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Problem Statement
Diabetes is a severe disease that may impair an individual and considerably decrease their life expectancy and overall quality of life. According to a 2014 estimate, nearly 29.1 million people in the U.S., or approximately 9.3% of the U.S. population, suffer from diabetes; out of these, only 21.0 million people had their diabetes diagnosed, whereas estimated 8.1 million people (27.8% of all the diseased) did not receive an appropriate clinical diagnosis for their diabetes (Centers for Disease Control and Prevention [CDC], 2014).
However, while studies often reveal that there is an association between the prevalence of diabetes and an individuals socioeconomic status, as well as their immigration status (immigrants often suffer from a higher prevalence of this disease) (Chaufan, Constantino, & Davis, 2012; Fedeli et al., 2015; Jaffiol, Thomas, Bean, Jégo, & Danchin, 2013), no current information has been found about the dependence of the prevalence of diabetes on the social status of the immigrant population in the state of California, which creates a gap. Because it is crucial to be aware of the factors which are associated with a higher or lower incidence of diabetes in a particular population, the current prospectus is offered so as to investigate these factors.
The problem of association between the social status of individuals and the prevalence of diabetes among them is meaningful because it is known that in general, the social status is associated with a higher incidence of this disease (Fisher-Hoch et al., 2010; Hwang & Shon, 2014; Kivimäki et al., 2015; Stringhini et al., 2013), and it is important due to the fact that knowing which groups exactly have a higher risk of achieving diabetes is needed so as to better be able to prevent those who are at a higher risk of getting diabetes from achieving it, as well as to better identify individuals who have undiagnosed diabetes (it has already been noted above that in 2014 in the U.S., estimated 27.8% of those having diabetes did not obtain a proper clinical diagnosis; CDC, 2014).
Studying the association between the social status and the frequency of diabetes incidence in the immigrant population is also justified due to the fact that immigrants have often been shown to often demonstrate a more frequent incidence of this disease (Fedeli et al., 2015; Janevic, Borrell, Savitz, Echeverria, & Rundle, 2014; OConnor, Dobra, Voss, Pihoker, & Doorenbos, 2015); however, the prevalence varied in different populations (Fedeli et al., 2015). Therefore, possessing data from a particular region is also pivotal so as to take into account the specifics of the population of that region.
Because of this, the purpose of the proposed study will be to investigate the relationship between the socioeconomic status of immigrants in California and the prevalence rates of diabetes. It should be stressed that socioeconomic status can often be assessed by taking into account the education that an individual has and their income. Thus, the research question for the offered study will be as follows: Is there an association between diabetes and socioeconomic status (income and education) among immigrants in California? Therefore, the target population will be immigrants in the state of California.
The dependent variable will be the diabetes status of participants, whereas the independent variables will be the income and the education of respondents. It is speculated that lower-income and lower level education will be associated with a higher prevalence of diabetes.
Significance
The offered study is aimed at filling the research gap related to the absence of relevant information pertaining to the relationship between the social status of immigrants in California and the prevalence of diabetes among them; the gap will be filled by analyzing whether such a relationship can be inferenced from the data used in the study, and what type of a relationship it is. The practical contribution that will be made as a result is determined by the fact that knowing which factors can help predict the incidence of diabetes allows for identifying the populations that are at a greater risk of developing this disease.
Understanding which populations are more susceptible to diabetes is pivotal in practice because once these populations have been identified, it is possible to implement targeted interventions aimed at reducing the prevalence of diabetes in them. In addition, public policies might be shaped so as to address the need to reduce the rates of occurrence of this disease in the susceptible populations, which are to be identified within the offered study.
The proposed claim that a lower socioeconomic status (as identified by lower levels of education and income) will be associated with a higher incidence of diabetes in the immigrant population of California aligns with the named research problem about the relationship between the social status of individuals and the prevalence of diabetes among them by allowing for concretely establishing that relationship; this reflects the potential relevance of this study to the society, for identifying such a relationship might help prevent diabetes in the vulnerable populations. Such prevention might lead to positive social change by increasing the quality of life of those who would not develop diabetes thanks to the implemented preventive measures.
