Socio-economic inequity in HIV testing in Malawi

Measuring Socioeconomic Inequalities in HIV Testing During Antenatal Care: A Peruvian National Survey

Although several Latin American countries have 70% antenatal care coverage, the proportion of human immunodeficiency virus (HIV) testing of Peruvian pregnant women and the socioeconomic inequalities of this preventive measure are unknown. This study aimed to determine socioeconomic inequalities and quantify the contribution of contextual and compositional factors on HIV testing during prenatal care in Peru. A cross-sectional study of the 2021 Demographic and Family Health Survey data was conducted. The outcome variable was HIV testing of pregnant women during prenatal care. An analysis of inequalities was performed including the determination of concentration curves and a decomposition analysis of concentration indices. Of a total of 17521 women aged 15 to 49 years, 91.4% had been tested for HIV during prenatal care. The concentration curves showed that prenatal HIV testing was concentrated among richer women, while the decomposition analysis determined that the main contributors to inequality were having a higher education, residing in an urban area, and in the highlands, belonging to the wealthy quintile, and being exposed to television and newspapers. Strategies focused on improving access, promotion and restructuring of prevention of mother-to-child transmission measures should be prioritized.

Trends and factors associated with recent HIV testing among women in Haiti: a cross-sectional study using data from nationally representative surveys

INTRODUCTION

In the Latin America and Caribbean region, Haiti is one of the countries with the highest rates of HIV. Therefore, this study examined the factors associated with HIV testing among women in Haiti and trends in HIV testing in 2006, 2012, and 2016/17.

METHODS

Data from the last three Haitian Demographic and Health Surveys (2006, 2012, and 2016/17) were used. The analysis was restricted to women aged of 15-49 years who made their sexual debut. STATA/SE 16.0 was employed to analyze the data by computing descriptive statistics, Chi‑square, and multilevel regression model to describe the trends and identify factors associated with HIV testing in Haiti. P-value less than 0.05 was taken as a significant association.

RESULTS

HIV testing prevalence increased more than twofold from 2006 (8.8%) to 2017 (21.3%); however, it decreased by 11.6% between 2012 and 2016/17. Additionally, the results indicated that age, place of residence, region, education level, wealth index, mass media exposure, marital status, health insurance, age at first sex and number of sexual partners were significantly associated with HIV testing.

CONCLUSIONS

To significantly increase HIV testing prevalence among women, the Haitian government must invest much more in their health education while targeting vulnerable groups (youth, women in union, and women with low economic status).

Investigating inequalities in HIV testing in sub-Saharan Africa: spatial analysis of cross-sectional population-based surveys in 25 countries

OBJECTIVES

We aim to explore spatial variations in socioeconomic inequalities in HIV testing uptake in sub-Saharan Africa (SSA) at different geographical scales to identify potential geographical hotspots of inequalities. Additionally, to evaluate the potential benefits of HIV testing programmes, we assess whether local levels of HIV testing match the local levels of HIV prevalence.

DESIGN

A multi-country analysis of population-based cross-sectional surveys in SSA.

SETTING

We analysed data from 25 SSA countries with Demographic and Health Surveys between 2011 and 2019.

PARTICIPANTS

Country-level analysis included 473 775 participants (312 104 women and 161 671 men) and cluster-level analysis included 328 283 individuals (241 084 women and 87 199 men). Women aged 15-49 years and men aged 15-54/59 years in selected households who were tested for HIV in the last 12 months were eligible. We quantified inequalities in self-reported recent HIV testing with the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII) across geographical scales to capture sex-specific within-country spatial variations. We also conducted local Getis-Ord Gi* statistics to consider the autocorrelation in fine-scale SII and RII across countries. To assess the efficiency of HIV testing programmes, we measured the correlation between recent HIV testing and HIV prevalence through Spearman correlation across geographical scales.

RESULTS

We observed varying inequalities in recent HIV testing in magnitude and spatial distribution on both absolute and relative scales in many countries for both sexes at national and subnational levels. Hotspots of absolute and relative inequalities were mostly observed in Western and Central Africa with a few regions in Eastern and Southern Africa. Despite significant sex-specific correlations between testing and prevalence in all countries when assessed at the national level, we report an absence of such a correlation at fine scale in 17 of 50 sex-country combinations.

