Literature DB >> 31083722

Association of Household Income With Life Expectancy and Cause-Specific Mortality in Norway, 2005-2015.

Jonas Minet Kinge1,2, Jørgen Heibø Modalsli3, Simon Øverland1,4, Håkon Kristian Gjessing1,4, Mette Christophersen Tollånes5, Ann Kristin Knudsen1,4, Vegard Skirbekk1,6, Bjørn Heine Strand1,2,7,8, Siri Eldevik Håberg1, Stein Emil Vollset4,9.   

Abstract

Importance: Examining causes of death and making comparisons across countries may increase understanding of the income-related differences in life expectancy.
Objectives: To describe income-related differences in life expectancy and causes of death in Norway and to compare those differences with US estimates. Design and Setting: A registry-based study including all Norwegian residents aged at least 40 years from 2005 to 2015. Exposures: Household income adjusted for household size. Main Outcomes and Measures: Life expectancy at 40 years of age and cause-specific mortality.
Results: In total, 3 041 828 persons contributed 25 805 277 person-years and 441 768 deaths during the study period (mean [SD] age, 59.3 years [13.6]; mean [SD] number of household members per person, 2.5 [1.3]). Life expectancy was highest for women with income in the top 1% (86.4 years [95% CI, 85.7-87.1]) which was 8.4 years (95% CI, 7.2-9.6) longer than women with income in the lowest 1%. Men with the lowest 1% income had the lowest life expectancy (70.6 years [95% CI, 69.6-71.6]), which was 13.8 years (95% CI, 12.3-15.2) less than men with the top 1% income. From 2005 to 2015, the differences in life expectancy by income increased, largely attributable to deaths from cardiovascular disease, cancers, chronic obstructive pulmonary disease, and dementia in older age groups and substance use deaths and suicides in younger age groups. Over the same period, life expectancy for women in the highest income quartile increased 3.2 years (95% CI, 2.7-3.7), while life expectancy for women in the lowest income quartile decreased 0.4 years (95% CI, -1.0 to 0.2). For men, life expectancy increased 3.1 years (95% CI, 2.5-3.7) in the highest income quartile and 0.9 years (95% CI, 0.2-1.6) in the lowest income quartile. Differences in life expectancy by income levels in Norway were similar to differences observed in the United States, except that life expectancy was higher in Norway in the lower to middle part of the income distribution in both men and women. Conclusions and Relevance: In Norway, there were substantial and increasing gaps in life expectancy by income level from 2005 to 2015. The largest differences in life expectancy between Norway and United States were for individuals in the lower to middle part of the income distribution.

Entities:  

Mesh:

Year:  2019        PMID: 31083722      PMCID: PMC6515574          DOI: 10.1001/jama.2019.4329

Source DB:  PubMed          Journal:  JAMA        ISSN: 0098-7484            Impact factor:   56.272


  19 in total

1.  Four indicators of socioeconomic position: relative ranking across causes of death.

Authors:  Oyvind Naess; Bjørgulf Claussen; Dag S Thelle; George Davey Smith
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2.  Socioeconomic inequalities in health in 22 European countries.

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Journal:  N Engl J Med       Date:  2008-06-05       Impact factor: 91.245

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4.  Role of income mobility for the measurement of inequality in life expectancy.

Authors:  Claus Thustrup Kreiner; Torben Heien Nielsen; Benjamin Ly Serena
Journal:  Proc Natl Acad Sci U S A       Date:  2018-10-29       Impact factor: 11.205

5.  Mortality inequality in populations with equal life expectancy: Arriaga's decomposition method in SAS, Stata, and Excel.

Authors:  Nathalie Auger; Pascaline Feuillet; Sylvie Martel; Ernest Lo; Amadou D Barry; Sam Harper
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6.  Addressing Social Determinants of Health and Health Inequalities.

Authors:  Nancy E Adler; M Maria Glymour; Jonathan Fielding
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7.  Trends and disparities in socioeconomic and behavioural characteristics, life expectancy, and cause-specific mortality of native-born and foreign-born populations in the United States, 1979-2003.

Authors:  Gopal K Singh; Robert A Hiatt
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8.  [Tobacco consumption among men and women 1927-2007].

