1,721,015 research outputs found
Willingness to pay for insecticide-treated mosquito nets in rural South-East Nigeria : an integration of socio-economic and socio-psychological models
No full textIncludes abstract.Includes bibliographical references.Malaria is no doubt a severe public health problem especially in sub-Saharan Africa. It is endemic in Nigeria and insecticide-treated mosquito nets have been found to be effective in its control. However, the cost of commercially-sold ITNs in Nigeria is considered to be beyond the reach of many households. Therefore, it is essential to ascertain how much the average rural household is willing to pay for a family-size ITN
Inpatient household economic burden of child malnutrition in Zimbabwe : a case study conducted at Harare Central hospital
No full textIncludes bibliographical references.Severe acute malnutrition is one of the leading underlying causes of mortality in children under the age of five years. Nearly one to two million child deaths worldwide can be attributable to this illness. Although it is considered to be a global public health issue, severe acute malnutrition imposes an uneven burden on health resources across the world, with low-income countries shouldering much of this burden. Like any illness, severe acute malnutrition imposes an economic burden on households that, if significantly large could result in the impoverishment of households. However, despite the existence of a large volume of literature on the intergenerational economic consequences of malnutrition, little is known about the short term household economic consequences of malnutrition. This mini-dissertation sets out to estimate the household economic burden imposed by severe acute malnutrition in children under the age of 5 years in Zimbabwe. Furthermore, it aims to investigate and evaluate household responses to the economic consequences of malnutrition and the effect of the responses on household economic welfare
Socioeconomic status (SES), food insecurity and the double burden of malnutrition within South African households
No full textThe co-existence of under- and over-nutrition, termed the double burden of malnutrition (DBM), is associated with a high prevalence of both communicable and non-communicable diseases and is becoming a large public health concern. In general, DBM development is associated with populations undergoing a nutrition transition and urbanisation. DBM can exist at a population, household or individual level. The household form is particularly difficult to target with interventions, because households, and particularly mother-child pairs, are often consuming the same foods. For example, frequent consumption of energy dense and nutrient poor ('junk’) foods can concurrently result in overweight adults, but underweight children. Although, household DBM is linked with poverty and food insecurity and its prevalence is steadfastly increasing it is yet to be investigated in South Africa, despite this country being one of the most inequitable in the world. In addition, South Africa has a high prevalence of obesity (34% of adult females obese), undernutrition (9% of children underweight) and poverty (25% unemployment). with a high prevalence of poverty and food insecurity. Therefore, this study aims to estimate the prevalence, and examine the associated factors of DBM, in South African households. Using the nationally representative data from 2014, South Africa National Income Dynamic Survey wave 4, , the prevalence of household DBM pairs (overweight/obese mother and underweight/stunted child) was estimated. Multivariate logistic regression was applied to examine the relationship between mother-child DBM pairs and (i) socioeconomic status (per capita household income, number of household residents, and mother’s race, education, marital status, household head status), (ii) food security (per capita food expenditure), and (iii) potentially important confounders (mother’s age and urban/rural household). The regression was adjusted for mother’s age as a potential confounder. Mother-child DBM prevalence was 11% in this nationally representative sample of South Africa. Mother’s characteristics of being African (adjusted odds [aOR]: 1.3; 95% confidence intervals [95%CI]: 1.0-1.7) and married (aOR: 1.4, 95%CI: 1.1-1.6) were associated with increased odds of DBM. In contrast mother’s having tertiary education (aOR: 0.7, 95%CI: 0.5-1.0) and greater household per capita income (aOR: 0.9, 95%CI: 0.8-1.0) were protective against DBM. This South African household DBM prevalence is higher than most other developing countries and is associated with mother’s being African, married and having less education; as well as households with less per capita income. This high prevalence warrants urgent attention by policy makers to further investigate this issue in South Africa. Moreover, interventions such as Brazil’s “Green my Favela” should be considered to reduce the cost and increase the supply of nutritious foods to impoverishes households of South Africa