Background
The main assertion of the proposed study that a lower socioeconomic status, as determined by lower levels of education and income, is associated with a higher incidence of diabetes in immigrants, is supported by a number of authors researching the same problems in similar populations in other regions. When it comes to the immigrant/non-immigrant status, Chaufan et al. (2012) found that immigrants and Latinos in Californian urban areas faced barriers to healthy eating, resulting in higher diabetes prevalence.
According to Fedeli et al. (2015), immigrants in Italy also had a high prevalence of diabetes, especially if they originated from South-East Asia and Africa; however, European immigrants had rates of diabetes prevalence similar to those of Italians. Fisher-Hoch et al. (2010), stating that Mexican Americans face an increased risk of diabetes, found out that those of them who had a lower socioeconomic status suffered from diabetes more often.
On the other hand, Ford, Narayan, & Mehta (2016) discovered that foreign-born Blacks living in the U.S. had lower rates of diabetes than U.S.-born Blacks, but taking into account, the body mass index eliminated the advantage. However, OConnor et al. (2015) found that East African immigrants had approximately a four times higher prevalence of diabetes that non-immigrant Black youth in the state of Washington. Next, Janevic et al. (2014) state that it is suggested that living in an ethnic enclave decreases the risk of gestational diabetes among immigrants; however, their study found no such dependence.
On the other hand, when considering the impact of socioeconomic status, Hwang & Shon (2014) found that Korean persons with the lowest socioeconomic status were more likely to have diabetes than those with the highest socioeconomic status; similar results were obtained by Jaffiol et al. (2013) in France, Krishnan, Cozier, Rosenberg, & Palmer (2010) in the U.S., Stringhini et al. (2013) in the U.K., and Kivimäki et al. (2015) in a meta-study of a large sample from a number of countries from several continents.
Also, in the article by Osborn, de Groot, & Wagner (2013), several socioeconomic status indicators mediated racial and/or ethnic differences in the prevalence of diabetes. Finally, Saydah, Imperatore, & Beckles (2013) found that lower socioeconomic status among adults with diabetes is associated with greater mortality rates.
On the whole, it can be seen that studies researching the relationship between the same variables (the prevalence of diabetes and the socioeconomic status) showed results similar to those which are expected to be gained in the proposed study.
Theoretical Framework
Prior to discussing a theoretical framework for the offered study, it should be noted that the definitions of a theoretical framework vary in the literature. It is possible to understand a theoretical framework as the basis of a theoretical structure; it consists of the main concepts, definitions, terms, and models which define the core of the theory (Swanson & Chermack, 2013). Presenting a theoretical framework involves explaining how the existence of a given research problem is determined by the theory in question (Swanson & Chermack, 2013).
Brown et al. (2004) offer a theoretical framework for studying problems similar to that which is going to be researched in the proposed study. The authors stress that the given problem emerges in a theory which supposes that the socioeconomic status of individuals has an association with their health via a number of factors which mediate or moderate this relationship; such factors may include, but might not be limited to, the access to health insurance and health care services, as well as the quality of the latter; the ability of individuals to purchase food and drink of sufficient quality; the particular behaviors related to health; and so on (Brown et al., 2004).
Therefore, the presented theoretical framework aligns with the proposed research question, which aims to establish the presence of the relationship between socioeconomic status and diabetes prevalence in the specified population; establishing such a relationship, in turn, requires conducting a quantitative study. In addition, it is paramount to stress that subsequent studies may investigate the concrete roles of the mentioned factors (e.g., access to health care) in the rates of diabetes in immigrants in California.
Research Question and Hypotheses
As has already been stressed, the research question for the proposed study will be as follows:
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RQ: Is there an association between diabetes and socioeconomic status (income and educational levels) among immigrants in California?
