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A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in the Field of Population-Based Field Epidemiology / Socio-economic status (SES) disparities do not only exist between racial groups in South Africa but also exists within the vulnerable black population with the devastating impacts of the HIV epidemic. Households are important determinants of human welfare. However, little is known about the effect of household socio-economic status on the establishment and break-up of households within a low-resource setting and a severe HIV epidemic. It is in the midst of these challenges in rural South Africa that this study examined the effect of household SES on household formation and dissolution among the black population in rural northern KwaZulu-Natal. METHODS Using longitudinal data from the period 2003-2012 from the Africa Centre for Health and Population Studies, the study used a cross-sectional study design approach to examine the effect of household SES on household formation. It also examined the effect of household SES change (i.e. either positive, negative change or stable SES) between the start and end of observation of a household within the study period. Household formation was defined as when an individual or individuals come from different households to form a new social unit with a new household head. Dissolution occurred when all individuals in a household end their membership to a household due to death, out-migration or by joining other households. Separate regression models for the two outcomes, household formation and dissolution were explored with household SES covariates while adjusting for other household variables. RESULTS Household formation and dissolution trends both decreased over the study period. Out of a total of 18,249 households, newly formed households had a relatively higher percentage of tertiary educated household heads (10.7% versus 2.5%), unemployed household members (41.6% versus 28.5%), grant recipient household members (37.1% versus 8.5 %) and households within the average to richest wealth quintiles (44.1% versus 36.4 %) than pre-existing households. Multivariate analysis showed that tertiary educated household heads (aOR=2.96, 95% (CI) 2.26-3.89) and households within the average to richest wealth quintiles most especially the 4th quintile (aOR=3.29, 95% (CI) 2.69-4.04) were associated with a higher odds of households being newly formed. However, the lesser the employed members (aOR=0.31, 95% (CI) 0.21-0.45) and grant recipients per household size in a household (aOR=0.15, 95% (CI) 0.12-0.18) the lower the odds of formation. Furthermore, small size households (aOR=0.68, 95% (CI) 0.56-0.80) and unmarried household heads (aOR =0.47, 95% (CI) 0.40-0.55) were associated with lower odds of being newly formed. Whereas female headed households (aOR=2.23, 95% (CI) 1.93-2.57) were associated with a higher odds of household formation. With regards to household dissolution, close to a quarter of households had an increase in SES over the study period compared to households with a decreased SES (24.6% versus 8.6 %). Similar to household formation, male headed households dominated the study population with the highest proportion in dissolved households (63.8% and 61.5% at start and end of household observation respectively). Also unmarried household heads were the majority in dissolved households (62.7% and 64.1% at start and end of household observation respectively). Approximately 65.6% of households that never dissolved had an extended family type of composition compared to 36.6% of dissolved households. The area was predominantly rural with about 47.2% households in rural segment of the study area. The study has shown that households had lower odds of dissolving if there is a positive change (i.e. an increase) in household SES compared with households with an unchanged SES over the period. In exact terms, an increment in the number of employed household members over the study period was associated 49% lower odds of a household being a dissolved (aOR=0.51 95% (CI) 0.42-0.61). Also, an increment in the number of household grant recipients over the period of observation was associated with a 69% lower odds to result in the dissolution (aOR=0.31 95% (CI) 0.25-0.39). Households with an improved wealth index over the period of study were associated with 55% lower odds of dissolution (aOR =0.45, 95% (CI) 0.38-0.54). However, households with both male and female death (multiple sex) were more likely to dissolve. Similarly, peri-urban (aOR=0.71; 95% (CI) 0.58-0.86) households were more likely to dissolve compared to urban households. Surprisingly divorced, widowed and separated couples were not significantly associated with household dissolution. CONCLUSION SES is an important determinant of household existence and stability. This study has shown a complex relationship between household SES and household formation. Although education and improved household wealth index were more likely to result in household formation, an increase in the number of employed household members and household grant recipients did not necessary have an effect on household formation. Government cash transfers, education, employment of household members are valuable cushioning mechanisms necessary for household stability. There is need for government and non-governmental organisations to set up interventions to improve the socio-economic conditions of poor households prioritising rural and female headed households. This is especially critical in a high HIV prevalence area where these interventions will also mitigate against the burden of the HIV epidemic on the population. / MT2017

