Application of Negative Binomial Regression for Assessing Public Awareness of the Health Effects of Nicotine and Cigarettes

Both the public and private sectors have acted responsibly to help decrease smoking-related deaths by putting health warnings on all cigarette packages. This study investigated the social or demographic factors associated with public awareness of health warnings on the harmful effects of environmental tobacco smoke based on baseline data collected by the South African Human Sciences Research Council (HSRC). Respondents in the survey were asked to recall thenumber of anti-smoking messages which appeared as warning messages on cigarette advertisements. The number of anti-smoking messages recalled ranged from 0 to 9 with a mean of 3.09 (variance of 5.99) and a median of 3.00. Because the variance was nearly two times greater than the mean, the negative binomial regression model provided an improved fit to the data and accounted better for overdispersion than the Poisson regression model, which assumed that the mean and variance are the same. The level of education and race were foundto be the most significant factors. Moreover, the lower socio-economic class nonsmokers’ anti-smoking messages recalling rate was 2.5 times that of the lower socio-economic class smokers. Unlike men, women’s anti-smoking message response rate increased with income

Analysis of demographic and health survey to measure poverty of household in Rwanda

The use of the asset index in poverty targeting is a modern technique. We used the principal component analysis (PCA) technique in order to create the asset index. Then the asset index was used to assess the socio-economic status (SES) of households. The reliability of the index was tested firstly by ascertaining whether the index was internally coherent, secondly the robustness was tested using the sub-indices such as housing infrastructure and ownership. The methodology is applied and demonstrated using the household survey data in Rwanda. The Rwanda data analysis showed that the age of household head, education level of the household head, gender of the household head, place of residence, the province of household head and size of the household (number of household members) were the significant predictors of poverty of the household in Rwand

Multiple correspondence analysis as a tool for analysis of large health surveys in African settings

Background: More than two thirds of the total population of Ethiopia is estimated to be at risk of malaria. Therefore, malaria is the leading public health problem in Ethiopia.Objective: To investigate the determinants of malaria Rapid Diagnosis Test (RDT) result and the association between socio-economic, demographic and geographic factors.Method: The study used data from household cluster malaria survey which was conducted from December 2006 to January 2007. A total of 224 clusters of about 25 households each were selected from the Amhara, Oromiya and Southern Nation Nationalities and People (SNNP) regions of Ethiopia. A multiple correspondence analysis was used to jointly analyse malaria RDT result, socio-economic, demographic and geographic factors.Results: The result from multiple correspondence analysis shows that there is association between malaria RDT result and different socio-economic, demographic and geographic variables.Conclusion: There is an indication that some socio-economic, demographic and geographic factors have joint effects. It is important to confirm the association between socio-economic, demographic and geographic factors using advanced statistical techniques.Keywords: MCA, CA, malaria, RDT

Balanced modified systematic sampling in the presence of linear trend

In the presence of linear trend, linear systematic sampling (LSS) is less efficient than stratified random sampling (STR) and more efficient than simple random sampling (SRS). Consequently, some authors have proposed modifications to the LSS design, which have shown to yield optimal results under certain conditions. In this paper, a further modified design, termed as balanced modified systematic sampling (BMSS), is proposed. BMSS is compared to various well-known modified LSS designs as well as LSS, SRS and STR. If half the sample size is an even integer, then BMSS is optimal. To obtain linear trend free sampling results for the other cases of the sample size, a BMSS with end corrections (BMSSEC) estimator is constructed. The results in this paper suggest that the proposed estimator performs better than all other estimators for odd sample sizes and even sampling intervals. Moreover, the proposed estimator is competitive for all other cases

A comparative study of multiple imputation and subset correspondence analysis in dealing with missing data

