Week 1Collapseweek 1 Discussionmohammadi Response
3 days ago
Ijeoma Nwazuruokeh
RE: Week 1 Introduction- Why Learn Statistics?
Hello Dr. Tawfik,
Why is it important that we learn and understand statistics?
As public health leaders, we will constantly be directly or indirectly exposed to statistical representations of public health issues. The understanding of reports and statistical analysis is essential for learning from research work (Frankfort-Nachmias, et al., 2020). In epidemiology, statistical significance can provide useful information that explains the likelihood of observed differences was not by chance (Bhattacharya, 2013). Information from statistics further strengthens the need for advocacy and public health policy to impact public health issues. Statistics especially now is part of our everyday life; the pandemic has constantly introduced us to data that guides our understanding of the virus and what mitigations in place work to reduce the burden of disease.
References
Bhattacharya, D. (2013). Public health policy. Issues, theories, and advocacy. Jossey-Bass.
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.).: Sage
4 days ago
Joy Garba
RE: Discussion – Week 1
The Research Article – Evaluation of a community-based intervention for health and economic empowerment of marginalized women in India by Sharma et al., 2020
Introduction
The article, Evaluation of a community-based intervention for health and economic empowerment of marginalized women in India understand how Empowered women have improved decision-making capacity and can demand equal access to health services (Sharma et al., 2020). Women groups are given awareness through Community-based interventions based on maternal and child health (MCH) through cost-effective approaches to improve access to health services (Sharma et al., 2020). The study evaluated a community-based intervention to enhance marginalized women’s awareness and utilization of MCH services and access to livelihood and savings from two districts of India.
Describing the usefulness of the research article
The research was done to explore interventions to improve marginalized women’s combined health and economic outcomes in India.
Identifying the independent variables and Dependent variables using Y=f(X) +E notation
The X and Y represents variables where Y is the dependent Variable and X the independent variable. f is a function that shows the relationship between the dependent variable and the independent variable. In this research, the dependent variable is the effect that is evaluated for a result which is marginalized women in India, and the independent variable is the cause which is the community-based intervention for health and economic empowerment (Frankfort-Nachmias et al., 2020).
How might the research models presented be wrong? What types of an error might be present in the reported research?
Questions The researcher answered the questions, including demographic questions, awareness of maternal and child health care, and understanding national health insurance schemes (Sharma et al., 2020). Other information on the possession of bank or post-office accounts and work participation by the women under the significant income-generating scheme of the government of India was asked by the researcher (Sharma et al., 2020). The research design used cannot ascertain the efficacy of the intervention (Sharma et al., 2020).
There could have been some errors like Sampling and randomized errors. There was no control group to compare against the experimental group of women sampled in the research. The generalization and validity of the study were therefore limited (Sharma et al., 2020). The sampling error could be from a generalized population of women from where the sample is drawn (Dietz & Kalof, 2009). The sample size may not represent the population of women observed during the study to generalize the findings. The data collected was collected from two districts of Uttar Pradesh, which were different from many other geographies not in all the districts in India (Sharma et al., 2020). However, both communities had a large population of marginalized people and limited availability of health services.
References
Dietz, T.,& Kalof, L. (2009). Introduction to Social Statistics: The Logic of Statistical reasoning. West Sussex, United Kingdom: Wiley-Blackwell.
Frankfort-Nachmias, C., Leon-Guerrero, A. Y., & Davis, G. (2020). Social Statistics for a Diverse Society (9th ed.). SAGE Publications, Inc.
Sharma, S., Mehra, D., Akhtar, F., & Mehra, S. (2020). Evaluation of a community-based intervention for health and economic empowerment of marginalized women in India. BMC Public Health, 20(1), 1766. https://doi-org.ezp.waldenulibrary.org/10.1186/s12889-020-09884-y
ErvaJean Stevens
RE: Discussion – Week 1
COLLAPSE
Week 1 Discussion
Mohammadi et al., (2021) conducted research to identify risk factors for late HIV diagnosis and determined survival of people living with HIV in Iran. The retrospective cohort study had a sample size of 4,402 HIV positive patients and spanned data from 1987 to 2016. The research concluded a 57% prevalence of late diagnosis among Iranians and risk factors including being male 50 years or older, transmission through blood transfusion and infection with TB.
Late diagnosis of HIV is a global challenge in the attempt to realize the goal of achieving epidemic control by 2030 (UNAIDS, 2021). The research findings can assist policy makers, advocates and programmers to prioritize men 50 years and older and persons with TB for HIV screening programmes. Through this prioritization, persons who may be HIV positive can be diagnosed early, access anti-retroviral treatment and live a healthier life. At a community level, it reduces the risk of HIV transmission.