MSc (Med), Population-Based Epidemiology, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, 2009 / Introduction: Although socioeconomic inequality in health and mortality is currently on the top of the epidemiologic debate, studies however on the subject among adult population in Africa has been hampered due to the long absence of data in many countries. With the present reliable records of deaths from emerged demographic surveillance systems on the continent, adult mortality can now be accurately estimated. Objectives: The study‟s main objectives were 1. To calculate and show trend in adult mortality rate in ACDIS between 2001 and 2007. 2. To measure the association between mortality and individual‟s socio-economic status in the ACDIS. Methods: Individuals were selected based on age (15-64 yrs) and residency (Resident in the DSA on 1st January 2001). The total number of adults who met the criteria was 33,677; out of whom 4,058 died during the seven years follow up period. Mortality rates were computed using Kaplan-Meier survival estimates expressed per 1000 PYO. Household wealth index was constructed by use of PCA. The association between SES and adult mortality was assessed using Cox proportional Hazard model controlling for potential confounders such as age, sex and marital status. Results: The High group of the socioeconomic quintile had the highest mortality rate of 22.2 per 1000 PYO, 95% CI (20.7 - 23.7). There was no significant trend in the rates among the SES groups. After adjusting for the potential confounders; the effect of socioeconomic status in the highest SES category was 0.10 times less likelihood for death compared to the lowest SES group [HR=0.90, p=0.042, 95% CI (0.81 - 0.99)]. Conclusion: This study revealed that adult socioeconomic status is not significantly associated with adult mortality. Reducing the gap between the rich and the poor might not be the effective way in reducing adult mortality.

Socioeconomic status and Aboriginal cultural status are believed to be key risk indicators of mental health status in youth.<p>The main purpose of the study was to explore the role of Aboriginal cultural status as an independent risk indicator associated with depressed mood after controlling for other covariates; including socioeconomic status. <p>Methods<br> A population based cross sectional survey was used. Every student in grades 5-8 in Saskatoon was asked to complete a short self-report questionnaire in their classroom in February of 2007. Depressed mood was measured with a validated depression scale (CES-D-12).<p>Results<br> In total, 4093 adolescents completed the study questionnaire. For youth whose parents were of Aboriginal cultural status, the prevalence rate of moderate or severe depressed mood was 21.6% in comparison to 8.9% for youth whose parents were Caucasian (RR=2.43; 95% CI 1.92-3.08).<p> In the final adjusted multivariate logistic regression model, moderate or severe depressed mood was more likely to be associated with female gender (OR=1.665; 95% CI 1.179-2.352), having low self esteem (OR=3.185; 95% CI 2.084-4.870), feeling like an outsider at school (OR=3.364; 95% CI 2.386-4.743), being bullied within the past year (OR=1.879; 95% CI 1.278-2.761), alcohol usage (OR=2.518; 95% CI 1.730-3.666), high levels of anxiety (OR=22.171; 95% CI 14.170-34.960), suicide ideation (OR=3.734; 95% CI 2.502-5.572), being hungry some or most of the time (OR=2.071; 95% CI 1.357-3.162) and parents having a lower education status (OR=1.503; 95% CI 1.066-2.120). Although Aboriginal cultural status was strongly associated with moderate or severe depressed mood after cross tabulation and stratification, Aboriginal cultural status was not associated with higher levels of depressed mood after full adjustment for other covariates in the final multivariate model (OR= 1.132; 95% CI 0.682-1.881).<p>Conclusions<br>The results demonstrate that Aboriginal cultural status has a more limited and statistically non-significant association with moderate or severe depressed mood in youth after controlling for other covariates. There is a need to transfer the results of this research to the Saskatoon community to allow policy makers and the public at large to know that prevention of disparity in mental health is possible because the determinants of mental health (i.e., education) are now modifiable (in comparison to Aboriginal cultural status).

Socioeconomic status and Aboriginal cultural status are believed to be key risk indicators of mental health status in youth.<p>The main purpose of the study was to explore the role of Aboriginal cultural status as an independent risk indicator associated with depressed mood after controlling for other covariates; including socioeconomic status. <p>Methods<br> A population based cross sectional survey was used. Every student in grades 5-8 in Saskatoon was asked to complete a short self-report questionnaire in their classroom in February of 2007. Depressed mood was measured with a validated depression scale (CES-D-12).<p>Results<br> In total, 4093 adolescents completed the study questionnaire. For youth whose parents were of Aboriginal cultural status, the prevalence rate of moderate or severe depressed mood was 21.6% in comparison to 8.9% for youth whose parents were Caucasian (RR=2.43; 95% CI 1.92-3.08).<p> In the final adjusted multivariate logistic regression model, moderate or severe depressed mood was more likely to be associated with female gender (OR=1.665; 95% CI 1.179-2.352), having low self esteem (OR=3.185; 95% CI 2.084-4.870), feeling like an outsider at school (OR=3.364; 95% CI 2.386-4.743), being bullied within the past year (OR=1.879; 95% CI 1.278-2.761), alcohol usage (OR=2.518; 95% CI 1.730-3.666), high levels of anxiety (OR=22.171; 95% CI 14.170-34.960), suicide ideation (OR=3.734; 95% CI 2.502-5.572), being hungry some or most of the time (OR=2.071; 95% CI 1.357-3.162) and parents having a lower education status (OR=1.503; 95% CI 1.066-2.120). Although Aboriginal cultural status was strongly associated with moderate or severe depressed mood after cross tabulation and stratification, Aboriginal cultural status was not associated with higher levels of depressed mood after full adjustment for other covariates in the final multivariate model (OR= 1.132; 95% CI 0.682-1.881).<p>Conclusions<br>The results demonstrate that Aboriginal cultural status has a more limited and statistically non-significant association with moderate or severe depressed mood in youth after controlling for other covariates. There is a need to transfer the results of this research to the Saskatoon community to allow policy makers and the public at large to know that prevention of disparity in mental health is possible because the determinants of mental health (i.e., education) are now modifiable (in comparison to Aboriginal cultural status).

