Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-22T18:09:55.278Z Has data issue: false hasContentIssue false

Multilevel influences of women’s empowerment and economic resources on risky sexual behaviour among young women in Zomba district, Malawi

Published online by Cambridge University Press:  20 October 2020

Melissa Ward-Peterson*
Affiliation:
Community-Based Research Institute, Florida International University, Miami, FL, USA
Kristopher Fennie
Affiliation:
Division of Natural Sciences, New College of Florida, Sarasota, FL, USA
Sarah Baird
Affiliation:
Department of Global Health, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
Stefany Coxe
Affiliation:
Department of Psychology, School of Integrated Science and Humanity, College of Arts, Sciences, and Education, Florida International University, Miami, FL, USA
Mary Jo Trepka
Affiliation:
Department of Epidemiology, Robert Stempel College of Public Health and Social Work, Florida International University, Miami, FL, USA
Purnima Madhivanan
Affiliation:
Health Promotion Sciences Department, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA Public Health Research Institute of India, Mysore, India
*
*Corresponding author. Email: [email protected]

Abstract

Gender disparities are pronounced in Zomba district, Malawi. Among women aged 15–49 years, HIV prevalence is 16.8%, compared with 9.3% among men of the same age. Complex structural factors are associated with risky sexual behaviour leading to HIV infection. This study’s objective was to explore associations between multilevel measures of economic resources and women’s empowerment with risky sexual behaviour among young women in Zomba. Four measures of risky sexual behaviour were examined: ever had sex, condom use and two indices measuring age during sexual activity and partner history. Multilevel regression models and regression models with cluster-robust standard errors were used to estimate associations, stratified by school enrolment status. Among the schoolgirl stratum, the percentage of girls enrolled in school at the community level had protective associations with ever having sex (OR = 0.76; 95% CI: 0.60, 0.96) and condom use (OR = 1.06; 95% CI: 1.01, 1.11). Belief in the right to refuse sex was protective against ever having sex (OR = 0.76; 95% CI: 0.60, 0.96). Participants from households with no secondary school education had higher odds of ever having sex (OR = 1.59; 95% CI: 1.14, 2.22). Among the dropout stratum, participants who had not achieved a secondary school level of education had riskier Age Factor and Partner History Factor scores (β = 0.51; 95% CI: 0.23, 0.79, and β = 0.24; 95% CI: 0.07, 0.41, respectively). Participants from households without a secondary school level of education had riskier Age Factor scores (β = 0.26; 95% CI: 0.03, 0.48). Across strata, the most consistent variables associated with risky sexual behaviour were those related to education, including girl’s level of education, highest level of education of her household of origin and the community percentage of girls enrolled in school. These results suggest that programmes seeking to reduce risky sexual behaviour among young women in Malawi should consider the role of improving access to education at multiple levels.