CONCLUSIONS

We highlight the importance of investigating the spatial variability of various HIV indicators and related inequalities across different geographical levels. Results may help inform an equitable distribution of HIV testing services.

Socioeconomic inequalities in the HIV testing during antenatal care: evidence from Indian demographic health survey, 2015–16

Background

In India, there is currently a lack of data on socioeconomic inequalities in HIV testing on a national scale; thus, understanding socioeconomic inequalities in response to expanded HIV testing is critical for assessing and ensuring equity of HIV programmes in accordance with the Sustainable Development Goals. The specific objective of the study was to determine the factor associated with HIV testing during antenatal care and assess the socio-economic inequalities in HIV testing during antenatal care (ANC) among Indian women aged 15–49 years with a live birth in the two years preceding the survey.

Methods

The results drawn from the state module of women data file of fourth round of National Family Health Survey (NFHS-4, 2015–16), considering HIV testing during antenatal care among women aged 15–49 who gave live birth in the two years preceding the survey and received the result of HIV test as a matter of fact. Method, such as, descriptive statistics, binary ogistic regression, concentration index were used in the analysis.

Results

The findings of the study show that HIV testing during antenatal care was low (30%) among women in India. Our findings reveal that there were significant inequalities exist in HIV testing during ANC between richer and poorer quintile of women. Education, place of residence, comprehensive knowledge of HIV/AIDS, and regular exposure of mass media were substantially contributing to socioeconomic inequality in HIV testing during ANC among women in India.

Conclusions

The socioeconomic inequities in HIV testing during pregnancy should be monitored and addressed in order to ensure an equitable distribution of the benefits specially among children and accomplishments of HIV programs in India.

Factors associated with HIV testing and counselling services among women and men in Nepal: a cross-sectional study using data from a nationally representative survey

OBJECTIVES

This study is set up to explore the factors associated with Human Immunodeficiency Virus (HIV) testing among women and men in Nepal.

STUDY DESIGN

Nepal Demographic and Health Survey, 2016 adopts a cross-sectional design.

SETTING

Nepal.

PARTICIPANTS

Women and men of age 15-49 years.

PRIMARY OUTCOME MEASURES

Our primary outcome was ever tested for HIV. We used multivariable analysis at a 95% level of significance to measure the effect in outcome variables.

RESULTS

About one in 10 women (10.8%) and one in five men (20.5%) ever tested for HIV. Women who had media exposure at least once a week ((adjusted odds ratio (aOR)=2.8; 95% CI: 1.4 to 5.3) were more likely to get tested for HIV compared with those who had no media exposure at all. Similarly, those who had their recent delivery in the health facility (aOR=3.9; 95% CI: 2.4 to 6.3) were more likely to get tests for HIV compared with those delivered elsewhere. Likewise, among men, compared with adolescents (15-19 years), those from older age groups were more likely to get tested for HIV. Compared with no education, secondary (aOR=2.3; 95% CI: 1.4 to 3.6) and higher education (aOR=1.7; 95% CI: 1.0 to 2.8) had higher odds of getting tested for HIV. Similarly, wealth quintiles in richer and richest groups were more likely to get tested for HIV compared with the poorest quintile. Other characteristics like media exposure, paid sex and 2+ sexual partners were positively associated with being tested for HIV.

CONCLUSIONS

HIV testing is not widespread and more men than women are accessing HIV services. More than two-thirds of women who delivered at health facilities never tested for HIV. It is imperative to reach out to people engaging in risky sexual behaviour, people with lower educational attainment, and those in the lower wealth quintile for achieving 95-95-95 targets by 2030.

Predictors of wealth index in Malawi – Analysis of Malawi demographic Health Survey 2004–2015/16

Objectives

To examine the wealth index over a decade utilizing Malawi’s Demographic and Health (DHS) survey data from 2004, 2010, and 2015/16, and to explore factors that predict higher wealth.

Study design

This was a retrospective descriptive study.

Methods

The study utilized DHS data from 2004, 2010, and 2015/2016. The total number of participants was 77,194. Linear regression models were used to assess the effects of the predictors. All analyses were conducted in Stata version 13.

