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BackgroundInterventions delivered by mobile phones have the potential to prevent cardiovascular disease (CVD) by supporting behavior change toward healthier lifestyles and treatment adherence. To allow replication and adaptation of these interventions across settings, it is important to fully understand how they have been developed. However, the development processes of these interventions have not previously been systematically examined. ObjectiveThis study aimed to systematically describe and compare the development process of text messaging interventions identified in the Text2PreventCVD systematic review. MethodsWe extracted data about the development process of the 9 interventions identified in the Text2PreventCVD systematic review. Data extraction, which was guided by frameworks for the development of complex interventions, considered the following development stages: intervention planning, design, development, and pretesting. Following data extraction, we invited the developers of the interventions to contribute to our study by reviewing the accuracy of the extracted data and providing additional data not reported in the available publications. ResultsA comprehensive description of the development process was available for 5 interventions. Multiple methodologies were used for the development of each intervention. Intervention planning involved gathering information from stakeholder consultations, literature reviews, examination of relevant theory, and preliminary qualitative research. Intervention design involved the use of behavior change theories and behavior change techniques. Intervention development involved (1) generating message content based on clinical guidelines and expert opinions; (2) conducting literature reviews and primary qualitative research to inform decisions about message frequency, timing, and level of tailoring; and (3) gathering end-user feedback concerning message readability, intervention acceptability, and perceived utility. Intervention pretesting involved pilot studies with samples of 10 to 30 participants receiving messages for a period ranging from 1 to 4 weeks. ConclusionsThe development process of the text messaging interventions examined was complex and comprehensive, involving multiple studies to guide decisions about the scope, content, and structure of the interventions. Additional research is needed to establish whether effective messaging systems can be adapted from work already done or whether this level of development is needed for application in other conditions and settings.

In tandem with the ever-increasing aging population in low and middle-income countries, the burden of dementia is rising on the African continent. Dementia prevalence varies from 2.3% to 20.0% and incidence rates are 13.3 per 1000 person-years with increasing mortality in parts of rapidly transforming Africa. Differences in nutrition, cardiovascular factors, comorbidities, infections, mortality, and detection likely contribute to lower incidence. Alzheimer's disease, vascular dementia, and human immunodeficiency virus/acquired immunodeficiency syndrome-associated neurocognitive disorders are the most common dementia subtypes. Comprehensive longitudinal studies with robust methodology and regional coverage would provide more reliable information. The apolipoprotein E (APOE) ε4 allele is most studied but has shown differential effects within African ancestry compared to Caucasian. More candidate gene and genome-wide association studies are needed to relate to dementia phenotypes. Validated culture-sensitive cognitive tools not influenced by education and language differences are critically needed for implementation across multidisciplinary groupings such as the proposed African Dementia Consortium.

Background and Aims: South Africa is a middle-income country with high levels of income inequality and a rapidly aging population and increasing dementia prevalence. Little is known about which risk factors for dementia are important and how they differ by social determinants of health as well as key demographic characteristics such as sex and wealth. We sought to calculate the population attributable risks (PARs) for established potentially modifiable risk factors for dementia among these different groups. Methods: We obtained risk factor prevalence from population-based surveys for established dementia risk factors (diabetes, midlife hypertension, midlife obesity, physical inactivity, depression, smoking, low educational attainment, social isolation). We used relative risk estimates reported in previous meta-analyses and estimated PARs using Levin's formula and accounting for communality. We tested for one-way and two-way interactions by sex and wealth using Pearson's χ2. In stratified analyses, we performed tests for trend using logistic regression. Results: The prevalence of established risk factors for dementia ranged from 5% for depression to 64% for low education. After accounting for communality, the risk factors contributing the greatest PAR were low education (weighted PAR 12%, 95% CI 7% to 18%), physical inactivity (9, 5-14%), and midlife hypertension (6, 5-14%). Together, 45% of dementia cases may be attributable to modifiable risk factors (95% CI 25-59%). We found significant interactions (p < 0.005) between sex, wealth, or both (sex * wealth) and each risk factor except social isolation and physical activity. Low education was inversely associated with wealth in both male and female. The PAR for midlife hypertension, obesity, and diabetes was associated with increasing wealth, and was higher in female. In contrast, the PAR for smoking was higher in male (8% vs. 2%) and was associated with increasing wealth among female only. We found that either a strategy of large reductions in selected risk factors with the highest PAR (midlife hypertension, smoking, physical inactivity) or small reductions across all risk factors could potentially reduce dementia cases by as many as 250,000 by 2050. Discussions: The potential impact on dementia risk by decreasing exposure to established dementia risk factors is large and differs by sex and social determinants of health like wealth. Risk factor PAR should inform national and local health policy dementia initiatives in South Africa including which risk factors to target in the whole population and which to target in high-risk groups for maximum public health benefit.

