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      Mobile phone ownership and willingness to receive mHealth services among patients with diabetes mellitus in South-West, Nigeria

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          mobile phone technology is increasingly used to overcome traditional barriers to limiting access to diabetes care. This study evaluated mobile phone ownership and willingness to receive and pay for mobile phone-based diabetic services among people with diabetes in South-West, Nigeria.


          two hundred and fifty nine patients with diabetes were consecutively recruited from three tertiary health institutions in South-West, Nigeria. Questionnaire was used to evaluate mobile phone ownership, willingness to receive and pay for mobile phone-based diabetic health care services via voice call and text messaging.


          97.3% owned a mobile phone, with 38.9% and 61.1% owning smartphone and basic phone respectively. Males were significantly more willing to receive mobile-phone-based health services than females (81.1% vs 68.1%, p=0.025), likewise married compared to unmarried [77.4% vs 57.1%, p=0.036]. Voice calls (41.3%) and text messages (32.4%), were the most preferred modes of receiving diabetes-related health education with social media (3.1%) and email (1.5%) least. Almost three-quarter of participants (72.6%) who owned mobile phone, were willing to receive mobile phone-based diabetes health services. The educational status of patients (adjusted OR [AOR]: 1.7{95% CI: 1.6 to 2.1}), glucometers possession (AOR: 2.0 [95% CI: 1.9 to 2.1) and type of mobile phone owned (AOR: 2.9 [95% CI: 2.8 to 5.0]) were significantly associated with the willingness to receive mobile phone-based diabetic services.


          the majority of study participants owned mobile phones and would be willing to receive and pay for diabetes-related healthcare delivery services provided the cost is minimal and affordable.

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          mHealth Application Areas and Technology Combinations

          Summary Background: With the continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth. While eHealth is broadly focused on information and communication technologies, mHealth seeks to explore more into mobile devices and wireless communication. Since mobile phone penetration has exceeded other infrastructure in low and middle-income countries (LMICs), mHealth is seen as a promising component to provide pervasive and patient-centered care. Objectives: The aim of our research work for this paper is to examine the mHealth literature to identify application areas, target diseases, and mHealth service and technology types that are most appropriate for LMICs. Methods: Based on the 2011 WHO mHealth report, a combination of search terms, all including the word “mHealth”, was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Articles were included if they were published in English, covered an mHealth solution/intervention, involved the use of a mobile communication device, and included a pilot evaluation study. Articles were excluded if they did not provide sufficient detail on the solution covered or did not focus on clinical efficacy/effectiveness. Cross-referencing was also performed on included articles. Results: 842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the highest number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternal and child’s health (MCH) (n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), tele-medicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short study durations. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence. Conclusions: SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in high income countries. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. Remaining application areas are rarely addressed. Diabetes is the most commonly targeted medical condition, yet remains deficient in LMICs.
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            Prevalence and Risk Factors for Diabetes Mellitus in Nigeria: A Systematic Review and Meta-Analysis

            Introduction There has been no nationwide health (diabetes) survey in Nigeria since 1992, when a diabetes mellitus (DM) prevalence of 2.2% was reported. We aimed to determine the prevalence of and risk factors for DM in Nigeria by performing a systematic review and meta-analysis. Methods We searched Medline, EMBASE, PubMed, PapersFirst, the Cochrane Library, Scopus, Bioline, African Journals Online, Institute of Scientific Information, and Google Scholar from the year 1990 to 2017. Using MeSH headings, the terms “diabetes mellitus,” “risk factors,” “prevalence,” and “Nigeria” as well as variations thereof were searched for. The last search was performed on 26 November 2017. We only included studies that utilized the random plasma glucose test, the fasting plasma glucose test, the oral glucose tolerance test (OGTT), or HbA1c to diagnose DM. A total of 23 studies (n = 14,650 persons) were evaluated. A random effects model was used to estimate the pooled prevalence of DM. We estimated the overall pooled prevalence of DM and subgroup-specific DM prevalences while accounting for inter-study and intra-study variability/heterogeneity. Results The overall pooled prevalence of DM was 5.77% (95% CI 4.3–7.1). The pooled prevalences of DM in the six geopolitical zones of Nigeria were 3.0% (95% CI 1.7–4.3) in the north-west, 5.9% (95% CI 2.4–9.4) in the north-east, 3.8% (95% CI 2.9–4.7) in the north-central zone, 5.5% (95% CI 4.0–7.1) in the south-west, 4.6% (95% CI 3.4–5.9) in the south-east, and 9.8% (95% CI 7.2–12.4) in the south-south zone. Risk factors for the pooled prevalence of DM were a family history of DM (4.6%; 95% CI 3.5–5.6); urban dwelling (6.0%; 95% CI 4.3–7.8); unhealthy dietary habits (8.0%; 95% CI 5.4–10.5); cigarette smoking (4.4%; 95% CI 1.3–10.2); older age (6.6%; 95% CI 4.5–8.7); physical inactivity (4.8%; 95% CI 3.2–6.4); and obesity (5.3%; 95% CI 3.8–6.9). Conclusion There has been an increase in the prevalence of DM in Nigeria. All regions of the country have been affected, with the highest prevalence seen in the south-south geopolitical zone. Urban dwelling, physical inactivity, advanced age, and unhealthy diet are important risk factors for DM among Nigerians. A national diabetes care and prevention policy is highly recommended.
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              Medication beliefs, treatment complexity, and non-adherence to different drug classes in patients with type 2 diabetes.

              To assess the relationship of patients' medication beliefs and treatment complexity with unintentional and intentional non-adherence for three therapeutic groups commonly used by patients with type 2 diabetes.

                Author and article information

                Pan Afr Med J
                The Pan African Medical Journal
                The African Field Epidemiology Network
                08 September 2020
                : 37
                [1 ]Department of Medicine, Endocrinology, Diabetes and Metabolism Unit, Ladoke Akintola University of Technology, Ladoke Akintola University of Technology Teaching Hospital, Ogbomoso, Oyo State, Nigeria,
                [2 ]Hasso Plattner Institut, Digital Health, University of Potsdam, Potsdam, Germany,
                [3 ]Department of Medicine, Endocrinology and Diabetes Unit, Ekiti State University, Ekiti State University Teaching Hospital, Ado-Ekiti, Ekiti State, Nigeria,
                [4 ]Department of Medicine, Bowen University, Bowen University Teaching Hospital, Ogbomoso, Oyo State, Nigeria,
                [5 ]Department of Pharmacology and Therapeutics, Ekiti State University, Ekiti State University Teaching Hospital, Ado-Ekiti, Ekiti State, Nigeria
                Author notes
                Corresponding author: Michael Adeyemi Olamoyegun, Department of Medicine, Endocrinology, Diabetes and Metabolism Unit, Ladoke Akintola University of Technology, Ladoke Akintola University of Technology Teaching Hospital, Ogbomoso, Oyo State, Nigeria. maolamoyegun@ 123456lautech.edu.ng
                Copyright: Michael Adeyemi Olamoyegun et al.

                The Pan African Medical Journal (ISSN: 1937-8688). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.



                nigeria, healthcare, diabetes, ownership, mobile phone


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