Results

Findings showed no significant increase in wealth between the survey years. However, significant increases in wealth were associated with smaller family size (−0.09[-0.10, −0.08]), age (0.02[0.02,0.02]), having formal education (0.21[0.18, 0.24]), and living in urban areas (−1.84[-1.98, −1.70]). Differences in wealth also existed among the different ethnic and religious groups with the Chewa reporting less wealth than other groups, and people with any form of religion reporting more wealth than people with no religion.

Conclusions

Minimal changes in wealth have occurred in Malawi between 2004 and 2015/16, and sociodemographic, socioeconomic, and cultural factors are associated with wealth in this population.

Clusters of sub-Saharan African countries based on sociobehavioural characteristics and associated HIV incidence

Introduction

HIV incidence varies widely between sub-Saharan African (SSA) countries. This variation coincides with a substantial sociobehavioural heterogeneity, which complicates the design of effective interventions. In this study, we investigated how sociobehavioural heterogeneity in sub-Saharan Africa could account for the variance of HIV incidence between countries.

Methods

We analysed aggregated data, at the national-level, from the most recent Demographic and Health Surveys of 29 SSA countries (2010–2017), which included 594,644 persons (183,310 men and 411,334 women). We preselected 48 demographic, socio-economic, behavioural and HIV-related attributes to describe each country. We used Principal Component Analysis to visualize sociobehavioural similarity between countries, and to identify the variables that accounted for most sociobehavioural variance in SSA. We used hierarchical clustering to identify groups of countries with similar sociobehavioural profiles, and we compared the distribution of HIV incidence (estimates from UNAIDS) and sociobehavioural variables within each cluster.

Results

The most important characteristics, which explained 69% of sociobehavioural variance across SSA among the variables we assessed were: religion; male circumcision; number of sexual partners; literacy; uptake of HIV testing; women’s empowerment; accepting attitude toward people living with HIV/AIDS; rurality; ART coverage; and, knowledge about AIDS. Our model revealed three groups of countries, each with characteristic sociobehavioural profiles. HIV incidence was mostly similar within each cluster and different between clusters (median (IQR); 0.5/1000 (0.6/1000), 1.8/1000 (1.3/1000) and 5.0/1000 (4.2/1000)).

Conclusions

Our findings suggest that the combination of sociobehavioural factors play a key role in determining the course of the HIV epidemic, and that similar techniques can help to predict the effects of behavioural change on the HIV epidemic and to design targeted interventions to impede HIV transmission in SSA.

The relationships between cognitive function, literacy and HIV status knowledge among older adults in rural South Africa

INTRODUCTION

Although HIV prevalence is exceptionally high in South Africa, HIV testing rates remain below targeted guidelines. Older adults living with HIV are substantially more likely to remain undiagnosed than younger people. Cognitive function and literacy could play key roles in HIV status knowledge due to the decision-making processes required around weighing the costs and benefits of testing, navigating testing logistics and processing results. We aimed to assess the independent relationships among each of cognitive function, literacy and education with HIV status knowledge in a population-based sample of older adults living in a rural South African community with high HIV prevalence.

METHODS

We analyzed data from a population-based study of 5059 men and women aged 40 years and older in rural South Africa (Health and Aging in Africa: A Longitudinal Study of an INDEPTH community (HAALSI)). HAALSI surveys, conducted between 2014 and 2015, queried self-reported literacy, educational attainment and HIV status knowledge. Laboratory tests were conducted to assess true HIV sero-status. Cognitive function was assessed with a battery of cognitive tests measuring time orientation, immediate and delayed recall, and numeracy and coded using confirmatory factor analysis as a z-standardized latent variable. We estimated the relationship between the outcome of HIV status knowledge and each of three exposures: (1) latent cognitive z-score, (2) literacy and (3) education, using confounder-adjusted modified Poisson regression models in the study population overall and stratified by HIV sero-status.

RESULTS

We found that HIV status knowledge was higher among those with higher cognitive z-scores (adjusted Prevalence Ratio (aPR) (95% CI): 1.18 (1.14, 1.21) per standard deviation unit), and among literate participants (aPR (95% CI): 1.24 (1.16, 1.32) vs. non-literate participants). Taken together, the associations with literacy and cognitive function completely attenuated the otherwise positive association between educational attainment and HIV status knowledge. The magnitudes of effect were generally similar among laboratory-confirmed HIV-negative and HIV-positive participants.

