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RESEARCH ARTICLE

Income inequality and Neisseria gonorrhoeae notifications in females: a country-level analysis

Amie L. Bingham A C , Anne M. Kavanagh A , Christopher Kit Fairley B , Louise A. Keogh A , Rebecca J. Bentley A and Jane S. Hocking A
+ Author Affiliations
- Author Affiliations

A Melbourne School of Population & Global Health Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, Vic. 3010, Australia.

B Melbourne Sexual Health Centre, 580 Swanston Street, Carlton, Vic. 3053, Australia.

C Corresponding author. Email: binghama@unimelb.edu.au

Sexual Health 11(6) 556-560 https://doi.org/10.1071/SH13188
Submitted: 8 February 2014  Accepted: 4 September 2014   Published: 1 December 2014

Abstract

Background: Patterns of population susceptibility to sexually transmissible infections may be influenced by various social determinants of health, however these receive relatively little attention. Income inequality is one such determinant that has been linked to a number of poor health outcomes. The objective of this analysis was to determine whether there is an association between income inequality and Neisseria gonorrhoeae notification rates when measured at the country level. Methods: Gini coefficients, gonorrhoea notification rates among women, per capita gross domestic product and approximate size of female population were obtained for 11 countries of the OECD. Linear regression was used to measure the association between income inequality and gonorrhoea notification rates, using generalised estimation equations (GEE) to control for the non-independence of repeat measures from particular countries. Results: A total of 36 observations from 11 countries were included. Gini coefficients ranged from 0.21 to 0.38 and gonorrhoea notifications from 0.7 to 153 per 100 000 females. Significant associations were found between country-level income inequality and gonorrhoea notification rates among women (b = 17.79 (95% CI: 10.64, 24.94, P < 0.01). Conclusions: Significant associations were found, highlighting the importance of acknowledging and accounting for social determinants of sexual health and suggesting that further research in this arena may be fruitful.

Additional keywords: gini coefficient, social determinants.


References

[1]  Dean HD, Fenton KA. Addressing social determinants of health in the prevention and control of HIV/AIDS, viral hepatitis, sexually transmitted infections, and tuberculosis. Public Health Rep 2010; 125 1–5.
| 20629250PubMed |

[2]  Bearinger LH, Sieving RE, Ferguson J, Sharma V. Global perspectives on the sexual and reproductive health of adolescents: patterns, prevention, and potential. Lancet 2007; 369 1220–31.
Global perspectives on the sexual and reproductive health of adolescents: patterns, prevention, and potential.Crossref | GoogleScholarGoogle Scholar | 17416266PubMed |

[3]  European Centre for Disease Prevention and Control (ECDC). Sexually transmitted infections in Europe, 1990–2010. Stockholm: ECDC; 2012.

[4]  Aral SO. Determinants of STD epidemics: implications for phase appropriate intervention strategies. Sex Transm Infect 2002; 78 i3–13.
Determinants of STD epidemics: implications for phase appropriate intervention strategies.Crossref | GoogleScholarGoogle Scholar | 12083444PubMed |

[5]  Harling G, Subramanian SV, Ãrnighausen T, Kawachi I. Income inequality and sexually transmitted in the United States: who bears the burden? Soc Sci Med 2014; 102 174–82.
Income inequality and sexually transmitted in the United States: who bears the burden?Crossref | GoogleScholarGoogle Scholar | 24565155PubMed |

[6]  Biello KB, Pettigrew MM, Niccolai LM. Multiple chlamydia infection among young women: comparing the role of individual- and neighbourhood-level measures of socioeconomic status. Sex Transm Infect 2011; 87 560–2.
Multiple chlamydia infection among young women: comparing the role of individual- and neighbourhood-level measures of socioeconomic status.Crossref | GoogleScholarGoogle Scholar | 21940727PubMed |

[7]  Sullivan AB, Gesink DC, Brown P, Zhou L, Kaufman JS, Fitch M, et al Are neighborhood sociocultural factors influencing the spatial pattern of gonorrhea in North Carolina? Ann Epidemiol 2011; 21 245–52.
Are neighborhood sociocultural factors influencing the spatial pattern of gonorrhea in North Carolina?Crossref | GoogleScholarGoogle Scholar | 21376271PubMed |

