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Trends and transitions in labour market outcomes among adults enrolled in the Free State province’s public sector antire

Trends and transitions in labour market outcomes among adults enrolled in the Free State province’s public sector antiretroviral treatment (ART) programme. Frikkie Booysen, Department of Economics / CHSR&D, University of the Free State

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Trends and transitions in labour market outcomes among adults enrolled in the Free State province’s public sector antire

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  1. Trends and transitions in labour market outcomes among adults enrolled in the Free State province’s public sector antiretroviral treatment (ART) programme Frikkie Booysen, Department of Economics / CHSR&D, University of the Free State Annual TIPS Forum: South Africa’s Economic Miracle – has the emperor lost his clothes? Cape Sun, Cape Town 29-31 October 2008

  2. Acknowledgement • The financial support of CIDA, DCI, DfID, IDRC, JEAPP, USAID, AUSAID, UNDP, The World Bank’s Research Committee, and BNP Programme • Patients in the ART programme who willingy sacrificed their time and energy to participate in this research, and frankly shared their views and experiences. • The management and health care staff of the Free State Department of Health and of several local municipalities, who facilitated access to the study participants.

  3. Background • Adverse macro- and microeconomic impacts of HIV and AIDS are relatively well documented • Access to ART is expanding rapidly in South Africa, Southern Africa and beyond, although coverage remains sub-optimal … how can ART ameliorate these adverse economic impacts of HIV and AIDS?

  4. Data: CP cohort study • Sampling frame • Eligible and certified ready to commence ART in 2004/05 • CD4<200 and/or WHO stage 4 + clinical assessment • Randomly sampled • 80/district proportional to treatment/non-treatment numbers • Xhariep = 44 patients only, census • Follow-up interviews at approximately 6- to 9-month intervals • Replaced from original sampling frame if lost to follow-up • Written, informed consent • Nursing sister at assessment site + enumerator • Sample size • 6 survey rounds: 454 (n) individuals observed 1,844 times (N) • 195 patients interviewed in all 6 survey rounds • Attrition rate = 42.1%, mostly due to death, migration and refusal

  5. Labour market outcomes: (a) Too ill to work (b) Labour force participation (c) Unemployment (d) Absorption (e) Discouraged Treatment outcomes: (a) Clinical markers CD4 count (copies/mm3) RNA level (copies/mL) CD4 > 350 and RNA < 500 (b) Self-reported illness (c) Health-related quality of life EQ-5D EQ-VAS (d) Self-reported side-effects (e) Hospitalisation Key outcomes TIME: TREATMENT CAREER

  6. Key questions (1) How do labour market outcomes and transitions in labour market outcomes vary by treatment duration and/or treatment responses? (2) Are treatment dynamics significant predictors of labour market outcomes and transitions in labour market outcomes?

  7. Figure 2: Clinical outcomes, by treatment duration (a) Pooled clinical data (b) Matched clinical data Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

  8. Table 4: Subjective, self-reported outcomes, by treatment duration Note: Standard errors reported in parentheses. Results for side effects only include patients on ARV treatment at the time. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27; N=130). Three asterisks denote differences that are statistically significant at the 1% level, while two asterisks denote differences that are statistically significant at the 5% level. Median values of all continuous variables also differ statistically significantly across treatment duration categories (p<0.001).

  9. Figure 15a: Predicted probability of being too ill to work, by treatment outcomes and duration Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

  10. Figure 15b: Predicted probability of participating in the labour force, by treatment outcomes and duration Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

  11. Figure 15c: Predicted probability of being absorped in the labour force, by treatment outcomes and duration Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

  12. Table 8: Subjective, self-reported treatment outcomes as predictors of labour market outcomes Note: Results are for random effects (RE) panel probit models including ONLY treatment dynamics as explanatory variable. All models are statistically significant in respect of overall fit (p<0.001). Results are reported as marginal effects of type eydx. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

  13. Table 9: Treatment duration and/or subjective, self-reported outcomes as predictors of labour market outcomes Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.001). Results are reported as marginal effects of type dydx. Adjusted for gender, age, race, education, dwelling, marital status, dependency ratio, employment status at first HIV-positive test, access to disability grant, breadwinner status, access to inter-household employment networks, self-reported stigmatisation, district, follow-up duration, and month and year of interview. Three asterisks denote differences statistically significant at the 1% level, two and one asterisk significance at 5% and 10% levels respectively.

