Rates of sexual partner acquisition from nationally representative surveys: variation between countries and by age, sex, wealth, partner and HIV status

Clara Calvert; Rachel Scott; Melissa Palmer; Albert Dube; Milly Marston; Kaye Wellings; Emma Slaymaker

doi:10.1071/SH23134

RESEARCH ARTICLE (Open Access)

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Rates of sexual partner acquisition from nationally representative surveys: variation between countries and by age, sex, wealth, partner and HIV status

Clara Calvert

^A ^B ^# , Rachel Scott

^A ^# , Melissa Palmer

^A , Albert Dube

^C , Milly Marston

^A , Kaye Wellings

^D and Emma Slaymaker

^A ^*

+ Author Affiliations

- Author Affiliations

^A Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.

^B Usher Institute, University of Edinburgh, Edinburgh, UK.

^C Malawi Epidemiological and Intervention Research Unit, Lilongwe, Malawi.

^D Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.

^* Correspondence to: emma.slaymaker@lshtm.ac.uk

^# These authors contributed equally to this paper

Handling Editor: Martin Holt

Sexual Health 21, SH23134 https://doi.org/10.1071/SH23134

Submitted: 3 August 2023 Accepted: 28 November 2023 Published: 18 December 2023

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC)

Abstract

Background

Knowing levels and determinants of partnership acquisition will help inform interventions that try to reduce transmission of sexually transmitted infections (STIs) including HIV.

Methods

We used population-based, cross-sectional data from 47 Demographic and Health Surveys to calculate rates of partner acquisition among men and women (15–49 years), and identified socio-demographic correlates for partner acquisition. Partner acquisition rates were estimated as the total number of acquisitions divided by the person-time in the period covered by the survey. For each survey and by sex, we estimated age-specific partner acquisition rates and used age-adjusted piecewise exponential survival models to explore whether there was any association between wealth, HIV status and partner status with partner acquisition rates.

Results

Across countries, the median partner acquisition rates were 30/100 person-years for men (interquartile range 21–45) and 13/100 person-years for women (interquartile range 6–18). There were substantial variations in partner acquisition rates by age. Associations between wealth and partner acquisition rates varied across countries. People with a cohabiting partner were less likely to acquire a new one, and this effect was stronger for women than men and varied substantially between countries. Women living with HIV had higher partner acquisition rates than HIV-negative women but this association was less apparent for men. At a population level, partner acquisition rates were correlated with HIV incidence.

Conclusions

Partner acquisition rates are variable and are associated with important correlates of STIs and thus could be used to identify groups at high risk of STIs.

Keywords: Africa, Central America, Eastern Europe, epidemiology, HIV, sexual behaviour, sexual partners, South America, South Asia, STI.

References

1 Rowley J, Vander Hoorn S, Korenromp E, et al. Chlamydia, gonorrhoea, trichomoniasis and syphilis: global prevalence and incidence estimates, 2016. Bull World Health Organ 2019; 97(8): 548-562.
| Crossref | Google Scholar | PubMed |

2 Looker KJ, Magaret AS, Turner KME, et al. Global estimates of prevalent and incident herpes simplex virus type 2 infections in 2012. PLoS ONE 2015; 10(1): e114989.
| Crossref | Google Scholar | PubMed |

3 UNAIDS. Global HIV & AIDS statistics – fact sheet. 2023. Available at https://www.unaids.org/en/resources/fact-sheet [accessed 13 September 2023]

4 UNAIDS. Global AIDS update – seizing the moment – tackling entrenched inequalities to end epidemics. Geneva: UNAIDS; 2020.

5 UNAIDS. Fact sheet – world AIDS day 2020. Geneva: UNAIDS; 2020.

6 Grabowski MK, Serwadda DM, Gray RH, et al. HIV prevention efforts and incidence of HIV in Uganda. N Engl J Med 2017; 377(22): 2154-2166.
| Crossref | Google Scholar | PubMed |

7 WHO. Guidelines for the management of symptomatic sexually transmitted infections. Geneva: World Health Organization; 2021.

8 Howes A, Risher KA, Nguyen VK, et al. Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa. PLOS. Global Public Health 2023; 3(4): e0001731.
| Crossref | Google Scholar | PubMed |

9 Anderson RM, Garnett GP. Mathematical models of the transmission and control of sexually transmitted diseases. Sexually Transmitted Diseases 2000; 27(10): 636-643.
| Crossref | Google Scholar | PubMed |

10 Garnett GP, Anderson RM. Balancing sexual partnerships in an age and activity stratified model of HIV transmission in heterosexual populations. IMA J Math Appl Med Biol 1994; 11(3): 161-192.
| Crossref | Google Scholar |

11 Anderson RM, Gupta S, Ng W. The significance of sexual partner contact networks for the transmission dynamics of HIV. J Acquir Immune Defic Syndr 1990; 3(4): 417-429.
| Google Scholar |

12 Rao DW, Wheatley MM, Goodreau SM, et al. Partnership dynamics in mathematical models and implications for representation of sexually transmitted infections: a review. Ann Epidemiol 2021; 59: 72-80.
| Crossref | Google Scholar | PubMed |

13 Anderson RM, Medley GF, May RM, et al. A preliminary study of the transmission dynamics of the human immunodeficiency virus (HIV), the causative agent of AIDS. IMA J Math Appl Med Biol 1986; 3(4): 229-263.
| Crossref | Google Scholar |