The research had two main dependent variables (Y); late diagnosis and survival. These variables as outlined by (Dietz, T., & Kalof, L., 2009) are influenced by the independent variables (X) which can be deduced as being a man over the age of 50, being a person who inject drugs and a person positive for TB. Applying the formula, Y=X(F) + E to the research, being a man over 50 years old, or a person who inject drugs or being diagnosed with TB may not accurately explain late HIV diagnosis. The possible errors (E) must be taken into consideration when considering the statistical model used in the analysis and interpreting the results.
Several limitations are associated with this research. The data used was not collected for research purposes and due to the nature of the study and the sensitivities around HIV and confidentiality, the data could not be verified. This exposes the research to selection bias or information bias. Furthermore, there are several documented variables that affect late diagnosis such as access to services, legal environment and stigma and discrimination that were not included in the analysis (UNAIDS, 2021). These were not measured in the research, nor were their confounding effects considered. The author highlighted in the article that the results of the research are questionable (Mohammadi et al., 2021).
References
Mohammadi, Y., Mirzaei, M., Shirmohammadi-Khorram, N., & Farhadian, M. (2021). Identifying risk factors for late HIV diagnosis and survival analysis of people living with HIV/AIDS in Iran (1987-2016). BMC Infectious Diseases, 21(1), 390. https://doi-org.ezp.waldenulibrary.org/10.1186/s12…
Dietz, T., & Kalof, L. (2009). Introduction to social statistics: The logic of statistical reasoning. West Sussex, United Kingdom: Wiley-Blackwell.
The Joint United Nations Programme on HIV and AIDS (2021). Global AIDS strategy Geneva.
Sandra Porter
RE: Discussion – Week 1
Hello All,
The public health initiative that I will like to focus on is reducing the obesity rates throughout communities to lower diabetic diagnoses. One major program that I can highlight is the National Diabetes Program.
Brief Description
The National Diabetes Prevention Program (National DPP) is a partnership of public and private organizations working to prevent or delay type 2 diabetes. Partners make it easier for people at risk for type 2 diabetes to participate in evidence-based lifestyle change programs to reduce their risk of type 2 diabetes. This is a 12-month group-based program with 16 one-hour weekly sessions for the first four months, followed by four months of bi-weekly sessions, and once-per-month sessions for the last four months; designed to be interactive and fun, and empowering. Topics include healthy eating, weight loss, increasing physical activity, reducing stress, problem solving, motivation, and long-term maintenance of healthy lifestyle changes.
Economic Principles
According to the CDC (2020), Modeling and economics studies use computer models to simulate the long-term health and cost outcomes of diabetes interventions. With limited heath care resources, decision-makers need information on the economic burden of diabetes, the long-term effects of diabetes interventions and policies, and which interventions offer the largest health benefit.
- Cost-effectiveness studies: help clinical and public health policy decision makers make evidence-based policy decisions and set intervention priorities.
- This principle can be easily applied through non-profits and private sectors. For example, Kaiser Permanente of Georgia (KPGA), has launched the NDPP and gained the CDC Full-Recognition award. With this award, anyone who is insured by Kaiser can utilize the program at no additional cost with a partner (National Diabetes Prevention Program 2015).
- Systematic Reviews on Cost-Effectiveness of Interventions: This study is designed to gather and analyze evidence from published literature on the cost-effectiveness of interventions for managing type 1 and type 2 diabetes and preventing type 2 diabetes.
- Computer Simulation Models on Long-Term Cost-Effectiveness of. Interventions: This study uses computer simulation models to assess the long-term cost-effectiveness of interventions for managing type 1 and type 2 diabetes and preventing type 2 diabetes (Modeling and Economics 2020).
Success of the initiative
The overall strategies of the program can promote a successful environment if those who are pre-diabetic abide by the goals listed.
If members are able to lose approximately 5% of their weight and adhere to the calorie count, then the pre-diabetic stage can be faded out. By losing the weight, one can jumpstart theory journey to a healthier lifestyle.
References
Centers for Disease Control and Prevention. (2019, August 10). National Diabetes Prevention Program. Centers for Disease Control and Prevention. https://www.cdc.gov/diabetes/prevention/index.html.
Centers for Disease Control and Prevention. (2020, September 9). Modeling and Economics. Centers for Disease Control and Prevention. https://www.cdc.gov/diabetes/research/modeling-economics.html.
National Diabetes Prevention Program. National Diabetes Prevention Program | Health Classes and Programs | Health & Wellness | Kaiser Permanente. (n.d.). https://healthy.kaiserpermanente.org/georgia/health-wellness/classes-programs/details/national-diabetes-prevention-program.