Experiences and social determinants of sexual violence and post-violence help-seeking behaviour among children and young people in Kenya
No full textThis dissertation examined the social determinants of sexual violence experience and help- seeking among Kenyan young men and women. Sexual violence is a public health concern because its levels are unacceptably high in Kenya, and it is a known risk factor for HIV infection.This is an urgent issue because Kenya has the third-largest HIV epidemic in the world and almosthalf of new HIV infections occur among young people. Therefore, preventing sexual violence is only possible if predictors of sexual violence and response pathways are continuously investigated. This study used Kenya's 2019 Nationally Representative Violence against Children Survey (VACS) data focusing on young men and women aged 13-24 years old. Sexual violence was defined as reporting unwanted touching, forced sex, attempted forced sex, or experiencing physical forced sex/rape, either in one's lifetime or in the past year both of which were binary variables. Help-seeking behavior was indicated by knowing where to seek formal help, seeking formal help, receiving formal help, and informal disclosure all of which are binary variables. This study first documents the pathway of sexual violence from exposure to help-seeking among young men and women in Kenya. Logistic regression models were then fitted to investigate predictors of sexual violence experience over the past year and lifetime disclosure of sexual violence in young women, controlling for age, being in a relationship, education status, HIV/AIDS testing, orphanhood, and household poverty. This study had 1344 female and 788 male participants. Young women reported a higher lifetime prevalence of sexual violence compared with young men (25.2% vs. 11.4%, p=0.000). Of these lifetime experiences of sexual violence, more young women than young men informally disclosedthese acts (45.1% vs. 22.7%, p=0.002). Although 33.7% of young women and 33.1% of young men knew where to seek formal help after experiencing sexual violence, more young women thanyoung men sought formal help after experiencing sexual violence (11.3% vs 6.8%, p=0.248). Gender inequitable attitudes [AOR 3.07 (1.10–8.56); p=0.032], experiencing emotional violence at home [AOR 2.11 (1.17–3.81); p=0.014], and cyberbullying [AOR 5.90 (2.83–12.29);p=0.000] are risk factors for sexual violence among young women. Life skills training [AOR 0.22 v (0.07– 0.73); p=0.014] and positive parental monitoring [AOR 0.31 (0.10–0.99);p=0.048] are protective against sexual violence among young women. Positive parental monitoring [AOR 3.85 (1.56– 9.46);p=0.004] was also associated with increased likelihood of informal disclosure among young women. This study highlights the protective value of life skills training and positive parental monitoring in sexual violence prevention. Moreover, this analysis demonstrated the possible role of gender inequitable attitudes, cyberbullying, and emotional violence at home in fueling sexual violence. Future VACS might consider increasing sample sizes to increase robustness of analyses, especially on help-seeking
Maternal health : cost analysis of introducing the Umbiflow Velocity Doppler System at primary health level : a pilot study conducted at Kraaifontein Community Health Centre and Durbanville Day Clinic
No full textBackground: A South African report, Saving Babies 2010-2011, reports 32,178 still births in a 2 year period of January 2010 to December 2011 within the 94% of the total hospitals who provide data to a Perinatal Problem Identification programme (PPIP). In order to deal with perinatal mortality, specifically Intra-Uterine Growth there is needed to equip the primary health care (PHC) with technology for monitoring. An instrument called the Umbiflow Doppler ultrasound machine has been developed and there is need to test its economic impact in the PHC. Methods: A cross- sectional analytical study was conducted in the Tygerberg Eastern Health District of the Metro Region of Western Cape, South Africa at two primary health care (PHC) facilities, one secondary level hospital, and one tertiary hospital namely Kraaifontein Community