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Journal:  Tidsskr Nor Laegeforen       Date:  2009-09-24

9.  Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

Authors: 
Journal:  Lancet       Date:  2018-11-08       Impact factor: 79.321

10.  Low migrant mortality in Germany for men aged 65 and older: fact or artifact?

Authors:  Eva Kibele; Rembrandt Scholz; Vladimir M Shkolnikov
Journal:  Eur J Epidemiol       Date:  2008-04-17       Impact factor: 8.082

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  29 in total

1.  Life Expectancy and Mortality Rates in the United States, 1959-2017.

Authors:  Steven H Woolf; Heidi Schoomaker
Journal:  JAMA       Date:  2019-11-26       Impact factor: 56.272

2.  Comparison of Health Outcomes Among High- and Low-Income Adults Aged 55 to 64 Years in the US vs England.

Authors:  HwaJung Choi; Andrew Steptoe; Michele Heisler; Philippa Clarke; Robert F Schoeni; Stephen Jivraj; Tsai-Chin Cho; Kenneth M Langa
Journal:  JAMA Intern Med       Date:  2020-07-13       Impact factor: 21.873

3.  Changes in life expectancy and disease burden in Norway, 1990-2019: an analysis of the Global Burden of Disease Study 2019.

Authors:  Benjamin Clarsen; Magne Nylenna; Søren Toksvig Klitkou; Stein Emil Vollset; Carl Michael Baravelli; Anette Kocbach Bølling; Gunn Marit Aasvang; Gerhard Sulo; Mohsen Naghavi; Maja Pasovic; Muhammad Asaduzzaman; Tone Bjørge; Anne Elise Eggen; Terje Andreas Eikemo; Christian Lycke Ellingsen; Øystein Ariansen Haaland; Alemayehu Hailu; Shoaib Hassan; Simon I Hay; Petur B Juliusson; Adnan Kisa; Sezer Kisa; Johan Månsson; Teferi Mekonnen; Christopher J L Murray; Ole F Norheim; Trygve Ottersen; Dominic Sagoe; Kam Sripada; Andrea Sylvia Winkler; Ann Kristin Skrindo Knudsen
Journal:  Lancet Public Health       Date:  2022-07

4.  Estimating risk factor attributable burden - challenges and potential solutions when using the comparative risk assessment methodology.

Authors:  Dietrich Plass; Henk Hilderink; Heli Lehtomäki; Simon Øverland; Terje A Eikemo; Taavi Lai; Vanessa Gorasso; Brecht Devleesschauwer
Journal:  Arch Public Health       Date:  2022-05-27

5.  Estimation of Potential Deaths Averted From Hypothetical US Income Support Policies.

Authors:  Anton L V Avanceña; Nicholas Miller; Ellen Kim DeLuca; Bradley Iott; Amanda Mauri; Daniel Eisenberg; David W Hutton
Journal:  JAMA Health Forum       Date:  2022-06-10

6.  Differential Trends in Disability Among Rich and Poor Adults in the United States and England From 2002 to 2016.

Authors:  HwaJung Choi; Robert F Schoeni; Andrew Steptoe; Tsai-Chin Cho; Kenneth M Langa
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2022-05-27       Impact factor: 4.942

7.  Mortality versus Municipal and State Government Spending in American Cities.

Authors:  Todd MacKenzie; Rebecca Lebeaux
Journal:  J Urban Health       Date:  2021-03-24       Impact factor: 5.801

8.  Comparison of Health Outcomes Among High- and Low-Income Adults Aged 55 to 64 Years in the US vs England.

Authors:  HwaJung Choi; Andrew Steptoe; Michele Heisler; Philippa Clarke; Robert F Schoeni; Stephen Jivraj; Tsai-Chin Cho; Kenneth M Langa
Journal:  JAMA Intern Med       Date:  2020-09-01       Impact factor: 21.873

9.  Changes in life expectancy and lifespan variability by income quartiles in four Nordic countries: a study based on nationwide register data.

Authors:  Henrik Brønnum-Hansen; Olof Östergren; Lasse Tarkiainen; Åsmund Hermansen; Pekka Martikainen; Kjetil A van der Wel; Olle Lundberg
Journal:  BMJ Open       Date:  2021-06-29       Impact factor: 2.692

10.  Parental income gradients in adult health: a national cohort study.

Authors:  Miriam Evensen; Søren Toksvig Klitkou; Mette C Tollånes; Simon Øverland; Torkild Hovde Lyngstad; Stein Emil Vollset; Jonas Minet Kinge
Journal:  BMC Med       Date:  2021-07-01       Impact factor: 8.775

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