Partner age differences and associated sexual risk behaviours among adolescent girls and young women in a cash transfer programme for schooling in Malawi

Abstract

Background: Age disparities in sexual relationships have been proposed as a key risk factor for HIV transmission in Sub-Saharan Africa, but evidence remains inconclusive. The SIHR study, a cluster randomised trial of a cash transfer programme in Malawi, found that young women in the intervention groups were less likely to have had a sexual partner aged 25 or older, and less likely to test positive for HIV and HSV-2 at follow-up compared to control groups. We examined the hypotheses that girls in the intervention groups had smaller age differences than control groups and that large age differences were associated with relationship-level HIV transmission risk factors: inconsistent condom use, sex frequency, and relationship duration.

Methods: We conducted an analysis of schoolgirls in the Schooling, Income, and Health Risk (SIHR) study aged 13-22 at baseline (n = 2907). We investigated the effects of study arm, trial stage and participant age on age differences in sexual relationships using a linear mixed-effects model. Cumulative-link mixed-effects models were used to estimate the effect of relationship age difference on condom use and sex frequency, and a Cox proportional hazard model was used to estimate the effect of relationship age difference on relationship duration. We controlled for the girl's age, number of partners, study group and study round.

Results: Girls receiving cash transfers, on average, had smaller age differences in relationships compared to controls, though the estimated difference was not statistically significant (- 0.43 years; 95% CI: -1.03, 0.17). The older the participant was, the smaller her age differences (- 0.67 per 4-year increase in age; 95% CI: -0.99, - 0.35). Among controls, after the cash transfers had ended the average age difference was 0.82 years larger than during the intervention (95% CI: 0.43, 1.21), suggesting a possible indirect effect of the study on behaviour in the community as a whole. Across treatment groups, larger age differences in relationships were associated with lower levels of condom use, more frequent sex, and longer relationship durations.

Conclusions: Cash-transfer programmes may prevent HIV transmission in part by encouraging young women to form age-similar relationships, which are characterised by increased condom use and reduced sex frequency. The benefits of these programmes may extend to those who are not directly receiving the cash.

Keywords: Age-disparate relationships; Age-mixing; Malawi; Sexual risk behaviour; Southern Africa.

Fig. 1

Overview of SIHR study intervention and data collection rounds. *HIV data collected during Round 2 biomarker collection were not made publicly available, and therefore, not used in our analysis

Fig. 2

Summary statistics for relationship characteristics, by study group and round. The panels contain summaries for: a. condom use (n = 1491); b. sex frequency (n = 1490); c. age difference (n = 1364); and d. relationship duration (n = 1256)

Fig. 3

Results of linear mixed-effects model with age difference as the outcome. Beta coefficient and 95% Confidence Interval (95% CI) plot for the (fixed) effects of age, study group, and round on age difference between a girl and her partner

Fig. 4

Results of cumulative-link mixed model with condom use as the outcome. In this model age difference was a spline term. a. cumulative probability of condom use categories for age difference. b. predicted effect of age difference on ordinal condom use score (scored as 0 for “never” up to 2 for “every time”), with shaded areas representing the 95% CI. c. proportional odds ratio (POR) and 95% CI plot for non-spline terms in the model

Fig. 5

Results of cumulative-link mixed model with sex frequency as the outcome. Both age and age difference were spline terms in this model. a. cumulative probability of sex frequency categories for age difference. b. cumulative probability of sex frequency categories for age of participant. c. predicted effect of age difference on ordinal sex frequency score (scored as 0 for “1-2 times” up to 4 for “4 per week”) for age difference, with the shaded areas representing 95% CIs. d. ordinal sex frequency score for age of participant with the shaded areas representing 95% CIs. e. proportional odds ratio (POR) and 95% CI plot for non-spline terms in the model

Fig. 6

Results of Cox proportional hazards model for relationship duration. In this model age difference was represented with a spline. a. coefficient plot of hazard ratios for ending relationships (HR and 95% CI) for all non-spline terms in the model. b. predicted HRs for age differences, with the median (age difference = 3) as the reference. c. expected survival curves for selected age differences (2.5th, 25th, 50th, 75th and 97.5th percentiles)