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Epidemiology and Social

Antiretroviral therapy coverage associated with increased co-residence between older and working-age adults in Africa

De Neve, Jan-Waltera,b; Karlsson, Omarc,d; Coetzee, Lelanie,f; Schröder, Henninga,g; Subramanian, S.V.h,i; Bärnighausen, Tilla,b,j; Vollmer, Sebastianb,k

Author Information
doi: 10.1097/QAD.0000000000001917

Abstract

Introduction

The toll of the HIV epidemic is changing demographic and household structures in sub-Saharan Africa [1]. The HIV epidemic causes deaths among working-age adults in particular, who often serve as primary caregivers of children and older family members – thereby decreasing the supply of family caregivers [2,3]. Their need, however, could not be greater. More than 17 million children are orphaned as a result of HIV [4] and the number of adults over age 60 is expected to rise by 60% between 2015 and 2030 [5]. These changes will further increase the demand for support by family members [6]. Unlike in middle- and high-income countries, where a public welfare system provides for older adults, in low-income countries ‘upward’ intergenerational transfers from adult offspring to parents ensure older adults’ welfare [7–11]. In the absence of public wealth transfers, families in low-income countries function as de facto social institutions to replace market or government institutions [12], and smooth consumption across the life cycle [13].

Global health policies have focused on rapidly expanding HIV treatment or antiretroviral therapy (ART) to curb the HIV epidemic by 2020 [14]. As a result, ART coverage is increasing dramatically in sub-Saharan Africa, from on average less than 1% in the early 2000s to currently over 50% (Figures S1-S2 in the Appendix, http://links.lww.com/QAD/B303) [15]. ART has been linked to improvements in the treated individual's outcomes, such as increased life expectancy [14], labor force participation [16,17], and recovery of employment [18–20]. Relatively little is known, however, on the effect of large-scale ART expansion on household outcomes [21]. ART coverage is likely to increase the number and productivity of working-age individuals with possibly large spillover effects to co-resident family members who depend on their support [22]. Although a few studies have assessed the consequences of ART for offspring [22,23], little is known about the extent to which ART coverage has affected the household arrangements of the preceding generation. This topic differs substantially from the mainstream focus of medicine on treatment effects in the treated individual, and assesses the meaning of HIV treatment in working-age adults for their co-residing household members who may or may not be on HIV treatment themselves.

In this article, we analyze the largest available, nationally representative, and mutually comparable repeated cross-sectional samples from 103 surveys in 28 countries to examine the quantitative relationship between ART coverage and co-residence between older and working-age (age 18–59) adults. The overarching research question is important, both scientifically and for policy – how does HIV treatment in a working-age adult affect the health, economic, and social outcomes of older adults? Our specific research questions are three-fold: to determine the relationship between HIV mortality and the living arrangements of older adults in sub-Saharan Africa; to determine whether ART coverage is associated with changes in the living arrangements of older adults; and to determine the potential impact of increased ART coverage on the number of older adults living with working-age household members.

Methods

Data source

Our data comes from the Demographic and Health Surveys, AIDS Indicator Surveys, and Malaria Indicator Surveys conducted by Macro International, Calverton, Maryland, USA [24]. These surveys are nationally representative household-level surveys and are typically performed at least once every 5 years. AIDS Indicator Surveys and Malaria Indicator Surveys are performed intermittently between Demographic and Health Surveys. The standard survey includes questions about household composition and living arrangements such as age and educational attainment of each member of the household. Although the Demographic and Health Surveys typically focus on children and working-age adults, the basic household roster includes data on all household members, including older adults. We included all sub-Saharan countries where multiple surveys had been conducted between 1990 and 2015. Our final sample included 297 331 older individuals (age 60 or older) surveyed during 103 survey waves in 28 countries: Benin, Burkina Faso, Burundi, Cameroon, Chad, Côte d’Ivoire, Democratic Republic of Congo, Gabon, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Niger, Nigeria, Rwanda, Togo, Senegal, Sierra Leone, Tanzania, Uganda, Zambia, and Zimbabwe. We show the complete list of countries and survey years in Table S1 in the Appendix, http://links.lww.com/QAD/B303.

Outcome measures

We investigated three measures of living arrangements of older people: the number of older individuals living without working-age adults; the number of older individuals living with only dependent children (i.e. also described in the literature as ‘missing generation’ or ‘skip generation’ households [2,3]); and the number of working-age adults per household where an older adult lives. Older adults may be harmed by living without working-age adults (e.g. by being ‘unattended’ or ‘unaccompanied’), incurring the burden of child support (in addition to the hardships of caring for themselves without adult support), or by living with fewer working-age adults. We defined an older adult to be 60 years of age or older, a younger adult to be between the ages of 18 and 59, and a dependent child to be under the age of 10. The age criterion of 60 years or older was used because it captures the oldest 5% of the sub-Saharan African population, who may require financial and physical support (by comparison, the oldest 5% of the population in the United States constitute people who are more than 75 years old) [5]. These three measures of living arrangements of older adults are documented in detail elsewhere [2].

