Association of Gender and Race with Diabetes

This assignment investigates the association between gender and race with diabetes status. Students utilize a Chi-Square test to analyze data from 280 patients diagnosed with diabetes at Zeta Medical Center. The study explores the relationship between these variables, considering categories like normal, prediabetes, and diabetes, ultimately aiming to determine if significant associations exist.

PUBH-6033/8033 - Application of Public Health Data
Student Name:
Lecturer name:
27th October 2017

RQ: Is there an association between Gender and Diabetes status? Is there an association between
Race and Diabetes status?
Dependent Variable: Diabetes Status
Independent Variable(s): Gender and Race
Null Hypothesis: There is no association between Gender and Diabetes status; there is no
association between Race and Diabetes status.
Alternate Hypothesis: There is an association between Gender and Diabetes status; there is an
association between Race and Diabetes status.
Statistical Test: Chi-Square test of association
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Methods
Study sample
The study population consisted of 280 patients diagnosed with diabetes at Zeta Medical Center
between 2010 and 2015. The diabetes status were grouped into three categories, that is, normal,
prediabetes and diabetes.
The majority of cases were male (52.5%) and the mean age was (42.92 ± 13.55). in terms of the
respondents’ races, 33.9% (n = 95) were whites, 32.9% (n = 92) were blacks and 33.2% (n = 93)
were from other race. 26.8% (n = 75) of the participants were diagnosed with diabetes, 37.1% (n
= 104) were prediabetes while 36.1% (n = 101) were normal for diabetes test.
Data collection
Clinical data were collected from chart review. Demographic information was obtained through
self-reported questionnaire. Variables included gender and race (independent variables) and
diabetes status (dependent variable).
Statistical analyses
Standard descriptive statistics such as mean, standard deviation, and frequencies were performed
to describe the sample population as well as disease outcomes. The dependent variable was
considered: diabetes status (Normal = 1, Prediabetes = 2, Diabetes = 3). The independent
variables considered were: gender (male = 0, female = 1) and race (white = 1, black = 2 and
other = 3). Chi-Square test of association was used to determine the difference between males
and females regarding diabetes status. Statistical analysis was performed using SPSS software
version 21 and p > .05 for statistical insignificance.
Also, a Chi-Square test of association was used to determine the difference between white,
blacks and other races regarding diabetes status. Statistical analysis was performed using SPSS
software version 21 and p > .05 for statistical insignificance.

References
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functions in fits to histograms. Nucl. Instrum. Methods Phys. Res, 221(15), 437-442.
Gagunashvili, N. D. (2010). Chi-square tests for comparing weighted histograms. 614, 287-296.
Jin-Ting, Z. (2005). Approximate and asymptotic distributions of Chi-squared-type mixtures
with applications. Journal of American Statistical Association, 100, 273-285.