The proposed RQ informs the design of the proposed study by necessitating the execution of a quantitative analysis, which will permit for identifying whether there exists an association between the named phenomena. The null and alternative hypotheses for the proposed study will be as follows:
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H0: The diabetes prevalence among immigrants in California cannot be predicted from their socioeconomic status as determined by their levels of income and education.
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H1: The diabetes prevalence among immigrants in California cannot be predicted from their socioeconomic status as determined by their levels of income and education.
Approach for the Study
The study which is offered in the current research prospectus will utilize a quantitative approach. This is necessitated by the proposed research question, which is aimed at establishing the existence of a relationship between a number of phenomena that may be expressed by utilizing categorical and/or dichotomous variables (Warner, 2013). Thanks to the possibility of expressing these phenomena via such variables, it is possible to examine the prevalence of diabetes in the groups created by the interaction of two variables corresponding to the socioeconomic status: levels of income and levels of education.
Employing a quantitative approach in the offered study aligns with the given problem statement due to the fact that it permits for investigating the relationship between the prevalence of diabetes among immigrants in California and their socioeconomic status.
Sources of Information
The data for the proposed study will be gathered by utilizing a number of different means. In particular, it is likely that the data will be obtained from several sources of information that can be found online. In particular, the main source of the analyzed data is going to be the California Health Interview Survey (University of California, Los Angeles, n.d.). It should be stressed that documents similar to those provided by the University of California, Los Angeles (2016a), and the University of California, Los Angeles (2016b) were used in the process of data collection.
In addition, it may be possible to employ such sources of information as the Behavioral Risk Factor Surveillance System (Centers for Disease Control and Prevention, 2016), Inter-university Consortium for Political and Social Research (ICPSR, n.d.), National Addiction & HIV Data Archive Program (NAHDAP, n.d.), and the U.S. Centers for Disease Control and Prevention (n.d.).
Statistical Analysis
The data which will be utilized in the proposed study can be organized by employing a number of categorical variables. In particular, the dependent variable (diabetes) will be dichotomous (yes/no), whereas the independent variables will reflect the levels of education and income (categorical, ordinal). In order to analyze the relationship between a number of categorical independent variables and a dependent dichotomous variable, it is possible to utilize a multinomial logistic regression (more specifically, a binomial logistic regression), which will permit for estimating the probability of a situation in which an observation falls into one of the two categories of the dependent variable, diabetes, using the variables denoting income and educational levels as predictors (Warner, 2013). It is possible to employ such statistical software as IBM SPSS Statistics for the declared analysis.
Other Relevant Information
The researcher conducting the study proposed in the current prospectus may face a number of challenges in the process of analyzing the data. For instance, because the data will mainly be gathered from the University of California, Los Angeles (n.d.), and not collected by the researcher utilizing a survey that was specifically tailored for the given study, it might be possible that there will be no variables which directly correspond to the ones that need to be examined in the offered study, which will force the researcher to perform transformations on the given variables or choose which variables, in particular, may be used.
In addition, it should be stressed that in case the data collected in the process of the study permits for analyzing some additional aspects of the given problem, it might be possible that the researcher considers including them in the study; however, this will probably mean that additional analytical procedures need to be carried out.
References
Brown, A. F., Ettner, S. L., Piette, J., Weinberger, M., Gregg, E., Shapiro, M. F.,&Beckles, G. L. (2004). Socioeconomic position and health among persons with diabetes mellitus: A conceptual framework and review of the literature. Epidemiologic Reviews, 26(1), 63-77. Web.
Centers for Disease Control and Prevention. (2014). National diabetes statistics report. Web.
Centers for Disease Control and Prevention. (2016). 2015 BRFSS survey data and documentation. Web.
Centers for Disease Control and Prevention. (n.d.). Centers for Disease Control and Prevention: Main page. Web.