  14. Tables 10-12: Other predictors of labour market outcomes Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.001). Results are reported as marginal effects of type dydx. Adjusted for treatment duration/outcomes, gender, age, race, education, dwelling, marital status, dependency ratio, employment status at first HIV-positive test, access to disability grant, breadwinner status, access to inter-household employment networks, self-reported stigmatisation, district, follow-up duration, and month and year of interview. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

  15. Table 13: Treatment duration and outcomes as predictors of transitions in select labour market outcomes Note: Results are for pooled or random effects (RE) panel probit models including ONLY treatment dynamics as explanatory variable. All models are statistically significant in respect of overall fit (p<0.10). Results are reported as marginal effects of type eydx. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

  16. Tables 14-16: Treatment duration and outcomes as predictors of transitions in select labour market outcomes Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.10). Results are reported as marginal effects of type dydx. Adjusted for gender, age, education, dwelling, marital status, dependency ratio, access to disability grant, breadwinner status, access to inter-household employment network, self-reported stigmatisation, district, follow-up duration, and survey round. Results for 2nd model also adjusted for employment status at first HIV-positive test, which was observed in survey rounds 5/6 only. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

  17. Tables 14-16: Other predictors of transitions in select labour market outcomes Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.10). Results are reported as marginal effects of type dydx. Adjusted for gender, age, education, dwelling, marital status, dependency ratio, access to disability grant, breadwinner status, access to inter-household employment network, self-reported stigmatisation, district, follow-up duration, and survey round. Results for 2nd model also adjusted for employment status at first HIV-positive test, which was observed in survey rounds 5/6 only. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

  18. Limitations • Observations of clinical (dates of facility visits) and labour market outcomes (interview dates) are not synchronised • Limited information regarding actual timing and/or duration of the observed labour market outcomes • Counterfactual unclear in absence of comparative samples of HIV-negative and/or HIV-positive persons not on ART • Potential attrition and selection bias in socio-demographics and key clinical and labour market outcomes • Poor overall fit of regression models for transitions in labour market outcomes: poor specification and/or unobservables? • ‘Over’-adjusting for time: treatment effects may ‘dissolve’ or ‘vanish’ if adjusting for temporal dimensions of survey data? • Endogeneity of select explanatory variables

  19. Key findings • Clinical outcomes and self-reported illness and/or health-related quality of life are strongly correlated • Initial increase in labour force participation early in treatment career, accompanied by decline in participation later in treatment career • ART patients worse off compared to representative LFS samples, with exception of (illness/disability and) labour force participation • Improvements in self-reported health rather than clinical markers explain labour market outcomes and/or transitions • Links to labour market and being employed at first HIV+ test significantly associated with labour market outcomes • Access to social grants remain key determinant of observed labour market outcomes: key protection or predicament? • Significantly ‘worse’ outcomes in informal settlements and rural areas (for persons residing in traditional dwellings‘’)

  20. Conclusions • Sustainable, effective treatment key for improved labour market outcomes , BUT ART is not a “magic bullet” for problems of poverty, development and underdevelopment? • Direct benefits for the economy relative limited among this group of ART clients (i.e. public sectors users), among which employment is low and often informal, especially in informal settlements and rural areas • Important therefore to estimate the indirect benefits or externalities of provision of treatment (e.g. time allocation, schooling, health care seeking behaviour) these social and economic spin-offs represents the focus of ongoing longitudinal research in this area

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