is over 35 y. We divided the race-county combinations of the US population into eight distinct groups, referred to as the \"eight Americas,\" to explore the causes of the disparities that can inform specific public health intervention policies and programs. METHODS AND FINDINGS: The eight Americas were defined based on race, location of the county of residence, population density, race-specific county-level per capita income, and cumulative homicide rate. Data sources for population and mortality figures were the Bureau of the Census and the National Center for Health Statistics. We estimated life expectancy, the risk of mortality from specific diseases, health insurance, and health-care utilization for the eight Americas. The life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was 20.7 y in 2001. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 y for males (Asians versus high-risk urban blacks) and 12.8 y for females (Asians versus low-income southern rural blacks). Mortality disparities among the eight Americas were largest for young (15-44 y) and middle-aged (45-59 y) adults, especially for men. The disparities were caused primarily by a number of chronic diseases and injuries with well-established risk factors. Between 1982 and 2001, the ordering of life expectancy among the eight Americas and the absolute difference between the advantaged and disadvantaged groups remained largely unchanged. Self-reported health plan coverage was lowest for western Native Americans and low-income southern rural blacks. Crude self-reported health-care utilization, however, was slightly higher for the more disadvantaged populations. CONCLUSIONS: Disparities in mortality across the eight Americas, each consisting of millions or tens of millions of Americans, are enormous by all international standards. The observed disparities in life expectancy cannot be explained by race, income, or basic health-care access and utilization alone. Because policies aimed at reducing fundamental socioeconomic inequalities are currently practically absent in the US, health disparities will have to be at least partly addressed through public health strategies that reduce risk factors for chronic diseases and injuries.", "link"=>"http://www.mendeley.com/research/eight-americas-investigating-mortality-disparities-across-races-counties-racecounties-united-states", "reader_count"=>314, "reader_count_by_academic_status"=>{"Unspecified"=>8, "Professor > Associate Professor"=>35, "Student > Doctoral Student"=>40, "Researcher"=>53, "Student > Ph. D. Student"=>63, "Student > Postgraduate"=>14, "Student > Master"=>43, "Other"=>19, "Student > Bachelor"=>18, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>17}, "reader_count_by_user_role"=>{"Unspecified"=>8, "Professor > Associate Professor"=>35, "Student > Doctoral Student"=>40, "Researcher"=>53, "Student > Ph. D. Student"=>63, "Student > Postgraduate"=>14, "Student > Master"=>43, "Other"=>19, "Student > Bachelor"=>18, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>17}, "reader_count_by_subject_area"=>{"Unspecified"=>22, "Agricultural and Biological Sciences"=>18, "Philosophy"=>2, "Arts and Humanities"=>1, "Business, Management and Accounting"=>4, "Chemistry"=>2, "Computer Science"=>1, "Decision Sciences"=>1, "Earth and Planetary Sciences"=>2, "Economics, Econometrics and Finance"=>6, "Engineering"=>7, "Environmental Science"=>2, "Nursing and Health Professions"=>16, "Biochemistry, Genetics and Molecular Biology"=>2, "Mathematics"=>2, "Medicine and Dentistry"=>101, "Design"=>1, "Sports and Recreations"=>1, "Psychology"=>18, "Social Sciences"=>104, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>101}, "Social Sciences"=>{"Social Sciences"=>104}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Psychology"=>{"Psychology"=>18}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>22}, "Environmental Science"=>{"Environmental Science"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>7}, "Chemistry"=>{"Chemistry"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>6}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>18}, "Computer Science"=>{"Computer Science"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>16}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Philosophy"=>{"Philosophy"=>2}}, "reader_count_by_country"=>{"Republic of Singapore"=>1, "United States"=>24, "Japan"=>1, "Tanzania"=>1, "United