Methods: Multiple imputation and subset correspondence analysis are applied to a set of child asthma data that is mainly categorical and suffers from non-response. Differences in the methods and in the outcomes they produce are studied. In addition, the inclusion of interactions in a subset correspondence analysis is illustrated. Results: Despite the vast differences in the two approaches, they yielded similar results in the identification of genetic, environmental and socio-economic factors that affect childhood asthma. A number of exposure related variables were found to be associated with the greater severity of asthma. It was also found that a finer distinction between the asthma severity levels and their associations with factors was possible with a subset correspondence analysis, compared to the multiple imputation approach. Conclusions: Both multiple imputation and subset correspondence analysis were able to identify several factors associated with childhood asthma while at the same time successfully managing the missing data. This offers the researcher a choice to select the method that best suits his/her study

Assessment of prevalence and risk factors of diabetes and pre‑diabetes in South Africa

AVAILABILITY OF DATA AND MATERIALS : This study utilized existing survey datasets that are in the public domain and freely available from https://www.dhsprogram.com/data/dataset_admin/ login_main.cfm with the permission from the DHS Program.BACKGROUND : Diabetes prevalence, as well as that of pre-diabetes, is rapidly increasing in South Africa. Individuals with pre-diabetes have a high risk of developing type 2 diabetes, which is reversible with a change in lifestyle. If left untreated, diabetes can lead to serious health complications. Our objective was to assess the prevalence of diabetes and pre-diabetes, and to investigate the associated risk factors of each in the South African population. METHOD : This study made use of the South African Demographic Health Survey 2016 data. The study participants included 6442 individuals aged 15 years and older. A generalized additive mixed model was employed to account for the complex survey design of the study as well as well spatial autocorrelation in the data. RESULTS : The observed prevalence of pre-diabetes and diabetes was 67% and 22%, respectively. Among those who had never been tested for diabetes prior to the survey, 10% of females and 6% of males were found to be diabetic, and 67% of both males and females were found to be pre-diabetic. Thus, a large proportion of the South African population remains undiagnosed. The model revealed both common and uncommon factors significantly associated with pre-diabetes and diabetes. This highlights the importance of considering diabetic status as a three-level categorical outcome, rather than binary. In addition, significant interactions between some of the lifestyle factors, demographic factors and anthropometric measures were revealed, which indicates that the effects each these factors have on the likelihood of an individual being pre-diabetic or diabetic is confounded by other factors. CONCLUSION : The risk factors for diabetes and pre-diabetes are many and complicated. Individuals need to be aware of their diabetic status before health complications arise. It is therefore important for all stakeholders in government and the private sector of South Africa to get involved in providing education and creating awareness about diabetes. Regular testing of diabetes, as well as leading a healthy lifestyle, should be encouraged.The South African Medical Research Council through its Division of Research Capacity Development under the Biostatistics Capacity Development partnership with the Belgian Development Agency (Enabel) under its framework of Building Academic Partnerships for Economic Development (BAPED).am2023Statistic

Costing national road accidents with partially complete national data: the case of Lesotho

No Abstract.African Safety Promotion Vol. 5(1) 2007: pp. 57-6

Teaching statistics to social science students: Making it valuable

In this age of rapid information expansion and technology, statistics is playing an ever increasing role in education, particularly also in the training of social scientists. Statistics enables the social scientist to obtain a quantitative awareness of socioeconomic phenomena hence is essential in their training. Statistics, however, is becoming increasingly problematic in its influence on the lives of social science students. Has statistics education of social science students evolved in order to keep pace with changes in modern society? This article examines the common trends in teaching statistics to social science students and then makes some suggestions that would potentially increase the social science graduate's appreciation for the power of statistics in their profession. South African Journal of Higher Education Vol. 20(4) 2006: pp.503-51

Demographic and academic factors affecting research productivity at the University of KwaZulu- Natal

Research output affects both the strength and funding of universities. Accordingly university academic staff members are under pressure to be active and productive in research. Though all academics have research interest, all are not producing research output which is accredited by the Department of Education (DOE). We analyzed the demographic and academic factors that affect DOE recognized research productivity of academics at the University of KwaZulu-Natal (UKZN) between 2004 and 2008. The results show that the demographic and academic profiles of staff that produce researchoutput differ from faculty to faculty. Thus, the intervention strategies that increase the number of research productive academics should be faculty based rather than being university based