Prevalence and characteristics associated with diabetes mellitus and impaired fasting glucose among people aged 15 to 64 years in rural and urban Rwanda: secondary data analysis of World Health Organization surveillance data

County Rurality and Incidence and Prevalence of Diagnosed Diabetes in the United States

OBJECTIVE

To examine differences in the incidence and prevalence of diagnosed diabetes by county rurality.

PATIENTS AND METHODS

This observational, cross-sectional study used US Centers for Disease Control and Prevention data from 2004 through 2019 for county estimates of incidence and prevalence of diagnosed diabetes. County rurality was based on 6 levels (large central metro counties [most urban] to noncore counties [most rural]). Weighted least squares regression was used to relate rurality with diabetes incidence rates (IRs; per 1000 adults) and prevalence (percentage) in adults aged 20 years or older after adjusting for county-level sociodemographic factors (eg, food environment, health care professionals, inactivity, obesity).

RESULTS

Overall, in 3148 counties and county equivalents, the crude IR and prevalence of diabetes were highest in noncore counties. In age and sex ratio-adjusted models, the IR of diabetes increased monotonically with increasing rurality (P<.001), whereas prevalence had a weak, nonmonotonic but statistically significant increase (P=.002). Further adjustment for sociodemographic factors including food environment, health care professionals, inactivity, and obesity attenuated differences in incidence across rurality levels, and reversed the pattern for prevalence (prevalence ratios [vs large central metro] ranged from 0.98 [95% CI, 0.97 to 0.99] for large fringe metro to 0.94 [95% CI, 0.93 to 0.96] for noncore). In region-stratified analyses adjusted for sociodemographic factors including inactivity and obesity, increasing rurality was inversely associated with incidence in the Midwest and West only and inversely associated with prevalence in all regions.

CONCLUSION

The crude incidence and prevalence of diagnosed diabetes increased with increasing county rurality. After accounting for sociodemographic factors including food environment, health care professionals, inactivity, and obesity, county rurality showed no association with incidence and an inverse association with prevalence. Therefore, interventions targeting modifiable sociodemographic factors may reduce diabetes disparities by region and rurality.

Blood pressure screening in Mata Sector, a rural area of Rwanda

In rural sub-Saharan Africa, knowledge of non-communicable diseases such as high blood pressure (BP) is rather limited. This report provides information about a BP screening in Mata Sector, a rural region in Southern Province of Rwanda. Community-based, house-to-house screening was performed between February and July 2020 on more than 7000 inhabitants. The screening was conducted by a local team composed by 20 community health care workers, five community health care supervisors, and one nurse with hypertension surveillance training. BP and heart rate were recorded after 5 min of resting, using a validated automated oscillometric OMRON M6 IT-HEM-7322-E monitor with Intelli Wrap Cuff (HEM-FL31-E) technology. The mean of the second and third value was retained. BP was normal (<140/90 mm Hg) in 6340 (88%) and elevated in 863 (12%) participants with 95% of unawareness. Grade 1 (140-159/90-99 mm Hg) hypertensive BP readings were detected in 697 (81%), grade 2 (160-179/100-109 mm Hg) in 134 (16%), and grade 3 (≥180/≥110 mm Hg) in 32 (3.7%) individuals. The prevalence of hypertensive readings was significantly age-dependent. Additionally, a slightly greater proportion of participants with high BP (14% versus 11%) had a body mass index (BMI) ≥ 25.0 kg/m2. Also resting heart rate was higher in individuals with high BP (82 versus 77 beats/min). Although individuals identified with occasionally elevated BP values need further confirmatory measurements to establish the diagnosis of hypertension, these data suggest that high BP represents a noteworthy and preventable reason of concern within sub-Saharan Africa.

Prevalence, medication adherence, and determinants of type 2 diabetes mellitus during Coronavirus Disease 2019 pandemic among adults in Tanzania

Introduction

Excessive consumption of comfort foods, which are mostly high in carbs, and limitations on outdoor and gym-based physical activities, for instance, are associated with foods high in the glycemic index and raise the risk of obesity and type 2 diabetes. In pandemic and or epidemic situations, peoples' lifestyles may change significantly to lead them to non-communicable diseases. However, lifestyle changes and the occurrence of type 2 diabetes mellitus during the Coronavirus Disease 2019 pandemic among adults have not been well established in Tanzania. This study assessed the prevalence, medication adherence, and determinants of type 2 diabetes mellitus among adults in the country.

Methods

A community-based analytical cross-sectional study was conducted in Dodoma region, Tanzania between September and October 2020 of which 107 adults aged above 18 years were studied regardless of whether they were newly diagnosed with type 2 diabetes mellitus or not using a quantitative research approach. Interviewer-administered lifestyle habits and medication adherence structured questionnaires benchmarked from previous studies served as the main tools of data collection. The statistical package for social sciences computer program was used to analyze the data descriptively for frequencies and percentages and by regression analysis model to determine the association between variables with a 95% confidence interval and 5% significance level.