Chaufan, C., Constantino, S., & Davis, M. (2012). Its a full time job being poor: Understanding barriers to diabetes prevention in immigrant communities in the USA. Critical Public Health, 22(2), 147-158.
Fedeli, U., Casotto, V., Ferroni, E., Saugo, M., Targher, G., & Zoppini, G. (2015). Prevalence of diabetes across different immigrant groups in North-Eastern Italy. Nutrition, Metabolism and Cardiovascular Diseases, 25(10), 924-930.
Fisher-Hoch, S. P., Rentfro, A. R., Wilson, J. G., Salinas, J. J., Reininger, B. M., Restrepo, B. I.,&Rahbar, M. H. (2010). Socioeconomic status and prevalence of obesity and diabetes in a Mexican American community, Cameron County, Texas, 2004-2007. Preventing Chronic Disease, 7(3), A53. Web.
Ford, N. D., Narayan, K. V., & Mehta, N. K. (2016). Diabetes among US-and foreign-born Blacks in the USA. Ethnicity & Health, 21(1), 71-84.
Hwang, J., & Shon, C. (2014). Relationship between socioeconomic status and type 2 diabetes: Results from Korea National Health and Nutrition Examination Survey (KNHANES) 2010-2012. BMJ Open, 4(8), e005710.
ICPSR. (n.d.). ICPSR: A partner in social science research. Web.
Jaffiol, C., Thomas, F., Bean, K., Jégo, B., & Danchin, N. (2013). Impact of socioeconomic status on diabetes and cardiovascular risk factors: Results of a large French survey. Diabetes & Metabolism, 39(1), 56-62.
Janevic, T., Borrell, L. N., Savitz, D. A., Echeverria, S. E., & Rundle, A. (2014). Ethnic enclaves and gestational diabetes among immigrant women in New York City. Social Science & Medicine, 120, 180-189.
Kivimäki, M., Virtanen, M., Kawachi, I., Nyberg, S. T., Alfredsson, L., Batty, G. D.,&Dragano, N. (2015). Long working hours, socioeconomic status, and the risk of incident type 2 diabetes: A meta-analysis of published and unpublished data from 222120 individuals. The Lancet: Diabetes & Endocrinology, 3(1), 27-34.
Krishnan, S., Cozier, Y. C., Rosenberg, L., & Palmer, J. R. (2010). Socioeconomic status and incidence of type 2 diabetes: Results from the Black Womens Health study. American Journal of Epidemiology, 171(5), 564-570.
NAHDAP. (n.d.). National addiction & HIV data archive program. Web.
OConnor, M. R., Dobra, A., Voss, J., Pihoker, C., & Doorenbos, A. (2015). Type 1 diabetes among East African immigrant and nonimmigrant Black youth in the US. Journal of Pediatric Nursing, 30(6), 834-841.
Osborn, C. Y., de Groot, M., & Wagner, J. A. (2013). Racial and ethnic disparities in diabetes complications in the northeastern United States: The role of socioeconomic status. Journal of the National Medical Association, 105(1), 51-58.
Saydah, S. H., Imperatore, G., & Beckles, G. L. (2013). Socioeconomic status and mortality. Diabetes Care, 36(1), 49-55.
Stringhini, S., Batty, G. D., Bovet, P., Shipley, M. J., Marmot, M. G., Kumari, M.,&Kivimäki, M. (2013). Association of lifecourse socioeconomic status with chronic inflammation and type 2 diabetes risk: The Whitehall II prospective cohort study. PLoS Medicine, 10(7), e1001479.
Swanson, R. A., & Chermack, T. J. (2013). Theory building in applied disciplines. San Francisco, CA: Berrett-Koehler Publishers.
University of California, Los Angeles. (2016a). CHIS 2015 adult questionnaire: Version 2.73. Web.
University of California, Los Angeles. (2016b). CHIS 2015 data dictionary. Web.
University of California, Los Angeles. (n.d.). California health interview survey. Web.
Warner, R. M. (2013). Applied statistics: From bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: SAGE Publications.
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