BackgroundEpilepsy is a devastating disorder that impacts on patients’ quality of life, irrespective of use of anti epileptic drugs (AEDs). This study estimates the health-related quality of life (HRQOL) and its associated predictors among epilepsy patients receiving AEDs.MethodsA total of 175 epilepsy patients already receiving AED for at least 3 months were randomly selected and interviewed from mental clinics at Mulago and Butabika national referral hospitals in Uganda between May - July 2011. A HRQOL index, the primary outcome, was constructed using items from Quality Of Life in Epilepsy Inventory (QOLIE-31) and the Hospital Anxiety and Depression Scale (HADS) questionnaires. The internal consistency and adequacy of these items was also computed using Cronbach's alpha and Kaiser-Meyer-Olkin tests. Partial correlations were used to evaluate the contribution of the health dimensions (mental, psychological, social, physical functioning and emotional well being) and, multiple linear regressions to determine factors independently associated with HRQOL.ResultsJust about half of the respondents (54%) were males, and nearly two thirds (62%) had received AEDs for at least 12 months. The average age was 26.6 years (SD = 11.1). The overall HRQOL mean score was 58 (SD = 13) on a scale of 0–100. The average scores of different dimensions or subscales ranged from 41 (physical) to 65 (psychological). At least three quarters (75%) of all subscales had good internal consistency and adequacy. The largest variations in the overall HRQOL were explained by social and mental functioning; each accounting for about 30% of the difference in the HRQOL but seizure control features explained a little (6%) variation. Factors negatively associated with HRQOL were poly-therapy (-1.16, p = 0.01) and frequency of seizures (-2.29, p = 0.00). Other factors associated with overall HRQOL included drug side effects, sex, marital status and education. Duration on AEDs was not a significant predictor of HRQOL.ConclusionThe HRQOL for epilepsy patients on AEDs is very low. The predictors of low HRQOL were socio factors (marital status, education) and drug side effects, frequency of seizure, and type of therapy.

BackgroundRecent evidence suggests that HIV prevalence is generally higher among older than younger persons. However, few studies have explored issues regarding HIV testing and awareness of HIV status among older persons. We explored the correlates of HIV status awareness among older adults (aged 45+ years) in Uganda.MethodsThis paper is based on secondary analysis of existing data on persons aged between 45 and 59 years from a nationally representative Uganda AIDS Indicator Survey which was conducted between February and September 2011. Records on the socio-demographics and HIV/AIDS-specific indicators for 2472 persons were extracted for analysis. Individuals were considered to be aware of their HIV status if they reported that they had tested and received their HIV test results within the past 12 months. Data analyses were done using the sample survey procedures to take into account the sampling structure of the data. Odds ratios were used to quantify the associations between receipt of HIV test results and potential factors.ResultsOf the 2472 respondents, 48% had ever tested and received their HIV test results while 23% tested and received their HIV results in the past 12 months or already knew that they are HIV positive. Individuals with the following characteristics had higher odds of being aware of their HIV status: being female (adjusted Odds Ratio (AOR) = 1.26; 95% CI: (1.04, 1.53), having high comprehensive knowledge of HIV/AIDS (AOR = 1.28; 95% CI: 1.04, 1.58), having attended secondary school education (AOR = 2.10; 95% CI: 1.47, 2.99) and engagement in high risk sexual behaviors (AOR = 1.53; 95% CI: (1.11, 2.10). A high level of stigma (holding at least three stigmatizing attitudes toward people living with HIV) was negatively correlated with awareness of HIV status (AOR =0.60; 95% CI: (0.45, 0.78).ConclusionLess than a quarter of older Ugandans are aware of their current HIV status. High levels of stigma and low comprehensive knowledge of HIV/AIDS remained critical barriers to HIV testing and awareness of HIV status. These findings suggest a need for innovative HIV testing strategies to increase HIV status awareness among older adults in Uganda.

Background: Although married couples can be at an elevated risk of HIV infection, few studies have explored the risk factors for HIV infection at the couple-level. We explored the risk factors for HIV infection among married couples in settings with differing HIV prevalence levels in Rakai, Uganda. Methods: This was a cross-sectional study conducted among 664 heterosexual couples living in three HIV prevalence strata (low: 9-11.2%; medium: 11.4-20% or high HIV prevalence: 21-43%) in Rakai District, south-western Uganda, between November 2013 and February 2014. Data were collected on socio-demographic and behavioural characteristics from all consenting adults and aggregated to allow for couple-level analyses. We conducted bivariate and multivariable Logistic regression to assess the factors that were independently associated with HIV infection among married couples. Data were analysed using STATA statistical software (version 14.1). Results: Of the 664 couples, 6.4% (n = 42) were in HIV-discordant relationships; 5.8% (n = 39) were in concordant HIV-positive relationships while 87.8% (n = 583) were in concordant HIV-negative relationships. At the bivariate analysis, we found that residing in a high HIV prevalence stratum, reporting extra-marital relations, age difference between partners and number of previous marriages were significantly associated with being part of an HIV infected couple. After adjusting for potential cofounders, living in a high HIV prevalence stratum (Adjusted OR [AOR] =2.31, 95% CI: 1.52, 3.52), being in a third or higher order relationship (AOR = 3.80, 95% CI: 2.30, 6.28), and engagement in extra-marital relations (AOR = 1.75; 95% CI: 1.19, 2.59) were associated with couple HIV infection. Individuals that had stayed together for six or more years had 28% odds of being part of an HIV infected couple (AOR = 0.28; 95%CI: 0.18, 0.43). Conclusion: Living in a high HIV prevalence stratum, engagement in extra-marital relations and having a higher number of previous marriages were significant risk factors for HIV infection among married couples. Long marital duration was associated with reduced risk of HIV infection. Interventions that increase marital stability and those that promote pre-marital couples' HIV testing before marital formation can reduce HIV transmission risk among married couples in this setting.

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