CONCLUSIONS

Campaigns that target older adults in rural South Africa with HIV testing messages should carefully consider the cognitive and literacy levels of the intended audience. Innovations to ease the cognitive load associated with HIV testing could prove fruitful to increase HIV status knowledge.

A method for measuring spatial effects on socioeconomic inequalities using the concentration index

BACKGROUND

Although spatial effects contribute to inequalities in health care service utilisation and other health outcomes in low and middle income countries, there have been no attempts to incorporate the impact of neighbourhood effects into equity analyses based on concentration indices. This study aimed to decompose and estimate the contribution of spatial effects on inequalities in uptake of HIV tests in Malawi.

METHODS

We developed a new method of reflecting spatial effects within the concentration index using a spatial weight matrix. Spatial autocorrelation is presented using a spatial lag model. We use data from the Malawi Demographic Health Survey (n = 24,562) to illustrate the new methodology. Need variables such as 'Any STI last 12 month', 'Genital sore/ulcer', 'Genital discharge' and non need variables such as Education, Literacy, Wealth, Marriage, and education were used in the concentration index. Using our modified concentration index that incorporates spatial effects, we estimate inequalities in uptake of HIV testing amongst both women and men living in Malawi in 2015-2016, controlling for need and non-need variables.

RESULTS

For women, inequalities due to need variables were estimated at - 0.001 and - 0.0009 (pro-poor) using the probit and new spatial probit estimators, respectively, whereas inequalities due to non-need variables were estimated at 0.01 and 0.0068 (pro-rich) using the probit and new spatial probit estimators. The results suggest that spatial effects increase estimated inequalities in HIV uptake amongst women. Horizontal inequity was almost identical (0.0103 vs 0.0102) after applying the spatial lag model. For men, inequalities due to need variables were estimated at - 0.0002 using both the probit and new spatial probit estimators; however, inequalities due to non-need variables were estimated at - 0.006 and - 0.0074 for the probit and new spatial probit models. Horizontal inequity was the same for both models (- 0.0057).

CONCLUSION

Our findings suggest that men from lower socioeconomic groups are more likely to receive an HIV test after adjustment for spatial effects. This study develops a novel methodological approach that incorporates estimation of spatial effects into a common approach to equity analysis. We find that a significant component of inequalities in HIV uptake in Malawi driven by non-need factors can be explained by spatial effects. When the spatial model was applied, the inequality due to non need in Lilongwe for men and horizontal inequity in Salima for women changed the sign. This approach can be used to explore inequalities in other contexts and settings to better understand the impact of spatial effects on health service use or other health outcomes, impacting on recommendations for service delivery.

Computational Prediction of Subjective Human Immunodeficiency Virus Status in Malawi Using a Random Forest Approach

An individual's subjective judgment about his or her Human Immunodeficiency Virus status depends on certain factors, behavioral, health, and sociodemographic alike. This paper aims to develop a model with good accuracy for predicting subjective HIV infection status using the random forest approach. A total of 12,796 responses of Malawians over a 12-year period were assessed. Fourteen risk factors including behavioral, health, and sociodemographic information were analysed as potential predictors of subjective Human Immunodeficiency Virus infection status in the general population and thirteen behavioral, health, and sociodemographic information were analysed among males and females. The random forest approach was adopted to build a comprehensive model comprising 14 risk factors in Malawi. It was revealed that age, worries about infection, and health rate were the most significant predictors as compared to use of condoms, marital status, and education which were the least important predictors of subjective Human Immunodeficiency Virus status in Malawi. However, the importance of infidelity on the part of a spouse and marital status as predictors of subjective Human Immunodeficiency Virus status alternated among males and females. The importance of infidelity and marital status was relatively high among females than among males. The model achieved a prediction accuracy of about 97%-99% measured by c-statistic with jack-knife cross validation and verified by Mathews correlation coefficient. As a result, RF based model has great potential to be an effective approach for analysing subjective health status.