14 Nsubuga RN, White RG, Mayanja BN, et al. Estimation of the HIV basic reproduction number in rural South West Uganda: 1991–2008. PLoS ONE 2014; 9(1): e83778.
| Crossref | Google Scholar |

15 Holmes CB, Kilonzo N, Zhao J, et al. Strengthening measurement and performance of HIV prevention programmes. Lancet HIV 2021; 8(5): e306-e310.
| Crossref | Google Scholar | PubMed |

16 Genberg BL, Kulich M, Kawichai S, et al. HIV risk behaviors in sub-Saharan Africa and Northern Thailand: baseline behavioral data from project accept. J Acquir Immune Defic Syndr 2008; 49(3): 309-319.
| Crossref | Google Scholar | PubMed |

17 Mercer CH, Jones KG, Geary RS, et al. Association of timing of sexual partnerships and perceptions of partners’ concurrency with reporting of sexually transmitted infection diagnosis. JAMA Network Open 2018; 1(8): e185957.
| Crossref | Google Scholar | PubMed |

18 Suchard MS, Martinson N, Malfeld S, et al. Alloimmunity to class 2 human leucocyte antigens may reduce HIV-1 acquisition – a nested case-control study in HIV-1 serodiscordant couples. Front Immunol 2022; 13: 813412.
| Crossref | Google Scholar | PubMed |

19 Wellings K, Collumbien M, Slaymaker E, et al. Sexual behaviour in context: a global perspective. Lancet 2006; 368(9548): 1706-1728.
| Crossref | Google Scholar | PubMed |

20 The DHS Program. Search. 2023. Available at https://dhsprogram.com/search/ [accessed 17 January 2023]

21 The DHS Program. DHS Model Questionnaire – Phase 7 (English, French). 2015. Available at https://dhsprogram.com/publications/publication-dhsq7-dhs-questionnaires-and-manuals.cfm [accessed 17 January 2023]

22 The DHS Program. Wealth index construction. 2019. Available at https://dhsprogram.com/topics/wealth-index/Wealth-Index-Construction.cfm [accessed 17 January 2022]

23 Nyemba DC, Medina-Marino A, Peters RPH, et al. Prevalence, incidence and associated risk factors of STIs during pregnancy in South Africa. Sex Transm Infect 2021; 97(5): 375-381.
| Crossref | Google Scholar | PubMed |

24 Ginindza TG, Stefan CD, Tsoka-Gwegweni JM, et al. Prevalence and risk factors associated with sexually transmitted infections (STIs) among women of reproductive age in Swaziland. Infect Agent Cancer 2017; 12(1): 29.
| Crossref | Google Scholar |

25 Croft TN, Marshall AMJ, Allen CK, et al. Guide to DHS statistics. ICF: Rockville, MD, USA; 2018. Available at https://dhsprogram.com/pubs/pdf/DHSG1/Guide_to_DHS_Statistics_DHS-7_v2.pdf

26 Nnko S, Boerma JT, Urassa M, et al. Secretive females or swaggering males?: an assessment of the quality of sexual partnership reporting in rural Tanzania. Soc Sci Med 2004; 59(2): 299-310.
| Crossref | Google Scholar | PubMed |

27 Marston M, Slaymaker E, Cremin I, et al. Trends in marriage and time spent single in sub-Saharan Africa: a comparative analysis of six population-based cohort studies and nine Demographic and Health Surveys. Sex Transm Infect 2009; 85(Suppl 1): i64-i71.
| Crossref | Google Scholar |

28 Wellings K, Collumbien M, Slaymaker E, et al. Sexual behaviour in context: a global perspective. Lancet 2006; 368(9548): 1706-1728.
| Crossref | Google Scholar |

29 Closson K, Hatcher A, Sikweyiya Y, et al. Gender role conflict and sexual health and relationship practices amongst young men living in urban informal settlements in South Africa. Cult Health Sex 2020; 22(1): 31-47.
| Crossref | Google Scholar | PubMed |

30 Pezzulo C, Hornby GM, Sorichetta A, et al. Sub-national mapping of population pyramids and dependency ratios in Africa and Asia. Sci Data 2017; 4(1): 170089.
| Crossref | Google Scholar |

31 Aicken CRH, Gray M, Clifton S, et al. Improving questions on sexual partnerships: lessons learned from cognitive interviews for Britain’s third National Survey of Sexual Attitudes and Lifestyles (“Natsal-3”). Arch Sex Behav 2013; 42(2): 173-185.
| Crossref | Google Scholar | PubMed |

32 Fenton KA, Johnson AM, McManus S, et al. Measuring sexual behaviour: methodological challenges in survey research. Sex Transm Infect 2001; 77(2): 84-92.
| Crossref | Google Scholar | PubMed |

33 Mitchell KR, Mercer CH, Prah P, et al. Why do men report more opposite-sex sexual partners than women? Analysis of the gender discrepancy in a British National Probability Survey. J Sex Res 2019; 56(1): 1-8.
| Crossref | Google Scholar | PubMed |

34 Jia KM, Eilerts H, Edun O, et al. Risk scores for predicting HIV incidence among adult heterosexual populations in sub-Saharan Africa: a systematic review and meta-analysis. J Int AIDS Soc 2022; 25(1): e25861.
| Crossref | Google Scholar | PubMed |

35 Auvert B, Buvé A, Ferry B, et al. Ecological and individual level analysis of risk factors for HIV infection in four urban populations in sub-Saharan Africa with different levels of HIV infection. AIDS 2001; 15: S15-S30.
| Crossref | Google Scholar | PubMed |