Money helps people gain access to the goods and services they require and it allows people to make choices without having dependence on others (Boucher & Kofos, 2012). Prior research has shown that when the concept of money is activated, participants behave in a less pro-social but a more self-sufficient way in that while they are less likely to offer help to others or to donate money, they make more effort to complete a task and they prefer to work alone rather than to work collectively with others (Vohs, Mead & Goode, 2006). In this study, we examined the effect of money activation on the level of support for government goods and services programmes as a function of the type of programmes (welfare related or universal) and the participantʼs socioeconomic position (higher or lower). All participants performed a memory task before completing a government goods and services survey. The memory task consisted of either money-related words (for the money primed group) or neutral words not associated with money (for the control group). The results show that relative to the participants in the control group, those primed with money had lower levels of support for government programmes, and the effect was stronger for welfare related compared with universal programmes. No significant interaction between priming and socioeconomic status was found, although there was a trend that activating the concept of money had a larger effect for the higher socioeconomic group compared with the lower socioeconomic group. These results provided converging evidence to previous research that activating the concept of money could change peopleʼs attitudes and behaviours, inducing them to become less sensitive to othersʼ needs. Our results also extend the findings of prior research to the valuation of existing government programmes. They suggest that money activation could lower peopleʼs support for social policies, resulting in unintended consequences.

Background. In Canada, motor vehicle collisions are the leading cause of unintentional injury deaths and second leading cause of injury hospitalization. Nationally, serious traffic injury has reduced 35% (1986-2005). Social determinants of health have not been studied with serious traffic injury in adulthood. Study Aims. To determine whether lower SES (measured by education, income, and employment), is associated with serious traffic and fall injury and injury severity and whether the pattern of association differed between traffic and fall injury. To reveal issues to be made by decision makers regarding at risk groups. Methods. Combined cycles (1.1, 2.1, and 3.1) of the cross-sectional Canadian Community Health Survey were used. Injuries in the past year ‘serious enough to limit normal activities’ were studied. Deaths and less serious injuries are not captured. “Transportation accident” was used to represent traffic injury. It does not specify victim type (e.g. driver, bicyclist) yet the category pertains to “automobiles” and published research used it as a proxy for motor vehicle collisions. Power analyses, survey weighting and bootstrapping were executed to prevent biased population estimates. Records with missing data were excluded. Logistic regression models were performed for tests with binary outcomes. Injury severity selected individuals’ highest treatment within 48 hours - admitted to hospital, Emergency Department visit, or seeing a health professional. Results. Socioeconomic variables were associated with serious traffic and fall injury and severity. For serious traffic injury, those with some post-secondary education were at higher risk (OR=1.34; 95%CI 1.08, 1.67) than post-secondary graduates. For serious fall injury, an education by gender interaction resulted. Males who did not complete high school had a higher risk (OR=1.14; 95%CI 1.03, 1.27) relative to post-secondary graduates. With the same reference group, females who completed high school had a lower risk (OR=0.86; 95%CI 0.75, 0.98). For serious fall injury, those in the lowest, versus top, personal income quintile had a higher risk (OR=1.37; 95%CI 1.23, 1.51). Females had a higher risk (OR=1.18; 95%CI 1.03, 1.35) of serious traffic injury relative to males. Youth/young adults had a higher risk of serious traffic injury (OR=1.75; 95%CI 1.50, 2.06) relative to the middle-aged group. The younger group had a higher risk of serious fall injury (OR=1.41; 95%CI 1.25, 1.60) relative to seniors. With serious traffic injury, seniors had a lower risk (OR=0.50; 95%CI 0.37, 0.68) than the middle-aged group. This did not support the literature with young and old at risk for traffic injury. In the two-level traffic severity model, employed, versus unemployed, individuals had a higher risk (OR=1.69; 95%CI 1.12, 2.55). Discussion. Associations were found between SES variables and serious traffic and fall injury for Canadians 12 years of age and over that were mostly but not always in the direction of lower SES having higher rates. Findings must be interpreted with caution due to sampling bias from missing data removal (27%). Information was not available on culpability or vehicle miles travelled. The traffic injury-SES relationship and SES-traffic severity relationship merit further inquiry in other contexts or with other datasets.