Type
Research Article
Copyright
© The Author(s) 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andersson, N, Paredes-Solís, S, Milne, D, Omer, K, Marokoane, N, Laetsang, D and Cockcroft, A (2012) Prevalence and risk factors for forced or coerced sex among school-going youth: national cross-sectional studies in 10 southern African countries in 2003 and 2007. BMJ Open 2(2), e000754.CrossRefGoogle ScholarPubMed
Baird, SJ, Garfein, RS, McIntosh, CT and Ozler, B (2012) Effect of a cash transfer programme for schooling on prevalence of HIV and herpes simplex type 2 in Malawi: a cluster randomised trial. The Lancet 379(9823), 13201329.CrossRefGoogle ScholarPubMed
Barnett, T and Whiteside, A (2002) AIDS in the Twenty-First Century: Disease and Globalization. Palgrave Macmillan, Basingstoke.CrossRefGoogle Scholar
Chersich, MF and Rees, HV (2008) Vulnerability of women in southern Africa to infection with HIV: biological determinants and priority health sector interventions. AIDS 22 (Supplement 4), S27S40.CrossRefGoogle ScholarPubMed
DiStefano, C, Zhu, M and Mîndrilă, D (2009) Understanding and using factor scores: considerations for the applied researcher. Practical Assessment, Research & Evaluation 14(20).Google Scholar
Gilbert, L and Walker, L (2002) Treading the path of least resistance: HIV/AIDS and social inequalities a South African case study. Social Science & Medicine 54(7), 10931110.CrossRefGoogle ScholarPubMed
Gillespie, S, Kadiyala, S and Greener, R (2007) Is poverty or wealth driving HIV transmission? AIDS 21 (Supplement 7), S5S16.CrossRefGoogle ScholarPubMed
Grice, JW (2001) Computing and evaluating factor scores. Psychological Methods 6(4), 430450.CrossRefGoogle ScholarPubMed
Gupta, GR (2002) How men’s power over women fuels the HIV epidemic. BMJ 324(7331), 183184.CrossRefGoogle ScholarPubMed
Hindin, M (2000) Women’s autonomy, women’s status and fertility-related behavior in Zimbabwe. Population Research and Policy Review 19, 255282.CrossRefGoogle Scholar
Hogan, DP, Berhanu, B and Hailemariam, A (1999) Household organization, women’s autonomy, and contraceptive behavior in southern Ethiopia. Studies in Family Planning 30(4), 302314.CrossRefGoogle ScholarPubMed
Hung, KJ, Scott, J, Ricciotti, HA, Johnson, TR and Tsai, AC (2012) Community-level and individual-level influences of intimate partner violence on birth spacing in sub-Saharan Africa. Obstetrics and Gynecology 119(5), 975982.CrossRefGoogle ScholarPubMed
Kamndaya, M, Kazembe, LN, Vearey, J, Kabiru, CW and Thomas, L (2015) Material deprivation and unemployment affect coercive sex among young people in the urban slums of Blantyre, Malawi: a multi-level approach. Health & Place 33, 90100.CrossRefGoogle ScholarPubMed
Krishnan, S, Dunbar, MS, Minnis, AM, Medlin, CA, Gerdts, CE and Padian, NS (2008) Poverty, gender inequities, and women’s risk of human immunodeficiency virus/AIDS. Annals of the New York Academy of Science of the USA 1136, 101110.CrossRefGoogle ScholarPubMed
Larsen, K and Merlo, J (2005) Appropriate assessment of neighborhood effects on individual health: integrating random and fixed effects in multilevel logistic regression. American Journal of Epidemiology 161(1), 8188.CrossRefGoogle ScholarPubMed
McNeish, D, Stapleton, LM and Silverman, RD (2017) On the unnecessary ubiquity of hierarchical linear modeling. Psychological Methods 22(1), 114140.CrossRefGoogle ScholarPubMed
Magadi, MA and Uchudi, J (2015) Onset of sexual activity among adolescents in HIV/AIDS-affected households in sub-Saharan Africa. Journal of Biosocial Science 47(2), 238257.CrossRefGoogle ScholarPubMed
Merlo, J, Chaix, B, Yang, M, Lynch, J and Råstam, L (2005a) A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon. Journal of Epidemiology and Community Health 59(6), 443449.CrossRefGoogle ScholarPubMed
Merlo, J, Chaix, B, Yang, M, Lynch, J and Råstam, L (2005b) A brief conceptual tutorial on multilevel analysis in social epidemiology: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health. Journal of Epidemiology and Community Health 59(12), 10221028.CrossRefGoogle ScholarPubMed
Merlo, J, Chaix, B, Ohlsson, H, Beckman, A, Johnell, K, Hjerpe, P et al. (2006) A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena. Journal of Epidemiology and Community Health 60(4), 290297.CrossRefGoogle ScholarPubMed