Objectives: More people with dementia live in low- and middle-income countries (LMICs) than in high-income countries, but best-practice care recommendations are often based on studies from high-income countries. We aimed to map the available evidence on dementia interventions in LMICs., Methods: We systematically mapped available evidence on interventions that aimed to improve the lives of people with dementia or mild cognitive impairment (MCI) and/or their carers in LMICs (registered on PROSPERO: CRD42018106206). We included randomised controlled trials (RCTs) published between 2008 and 2018. We searched 11 electronic academic and grey literature databases (MEDLINE, EMBASE, PsycINFO, CINAHL Plus, Global Health, World Health Organization Global Index Medicus, Virtual Health Library, Cochrane CENTRAL, Social Care Online, BASE, MODEM Toolkit) and examined the number and characteristics of RCTs according to intervention type. We used the Cochrane risk of bias 2.0 tool to assess the risk of bias., Results: We included 340 RCTs with 29,882 (median, 68) participants, published 2008-2018. Over two-thirds of the studies were conducted in China (n = 237, 69.7%). Ten LMICs accounted for 95.9% of included RCTs. The largest category of interventions was Traditional Chinese Medicine (n = 149, 43.8%), followed by Western medicine pharmaceuticals (n = 109, 32.1%), supplements (n = 43, 12.6%), and structured therapeutic psychosocial interventions (n = 37, 10.9%). Overall risk of bias was judged to be high for 201 RCTs (59.1%), moderate for 136 (40.0%), and low for 3 (0.9%)., Conclusions: Evidence-generation on interventions for people with dementia or MCI and/or their carers in LMICs is concentrated in just a few countries, with no RCTs reported in the vast majority of LMICs. The body of evidence is skewed towards selected interventions and overall subject to high risk of bias. There is a need for a more coordinated approach to robust evidence-generation for LMICs., (© 2023 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons Ltd.)

Introduction: Monitoring and treatment of type 2 diabetes in South Africa usually takes place in primary care using random blood glucose testing to guide treatment decisions. This study explored the feasibility of using point-of-care haemoglobin A1c (HbA 1c ) testing in addition to glucose testing in a busy primary care clinic in Cape Town, South Africa., Subjects: 185 adults aged 19-88 years with type 2 diabetes., Materials and Methods: Participants recruited to this mixed methods cohort study received a point-of-care HbA 1c test. Doctors were asked to use the point-of-care HbA 1c result for clinical decision-making. Qualitative interviews were held with clinical staff., Results: Point-of-care HbA 1c test results were obtained for 165 participants of whom 109 (65%) had poor glycaemic control (>8% HbA 1c , 64 mmol/mol). Medical officers reported using a combination of HbA 1c and blood glucose 77% of the time for clinical decision-making. Nurses found the analyser easy to use and doctors valued having the HbA 1c result to help with decision-making., Discussion: Our results suggest that 30% of patients may have received inappropriate medication or not received necessary additional medication if random blood glucose alone had been used in routine appointments. Clinicians valued having access to the HbA 1c test result to help them make treatment decisions., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: The extent to which diabetes (DM) practice guidelines, often based on evidence from high-income countries (HIC), can be implemented to improve outcomes in low- and middle-income countries (LMIC) is a critical challenge. We carried out a systematic review to compare type 2 DM guidelines in individual LMIC versus HIC over the past decade to identify aspects that could be improved to facilitate implementation., Research Design and Methods: Eligible guidelines were sought from online databases and websites of diabetes associations and ministries of health. Type 2 DM guidelines published between 2006 and 2016 with accessible full publications were included. Each of the 54 eligible guidelines was assessed for compliance with the Institute of Medicine (IOM) standards, coverage of the cardiovascular quadrangle (epidemiologic surveillance, prevention, acute care, and rehabilitation), translatability, and its target audiences., Results: Most LMIC guidelines were inadequate in terms of applicability, clarity, and dissemination plan as well as socioeconomic and ethical-legal contextualization. LMIC guidelines targeted mainly health care providers, with only a few including patients (7%), payers (11%), and policy makers (18%) as their target audiences. Compared with HIC guidelines, the spectrum of DM clinical care addressed by LMIC guidelines was narrow. Most guidelines from the LMIC complied with less than half of the IOM standards, with 12% of the LMIC guidelines satisfying at least four IOM criteria as opposed to 60% of the HIC guidelines ( P < 0.001)., Conclusions: A new approach to the contextualization, content development, and delivery of LMIC guidelines is needed to improve outcomes., (© 2018 by the American Diabetes Association.)