2 days ago
Dominique Morgan
RE: Discussion – Week 1
Post a brief description of the public health initiative you selected
The United States has the highest maternal mortality rate among developed countries (Tikkanen et al., 2020). The infant mortality rate in the United States had a decrease of 2.3% from 2017 to 2018 but remained higher compared to similar countries (Xu et al., 2020). The Healthy Mothers, Healthy Babies Coalition of Georgia has been a constant and bold voice for changes in access to healthcare and improvements in health outcomes for Georgia’s moms and babies (Healthy Mothers Healthy Babies Coalition of Georgia [HMHBGA], n.d.). Since 1974, HMHBGA has offered direct services to mothers and babies, participates in collaborative advocacy, and provides community education (HMHBGA, n.d.). Most notably, they provide perinatal education (before and after birth), including maternal care information, infant mortality prevention information, and other resources (HMHBGA, n.d.).
Describe three economic principles and how they may have been applied to that public health initiative
The following economic principles are used as aids to assist in understanding society and the decisions they make (Getzen, 2013). The first principle, trade, says that individuals participate in exchanging or trading things, time, money, and information to better themselves on both sides (Getzen, 2013). HMHBGA applies the principle of trade in their practices and processes by exchanging information between program staff, program participants (mothers and families), legislators, funding partners, and other community organizations. The information being traded ranges from prenatal information, referrals, agency information, and more. The second principle is investment which is taking specific actions now to increase future successes and productivity (Getzen, 2013). HMHBGA applies the principle of investment in their practices by educating their participants on maternal and infant health to ensure future success in both mom and babies’ lives. They are hoping to impact the knowledge that mothers and families have now to be more aware and better equipped to lead families going into their future. Also, they apply this principle with their advocacy efforts to change future legislation concerning mothers and children. The third principle is that organizations adapt and evolve, looking at the evolution of trust and efficiency in exchanges. HMHBGA uses laws, policies, and partnerships with various funding sources to effect change in maternal and child health. HMHBGA advocates with state and federal legislation to enact changes that will directly impact families.
Explain how they may have contributed to the success of the initiative.
The principles of trade, investment, and organizations adapting and evolving do appear to have contributed to the success of HMHBGA initiatives. Their educational efforts have resulted in 100% of participants reporting increased knowledge in maternal and infant topics and 50,000 Georgia families being assisted in the last year (HMHBGA, n.d.). Through their advocacy efforts and partnering with legislators, healthcare providers, businesses, and other community organizations, HMHBGA has successfully encouraged and influenced the passing of policies that promote access to care for women and children’s health outcomes. Two of the most recent bills that HMHBGA advocated for that passed in Georgia for 2021 were HB 146 that “provides three weeks of paid parental leave for teachers and eligible state employees following the birth, adoption or foster placement of a child,” and HB 231 that “expands the applicability of protective orders for victims of stalking to include people with whom they have had a current or past pregnancy or relationship” (HMHBGA, n.d.). Policies are an influential aspect of determining how public health is provided, reimbursement, and access (Laureate Education, 2012). Overall, economics in public health involves backing the decision making of how society can use resources, time, information, and more to meet goals (Tudor Edwards et al., 2013).
References
Getzen, T.E. (2013). Health economics and financing (5th ed.). John Wiley & Sons Inc.
Healthy Mothers Healthy Babies Coalition of Georgia. (n.d.). Healthy Mothers Healthy Babies Coalition of Georgia. https://hmhbga.org/
Laureate Education. (2012). Introduction to economics [Video]. Walden University Blackboard. https://class.waldenu.edu
Tikkanen, R., Gunja, M.Z., FitzGerald, M., & Zephyrin, L. (2020). Maternal mortality and maternal care in the United States compared to 10 other developed countries. The Commonwealth Fund. https://www.commonwealthfund.org/publications/issue-briefs/2020/nov/maternal-mortality-maternity-care-us-compared-10-countries
Tudor Edwards, R., Charles, J.M., & Lloyd-Williams, H. (2013). Public health economics: a systematic review of guidance for the economic evaluation of public health interventions and discussion of key methodological issues. BMC Public Health, 13(1), 1–26. https://doi-org.ezp.waldenulibrary.org/10.1186/1471-2458-13-1001
Xu, J., Murphy, S.L., Kochanek, K.D., & Arias, E. (2020). Mortality in the United States, 2018. Centers for Disease Control and Prevention. https://www.cdc.gov/nchs/products/databriefs/db355.htm