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Measures in Epidemiology
Epidemiology is the backbone of measuring a population’s mortality and morbidity occurrence. These measures provide insights to guide health intervention efforts to reduce disease occurrence and societal burden (Friis & Sellers, 2021). Also, it provides a tool for stakeholders to examine the effectiveness of health intervention strategies targeting a given population. This paper aims to calculate sex ratios and provide possible reasons behind the differences. Also, this paper discusses the infant mortality rates in developing vs developed countries. Lastly, strategies a community healthcare nurse can use to help at-risk populations and combat future incidences are discussed.
Reasons for the Differences in Sex Ratios
The high sex ratio recorded from the calculation shows a higher prevalence of malignant Neoplasms among males than females. Many factors could be attributed to these results. First, sex is a crucial factor that informs malignant Neoplasms, disease progression and mortality, especially across the different types of cancer (Kim et al., 2018). This source posits that cancer incidence among men stood at 20% higher than among women, and the mortality for this condition stood at 40% higher among men than women between 2009 and 2013. Sex influences vulnerability due to the uniqueness of genetics or molecular makeup. Evidence from the literature shows the differences in chemotherapy efficacy and toxicity between the male and female participants (Kim et al., 2018). Adverse reactions to cancer therapy were noted among women more than men. Also, the high exposure due to the nature of work or living environment could inform the differences in the results. The variabilities in health-seeking behaviors between men and women and subsequent screening for malignant Neoplasms could affect the difference.
The results show a high HIV mortality rate among males than females. One of the reasons that could explain these results is the differences in HIV exposure. Sajadipour et al. (2022) found a higher prevalence among males than females. These results mainly resulted from a history of imprisonment and drug abuse (Sajadipour et al., 2022). The high rate of drug abuse among males could influence the seen results because drugs impair judgement leaving the abusers vulnerable to high-risk behaviors such as unprotected sex and sex with multiple partners. The calculated results show high rates of Septicemia-related mortality among females than males. The reasons that could contribute to these findings include the difference in Septicemia susceptibility and the high prevalence of conditions that leave females vulnerable to septicemia.
Infant Mortality Rates in Developing and Developed Countries
Developing countries record disproportionately higher infant mortality rates than developed economies. The World Health Organization (2022) reports that Sub-Saharan Africa has the highest neonatal mortality rates, with 27 deaths per 1000 live births. South Asia ranks second in this rating, with 23 deaths per 1000 live births (WHO, 2022). These statistics indicate that a child born in sub-Saharan Africa is ten times more vulnerable to death within the first month than a child born in a developed country.
Causes
Socioeconomic factors influence child mortality. Rahman et al. (2022) found that increased public expenditure on healthcare programs can improve the health of a population and reduce adverse outcomes. Lack of resources in developing countries translates to low expenditure on healthcare hence the poor health outcomes (Rahman et al., 2022). Increased expenditure of public resources on healthcare allows poor people to easily access healthcare services.
Low education levels among the population in some developing countries are another reason behind the high infant mortality rates. Education creates awareness about healthy lifestyles, including preventive care, such as ensuring that the child is up to date with the age-appropriate vaccination (Rahman et al., 2022). Besides, education influences one’s employment prospects which also dictates income level. Unemployment among many people in developing countries means a lack of health insurance and access to healthcare services, which can also contribute to high infant mortality rates.
HIV prevalence is another factor affecting infant mortality rates. Rahman et al. (2022) found a positive and significant association between HIV and infant mortality. It is noted that the HIV disease prevalence, especially in sub-Saharan Africa, contributes to the high infant mortality in this part of the world. A study by Baraki et al. (2020) found out that a child sex, prematurity, multiple births, and residence posed a higher risk for infant mortality among Ethiopia’s general population in 2016.
Strategies a Community Healthcare Nurse Can Use in Order to Help At-risk Populations and Combat Future Incidences.
One of the strategies community health nurses can employ to help at-risk populations and combat future incidence is health education and awareness creation. Notably, the community health nurse can focus on promoting healthy lifestyles among vulnerable populations to reduce the disease burden in society (Stanhope & Lancaster, 2019). Besides, health promotion can help change people’s attitudes towards health-seeking behaviors.
The community health nurse can conduct regular screening within the society to help identify diseases at the early stages where they can be successfully treated before it progresses to advanced stages. Initiatives on this front include screening for high blood pressure, diabetes, and cancer. Furthermore, some people register poor health outcomes due to the need for more knowledge and resources to improve their health and well-being (Stanhope & Lancaster, 2019). Hence, a community health nurse can empower individuals by supporting self–management skills and providing resources that can help improve people’s health.
