Diabetes, Metabolic Syndrome and Risk of Malaria in Cameroon

Overview

Non-communicable diseases (NCDs) such as diabetes are increasing in countries where malaria transmission is common. This study aims to investigate the relationship between NCDs and parasitic infections in Cameroon. The investigators will assess the risk of malaria, as well as other parasitic diseases, in a prospectively followed group of adults with diabetes, compared with those without diabetes. Malaria parasites and intestinal worms will be tested using blood and stool collected at four time points during a one-year follow-up. In addition, this project will investigate how natural protection against malaria is affected by diabetes and other risk factors for heart diseases.

Studies have suggested that diabetes could be associated with both increased risk of and protection from infection with certain protozoans and helminths. A study from Ghana demonstrated an increased risk of asymptomatic malaria in individuals with type 2 diabetes, compared to healthy subjects. On the contrary, a Chinese study found a lower prevalence of diabetes and metabolic syndrome among adults previously exposed to Schistosoma. In sub-Saharan Africa, endemic to these parasitic infections, limited is known on their interaction with diabetes and metabolic syndrome. Findings from this study can inform policy to better integrate public health measures to improve the care of individuals with chronic non-communicable diseases such as diabetes and metabolic syndrome living at risk of malaria and other parasitic infections and prevent them from complications. This study aims to investigate whether diabetes with/without metabolic syndrome affects the risk of malaria and antibody-mediated immunity to malaria in adults, and if this risk is specific to malaria or also observed in other parasitic infections. This will be a prospective cohort study conducted at the Limbe Regional Hospital and Global Health Systems Laboratory in the Southwest Region of Cameroon. This cohort will comprise two groups of participants: the exposed group comprised of patients with type 2 diabetes (T2DM), and an unexposed group made of individuals without diabetes. Participants will be aged 21 years and above and must provide written informed consent to be part of the cohort. For every patient with diabetes included in the study, a participant without diabetes matched for sex and age (±5 years) and living in the same neighborhood will be identified and involved in the study. All participants will be assessed at the beginning, and every third months after the initiation into the cohort, and up to 4 times in 1 year. During each study encounter, participants will be tested for malaria through microscopy rapid diagnostic testing (RDT), and PCR to detect low-level parasitemia and confirm the plasmodium species. Also, stool analysis and urine microscopy will be performed, together with serological markers to enable the detection of helminths. At each visit, a full blood count, lipid profile, fasting plasma glucose, hemoglobin electrophoresis, creatinine for kidney function, HIV, and glycated hemoglobin tests will be done. The blood pressure, weight and height, and waist circumference will be measured at each encounter to aid in determining metabolic syndrome. Stored plasma samples will be analyzed on a panel of antigens using ELISA and a Luminex assay to measure the antibody response to malaria. Data will be analyzed using STATA. Descriptive statistics will be performed to determine the incidence of parasites using the Kaplan-Meyer method, and between-group comparisons of proportions done using the Chi-Squared tests or Fisher´s exact tests, and continuous data using the t-test. The risk of asymptomatic parasitemia in the exposed and the unexposed groups will be estimated using Cox proportional hazards regression. Age, sex, BMI, and additional patient characteristics such as socioeconomic factors, HIV status, and hemoglobinopathies will be included in a multivariable model to adjust for confounding. Stratified analyses and interaction terms will be used to evaluate if metabolic syndrome modifies the risk. Age and sex-stratified analysis will also be performed.