[8]  Layte R. The association between income inequality and mental health: testing status anxiety, social capital, and neo-materialist explanations. Eur Sociol Rev 2012; 28 498–511.
The association between income inequality and mental health: testing status anxiety, social capital, and neo-materialist explanations.Crossref | GoogleScholarGoogle Scholar |

[9]  Wilkinson R, Pickett K. Income inequality and population health: a review and explanation of the evidence. Soc Sci Med 2006; 62 1768–84.
Income inequality and population health: a review and explanation of the evidence.Crossref | GoogleScholarGoogle Scholar | 16226363PubMed |

[10]  Pabayo R, Kawachi I, Gilman SE. Income inequality among American states and the incidence of major depression. J Epidemiol Community Health 2014; 68 110–5.
Income inequality among American states and the incidence of major depression.Crossref | GoogleScholarGoogle Scholar | 24064745PubMed |

[11]  Pickett KE, Wilkinson RG. Inequality: an under acknowledged source of mental illness and distress. Br J Psychiatry 2010; 197 426–8.
Inequality: an under acknowledged source of mental illness and distress.Crossref | GoogleScholarGoogle Scholar | 21119145PubMed |

[12]  Holtgrave DR, Crosby RA. Social capital, poverty, and income inequality as predictors of gonorrhoea, syphilis, chlamydia and AIDS case rates in the United States. Sex Transm Infect 2003; 79 62–4.
Social capital, poverty, and income inequality as predictors of gonorrhoea, syphilis, chlamydia and AIDS case rates in the United States.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3s%2Fms12gsQ%3D%3D&md5=6e66522e0c6c59f87bab454286e96cefCAS | 12576618PubMed |

[13]  Krieger N, Waterman PD, Chen JT, Soobader M-J, Subramanian SV. Monitoring socioeconomic inequalities in sexually transmitted infections, tuberculosis, and violence: geocoding and choice of area-based socioeconomic measures: the Public Health Disparities Geocoding Project (US). Public Health Rep 2003; 118 240–60.
| 12766219PubMed |

[14]  Drain PK, Smith JS, Hughes JP, Halperin DT, Holmes KK. Correlates of national HIV seroprevalence: an ecologic analysis of 122 developing countries. J Acquir Immune Defic Syndr 2004; 35 407–20.
Correlates of national HIV seroprevalence: an ecologic analysis of 122 developing countries.Crossref | GoogleScholarGoogle Scholar | 15097158PubMed |

[15]  Crosby RA, Holtgrave DR, DiClemente RJ, Wingood GM, Gayle JA. Social capital as a predictor of adolescents’ sexual risk behavior: a state-level exploratory study. AIDS Behav 2003; 7 245–52.
Social capital as a predictor of adolescents’ sexual risk behavior: a state-level exploratory study.Crossref | GoogleScholarGoogle Scholar | 14586187PubMed |

[16]  Chen Z, Gotway Crawford CA. The role of geographic scale in testing the income inequality hypothesis as an explanation of health disparities. Soc Sci Med 2012; 75 1022–31.
The role of geographic scale in testing the income inequality hypothesis as an explanation of health disparities.Crossref | GoogleScholarGoogle Scholar | 22694992PubMed |

[17]  Kondo N, van Dam RM, Sembajwe G, Subramanian SV, Kawachi I, Yamagata Z. Income inequality and health: the role of population size, inequality threshold, period effects and lag effects. J Epidemiol Community Health 2012; 66 e11
Income inequality and health: the role of population size, inequality threshold, period effects and lag effects.Crossref | GoogleScholarGoogle Scholar | 22012964PubMed |

[18]  Department of Health and Ageing, National Notifiable Diseases Surveillance System. Notifications of Gonococcal infection, Australia, by age group, sex and year. Online Database: Department of Health and Ageing, Commonwealth of Australia; 2012. Accessed online at: http://www9.health.gov.au/cda/Sourc/Rpt_5_sel.cfm [verified 12 February 2012].