Health Centre (CHC), Durbanville Day Clinic, Karl Bremmer District Hospital, and Tygerberg Hospital respectively. The aim of the research was to conduct a cost analysis in the introduction of an Umbiflow Doppler machine in the primary health care with the major goal being to reduce the number of perinatal deaths in the public health system. A societal perspective was adopted. The cost analysis study was carried out on the already approved sample size of 139 patients stemming from the Umbiflow Clinical study. The inclusion criteria for patient participation was poor SF growth and late bookers >28 weeks attending Kraaifontein Community Health Care Centre and Durbanville Clinic for antenatal services
Factors associated with partial health insurance coverage among households in Malawi
No full textHealth insurance has proven ideal for curbing the increase in household contribution towards health expenditure. However, despite efforts to expand health insurance in Sub-Saharan Africa, coverage has remained low and favouring higher-income groups. Malawi is among the countries that face this low uptake, with only 3% of the total population insured. Moreover, within insured households, coverage is often incomplete, leaving some members without protection. This partial insurance coverage increasingly contributes to a reliance on out-of-pocket expenditure (OOPE), a regressive and inequitable financing mechanism that disproportionately affects vulnerable households. However, there is dearth of evidence on factors associated with this phenomenon among households in Malawi, thus, understanding the dynamics of partially insured households is crucial to addressing these gaps, reducing financial barriers to healthcare, and promoting Universal Health Coverage (UHC). Methodology: This study aimed to examine the determinants associated with partially insured households in Malawi. The thesis is divided into three parts: a structured literature review, a journal manuscript and a policy brief. The literature review revealed that most studies in Africa and elsewhere have focused on individual health insurance coverage determinants and not intrahousehold health insurance coverage status determinants. In Malawi, this is coupled with a low health insurance uptake. There is also limited information on factors influencing households to insure some but not all members. This study therefore aimed to fill this gap in literature and inform health financing policies. This quantitative study used cross-sectional secondary Data from the 2019-2020 Multiple Indicator Cluster Survey (MICS). The individual health insurance status; insured and uninsured, was defined as coverage by any health insurance. Using unique identifiers (cluster number, household number and line number), every individual was grouped into their respective households. Consequently, household size was used to determine a household's health insurance coverage status where a household with all members as insured was categorized as fully insured, a household with at least one but not all members insured as partially insured and a household with no member covered as completely uninsured. A two-stage analysis approach was then utilized in this study. Firstly, descriptive statistics were used to analyse and compare fully insured households, partially insured households and completely uninsured households. Zoning into partially insured households, the second stage applied multivariate binary logistic regression to identify factors associated with health insurance coverage. Analysis was done using STATA statistical package version 18. Results: This study had 64,615 unique individuals from 22,886 households. Only 0.6% of individuals had health insurance. A higher proportion of the households were completely uninsured (22,649; 98.96%) with 228 households (1%) being partially insured and the remaining 9 households (0.04%) were fully insured. Household sizes differed significantly among fully, partially insured, and completely uninsured households (median of 1, 5, & 4 respectively; p-value=<0.001). Higher education levels of household heads were strongly associated with full and partial insurance coverage and in contrast, lower education levels, such as no education or primary education, were linked to a lack of insurance coverage (89% vs 50% vs 72%; p-value=<0.001). All fully insured households were from the richest quintile. Age of household head [AOR 1.025 (1.000-1.050);p-value=0.045], higher education level of an individual [ AOR 4.470 (1.519-13.154); p-value=0.007], an individual's access to media [AOR 2.276 (1.050-4.931); p-value=0.037] and a higher