Relationship Between ABO, Rhesus D Blood Groups And Diabetes Mellitus In Patients Attending Kandara Sub-County Hospital In Murang’a County, Kenya
Keywords:
ABO Blood group,, Rhesus D, Diabetes MellitusAbstract
Background: Blood is categorized into types depending on the presence or absence of antigens on red blood cell surfaces. Currently, there are four blood groups: A, B, AB, and O. In addition to blood grouping, blood can be classified as rhesus negative or positive based on the lack or presence of a protein on the surface of red blood cells known as the rhesus D antigen. Diabetes is one of the four most common non-communicable diseases, accounting for around 4 million deaths globally. Diabetes is classified into three types: T1DM, T2DM, and GDM. DM is a group of disorders that impact how the body processes blood glucose. Gestational diabetes is described as varying degrees of glucose intolerance that develops during pregnancy. To yet, there is insufficient evidence linking the ABO and rhesus D blood groups to diabetes mellitus. The link between ABO blood type distribution and diabetes mellitus is always ambiguous because no diseases have been linked to a lack of ABO blood group antigen expression. The link between ABO, rhesus D blood types, and diabetes mellitus was investigated at Kandara Sub-County Hospital in Murang'a County.
Methods: Participants in the study were recruited at random from individuals with high blood sugar levels. The subjects' blood groups and sugar levels were determined using Anti A, Anti B, and Anti D sera and a Ceracheck glucometer, respectively. The data from this study was documented on an Excel Spread Sheet. The data was analyzed with SPSS version 20. The frequency, mean, median, and standard deviation of blood groups as well as blood sugar levels were calculated. A correlation analysis was performed to investigate the association between blood types, the rhesus factor, and diabetes. The majority of diabetic patients were female (69.4%), with 30.6% being male. The age range was 2 to 85 years, with a mean of 30.97.
Results: Blood group O+ had the highest occurrence in both male and female diabetic patients, at 47% and 51% respectively. However, the prevalence of blood groups did not differ substantially between male and female diabetes patients (F (1, 14) =1.20, p=0.29). The study individuals' glucose concentrations ranged from 7 mmol/L to 17 mmol/L. The mean glucose levels ranged from 7.5 to 12.95 mmol/L among diabetes individuals of diverse ages. Females aged 61-65 years had the highest mean glucose levels (14.9mmol/l). Males aged 26-30 had the highest mean glucose levels (13.3 mmol/l). However, there was no significant difference in glucose concentrations between male and female diabetes patients throughout age groups (t15=1.10, p=0.287). Diabetic patients with blood group AB+ had the highest blood sugar level, 11.21 mmol/L. However, blood sugar concentrations in male and female diabetic patients did not change substantially among age groups (t6=0.27, p=0.79). The Pearson correlation coefficient was R=0.24, SE=0.45, 95% CI, p>0.05. This implies that there is no link between blood groups and blood sugar levels, with the blood group effect accounting for 5% of the variation in blood sugar level. It is established that there is no link between diabetes and ABO blood groups, and persons with Group-AB+ are more likely to develop the condition.
Conclusion: The current study had several limitations, including the prevalence of blood groups being affected by geographical distribution, race, and ethnicity, as well as underage children whose parents did not consent for them to participate in the study, resulting in a low number of children participants: However, these findings are insufficient to draw a strong conclusion. Other genetic factors may be involved, necessitating more broad and thorough analysis. This study's findings were valuable to stakeholders involved in diabetes management. The Ministry of Health and non-governmental organizations working on diabetes used the gathered data to develop strategies for effective diabetes management.