Kingdom"=>5, "Germany"=>1, "India"=>1}, "group_count"=>13}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/956511"], "description"=>"<p>Construction of the Eight Americas from 8,288 Race-County Units</p>", "links"=>[], "tags"=>["americas", "race-county"], "article_id"=>626784, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0030260.g002", "stats"=>{"downloads"=>1, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Construction_of_the_Eight_Americas_from_8_288_Race_County_Units_/626784", "title"=>"Construction of the Eight Americas from 8,288 Race-County Units", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 13:14:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/470762", "https://ndownloader.figshare.com/files/470792", "https://ndownloader.figshare.com/files/470851"], "description"=>"<div><h3>Background</h3><p>The gap between the highest and lowest life expectancies for race-county combinations in the United States is over 35 y. We divided the race-county combinations of the US population into eight distinct groups, referred to as the “eight Americas,” to explore the causes of the disparities that can inform specific public health intervention policies and programs.</p> <h3>Methods and Findings</h3><p>The eight Americas were defined based on race, location of the county of residence, population density, race-specific county-level per capita income, and cumulative homicide rate. Data sources for population and mortality figures were the Bureau of the Census and the National Center for Health Statistics. We estimated life expectancy, the risk of mortality from specific diseases, health insurance, and health-care utilization for the eight Americas. The life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was 20.7 y in 2001. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 y for males (Asians versus high-risk urban blacks) and 12.8 y for females (Asians versus low-income southern rural blacks). Mortality disparities among the eight Americas were largest for young (15–44 y) and middle-aged (45–59 y) adults, especially for men. The disparities were caused primarily by a number of chronic diseases and injuries with well-established risk factors. Between 1982 and 2001, the ordering of life expectancy among the eight Americas and the absolute difference between the advantaged and disadvantaged groups remained largely unchanged. Self-reported health plan coverage was lowest for western Native Americans and low-income southern rural blacks. Crude self-reported health-care utilization, however, was slightly higher for the more disadvantaged populations.</p> <h3>Conclusions</h3><p>Disparities in mortality across the eight Americas, each consisting of millions or tens of millions of Americans, are enormous by all international standards. The observed disparities in life expectancy cannot be explained by race, income, or basic health-care access and utilization alone. Because policies aimed at reducing fundamental socioeconomic inequalities are currently practically absent in the US, health disparities will have to be at least partly addressed through public health strategies that reduce risk factors for chronic diseases and injuries.</p> </div>", "links"=>[], "tags"=>["investigating", "disparities", "race-counties", "united", "states"], "article_id"=>152834, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.0030260.sd001", "https://dx.doi.org/10.1371/journal.pmed.0030260.sg001", "https://dx.doi.org/10.1371/journal.pmed.0030260.sg002"], "stats"=>{"downloads"=>11, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Eight_Americas_Investigating_Mortality_Disparities_across_Races_Counties_and_Race_Counties_in_the_United_States/152834", "title"=>"Eight Americas: Investigating Mortality Disparities across Races, Counties, and Race-Counties in the United States", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2006-09-12 00:47:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/956455"], "description"=>"<div><p>Deaths were averaged for 1997–2001 to reduce sensitivity to small numbers and outliers.</p>\n <p>(A) Life expectancy at birth for black males and females. Only counties with more than five deaths for any 5-y age group (0–85) were mapped, to avoid unstable results.</p>\n <p>(B) Life expectancy at birth for white males and females.