dependency ratio [AOR 1.655 (1.111-2.466);p-value=0.014] were positively associated with being an insured individual from a partially insured household with household size [AOR 0.813 (0.682-0.969); p-value=0.022] being negatively associated with the outcome. On the other hand, residential area, sex of an individual and region were not associated with health insurance ownership in partially insured households. Households, therefore, were partially insured mainly because of being with large household members (median size of 5), higher dependency ratio, media access, individuals having no or primary education and being from the poorest quintile. Conclusion: Socioeconomics and household dynamics influence health insurance coverage. This study highlights education, household size, wealth, dependency ratio, and media exposure as significant determinants influencing partial household health insurance enrolment. Partially insured households remain particularly vulnerable as they continue to face financial risks due to uninsured members, highlighting the need for targeted interventions to facilitate their transition to full coverage. The findings emphasize socioeconomic and informational disparities. Therefore, efforts to enhance health insurance enrolment should focus on improving education access, supporting larger and economically disadvantaged households, and leveraging media channels to raise awareness about the benefits of comprehensive health insurance coverage. Implementing policies that enhance affordability, and accessibility will also be essential in achieving universal coverage and reducing financial vulnerability among households. Moreover, these findings are timely given Malawi's commitment to UHC, Sustainable Development Goal 3, and regional targets such as the Abuja Declaration, reinforcing the need for equitable health financing policies that address partial household insurance coverage
HIV self testing uptake and associated factors in Cape Town: a contextual framework
No full textSouth Africa bears one of the highest HIV burdens globally, with nearly 8 million people living with the virus. Despite hosting the world's largest antiretroviral therapy (ART) program, HIV-related deaths remain significant, accounting for over 23% of all deaths in 2019. Early detection and timely initiation of ART are essential to prevent transmission, improve quality of life, and reduce HIV-related morbidity and mortality. However, insufficient testing coverage among males and younger individuals remains a concern. HIV self-testing (HIVST) has emerged as a promising strategy to bridge these gaps, offering a private and convenient option for individuals hesitant to access healthcare facilities. The World Health Organization (WHO) endorses HIVST as a complementary approach to enhance access, particularly for populations underserved by traditional testing methods. While research has examined HIVST uptake in various settings, little is known about the specific factors influencing its adoption in Cape Town. Given South Africa's unique socio-economic landscape and the disparities between urban and rural areas, understanding the factors shaping HIVST uptake is crucial for developing tailored interventions. This thesis seeks to address this gap by investigating and analyzing the demographic, socio-economic, and community-level factors associated with HIVST uptake in Cape Town. Methods: This study utilized a cross-sectional design to examine HIV testing uptake and associated factors in Cape Town, South Africa, between January and December 2022. The analysis leveraged routine HIV Testing Services (HTS) programmatic data collected by the Anova Health Institute. The dataset included a total of 266,284 observations: 30,785 for HIV self-testing (HIVST) and 235,499 for conventional HIV testing. Data were drawn from individuals aged 18 years and older across the eight subdistricts of the Cape Town metropolitan area: Eastern, Northern, Southern, Western, Khayelitsha, Klipfontein, Mitchells Plain, and Tygerberg. The data, comprising sociodemographic details and testing information, were deidentified with formal permission from Anova Health Institute and the Department of Health. Individual-level data was recorded through consent forms and HTS registers and subsequently transferred to Red Cap and Power BI for quality checks and analysis. Community-level data, including the number of healthcare facilities, new and registered ART patients, and child acute malnutrition rates, were sourced from City of Cape Town health profiles (2021). Predictors were selected based on a socio-ecological framework, capturing