Exposure

ART coverage was defined as the percentage of all people living with HIV who are receiving ART. We used the annual estimates of ART coverage by country from UNAIDS [15] and matched these estimates to our 103 surveys based on country and year.

Statistical analyses

Our analysis proceeded in three steps. First, we graphically assessed the naïve relationship between HIV mortality rates and the proportion of older adults living without a working-age adult in sub-Saharan Africa [2]. We also graphically assessed how ART coverage relates to the living arrangements of older adults. Second, for binary dependent variables (older adults living without working-age adults and older adults in missing generation households), we estimated the importance of ART coverage at the time of the survey by using probit models. For the number of working-age adults living in households with older people, we used ordinary least squares (OLS) regressions. Where we used probit models, we report marginal effects, which represent the change in likelihood of the outcome given a one-point change in the predictor variable. We estimated probit models of the form:

We estimated a separate model for each of the binary outcome variables (older adults living without working-age adults and older adults in missing generation households). Our main parameter of interest is γ, which represents the relationship between national ART coverage at the time of survey year j (at the aggregate level), and the outcome yij for senior i in survey year j (at the individual level). Bij is a vector of parameters, including controls for age (years), sex, area of residence (urban vs. rural), education (years), measures of household socioeconomic status (electricity, radio, and bicycle), and indicators for country and survey year to adjust for unobserved differences between countries and account for common linear changes over time (i.e. country and year fixed effects). Our identifying assumption is that unobservable factors that might simultaneously affect ART coverage and our measures of the living arrangements of older adults are time-invariant. We clustered standard errors at the country and survey-specific primary sampling unit level to account for spatial correlation. We assessed the relationship between ART coverage and living arrangements of older adults using pooled data from all countries, when stratifying by country HIV prevalence [25], and when stratifying by sex of the older adult [26].

Third, we used our regression results to estimate the potential (positive) impact in the number of older adults living with working-age adults associated with increased ART coverage in countries where the HIV epidemic is generalized or hyperendemic (Lesotho, Kenya, Malawi, Mozambique, Namibia, Tanzania, Uganda, Zambia, and Zimbabwe). To do so, we multiplied the estimated marginal effects of ART coverage by the number of older people (ages 60+), yielding the estimated number of older adults living with a working-age adults resulting from increased ART coverage (1%). We calculated estimates of the number of older adults living with working-age adults associated with ART coverage separately by country. These calculations assume that the same parametric relationship between the probability of an older adult living without a working-age adult and ART coverage within our study sample holds for each country.

Sensitivity analyses

We conducted a number of sensitivity analyses to generate additional confidence in our regression results. First, we used alternative functions for age to model the nonlinear relationship between age and the living arrangements of older adults in our analytical sample (Figure S3 in the Appendix, http://links.lww.com/QAD/B303). Second, we modelled our outcomes with a log link function in Poisson regression models. Third, to investigate the potential role of outliers and the robustness of our results to the exclusion of individual countries in our sample, we re-estimated our main equations omitting each individual country from our sample. Fourth, we reweighted the observations with the population size of the country using the country population over 60 years old at the time of the survey. Fifth, we excluded surveys conducted prior to 2000, when ART coverage was very low. Finally, we used alternative definitions for the age cut-off of defining older age. We used ages 50 and 70 years to define an older adult (instead of 60 years), which capture the oldest 10 and 2% of the sub-Saharan African population, respectively [5].

Stata (version 15.0; Stata Corp., College Station, Texas, USA) was used for all statistical analyses.

Results

Descriptive statistics

Table 1 shows summary statistics. Our analytical sample included 297 331 older adults. The proportion of older adults living without a working-age adult largely remained similar between the 1991–2000 surveys (25.9%) and 2011–2015 surveys (26.3%). In countries where HIV is highly endemic (5% or higher), the proportion of older adults living without a working-age adult increased from 31.8 to 33.5% over the same period. Compared with older individuals who lived with working-age adults, older adults living without working-age adults were more likely to be women, to live in rural areas, and have completed fewer years of schooling. They were also less likely to have assets at home such as a radio. These findings suggest that, on average, older adults living without working-age adults live in poorer socioeconomic conditions relative to those living with working-age adults.