A community health nurse can improve health outcomes by conducting disease surveillance and data analysis. The data should cover disease trends and epidemiologic disparities in health outcomes (Stanhope & Lancaster, 2019). Such surveillance findings can guide public health authorities to address health challenges such as high infant mortality (Stanhope & Lancaster, 2019). Also, surveillance and data analysis can be used to monitor the effectiveness of health intervention strategies.
The community health nurse can use the Epidemiologic (EPI) triangle to influence disease prevention and health promotion efforts. The EPI triangle contains three elements that affect disease outbreaks and epidemics in society (Kuhl, 2021). At one corner of the triangle is the agent, which refers to the disease-causing microbes, followed by the host, which is human, and lastly environment, which entails the external factors that influence disease transmission (Kuhl, 2021). Based on this concept, a community health nurse can break the disease transmission circle by influencing each element. For instance, health education can empower the host to ensure a healthy lifestyle, thus reducing disease vulnerability. Secondly, the host can be empowered to improve living conditions and hygiene in their environment to alleviate disease spread. A clean and healthy environment reduces the risk of some pathogen transmission.
Conclusion
Epidemiology provides insights regarding mortality and morbidity. The differences in sex ratios could be attributed to health-seeking behaviors and individual lifestyle choices, among other factors. A community health nurse can use different strategies to help at-risk populations and combat future incidences. These include disease screening and health promotion, and awareness creation. The concept of the EPI triangle can also be used to help shape public health intervention to reduce disease burden in a community.
References
Baraki, A. G., Akalu, T. Y., Wolde, H. F., Lakew, A. M., & Gonete, K. A. (2020). Factors affecting infant mortality in the general population: Evidence from the 2016 Ethiopian demographic and health survey (EDHS); a multilevel analysis. BMC Pregnancy Childbirth, 20(1): 299. https://doi.org/10.1186/s12884-020-03002-x
Friis, R. H., & Sellers, T.A. (2021). Epidemiology for Public Health Practice. Jones & Bartlett Learning.
Kim, H. I., Lim, H., & Moon, A. (2018). Sex Differences in Cancer: Epidemiology, Genetics and Therapy. Biomolecules & Therapeutics, 26(4), 335–342. https://doi.org/10.4062/biomolther.2018.103
Kuhl, E. (2021). Computational Epidemiology. Springer International Publishing.
Rahman, M. M., Alam, K., & Khanam, R. (2022). Socio-economic factors affecting high infant and child mortality rates in selected African countries: does globalisation play any role?. Globalization and Health, 18(1), 1-13. https://doi.org/10.1186/s12992-022-00855-z
Sajadipour, M., Rezaei, S., Irandoost, S. F., Ghaumzadeh, M., Gholami, M., Salimi, Y., & Jorjoran Shushtari, Z. (2022). What explains gender inequality in HIV infection among high-risk people? A Blinder-Oaxaca decomposition. Archives of Public Health, 80(1), 1-9. https://doi.org/10.1186/s13690-021-00758-2
Stanhope, M., & Lancaster, J. (2019). Public health nursing e-book: Population-centered health care in the community. Elsevier Health Sciences.
World Health Organization (2022 January 28). Newborn Mortality. https://www.who.int/news-room/fact-sheets/detail/levels-and-trends-in-child-mortality-report-2021#:~:text=Sub%2DSaharan%20Africa%20has%20the,36%25%20of%20global%20newborn%20deaths.
Appendix
Compute the sex ratios for the numbers of deaths shown in the following table. Compare the sex ratios for mortality from the specific causes shown in the table and, based on your own ideas and research, suggest reasons for the differences in the sex ratios for the three causes of death.
| Number of Deaths, 2016
|
||
| Cause of Death Males | Females | Males |
|
All Malignant Neoplasms |
314,571 | 263,467 |
| HIV Disease | 4,554 | 1,606 |
| Septicemia | 19,678 | 20,935 |
Sex ratios for mortality for the specific causes in 2016 can be calculated as follows.
All malignant Neoplasms:
Total male deaths= 314,571
Female deaths = 263,467
Hence, the sex ratio is (314,571 / 263,467) * 100 = 119.3
For, HIV Disease:
Total deaths recorded among males= 4,554
Deaths recorded among females: 1,606
Sex ratio: (4,554 / 1,606) * 100 = 283.6
For Septicemia:
Total deaths recorded among males: 19,678
Deaths recorded among females: 20,935
Hence, the sex ratio: (19,678 / 20,935) * 100 = 93.9