both individual- and community-level factors. Individual-level variables included age, gender, and HIV testing history. Community-level factors encompassed healthcare access (number of healthcare facilities), HIV burden (number of registered and new ART patients), and socioeconomic status (child acute malnutrition rate). Descriptive statistics summarize the frequencies of HIVST, and conventional testing variables stratified by subdistrict, alongside community-level factors. A bivariate logistic regression model was conducted to assess associations between individual predictors and HIV testing options. Subsequently, a multivariate logistic regression model was employed to evaluate the influence of both individual- and community-level predictors on HIV testing choices (conventional vs. HIVST). Odds ratios were calculated with 95% confidence intervals to quantify these associations. This methodology integrates diverse data sources and robust statistical approaches, enabling a comprehensive examination of the factors influencing the uptake of HIV self-testing in Cape Town. Results: The study had a sample size of 265,063 of which 234,853 (88.60%) had utilized conventional HIV testing method and 30,210 (11.40%) opting for self-testing. Majority of individuals undergoing conventional testing are adults aged 25- 49 (63.16%), followed by older adults aged 50+ (17.16%). Similarly, for self-testing, most users are also within the 25-49 age group (63.84%), but there is a higher proportion of young adults aged 20-24 choosing self-testing (23.72%) compared to conventional testing (15.59%). Additionally, adolescents aged 18-19 are more likely to opt for self-testing (7.75%) than conventional testing (4.08%). Regarding gender, females constitute a larger share of those undergoing conventional testing (65.62%) compared to males (34.38%). The trend is similar for self-testing, where females account for 65.32%, and males make up 34.68%. In terms of the last HIV test, self-testing is more prevalent among individuals who were tested within the past 12 months (63.51%), while conventional testing is more common among those whose last test was over a year ago. Subdistrict analysis shows that conventional testing is most frequent in Tygerberg (20.06%) and Khayelitsha (16.87%), followed by Western (13.24%) and Eastern (12.45%). In contrast, self-testing is more widely utilized in Western (19.38%), Southern (15.33%), and Mitchell's Plain (16.97%). The bivariate logistic regression indicated that age was a significant factor influencing self-testing preferences, with the likelihood of using HIVST decreasing with age. Individuals aged 20‐24 had 20% lower odds of using self‐testing compared to adolescents aged 18‐19 (OR = 0.80, 95% CI: 0.76–0.85, p < 0.005). Those aged 25‐49 had 47% lower odds compared to the adolescent group (OR = 0.53, 95% CI: 0.51–0.56, p < 0.005), and adults aged 50 and above had 86% lower odds (OR = 0.14, 95% CI: 0.13–0.15, p < 0.005). Additionally, for facility testing those who had tested for HIV within the last 12 months were more inclined towards self‐testing. In contrast, individuals who last tested more than 12 months ago were 77% less likely to choose self‐testing (OR = 0.23, 95% CI: 0.22–0.25, p < 0.005), and those who had never been tested were 40% less likely (OR = 0.60, 95% CI: 0.54–0.67, p < 0.005) to use self‐testing. HIVST was more popular among people living in areas with a high concentration of registered ART patients. Specifically, the odds of choosing self‐testing increased by 32% in high-density areas (≥30,001 registered ART patients) (OR = 1.32, 95% CI: 1.28–1.37, p < 0.005) and by 53% in medium-density areas (20,001–30,000 registered ART patients) (OR = 1.53, 95% CI: 1.49–1.58, p < 0.005), compared to areas with fewer than 20,000 registered ART patients. On the other hand, people living in areas with a higher number of healthcare facilities were more likely to choose conventional HIV testing. The odds of self‐testing decreased by 15% in subdistricts with a medium number of healthcare facilities (15–25 facilities) (OR = 0.85, 95% CI: 0.82–0.87, p < 0.005) and by 27% in areas with a high number of facilities (26 or more) (OR = 0.73, 95% CI: 0.71–0.76, p < 0.005), relative to areas with fewer than 15 facilities. Additionally, communities with a high number of newly enrolled ART patients (≥2,901) showed a 31% lower likelihood of opting for self-testing (OR = 0.69, 95% CI: 0.67–0.72, p < 0.005). Subdistrict variations were evident, with Southern (OR = 2.04, 95% CI: 1.94–2.13, p < 0.005) and Mitchell's Plain (OR = 2.12, 95% CI: 2.03–2.23, p < 0.005) showing more than