This thesis aims to describe health inequalities among older people in Britain in the 1980s and 1990s and to assess whether various personal circumstances and experiences contribute towards this variation. Three sources of data are used: the Longitudinal Study; the first Whitehall cohort of male civil servants; and baseline quality of life information from the MRC Trial of the Assessment and Management of Older People in the Community (MRC Study). Housing tenure, car availability, and employment grade are the main socioeconomic measures used, but also social class and income. Findings: People disadvantaged in mid-life socioeconomic circumstances continue to experience increased risks of mortality, insitutionalisation, poor self-reported health and functioning 20-30 years later. Smoking and cardio-respiratory factors in middle age partially accounted for the differentials found in the Whitehall Study. The MRC Study revealed worse prospects for five dimensions of health-related quality of life among people in rented homes compared to owner-occupied ones, even among those who were deemed independent. Symptoms of ill health, and health behaviours accounted for over 40% of the housing tenure differentials in quality of life among these independent people. Being in a deprived or densely-populated area was not as strong a discriminator of quality of life as personal housing-tenure. Finally, people whose socioeconomic circumstances become worse in late middle age have greater risks of poor health outcomes than those who stay advantaged. The findings on benefits of improvements in socioeconomic circumstances are more mixed and complicated by ill health leading to apparent upward socioeconomic mobility. Conclusions: The three studies provide evidence of both long-term implications of socioeconomic position in mid-life and continuing relevance of socioeconomic position in old age. Although personal factors and health symptoms contribute to health inequalities in old age they are also seen as a possible product of socioeconomic position.

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Includes bibliographical references / This thesis uses the National Income Dynamics Study (NIDS) data to estimate the extent of, and the factors correlated with, socio economic related health inequalities in South Africa. We extend our analysis by investigating whether income has a causal effect on health outcomes. The thesis is divided into four separate, but related chapters. In chapter two, we describe the data and the variables used in the study. We then check the quality of health related data in the NIDS by analyzing attrition trends and establishing whether attrition affects the representativeness of the data in subsequent waves. We use three health outcomes, self-assessed health, body mass index and depression, to test for the potential effects of attrition bias on parameter estimates. We test using the attrition probit and Becketti, Gould, Lillard and Welch (BGLW) tests, which are two well-known tests for attrition bias in panel data. We find that although the attrition rates of individuals from the sample are high in wave 2 and 3 (21% and 20% respectively), their attrition is random with respect to the health outcomes we use. In chapter three, we establish the socioeconomic factors correlated with health outcomes in South Africa. We use bivariate and panel data approaches. We find significant correlations between health outcomes and socioeconomic factors (income, educational attainment, and demographic factors). Income is positively correlated with self-assessed health and body mass index, and it is negatively correlated with depressive symptoms. In chapter four, we build on the findings discussed in chapter three to estimate the extent of Income Related Health Inequality (IRHI). We estimate the index of inequality using a health concentration index. We then decompose the concentration index to establish the extent to which the correlates of health outcome drive the IRHI. The panel nature of the data allows us to investigate whether IRHI is narrowing or widening. We find a positive health concentration index. This implies that better health is concentrated among the rich. The decomposition of the index reveals that these differences are explained by disparities in income and educational attainment. We also find that the IRHI has narrowed from 2008 to 2012. Most of the narrowing is unexplained but about 21% and 20% of the decrease is correlated with the changes in the distribution and response to covariates respectively. One of the socioeconomic determinants identified from the previous chapters to be correlated with health is income. In the last part of this thesis, we extend the analysis to investigate whether this relationship is causal. To do so, we use the Old Age Pension (OAP) programme as a natural experiment. The OAP is based on age eligibility. Therefore, we use this age eligibility as an exogenous income shock to isolate the effect of income on health. We apply a Regression Discontinuity Design on the NIDS data to identify this effect. We do not find any contemporaneous effect of income on three health outcomes considered, namely; self assessed health (SAH), body mass index (BMI), and depression.