Lydia Kaduka

Moving to an A1C-Based Diagnosis of Diabetes Has a Different Impact on Prevalence in Different Ethnic Groups

OBJECTIVE To compare screen-detected diabetes prevalence and the degree of diagnostic agreement by ethnicity with the current oral glucose tolerance test (OGTT)-based and newly proposed A1C-based diagnostic criteria. RESEARCH DESIGN AND METHODS Six studies (1999–2009) from Denmark, the U.K., Australia, Greenland, Kenya, and India were tested for the probability of an A1C ≥6.5% among diabetic case subjects based on an OGTT. The difference in probability between centers was analyzed by logistic regression adjusting for relevant confounders. RESULTS Diabetes prevalence was lower with the A1C-based diagnostic criteria in four of six studies. The probability of an A1C ≥6.5% among OGTT-diagnosed case subjects ranged widely (17.0–78.0%) by study center. Differences in diagnostic agreement between ethnic subgroups in the U.K. study were of the same magnitude as between-country comparisons. CONCLUSIONS A shift to an A1C-based diagnosis for diabetes will have substantially different consequences for diabetes prevalence across ethnic groups and populations.

Obesity and regional fat distribution in Kenyan populations: Impact of ethnicity and urbanization

Background: Obesity is increasing rapidly in Africa, and may not be associated with the same changes in body composition among different ethnic groups in Africa. Objective: To assess abdominal visceral and subcutaneous fat thickness, prevalence of obesity, and differences in body composition in rural and urban Kenya. Subjects and methods: In a cross-sectional study carried out among Luo, Kamba and Maasai in rural and urban Kenya, abdominal visceral and subcutaneous fat thicknesses were measured by ultrasonography. Height and weight, waist, mid-upper arm circumferences, and triceps skinfold thickness were measured. Body mass index (BMI), arm fat area (AFA) and arm muscle area (AMA) were calculated. Results: Among 1430 individuals (58.3% females) aged 17–68 years, abdominal visceral and subcutaneous fat, BMI, AFA and waist circumference (WC) increased with age, and were highest in the Maasai and in the urban population. AMA was only higher with increasing age among males. The prevalence of overweight (BMI ≥ 25) (39.8% vs. 15.8%) and obesity (BMI ≥ 30) (15.5% vs. 5.1%) was highest in the urban vs. rural population. Conclusion: Abdominal visceral and subcutaneous fat thickness was higher with urban residency. A high prevalence of overweight and obesity was found. The Maasai had the highest overall fat accumulation.

Prevalence of glucose intolerance and associated risk factors in rural and urban populations of different ethnic groups in Kenya.

OBJECTIVE To assess the prevalence of glucose intolerance in rural and urban Kenyan populations and in different ethnic groups. Further, to identify associations between lifestyle risk factors and glucose intolerance. RESEARCH DESIGN AND METHODS A cross-sectional study included an opportunity sample of Luo, Kamba, Maasai, and an ethnically mixed group from rural and urban Kenya. Diabetes and IGT were diagnosed using a standard OGTT. BMI, WC, AFA, AMA and abdominal subcutaneous and visceral fat thicknesses, physical activity and fitness were measured. Questionnaires were used to determine previous diabetes diagnosis, family history of diabetes, smoking habits, and alcohol consumption. RESULTS Among 1459 participants, mean age 38.6 years (range 17-68 years), the overall age-standardized prevalence of diabetes and IGT was 4.2% and 12.0%. The Luo had the highest prevalence of glucose intolerance among the rural ethnic groups. High BMI, WC, AFA, abdominal visceral and subcutaneous fat thickness, low fitness and physical activity, frequent alcohol consumption, and urban residence were associated with glucose intolerance. CONCLUSIONS The prevalence of diabetes and IGT among different Kenyan population groups was moderate, and highest in the Luo. The role of lifestyle changes and ethnicity on the effect of diabetes in African populations needs further exploration.