[19]  Hepatitis C and STI Surveillance and Epidemiology Section. Community Acquired Infections Division, Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada; Reported cases and rates of gonorrhoea by age group and sex, 1980 to 2009. Public Health Agency of Canada, On-line Database; 2010. Accessed online at: http://www.phac-aspc.gc.ca/std-mts/sti-its_tab/gonorrhea_pts-eng.php [verified 3 November 2011].

[20]  US Department of Health and Human Services Centers for Disease Control and Prevention. National Center for HIV, STD and TB Prevention (NCHSTP), Division of STD/HIV Prevention, Sexually Transmitted Diseases Morbidity for selected STDs by age, race/ethnicity and gender 1996–2009, CDC WONDER On-line Database; June 2011. Accessed online at: http://wonder.cdc.gov/std-std-race-age.html [verified 03 November 2011].

[21]  Subramanian SV, Kawachi I. Income inequality and health: what have we learned so far? Epidemiol Rev 2004; 26 78–91.
Income inequality and health: what have we learned so far?Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2czjt1Cruw%3D%3D&md5=da1dc653eb1f33c887a603bacc135b29CAS | 15234949PubMed |

[22]  Organisation for Economic Co-operation & Development. OECD StatExtracts. Accessed online at: http://stats.oecd.org/ [verified 03 November 2011].

[23]  Central Intelligence Agency. The World Factbook. Washington, DC: Central Intelligence Agency; 2002.

[24]  De Maio F. Advancing the income inequality – health hypothesis. Crit Public Health 2012; 22 39–46.
Advancing the income inequality – health hypothesis.Crossref | GoogleScholarGoogle Scholar |

[25]  Chen Z, Gotway Crawford CA. The role of geographic scale in testing the income inequality hypothesis as an explanation of health disparities. Soc Sci Med 2012; 75 1022–31.
The role of geographic scale in testing the income inequality hypothesis as an explanation of health disparities.Crossref | GoogleScholarGoogle Scholar | 22694992PubMed |

[26]  Huedo-Medina TB, Boynton MH, Warren MR, Lacroix JM, Carey MP, Johnson BT. Efficacy of HIV prevention interventions in Latin American and Caribbean nations, 1995–2008: a meta-analysis. AIDS Behav 2010; 14 1237–51.
Efficacy of HIV prevention interventions in Latin American and Caribbean nations, 1995–2008: a meta-analysis.Crossref | GoogleScholarGoogle Scholar | 20661768PubMed |

[27]  Cohen D, Spear S, Scribner R, Kissinger P, Mason K, Wildgen J. “Broken windows” and the risk of gonorrhea. Am J Public Health 2000; 90 230–6.
“Broken windows” and the risk of gonorrhea.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3c7jtFygtA%3D%3D&md5=f80251111f5df40eb8c1d766ddb7805bCAS | 10667184PubMed |

[28]  Siddiqi A, Kawachi I, Berkman L, Hertzman C, Subramanian SV. Education determines a nation’s health, but what determines educational outcomes? A cross-national comparative analysis. J Public Health Policy 2012; 33 1–15.
Education determines a nation’s health, but what determines educational outcomes? A cross-national comparative analysis.Crossref | GoogleScholarGoogle Scholar | 22048059PubMed |

[29]  Ram R. Further examination of the cross-country association between income inequality and population health. Soc Sci Med 2006; 62 779–91.
Further examination of the cross-country association between income inequality and population health.Crossref | GoogleScholarGoogle Scholar | 16051408PubMed |

[30]  Babones SJ. Income inequality and population health: correlation and causality. Soc Sci Med 2008; 66 1614–26.
Income inequality and population health: correlation and causality.Crossref | GoogleScholarGoogle Scholar | 18222588PubMed |

[31]  Woolf SH, Braveman P. Where health disparities begin: the role of social and economic determinants–and why current policies may make matters worse. Health Aff 2011; 30 1852–9.
Where health disparities begin: the role of social and economic determinants–and why current policies may make matters worse.Crossref | GoogleScholarGoogle Scholar |