Merlo, J, Yang, M, Chaix, B, Lynch, J and Råstam, L (2005c) A brief conceptual tutorial on multilevel analysis in social epidemiology: Investigating contextual phenomena in different groups of people. Journal of Epidemiology and Community Health 59(9), 729736.CrossRefGoogle ScholarPubMed
Nagoli, J, Holvoet, K and Remme, M (2010) HIV and AIDS vulnerability in fishing communities in Mangochi district, Malawi. African Journal of AIDS Research 9(1), 7180.CrossRefGoogle ScholarPubMed
NSO (2012) Integrated Household Survey 2010–2011. Household Socio-Economic Characteristics Report. National Statistical Office [Malawi], Zomba.Google Scholar
NSO and ICF (2017) Malawi Demographic and Health Survey 2015–16. NSO and ICF, Zomba and Rockville.Google Scholar
NSO and ICF Macro (2011) Malawi Demographic and Health Survey 2010. NSO and ICF Macro, Zomba and Calverton, MD.Google Scholar
NSO and ORC Macro (2005) Malawi Demographic and Health Survey 2004. NSO and ORC Macro, Zomba and Calverton, MD.Google Scholar
Pettifor, A, Measham, D, Rees, H and Padian, N (2004) Sexual power and HIV risk, South Africa. Emerging Infectious Diseases 10(11), 19962004.CrossRefGoogle Scholar
Qiao, S, Li, X and Stanton, B (2014) Social support and HIV-related risk behaviours: a systematic review of the global literature. AIDS and Behavior 18(2), 419441.CrossRefGoogle ScholarPubMed
Rahman, M, Mostofa, M and Hoque, M (2014) Women’s household decision-making autonomy and contraceptive behavior among Bangladeshi women. Sexual & Reproductive Healthcare 5(1), 915.CrossRefGoogle ScholarPubMed
Robertson, L, Gregson, S and Garnett, GP (2010) Sexual risk among orphaned adolescents: is country-level HIV prevalence an important factor? AIDS Care 22(8), 927938.CrossRefGoogle ScholarPubMed
Schempf, AH and Kaufman, JS (2012) Accounting for context in studies of health inequalities: a review and comparison of analytic approaches. Annals of Epidemiology 22(10), 683690.CrossRefGoogle ScholarPubMed
Stephenson, R (2010) Community-level gender equity and extramarital sexual risk-taking among married men in eight African countries. International Perspectives on Sexual and Reproductive Health 36(4), 178188.CrossRefGoogle ScholarPubMed
Sullivan, LM, Dukes, KA and Losina, E (1999) Tutorial in biostatistics: an introduction to hierarchical linear modelling. Statistics in Medicine 18(7), 855888.3.0.CO;2-7>CrossRefGoogle ScholarPubMed
Sweat, MD and Denison, JA (1995) Reducing HIV incidence in developing countries with structural and environmental interventions. AIDS 9 (Supplement A), S251S257.Google ScholarPubMed
Uchudi, J, Magadi, M and Mostazir, M (2012) A multilevel analysis of the determinants of high-risk sexual behaviour in sub-Saharan Africa. Journal of Biosocial Science 44(3), 289311.CrossRefGoogle ScholarPubMed
Uthman, OA, Lawoko, S and Moradi, T (2010) The role of individual, community and societal gender inequality in forming women’s attitudes toward intimate-partner violence against women: a multilevel analysis. World Health & Population 12(2), 517.CrossRefGoogle ScholarPubMed
Uthman, OA, Moradi, T and Lawoko, S (2009) The independent contribution of individual-, neighbourhood-, and country-level socioeconomic position on attitudes towards intimate partner violence against women in sub-Saharan Africa: a multilevel model of direct and moderating effects. Social Science & Medicine 68(10), 18011809.CrossRefGoogle ScholarPubMed
Ward-Peterson, M, Fennie, K, Baird, S, Coxe, S, Trepka, M and Madhivanan, P (2018) Association between HIV awareness factors, health facility characteristics and risky sexual behaviour among young women in Zomba district, Malawi. Journal of Biosocial Science 50(6), 853867.CrossRefGoogle ScholarPubMed
World Bank (n.d., a) Poverty. URL: https://data.worldbank.org/topic/poverty (accessed 1st July 2017).Google Scholar
World Bank (n.d., b) GDP Per Capita (Current US$). URL: http://data.worldbank.org/indicator/NY.GDP.PCAP.CD (accessed 1st July 2017).Google Scholar
Zierler, S and Krieger, N (1997) Reframing women’s risk: social inequalities and HIV infection. Annual Review of Public Health 18, 401436.CrossRefGoogle ScholarPubMed
Zomba District Assembly (2009) Zomba District Socio-Economic Profile 2009–2012. Zomba District Assembly, Zomba.Google Scholar
Zomba District Council (2017) Zomba District Socio-Economic Profile 2017–2022. Zomba District Assembly, Zomba.Google Scholar
Zuilkowski, SS and Jukes, MC (2012) The impact of education on sexual behaviour in sub-Saharan Africa: a review of the evidence. AIDS Care 24(5), 562576.CrossRefGoogle Scholar