twice the odds of self‐testing compared to the Eastern subdistrict. Other subdistricts with significantly higher odds of self-testing included Western (OR = 1.63, 95% CI: 1.56–1.71, p < 0.005) and Klipfontein (OR = 1.12, 95% CI: 1.06–1.18, p < 0.005). Conversely, Northern (OR = 0.52, 95% CI: 0.48–0.55, p < 0.005), Tygerberg (OR = 0.55, 95% CI: 0.52–0.57, p < 0.005), and Khayelitsha (OR = 0.97, 95% CI: 0.83–0.91, p < 0.005) had significantly lower odds. Finally, testing preferences assessed through the multivariate logistic regression model highlighted the influence of both individual- and community-level factors. Consistent with the bivariate analysis findings, age remained a strong predictor of HIVST. Individuals aged 20–24 had 23% lower odds of using self-testing compared to those aged 18–19 (OR = 0.77, 95% CI: 0.73–0.82, p < 0.005), while those aged 25–49 had 49% lower odds (OR = 0.51, 95% CI: 0.48–0.53, p < 0.005). The oldest age group (50 years and above) had 86% lower odds of choosing self-testing compared to the youngest group (OR = 0.14, 95% CI: 0.13–0.15, p < 0.005). 5 Individuals residing in communities with a medium (20,001–30,000) and high (≥30,001) number of registered ART patients had 240% (OR = 3.40, 95% CI: 3.18–3.65) and 182% (OR = 2.82, 95% CI: 2.70– 2.96, p < 0.005) higher odds of using self-testing, respectively, compared to those in areas with low ART caseloads (<20,000). Additionally, living in areas with more newly enrolled ART patients was negatively associated with self- testing. Residing in communities with a medium number of new ART patients (1,800–2,900) was associated with 68% lower odds of self-testing (OR = 0.32, 95% CI: 0.29–0.34, p < 0.001), while living in areas with a high number of new ART initiations (≥2,901) was associated with 81% lower odds (OR = 0.19, 95% CI: 0.18–0.21, p < 0.001), compared to areas with a low number of new ART patients (<1,800). Unlike in the bivariate analysis, gender also played a significant role in the multivariate model, with females having 8% lower odds of choosing self-testing compared to males (OR = 0.92, 95% CI: 0.90– 0.94, p < 0.005). Additionally, individuals who received a positive HIV test result had 9% lower odds of having used self-testing compared to those who tested negative (OR = 0.91, 95% CI: 0.84–0.98, p = 0.005). The number of healthcare facilities was also positively associated with self-testing uptake. Living in areas with a medium (15–25) or high (≥26) number of healthcare facilities increased the odds of self-testing by 13% and 34%, respectively (OR = 1.13, 95% CI: 1.09–1.17, p < 0.005; and OR = 1.34, 95% CI: 1.26–1.43, p < 0.005), compared to areas with a low number of facilities (0–14). Conclusion: In conclusion, the study underscores the complex interplay of individual and community-level factors influencing HIV testing preferences in Cape Town. Younger age, recent HIV testing history, male gender, and residence in areas with higher number of registered ART patient and more healthcare facilities were associated with increased likelihood of HIV self-testing (HIVST). Conversely, older age, female gender, living in communities with more newly initiated ART clients, and receiving a positive HIV diagnosis were linked to a lower likelihood of using HIVST. Geographic disparities across subdistricts further highlight the need for targeted, context-specific strategies to enhance HIV testing uptake, particularly among underrepresented groups, and to optimize the reach and impact of self-testing interventions
Rural internship job preferences of final year medical students in South Africa: a discrete choice experiment
No full textTo achieve Sustainable Development Goal 3 in developing countries, Good health and wellbeing for all, the health workforce is vital however the unpopularity of rural medical practice results in widening healthcare inequalities between urban and rural areas. This study determined the heterogeneity in valuations for rural facility attributes by final year medical students at one South African public university to inform cost-effective recruitment policy recommendations. Focus groups conducted identified facility attributes, a D-efficient design was generated with 15 choice sets, each with two rural hospital alternatives and no opt-out option. An online, unlabelled discrete choice experiment (DCE) was conducted, the results effects coded, and mixed logit models applied. The final sample size was 193 (86,16% of the class), majority female 130 (66.33%), with urban origins 176 (89.80%), unmarried 183 (93.37%) and without children 193 (98.47%). Most had undergraduate rural medicine