Table 1
Table 1:
Characteristics of the older adults in this study.

Figure 1 illustrates the relationship between the living arrangements of older adults and HIV mortality rates in sub-Saharan Africa. As expected, we find that higher HIV mortality is associated with higher fractions of older adults living without working-age adults. In Figure S4 in the Appendix, http://links.lww.com/QAD/B303, we show the naive correlation between ART coverage and the proportion of older adults living without working-age adults using the most recent survey for each country included in our study. Additional ART coverage appears weakly associated with reduced co-residence between older and working-age adults. When we stratify by HIV prevalence, however, the relationship reverses in countries where HIV is highly endemic (≥5%). One empirical concern with these naïve correlations between ART coverage and the living arrangements of older adults is that countries with higher ART coverage are likely to have higher mortality among younger generations for a range of other country-specific factors (such as increased mortality from tuberculosis [27]). We, therefore, turn to multivariable models that allow us to control for country and survey year indicators, in addition to a range of demographic and socioeconomic characteristics.

Fig. 1
Fig. 1:
Proportion of older adults living without working-age adults and HIV mortality rate.HIV mortality rate and the proportion of older people (ages 60 or higher) living without working-age adults (ages of 18–59) are shown. Each data point in the figure represents a country-year observation. The line represents unadjusted linear regression showing higher fractions of older adults living without working-age adults associated with higher HIV mortality rates. Sources: authors’ calculations using the World Bank World Development Indicators and Global Burden of Disease Results Tool (http://ghdx.healthdata.org/gbd-results-tool).

In Table 2 and S2 in the Appendix, http://links.lww.com/QAD/B303, we present our main results. We show the marginal effects obtained from probit regression models and coefficient estimates from the OLS models. Among countries where HIV was highly prevalent, ART coverage was significantly associated with a decrease in the proportion of older people living alone. Adjusting for an older adult's age, sex, area of residence (urban vs. rural), education, measures of household wealth, as well as survey year and country, a 1% point increase in national ART coverage at the time of the survey was associated with an absolute reduction of 0.7% points (P < 0.001) in the proportion of older people living alone and a 0.2% points reduction (P = 0.005) in the proportion of older people living in missing generation households. ART coverage was also associated with an increase in the number of working-age adults in households where an older adult lives (0.023, P < 0.001). As expected, in non-HIV-endemic countries, where the national roll-out of ART is unlikely to have affected the living arrangements of older adults, we find no significant relationship across all three measures of these living arrangements. In Table S3, http://links.lww.com/QAD/B303, we show results when stratifying by sex of the older adult and find slightly larger effects overall among female older adults. Our results were consistent across a range of robustness checks including when using alternative model and sample specifications, alternative definitions of older adults (50 and 70 years old), as well as when weighting the results by country population size (Tables S4–S8, http://links.lww.com/QAD/B303).

Table 2
Table 2:
Living arrangements of older adults and antiretroviral therapy coverage.

In Table 3, we used our parametric estimates to assess the potential population impact of increased ART coverage on the living arrangements of older adults. Our estimates suggest that in the countries with an HIV prevalence of ≥5% included in our study, an additional 103 000–358 000 older adults could be living with working-age adults as a result of increased ART coverage (1%). These findings suggest that the scale-up of ART is linked to substantial consequences for the living arrangements and well being of older adults in the region.

Table 3
Table 3:
Number of co-residing working-age adults associated with increased ART coverage.

Discussion

In this retrospective analysis, using data from nearly 300 000 older adults in sub-Saharan Africa, we demonstrate that ART coverage is positively associated with three major changes in the living conditions of older adults: an increase in the number living with working-age adults; a reduction in the number living by themselves in households with children under age 10 (i.e. ‘missing generation’ households); and an increase in the number of working-age adults living with older individuals in households where older and working-age adults live together. In countries where HIV is highly endemic, an additional 103 000–358 000 older adults could be living with working-age adults as a result of increased ART coverage (1%). To our knowledge, this study is the first multicountry analysis assessing the role of ART in the well being of older adults. Estimates of the returns to investments in a life-saving treatment for working-age adults are likely to be inaccurate without considering the broader societal consequences and meaning among household members who depend on their support.

These results are consistent with previous research on the relationship between HIV mortality and the well being of older adults in Africa [2,3,28]. Two cross-national retrospective analyses found that an increase in HIV mortality rate was associated with an increase in the proportions of older people living alone and in missing generation households [2,3]. Our study reveals a similar relationship between HIV mortality and the living arrangements of older adults using more recent data from Africa as well as additional data from the AIDS Indicator Surveys and Malaria Indicator Surveys (Fig. 1). Taken together, these findings suggest that improved ART coverage might reverse some of the burden induced by the HIV epidemic for older adults who lose their support and provide for young children. In households where older adults depend on co-residence with working-age adults, the continued scale-up of HIV treatment may have large positive spillover effects for older adults [9].