</p></div>", "links"=>[], "tags"=>["expectancies"], "article_id"=>626726, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0030260.g001", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_County_Life_Expectancies_by_Race_/626726", "title"=>"County Life Expectancies by Race", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 13:13:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/956724"], "description"=>"<p>Health Plan Coverage and Health Service Utilization in the Eight Americas</p>", "links"=>[], "tags"=>["public health and epidemiology", "non-clinical medicine/health policy"], "article_id"=>626993, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0030260.g006", "stats"=>{"downloads"=>2, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Health_Plan_Coverage_and_Health_Service_Utilization_in_the_Eight_Americas_/626993", "title"=>"Health Plan Coverage and Health Service Utilization in the Eight Americas", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 13:16:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/956680"], "description"=>"<div><p>(A) Probability of death between the ages of 15 and 59 y in the eight Americas from all causes.</p>\n <p>(B) Probability of death between the ages of 15 and 59 y in the eight Americas after deleting deaths from homicide and HIV.</p></div>", "links"=>[], "tags"=>["ages", "15", "59"], "article_id"=>626953, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0030260.g005", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_Death_between_the_Ages_of_15_and_59_y_in_the_Eight_Americas_/626953", "title"=>"Probability of Death between the Ages of 15 and 59 y in the Eight Americas", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 13:16:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/956637"], "description"=>"<div><p>(A) Probability of death by sex, age, and disease for the eight Americas in 2001.</p>\n <p>(B) Probability of death by sex, age, and disease for Americas 1 and 8 compared to Japan, UK, the Russian Federation, and high-mortality countries in sub-Saharan Africa (AFR-high-mortality; made up largely of countries in West Africa and excluding countries with very high mortality due to HIV/AIDS) in 2001.</p>\n <p>Results are not shown for ages 5–14 y because there are few deaths in this age range in the US.</p></div>", "links"=>[], "tags"=>["ranges"], "article_id"=>626914, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0030260.g004", "stats"=>{"downloads"=>2, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_Dying_in_Specific_Age_Ranges_in_the_Eight_Americas_/626914", "title"=>"Probability of Dying in Specific Age Ranges in the Eight Americas", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 13:15:26"}
  • {"files"=>["https://ndownloader.figshare.com/files/956756"], "description"=>"<p>The estimates refer to the Global Burden of Disease epidemiological region that includes Canada, Cuba, and the US [<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0030260#pmed-0030260-b045\" target=\"_blank\">45</a>]; more than 85% of this region's population live in the US and most data sources apply to the US.</p>", "links"=>[], "tags"=>["attributable", "very-low-mortality", "countries"], "article_id"=>627022, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0030260.g007", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Burden_of_Disease_Attributable_to_the_Ten_Leading_Risk_Factors_in_the_very_low_mortality_countries_of_the_Region_of_Americas_/627022", "title"=>"Burden of Disease Attributable to the Ten Leading Risk Factors in the very-low-mortality countries of the Region of Americas", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 13:17:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/956592"], "description"=>"<p>Estimates for Americas 1 and 3 have been adjusted for differential underestimation of population and mortality among Asians (see <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0030260#st2\" target=\"_blank\">Methods</a>).</p>", "links"=>[], "tags"=>["expectancy", "americas"], "article_id"=>626865, "categories"=>["Medicine", "Biotechnology"], "users"=>["Christopher J. L Murray", "Sandeep C Kulkarni", "Catherine Michaud", "Niels Tomijima", "Maria T Bulzacchelli", "Terrell J Iandiorio", "Majid Ezzati"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0030260.g003", "stats"=>{"downloads"=>1, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Life_Expectancy_at_Birth_in_the_Eight_Americas_1982_8211_2001_/626865", "title"=>"Life Expectancy at Birth in the Eight Americas (1982–2001)", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 13:14:55"}