exposure 110 (56.12%) and intended to specialise 109 (55.61%). The main-effects mixed logit found advanced practical experience, hospital safety, correctly fitted personal protective equipment (PPE) and availability of basic resources the highest weighted attributes with their mean utilities increasing by 0.82, 0.64, 0.62 and 0.52 respectively (p=0.000). In contrast, increases in rural allowance and the provision of housing provided smaller mean utility increases of 0.001 (p<0.01) and 0.09 (p<0.05) respectively. The interaction terms; female, general practise and prior rural medicine exposure, were associated with higher weighting for hospital safety, mean utility increases 1.59, 1.82, 1.42 respectively (p=0.000). Participants were willing to pay ZAR 2636.45 monthly (95%CI: 1398.55;3874.355) to gain advanced practical experience (equivalent to 65.91% of current rural allowance). Medical students’ facility preferences have been found to be influenced by their gender, career aspirations and prior experienced with rural medicine. The policy recommendations derived from this research include publicising rural health facility “draw-cards” among medical graduates, such as the opportunity to gain practical experience, improving the physical and occupational safety at rural health facilities and providing greater transparency about rural facility attributes to medical graduates
Socio-economic factors associated with knowledge, attitudes, and practices response to the 2019 novel coronavirus (COVID-19) and preventive measures of COVID-19 in South Africa: An internet based cross-sectional study
No full textAs part of a comprehensive response for COVID-19 prevention and control, South Africa, as well as many other countries, implemented extensive health and hygiene interventions to curb the spread of the disease. Extensive educational campaigns on all social media platforms as well as government agencies have been implemented in South Africa, however, adherence to these interventions, is affected by people's knowledge, attitude, and practice (KAP) as well as the economic status for the given information to be effective. This KAP study was to examine changes in knowledge, attitudes and practices and socio-economic factors associated with the knowledge, attitude, and practice response to the 2019 novel coronavirus (COVID-19) and preventive measures of COVID-19 in South Africa: an internet-based cross-sectional study. Surveys in Egypt, Pakistan, Saudi Arabia, Malaysia, Vietnam, Jordan, Pakistan, China, Iran, Bangladesh, and Uganda revealed that most respondents had a good knowledge of COVID19. Methods The study used an analytical cross-sectional design, and it was conducted in South Africa. At the time of the study, it was impossible to do community-based surveys due to the COVID-19 pandemic, hence, data was collected online. Data was collected using an online electronic survey where participants completed the online questionnaire once. The survey was drawn up using REDCap software. The KAP results were analyzed as proportions and then the association between KAP and demographic characteristics was done using ordered logit regression models for knowledge, attitude, and practice scores. Results Of the 188 study participants, majority were females (57%) and about (43%) were males. For age and income, the means and standard deviations were [(36.84;10.89) & (R13 344.50; R14 765.23)]. A greater proportion of the participants resided in formal residents (74%), had at least attained matric education (74%), also resided in the Western Cape province (97%) and were employed full time (60%). Income was a significant predictor of knowledge and practices with a unit increase in income increasing the ordered log-odds scale of knowledge by 5.13, while reducing ordered log-odds (OLO) scale for practices by 1.28. While a unit increase in age increased the OLO of knowledge (0.02), attitudes (0.02) and practices (0.03). Having matric education increased the OLO of knowledge (0.75) and practices (1.06) compared to participants with less than grade 11 education, while for attitudes it reduced the OLO of attitudes by 1.12. Additionally, staying in an informal house reduced the OLO of knowledge (15.55), attitudes (0.08) and practices (44.97) compared to staying in flat or house. However, having access to water [knowledge (16.40) and practices (30.31)] and electricity [knowledge (1.80) and practices (49.96)] increased the OLO of knowledge and practices compared to not having access. While being full-time and part-time employed increased the OLO of attitudes and practices [full-time; attitudes(1.16) & practices (1.57)] ; [part-time; attitudes(0.25) & practices (0.44)]. Lastly, staying in formal residence area increased the OLO of knowledge (0.21), attitudes (1.67) and practices (0.02), compared to staying in informal residences. Regarding the knowledge dimension participants showed that they were knowledgeable [(65%;Good knowledge), (9%;Fair knowledge), (26%;Poor knowledge)]. While for attitudes participants generally reported poor attitudes [42%;(Poor attitudes), (35%;Fair attitudes) (23%;Good attitudes)]. Lastly, participants had fairly good practices [(62%;Good practices), (13%; Fair practices), (25%;Poor practices)]. Conclusion This study showed significantly higher proportions of people with good knowledge and good practices, however, it also recorded a greater proportion of the participants who had poor attitudes. This information would be useful in the formulation of policy for community projects addressing behavioural change and adds to the global data on the same subject. The personal responsibility narrative was used during the pandemic, however people found it difficult to adhere to lockdown restrictions thus multipronged action will be needed to address the factors that affect KAP
Neighbourhood deprivation and adult adiposity in South Africa
No full textOver the past three decades there has been a significant increase in adiposity - prevalence of accumulation of excess fat around some human organs - globally. This has been characterised by an increase of body mass index (BMI) among men and women. In Sub-Sahara Africa, South Africa has one of the highest prevalence of obesity and the country currently experiences some epidemiological transitions. Excess adiposity is a major risk factor for a number of non-communicable diseases creating a burden for individuals, families, the health care system and society at large (Colditz, 1999). Therefore, there are both direct and indirect costs that can be averted by effectively controlling the obesity epidemic. Still this can only be achieved when there is a good understanding of its determinants. This study sought to investigate association between neighbourhood deprivation and adult adiposity (a combination of body mass index and waist circumference), the association of neighbourhood deprivation and body mass index and waist circumference individually and to examine individual and household level determinants impacting adult adiposity. The study utilised the South African National Income Dynamic Survey (NIDS) 2012 (wave 3) and the ward level South African Index of Multiple Deprivation 2011 (SAIMD 2011) produced by Southern Africa Labour and Development Research Unit (SALDRU) and the Southern African Social Policy Research Institute/Insights (SASPRI) respectively. Individuals with high body mass index (BMI ≥ 25kg/m²) and an expanded waist circumference (WC ≥ 102cm for men and WC ≥ 88cm for women) were considered as having high adiposity. Multilevel logistic regression was used for data analysis due to hierarchical nature of the data to allow simultaneous examination of the impact of some socio-economic factors influencing adiposity. The results showed that individuals that were living in districts that are in quintile 3 (OR= 0.659; 95% CI 0.461, 0.942) of the multiple deprivation score had significantly lower odds of having high adiposity as compared to those living in the least deprived districts. Those living in districts that are in quintiles 3 (OR= 0.652; 95% 0.449, 0.945) and 4 (OR= 0.621; 95% 0.393, 0.983) of the multiple deprivation score were at significantly lower odds of having high BMI as compared to those living in the least deprived districts. When the analysis was stratified by gender the results showed that women living in districts in that are in quintiles 3 (OR= 0.654; 95% 0.450, 0.951) and 4 (OR= 0.624; 95% 0.394, 0.986) of the multiple deprivation score were at lower odds of having high adiposity as compared to women living in the least deprived district. The results for men on the other hand showed no association between adiposity and district level deprivation. Our results show that individual level characteristics and neighbourhood level deprivation regardless of how far distal has an impact on adiposity. Neighbourhood affluence seems to be a buffer that promotes weight gain. The impact of neighbourhood deprivation on adiposity is stronger among women as compared to men. However, further studies that employ a smaller area metric of analysis (preferably ward level) are required to better inform policy prescriptions of neighbourhood deprivation and adiposity
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