Department of Statistics, University of Johannesburg, Johannesburg 2028, South Africa.
School of Mathematics, Statistics and Computer Sciences, University of KwaZulu-Natal, Durban 4041, South Africa.
Int J Environ Res Public Health. 2022 Aug 25;19(17):10611. doi: 10.3390/ijerph191710611.
TB is preventable and treatable but remains the leading cause of death in South Africa. The deaths due to TB have declined, but in 2017, around 322,000 new cases were reported in the country. The need to eradicate the disease through research is increasing. This study used population-based National Income Dynamics Survey data (Wave 1 to Wave 5) from 2008 to 2017. By determining the simultaneous multilevel and individual-level predictors of TB, this research examined the factors associated with TB-diagnosed individuals and to what extent the factors vary across such individuals belonging to the same province in South Africa for the five waves. Multilevel logistic regression models were fitted using frequentist and Bayesian techniques, and the results were presented as odds ratios with statistical significance set at < 0.05. The results obtained from the two approaches were compared and discussed. Findings reveal that the TB factors that prevailed consistently from wave 1 to wave 5 were marital status, age, gender, education, smoking, suffering from other diseases, and consultation with a health practitioner. Also, over the years, the single males aged 30-44 years suffering from other diseases with no education were highly associated with TB between 2008 and 2017. The methodological findings were that the frequentist and Bayesian models resulted in the same TB factors. Both models showed that some form of variation in TB infections is due to the different provinces these individuals belonged. Variation in TB patients within the same province over the waves was minimal. We conclude that demographic and behavioural factors also drive TB infections in South Africa. This research supports the existing findings that controlling the social determinants of health will help eradicate TB.
结核病是可预防和可治疗的,但仍是南非的主要死因。结核病死亡人数有所下降,但 2017 年该国报告了约 32.2 万例新发病例。通过研究消除这种疾病的需求正在增加。本研究使用了 2008 年至 2017 年基于人群的国家收入动态调查数据(第 1 波至第 5 波)。通过确定结核病同时的多水平和个体水平预测因素,本研究调查了与被诊断患有结核病的个体相关的因素,以及这些个体在南非同一省份的因素在五个波次中存在何种差异。使用频率论和贝叶斯技术拟合多水平逻辑回归模型,并将结果表示为优势比,统计学意义设定为 < 0.05。比较和讨论了两种方法的结果。研究结果表明,从第 1 波到第 5 波一直存在的结核病因素包括婚姻状况、年龄、性别、教育程度、吸烟、患有其他疾病和咨询医疗保健从业者。此外,多年来,30-44 岁的单身男性患有其他疾病且未接受教育,他们与 2008 年至 2017 年期间的结核病高度相关。方法学研究结果表明,频率论和贝叶斯模型产生了相同的结核病因素。两种模型都表明,结核病感染的某种形式差异是由于这些个体所属的不同省份造成的。同一省份内的结核病患者在不同波次之间的变化很小。我们得出结论,人口统计学和行为因素也会导致南非的结核病感染。这项研究支持了现有的发现,即控制健康的社会决定因素将有助于消除结核病。