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  • {"unique-ip"=>"30", "full-text"=>"41", "pdf"=>"9", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"14", "supp-data"=>"3", "cited-by"=>"1", "year"=>"2021", "month"=>"1"}

Relative Metric

{"start_date"=>"2006-01-01T00:00:00Z", "end_date"=>"2006-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Population biology", "average_usage"=>[315, 1047, 1369, 1752, 1924, 2048, 2139, 2198, 2275, 2326, 2417, 2568, 2651, 2710, 2822, 2894, 2962, 3046, 3108, 3163, 3220, 3252, 3317, 3346, 3408, 3568, 3622, 3635, 3674, 3748, 3804, 3894, 4037, 4157, 4267, 4368, 4450, 4510, 4554, 4594, 4667, 4757, 4822, 4879, 4979, 5020, 5097, 5150, 5179, 5213, 5230, 5251, 5279, 5304, 5345, 5372, 5384, 5412, 5430, 5475, 5531, 5568, 5622, 5668, 5711, 5798, 5870, 5934, 6011, 6083, 6132, 6205, 6287, 6374, 6469, 6549, 6718, 6791, 6841, 6935, 7031, 7062, 7087, 7126, 7226, 7366, 7446, 7602, 7673, 7725, 7784, 7839, 7905, 7969, 8012, 8111, 8172]}, {"subject_area"=>"/Medicine and health sciences/Health care", "average_usage"=>[589, 1111, 1414, 1478, 1651, 1723, 1754, 1794, 1829, 1920, 1995, 2035, 2068, 2152, 2239, 2325, 2434, 2472, 2491, 2518, 2576, 2609, 2731, 2839, 2910, 2929, 2949, 2978, 3119, 3246, 3326, 3391, 3572, 3654, 3746, 3816, 3863, 3959, 4051, 4145, 4243, 4360, 4450, 4513, 4574, 4644, 4703, 4772, 4836, 4878, 4939, 4989, 5038, 5059, 5086, 5113, 5151, 5173, 5202, 5228, 5265, 5290, 5321, 5376, 5439, 5501, 5579, 5631, 5693, 5767, 5867, 5918, 5995, 6073, 6146, 6246, 6359, 6411, 6445, 6488, 6560, 6684, 6751, 6808, 6876, 6920, 6992, 7059, 7112, 7227, 7299, 7357, 7406, 7451, 7534, 7624, 7701, 7812]}, {"subject_area"=>"/People and places/Population groupings", "average_usage"=>[497, 1112, 1352, 1467, 1562, 1632, 1698, 1760, 1821, 1897, 1986, 2058, 2133, 2233, 2308, 2392, 2517, 2578, 2594, 2624, 2709, 2776, 2827, 2860, 2920, 2984, 3040, 3086, 3131, 3216, 3272, 3353, 3499, 3535, 3591, 3660, 3722, 3827, 3898, 3964, 4046, 4075, 4112, 4137, 4168, 4215, 4272, 4331, 4386, 4427, 4466, 4502, 4518, 4549, 4572, 4608, 4650, 4696, 4739, 4784, 4816, 4837, 4893, 4947, 5027, 5106, 5195, 5268, 5344, 5408, 5466, 5514, 5568, 5624, 5673, 5734, 5784, 5837, 5889, 5956, 6017, 6077, 6130, 6171, 6217, 6255, 6301, 6377, 6449, 6498, 6547, 6624, 6691, 6734, 6775, 6805, 6891]}, {"subject_area"=>"/Social sciences", "average_usage"=>[607, 1452, 1698, 1869, 1982, 2084, 2168, 2295, 2408, 2473, 2543, 2674, 2752, 2803, 2862, 2922, 2972, 3031, 3099, 3196, 3325, 3407, 3463, 3544, 3623, 3732, 3853, 3936, 3981, 4036, 4121, 4211, 4295, 4368, 4468, 4558, 4642, 4706, 4784, 4836, 4898, 4994, 5080, 5181, 5248, 5321, 5388, 5467, 5529, 5598, 5642, 5697, 5742, 5813, 5931, 6024, 6060, 6105, 6154, 6208, 6287, 6356, 6444, 6521, 6651, 6727, 6799, 6865, 6920, 7008, 7092, 7171, 7283, 7377, 7457, 7528, 7604, 7688, 7794, 7935, 7996, 8052, 8146, 8237, 8338, 8422, 8508, 8630, 8687, 8748, 8852, 8928, 8992, 9054, 9133, 9222, 9318, 9402]}, {"subject_area"=>"/Social sciences/Sociology", "average_usage"=>[1199, 2001, 2261, 2470, 2661, 2890, 3026, 3153, 3260, 3360, 3463, 3569, 3668, 3753, 3810, 3872, 3981, 4088, 4211, 4329, 4505, 4754, 5121, 5241, 5351, 5446, 5544, 5642, 5729, 5826, 5938, 6229, 6382, 6626, 6782, 7039, 7187, 7300, 7415, 7533, 7598, 7663, 7732, 7786, 7839, 7892, 7985, 8066, 8138, 8198, 8257, 8359, 8482, 8573, 8656, 8745, 8852, 8941, 9029, 9095, 9160, 9236, 9328, 9390, 9456, 9519, 9573, 9676, 9813, 9987, 10106, 10210, 10324, 10368, 10454, 10540, 10626, 10741, 10828, 10915, 11040, 11350, 11512, 11632, 11745, 11794, 11879, 11995, 12203, 12370, 12456, 12530, 12625, 12741, 12863, 12975, 13050, 13156]}]}
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Net::HTTPTooManyRequests

Source
Scopus
Time
2019-08-27 21:06:07 UTC
Target URL
https://api.elsevier.com/content/search/index:SCOPUS?query=DOI(10.1371%2Fjournal.pmed.0030260)
Trace

/app/models/concerns/networkable.rb:21:in `get_result'
/app/models/source.rb:165:in `get_data'
/app/models/retrieval_status.rb:47:in `perform_get_data'
/app/jobs/source_job.rb:52:in `block (2 levels) in perform'
/app/jobs/source_job.rb:51:in `block in perform'
/app/jobs/source_job.rb:35:in `each'
/app/jobs/source_job.rb:35:in `perform'