This study has a few limitations. First, causality cannot be determined with the current study design. Nevertheless, we controlled for known confounders, which were available in the Demographic and Health Surveys, AIDS Indicator Surveys, and Malaria Indicator Surveys [24,29,30]. We also controlled for time-invariant, unobservable factors. Second, in addition to improving life expectancy [14], ART coverage may lead to changes in labor migration, which affect our outcomes [31,32]. Circular migration, in particular, is associated with temporary periods spent away earning wages and sending remittances with subsequent returns to the home community [33]. Working-age adults may need to migrate for work, which would be more common with increased ART coverage [18]. Increased migration, however, would likely bias our estimates downwards as it would lead to less co-residence between older and working-age adults – thereby reducing the magnitude of the coefficient on ART coverage in our models. Third, we did not directly compare the health outcomes of older adults living without working-age adults vis-à-vis older adults who lived with (and may be supported by) working-age family members. The living arrangements of older adults, however, have been linked to substantial changes in health outcomes [34,35]. Fourth, increased co-residence between older adults and younger generations in sub-Saharan Africa does not necessarily imply improved support for older adults. Older adults may have accumulated assets or savings, or support themselves through subsistence agriculture [36]. Older adults may also benefit from state old age pensions in a number of the countries included in the study, such as Lesotho, Namibia, and more recently, Uganda [37,38]. In many households, intergenerational wealth transfers may occur from older adults to the younger generation, rather than the other way around [11]. Nevertheless, prior research suggests that, on average, older adults living without working-age adults and those in missing generation households are less well off compared with other household compositions [30]. Fifth, probit models with fixed effects have been suggested to be biased because of the ‘incidental parameters problem’ in nonlinear fixed-effects model [39]. However, we used a relatively limited number of dummy variable coefficients, which minimizes this risk and found similar results using linear probability models.

Finally, to assist in explaining and interpreting our quantitative findings, we will conduct a qualitative analysis in a sequential explanatory study design [40]. Qualitative data will be collected in selected countries in Africa (e.g. Botswana, Mozambique, South Africa, and Swaziland) through interviews with older adults (ages 60+). This mixed-methods data generation will generate a nuanced understanding of the features of HIV treatment for aging in Africa and how it is likely to contribute to the living arrangements of older adults [36]. Although the current analysis provides evidence as to whether ART coverage is associated with changes in the living arrangements of older adults, the qualitative component will allow us to make conclusions regarding why ART coverage had the observed effects.

Conclusion

The HIV epidemic is changing demographic and household structures in Africa. Increasing coverage of HIV treatment may provide substantial benefits to older adults who otherwise lack support from co-residing adults and provide for children.

Acknowledgements

We are grateful to study participants in the Demographic and Health Surveys, AIDS Indicator Surveys, and Malaria Indicator Surveys. The data used in this study are publicly available and are accessible at no cost from the Demographic and Health Surveys Program (www.dhsprogram.com).

Contributors: J.W.D.N., O.K., L.C., H.S., S.V.S., T.B., and S.V. conceived and designed the study. J.W.D.N. conducted the statistical analyses under the guidance of S.V., T.B., and S.V.S. J.W.D.N. and S.V. wrote the report. O.K. and S.V.S. suggested improvements to the statistical analyses. O.K., L.C., H.S., T.B., S.V.S., and S.V. contributed important revisions to the report. All authors approved the final submitted version of the report. J.W.D.N. is the guarantor.

Sources of funding: The current study was conducted with the support of the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award and a Humboldt Research Fellowship, funded by the Federal Ministry of Education and Research. T.B. was also supported by the European Commission; Wellcome Trust; the Clinton Health Access Initiative; NICHD of NIH (R01-HD084233), NIA of NIH (P01-AG041710), NIAID of NIH (R01-AI124389 and R01-AI112339), and FIC of NIH (D43-TW009775). For the remaining authors none were declared.

Role of funding source: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Ethical clearance: The current study was considered exempt from full review by the Harvard T.H. Chan School of Public Health Institutional Review Board as the analysis was based on an anonymous public use data set with no identifiable information on the survey participants.

Conflicts of interest

There are no conflicts of interest.

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Keywords:

antiretroviral therapy; family characteristics; HIV; households; intergenerational support; sub-Saharan Africa

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