Prevalence of Metabolic Syndrome Among an Urban Population in Kenya

OBJECTIVE Developing countries are undergoing an epidemiologic transition accompanied by increasing burden of cardiovascular disease (CVD) linked to urbanization and lifestyle modifications. Metabolic syndrome is a cluster of CVD risk factors whose extent in Kenya remains unknown. The aim of this study was to determine the prevalence of metabolic syndrome and factors associated with its occurrence among an urban population in Kenya. RESEARCH DESIGN AND METHODS This was a household cross-sectional survey comprising 539 adults (aged ≥18 years) living in Nairobi, drawn from 30 clusters across five socioeconomic classes. Measurements included waist circumference, HDL cholesterol, triacylglycerides (TAGs), fasting glucose, and blood pressure. RESULTS The prevalence of metabolic syndrome was 34.6% and was higher in women than in men (40.2 vs. 29%; P < 0.001). The most frequently observed features were raised blood pressure, a higher waist circumference, and low HDL cholesterol (men: 96.2, 80.8, and 80%; women: 89.8, 97.2, and 96.3%, respectively), whereas raised fasting glucose and TAGs were observed less frequently (men: 26.9 and 63.3%; women: 26.9 and 30.6%, respectively). The main factors associated with the presence of metabolic syndrome were increasing age, socioeconomic status, and education. CONCLUSIONS Metabolic syndrome is prevalent in this urban population, especially among women, but the incidence of individual factors suggests that poor glycemic control is not the major contributor. Longitudinal studies are required to establish true causes of metabolic syndrome in Kenya. The Kenyan government needs to create awareness, develop prevention strategies, and strengthen the health care system to accommodate screening and management of CVDs.

Food Insecurity and Not Dietary Diversity Is a Predictor of Nutrition Status in Children within Semiarid Agro-Ecological Zones in Eastern Kenya

Machakos and Makueni counties in Kenya are associated with historical land degradation, climate change, and food insecurity. Both counties lie in lower midland (LM) lower humidity to semiarid (LM4), and semiarid (LM5) agroecological zones (AEZ). We assessed food security, dietary diversity, and nutritional status of children and women. Materials and Methods. A total of 277 woman-child pairs aged 15–46 years and 6–36 months respectively, were recruited from farmer households. Food security and dietary diversity were assessed using standard tools. Weight and height, or length in children, were used for computation of nutritional status. Findings. No significant difference (P > 0.05) was observed in food security and dietary diversity score (DDS) between LM4 and LM5. Stunting, wasting, and underweight levels among children in LM4 and LM5 were comparable as were BMI scores among women. However, significant associations (P = 0.023) were found between severe food insecurity and nutritional status of children but not of their caregivers. Stunting was significantly higher in older children (>2 years) and among children whose caregivers were older. Conclusion. Differences in AEZ may not affect dietary diversity and nutritional status of farmer households. Consequently use of DDS may lead to underestimation of food insecurity in semiarid settings.

Hemoglobin levels and blood pressure are associated in rural black africans.

The association between blood levels of hemoglobin (B‐hgb) and blood pressure (BP) has been widely investigated in Caucasians and Asians but there is a paucity of data in rural black Africans. The objective was to investigate the association between B‐hgb and BP in a rural black African population.

Stroke Mortality in Kenya’s Public Tertiary Hospitals: A Prospective Facility-Based Study

Background: Despite the increasing global burden of stroke, there are limited data on stroke from Kenya to guide in decision-making. Stroke occurrence in sub-Saharan Africa has been associated with poor health outcomes. This study sought to establish the stroke incidence density and mortality in Kenya’s leading public tertiary hospitals for purposes of informing clinical practice and policy. Methods: This is a prospective study conducted at Kenya’s leading referral hospitals, namely, Kenyatta National Hospital (KNH) and Moi Teaching and Referral Hospital (MTRH). Adult patients with confirmed cases of stroke were recruited from February 2015 to January 2016 and followed up for a minimum period of 1 year. The WHO 2006 Stroke STEPS instrument was used to collect data on incidence and mortality at days 10 and 28 and every 3 months for 24 months. The person-time of follow-up was computed from admission to death, loss to follow-up, or the end of the study. A survival regression analysis was done using the Cox proportional hazards model. Results: A total of 719 patients were recruited (KNH: n = 406 [56.5%]; MTRH: n = 313 [43.5%]). The mean age was 58.6 ± 18.7 years, and the male-to-female ratio was 1: 1.4. Ischemic stroke accounted for 56.1% of the stroke cases. The peak age for stroke was between 50 and 69 years, when 36.3% of the cases occurred. Mortality at day 10 and day 28 was 18.4 and 26.7%, respectively. The inpatient mortality rate was 21.6%. The stroke incidence density was 507 deaths per 1,000 person-years of follow-up. The mean survival time was significantly different between inpatients (13.9 months; 95% CI: 13.0–14.7) and outpatients (18.6 months; 95% CI: 17.2–19.9) (p < 0.001). A 1-year increase in age increased the hazard by 1.8%. Inpatients had a 3.9-fold increase in hazard compared to outpatients. Conclusions: Mortality due to stroke is high, with poor survival observed in the first year after stroke. The risk of death increases with increasing age and duration of hospital stay. There is need for attention to quality of care and long-term needs of stroke patients to mitigate the high mortality rates observed. Public health initiatives aimed at early screening and diagnosis should be enhanced. Further research is recommended to establish the true burden of stroke at the community level to inform appropriate mitigation measures.