Results

With a mean age of 31 ± 2.527 years, 59.8% of the respondents were female. 60.7% and 11.7% of the respondents had unhealthy and moderate lifestyle choices respectively. The prevalence of type 2 diabetes mellitus accounted for 63.9% of the respondents of which 44.6% were diagnostically confirmed during the Coronavirus Disease 2019 pandemic against 19.3% of respondents who were diagnosed before the pandemic. Medication adherence among the type 2 diabetes mellitus respondents accounted for 77.9% of the study respondents. Type 2 diabetes mellitus was significantly associated with being in the 36-55 age group (AOR = 1.054; 95% CI: 0.292, 3.162; p < 0.05); being female (AOR = 1.398; 95% CI: 0.205, 3.048; p < 0.05); having a job (AOR = 2.597; 95% CI: 1.243, 4.402, p < 0.05); and having unhealthy lifestyle habits (AOR = 3.301; 95% CI: 1.199, 6.52; p < 0.05).

Conclusion

The majority of adults had type 2 diabetes mellitus of which most of them were confirmed to have the disease during the Coronavirus Disease 2019 pandemic. Few type 2 diabetes mellitus adults did not adhere to their medications as recommended. Their sociodemographic characteristics profiles and unhealthy lifestyles significantly led them to have the problem. The treatment of the disease above and health promotion activities may need to take unhealthy lifestyle choices and certain sociodemographic profiles of adults into consideration to assist in preventing the problem.

Uncovering the Burden of Diabetes in Ekiti State, Nigeria: Insights From a Statewide, Household-Based, Cross-Sectional Study

INTRODUCTION

Diabetes mellitus (DM) is an important global public health challenge, and the burden of the disease is huge, particularly in low- and middle-income countries (LMICs), where the majority of people with this condition reside. Undiagnosed DM is more prevalent in LMICs. The aim of this study is to determine the prevalence and associated factors for DM in Ekiti State.

MATERIALS AND METHODS

A cross-sectional, household-based survey using a four-stage multistage sampling design and the World Health Organization (WHO)-STEPS survey manual was conducted from July to September 2020 as a part of the Ekiti State coronavirus disease 2019 (COVID-19) survey. Of the 5,145 sampled households, 4,726 individuals gave consent to participate in the survey. Out of these, 3043 had fasting plasma glucose results available and were included in the analysis.

RESULTS

There were 2257 (74.2%) women and 786 (25.8%) men. The prevalence of DM was 6.5% (6.5% in males and 6.6% in females, P = 0.946). Diabetes was found to be more prevalent among those with a secondary school education or higher (10.9%); employed in the formal sector (13.4%); separated, divorced, or widowed (8.5%); with raised blood pressure (9.3%); and who were aged 30-59 years (all P < 0.05). Multivariable logistic regression showed that age, education, occupation, and hypertension were all positively and significantly associated with an increased risk of DM.

CONCLUSION

The prevalence of DM in Ekiti State is high, and its predictors include advancing age, hypertension, education, and occupation. This calls for scaling up public health interventions for controlling DM, targeting the identified risk factors among the people of Ekiti.

Taking stock of population-level interventions targeting risk factors for hypertension and diabetes in Rwanda and South Africa: methodological reflections and lessons learnt from conducting a multi-component situational analysis

BACKGROUND

Hypertension and diabetes are on the rise both in Rwanda and South Africa. The responsibility for NCD risk factors cut across different sectors, which makes it complex to effectively manage. Policy-relevant intervention research is thus critical for addressing the NCD challenge. We conducted a situational analysis in both countries to identify and describe current population-level interventions targeting risk factors for diabetes and hypertension. This paper presents this methodology and shares challenges encountered, and lessons learnt in applying the methodology.

METHODS

We describe a multi-component methodology for conducting a situational analysis, which included a desk review, stakeholder mapping, survey, key informant interviews, and a consultative workshop. This methodology was applied in a standardized manner in two African countries. Following the analysis, the authors held iterative team consultations to reflect on challenges and lessons learnt during this process.

RESULTS

Key challenges and lessons learnt relate to i) stakeholder recruitment, engagement and retainment; ii) utilization and triangulation of multiple sources of data; and iii) evolving circumstances, particularly related to the Covid-19 pandemic. It proved challenging to recruit stakeholders outside the health sector and in the private sector, as they often do not consider themselves as making or influencing policies and thus were reluctant to engage. The difficulties with responsiveness were often overcome through face-to-face visits, an opportunity to explain the relevance of their participation. With regards to health sector stakeholders and all other stakeholders, continued engagement over prolonged periods of time also turned out to be challenging. Covid-19 restrictions were preserved to be an impediment throughout the conduct of the situational analysis, specifically in South Africa. The use of multi-stage mixed methods was found to be appropriate for addressing the study objectives, as each step yielded unique data, concepts, and perspectives that complemented the other data.