The Association of Material Hardship with Medication Adherence and Perceived Stress Among People Living with HIV in Rural Zambia

The intersection of poverty and HIV/AIDS has exacerbated socioeconomic inequalities in Zambia. For example, the downstream consequences of HIV/AIDS are likely to be severe among the poor. Current research has relied on multidimensional indicators of poverty, which encompass various forms of deprivation, including material. Although comprehensive measures help us understand what constitutes poverty and deprivation, their complexity and scope may hinder the development of appropriate and feasible interventions. These limitations prompted us to examine whether material hardship, a more practicable, modifiable aspect of poverty, is associated with medication adherence and perceived stress among people living with HIV (PLHIV) in Zambia. We used cross-sectional data from 101 PLHIV in Lundazi District, Eastern Province. Data were collected using a questionnaire and hospital records. Material hardship was measured using a five-item scale. Perceived stress was measured using the ten-item perceived stress scale. Adherence was a binary variable measured using a visual analog scale and medication possession ratio (MPR) obtained from pharmacy data. We analyzed the data with multivariable linear and logistic regressions using multiply imputed datasets. Results indicated that greater material hardship was significantly associated with MPR nonadherence (odds ratio = 0.83) and higher levels of perceived mental distress (β = 0.34). Our findings provide one of the first evidence on the association of material hardship with treatment and mental health outcomes among PLHIV. The findings also draw attention to the importance of economic opportunities for PLHIV and their implications for reducing material hardship and improving adherence and mental health status.

Costs of accessing HIV testing services among rural Malawi communities

HIV testing is free in Malawi, but users may still incur costs that can deter or delay them accessing these services. We sought to identify and quantify these costs among HIV testing service clients in Malawi. We asked residents of communities participating in a cluster randomised trial investigating the impact of HIV self-testing about their past HIV testing experiences and the direct non-medical and indirect costs incurred to access HIV testing. We recruited 749 participants whose most recent HIV test was within the past 12 months. The mean total cost to access testing was US$2.45 (95%CI: US$2.11–US$2.70). Men incurred higher costs (US$3.81; 95%CI: US$2.91–US$4.50) than women (US$1.83; 95%CI: US$1.61–US$2.00). Results from a two-part multivariable regression analysis suggest that age, testing location, time taken to test, visiting a facility specifically for an HIV test and district of residence significantly affected the odds of incurring costs to testing. In addition, gender, wealth, age, education and district of residence were associated with significant user costs.

Wealth-related inequality in early uptake of HIV testing among pregnant women: an analysis of data from a national cross-sectional survey, South Africa

OBJECTIVES

Wealth-related inequality across the South African antenatal HIV care cascade has not been considered in detail as a potential hindrance to eliminating mother-to-child HIV transmission (EMTCT). We aimed to measure wealth-related inequality in early (before enrolling into antenatal care) uptake of HIV testing and identify the contributing determinants.

DESIGN

Cross-sectional survey.

SETTINGS

South African primary public health facilities in 2012.

PARTICIPANTS

A national-level sample of 8618 pregnant women.

OUTCOME MEASURES

Wealth-related inequality in early uptake of HIV testing was measured using the Erreygers concentration index (CI) further adjusted for inequality introduced by predicted healthcare need (ie, need-standardised). Determinants contributing to the observed inequality were identified using the Erreygers and Wagstaff decomposition methods.

RESULTS

Participants were aged 13 to 49 years. Antenatal HIV prevalence was 33.2%, of which 43.7% came from the lowest 40% wealth group. A pro-poor wealth-related inequality in early HIV testing was observed. The need-standardised concentration index was -0.030 (95% confidence interval -0.038 to -0.022). The proportion of early HIV testing was significantly better in the lower 40% wealth group compared with the higher 40% wealth group (p value=0.040). The largest contributions to the observed inequality were from underlying inequalities in province (contribution, 65.27%), age (-44.38%), wealth group (24.73%) and transport means (21.61%).

CONCLUSIONS

Our results on better early uptake of HIV testing among the poorer subpopulation compared with the richer highlights inequity in uptake of HIV testing in South Africa. This socioeconomic difference could contribute to fast-tracking EMTCT given the high HIV prevalence among the lower wealth group. The high contribution of provinces and age to inequality highlights the need to shift from reliance on national-level estimates alone but identify subregional-specific and age-specific bottlenecks. Future interventions need to be context specific and tailored for specific subpopulations and subregional settings.