Trends in Obesity and Diabetes Across Africa in 1980-2014
The broad topic area of the study by the Africa Working Group (2017) is obesity and diabetes occurrence patterns in African regions, both as a whole and in large countries of the area. In order to examine the progression and promote the policymaking process, the study assessed such variables as age-standardized median body mass index and diabetes occurrence in African states from 1980 to 2014 (Africa Working Group, 2017). The population of interest and sample in the study is the African population aged 18 and higher. For body mass index calculations, the researchers analyzed data from 245 population-based questionnaires with more than 1 million individuals aged 18 and 76 questionnaires with 182,000 people for diabetes projections (Africa Working Group, 2017). For body mass index, data was gathered in 50 states, more specifically 94 percent of African countries, between 1984 and 2014 (Africa Working Group, 2017). Meanwhile, for diabetes, data was retrieved from 32 states, more specifically, 60 percent of African countries, between 1981 and 2014.
As for the sampling method, to evaluate diabetes prevalence in persons 18 years of age, the researchers used statistics from African and global population-based researchers that analyzed height and body weight. A Bayesian hierarchical analysis was used to predict patterns by gender in average body mass index and diabetes predominance (Africa Working Group, 2017). An example of inferential statistics is provided in the findings, with the prevalence of diabetes in men rising from 3.4% to 8.5% and 4.1% to 8.9% (6.9–11.2) in women. The predominance was identified with descriptive statistics, such as fasting blood glucose of 7.0 mmol/l, the prevalence of diabetes in the family, or usage of medication or glucose control agents.
Epidemiology and Survival Outcomes of Breast Cancer
The broad topic area of the study conducted by Liu et al. (2017) is the prevalence of breast cancer among Taiwanese women. Among the variables found in the study, the significant variables included the age of the patients, their place of residence, and income levels. The population of interest for the study was the female population in Taiwan between the years 1997 and 2013 (Liu et al., 2017). However, the population in 2013 served as a reference and was used as a sample to identify changes in breast cancer prevalence and severity.
Between these years, the research population included 22 million qualified NHI members in Taiwan, which is an example of a descriptive statistic. A total number of 125,253 female breast cancer cases were detected that served as a sample (Liu et al., 2017). Women in rural regions accounted for just one-third of all breast cancer diagnoses. In contrast, women in cities and suburbs each accounted for one-third of all instances, which is an example of inferential statistics (Liu et al., 2017). In addition, the incidence of breast cancer decreased among women with lower income (Liu et al., 2017). According to the statistical investigation, breast cancer was shown to be more common in Taiwan’s high-income metropolitan regions.
As for the sampling method, researchers estimated the age-standardized occurrence of breast cancer between the years 1997 and 2013. In the study, the NHI database served as the critical data provider (Liu et al., 2017). This system gathered healthcare information on all NHI-eligible patients on a regular basis (Liu et al., 2017). Researchers utilized the National Cancer Registry as a reference to determine the positive and negative predictive value of the diagnosis of breast cancer in the NHI system in order to ensure its accuracy.
A Quantitative Observational Study of Physician Influence on Hospital Costs
The broad topic area of the study conducted by Wong et al. (2018) is the healthcare professionals’ influence on hospital costs. In the given work, researchers investigated and evaluated the magnitude of physician impact on hospital inpatient expenditures apart from business services using all-payer inpatient data from two states (Wong et al., 2018). Thus, the study involves such variables as costs of inpatient hospital visits and healthcare professionals’ characteristics, as well as the type of service financing.
The population of interest and sample in the study is healthcare professionals in two states, such as Arizona and Florida. The researchers used statistics from all payers from two given states, which included 15,237 doctors and 2.5 million hospital visits, which is a descriptive statistic (Wong et al., 2018). As for the sampling method for the two states, the researchers utilized the Healthcare Cost and Utilization Project 2008 State Inpatient Databases (Wong et al., 2018). All patient admissions for practically all critical medical nongovernment facilities in the relevant states were included in these records (Wong et al., 2018). The SID contains a specific diagnosis process, as well as total costs and patient information such as age, gender, ethnicity, and anticipated financing sources, more specifically insurance or self-pay (Wong et al., 2018). Researchers used empirical models to use a hierarchical framework that includes health professional features, patient history, socioeconomic status, medical danger, and facility qualities. According to the findings, visits of female healthcare professionals provided a 0.1 percent lower average cost than visits of male professionals, which is an inferential statistic.
References
Africa Working Group. (2017). Trends in obesity and diabetes across Africa from 1980 to 2014: An analysis of pooled population-based studies. International Journal of Epidemiology, 46(5), 1421–1432.
Liu, F. C., Lin, H. T., Kuo, C. F., See, L. C., Chiou, M. J., & Yu, H. P. (2017). Epidemiology and survival outcome of breast cancer in a nationwide study. Oncotarget, 8(10), 16939.
Wong, H., Karaca, Z., & Gibson, T. B. (2018). A quantitative observational study of physician influence on hospital costs. The Journal of Health Care Organization, Provision, and Financing, 55, 1-12. Web.