CONCLUSION

Conducting a situational analysis is crucial for understanding the current state of interventions and identifying opportunities for new interventions. The multi-component methodology used in two African countries was found to be feasible, appropriate, and informative. Others planning to conduct situational analysis may follow, adapt and improve upon our approach, reacting to the challenges encountered.

Community Health Worker-Led Cardiovascular Disease Risk Screening and Referral for Care and Further Management in Rural and Urban Communities in Rwanda

Cardiovascular disease (CVD) is a global health issue. Low- and middle-income countries (LMICs) are facing early CVD-related morbidity. Early diagnosis and treatment are an effective strategy to tackle CVD. The aim of this study was to assess the ability of community health workers (CHWs) to screen and identify persons with high risks of CVD in the communities, using a body mass index (BMI)-based CVD risk assessment tool, and to refer them to the health facility for care and follow-up. This was an action research study conducted in rural and urban communities, conveniently sampled in Rwanda. Five villages were randomly selected from each community, and one CHW per each selected village was identified and trained to conduct CVD risk screening using a BMI-based CVD risk screening tool. Each CHW was assigned to screen 100 fellow community members (CMs) for CVD risk and to refer those with CVD risk scores ≥10 (either moderate or high CVD risk) to a health facility for care and further management. Descriptive statistics with Pearson's chi-square test were used to assess any differences between rural and urban study participants vis-à-vis the key studied variables. Spearman's rank coefficient and Cohen's Kappa coefficient were mainly used to compare the CVD risk scoring from the CHWs with the CVD risk scoring from the nurses. Community members aged 35 to 74 years were included in the study. The participation rates were 99.6% and 99.4% in rural and urban communities, respectively, with female predominance (57.8% vs. 55.3% for rural and urban, p-value: 0.426). Of the participants screened, 7.4% had a high CVD risk (≥20%), with predominance in the rural community compared to the urban community (8.0% vs. 6.8%, p-value: 0.111). Furthermore, the prevalence of moderate or high CVD risk (≥10%) was higher in the rural community than in the urban community (26.7% vs. 21.1%, p-value: 0.111). There was a strong positive correlation between CHW-based CVD risk scoring and nurse-based CVD risk scoring in both rural and urban communities, 0.6215 (p-value < 0.001) vs. 0.7308 (p-value = 0.005). In regard to CVD risk characterization, the observed agreement to both the CHW-generated 10-year CVD risk assessment and the nurse-generated 10-year CVD risk assessment was characterized as "fair" in both rural and urban areas at 41.6% with the kappa statistic of 0.3275 (p-value < 001) and 43.2% with kappa statistic of 0.3229 (p-value =0.057), respectively. In Rwanda, CHWs can screen their fellow CMs for CVD risk and link those with high CVD risk to the healthcare facility for care and follow-up. CHWs could contribute to the prevention of CVDs through early diagnosis and early treatment at the bottom of the health system.

Population-Level Interventions Targeting Risk Factors for Hypertension and Diabetes in Rwanda: A Situational Analysis

Background

Eighty percent (80%) of global Non-Communicable Diseases attributed deaths occur in low- and middle-income countries (LMIC) with hypertension and diabetes being key contributors. The overall prevalence of hypertension was 15.3% the national prevalence of diabetes in rural and urban was 7.5 and 9.7%, respectively among 15–64 years. Hypertension represents a leading cause of death (43%) among hospitalized patients at the University teaching hospital of Kigali. This study aimed to identify ongoing population-level interventions targeting risk factors for diabetes and hypertension and to explore perceived barriers and facilitators for their implementation in Rwanda.

Methods

This situational analysis comprised a desk review, key informant interviews, and stakeholders' consultation. Ongoing population-level interventions were identified through searches of government websites, complemented by one-on-one consultations with 60 individuals nominated by their respective organizations involved with prevention efforts. Semi-structured interviews with purposively selected key informants sought to identify perceived barriers and facilitators for the implementation of population-level interventions. A consultative workshop with stakeholders was organized to validate and consolidate the findings.

Results

We identified a range of policies in the areas of food and nutrition, physical activity promotion, and tobacco control. Supporting program and environment interventions were mainly awareness campaigns to improve knowledge, attitudes, and practices toward healthy eating, physical activity, and alcohol and tobacco use reduction, healthy food production, physical activity infrastructure, smoke-free areas, limits on tobacco production and bans on non-standardized alcohol production. Perceived barriers included limited stakeholder involvement, misbeliefs about ongoing interventions, insufficient funding, inconsistency in intervention implementation, weak policy enforcement, and conflicts between commercial and public health interests. Perceived facilitators were strengthened multi-sectoral collaboration and involvement in ongoing interventions, enhanced community awareness of ongoing interventions, special attention paid to the elderly, and increased funds for population-level interventions and policy enforcement.

Conclusion

There are many ongoing population-level interventions in Rwanda targeting risk factors for diabetes and hypertension. Identified gaps, perceived barriers, and facilitators provide a useful starting point for strengthening efforts to address the significant burden of disease attributable to diabetes and hypertension.