The Bangladesh D-Magic Trial. Diabetes Mellitus: Action Through Groups or Information for Better Control?

随着低收入国家生存状况的改善，包括糖尿病在内的非传染性疾病问题也在增加。糖尿病目前影响着孟加拉国20-30%的人口，要么是糖尿病前期，要么是完全表达型糖尿病。糖尿病及其并发症问题日益受到社区、卫生服务提供者和决策者的关注，但关于该问题的严重程度和根本原因的原始数据很少，特别是在农村地区。孟加拉国发病率上升的根本原因是饮食模式的改变、生活方式的改变以及缺乏锻炼和吸烟等其他风险因素的增加。我们的研究将生成孟加拉国农村糖尿病前期、糖尿病和相关危险因素的流行数据，并探索两种干预措施对改善这些贫困人群糖尿病的检测、管理和预防的影响。第一项干预措施将使用移动电话技术向人口发送健康促进信息和有针对性的糖尿病预防和管理信息，同时还实施简单的信息和测验“应用程序”，以促进与糖尿病护理有关的保健提供者培训和决策支持。第二项干预措施将侧重于参与性社区团体，使社区参与一系列会议，在这些会议中，居民自己确定和处理可能增加其患糖尿病风险或妨碍对该疾病进行有效管理的因素。假设以这种方式进行集体社区信息传递和参与将提高认识并引发行为改变，从而通过大型社区调查来降低风险因素和疾病指标的负担。同时对不同地区的两种干预措施进行评估，可以将每种干预措施的益处与只接受标准糖尿病预防和护理服务的“对照”地区进行比较。高度重视实施和过程评价将确定这些干预措施可能的可扩展性和可持续性。

As survival improves in low-income countries the problem of non-communicable diseases, including diabetes, increases. Diabetes currently affects between 20-30% of the population of Bangladesh either as pre-diabetes or fully expressed diabetes mellitus. The problem of diabetes and its complications is a growing concern among communities, health service providers and policymakers, yet raw data on the magnitude and underlying causes of the problem are scarce, especially in rural areas. Underlying the increasing prevalence in Bangladesh are patterns of dietary change, changing lifestyles and increases in other risk factors like lack of exercise and smoking. Our study will generate prevalence data on pre-diabetes, diabetes, and associated risk factors in rural villages in Bangladesh and explore the impacts of two interventions to improve the detection, management and prevention of diabetes in these deprived populations. The first intervention will use mobile phone technology to send health promotion information and targeted diabetes prevention and management messages to the population whilst also implementing simple messages and quiz 'apps' to facilitate health provider training and decision support in relation to diabetes care. The second intervention will focus on participatory community groups, engaging communities in a series of meetings in which the population themselves identify and address factors that may increase their risks of diabetes or prevent the effective management of the disease. It is hypothesised that collective community messaging and engagement in this way will enhance awareness and trigger behaviour change leading to lower burdens of risk factors and disease indicators, measured through large community surveys. The simultaneous evaluation of the two interventions in different areas will allow a comparison of the benefits of each compared to a 'control' area that only receives standard diabetes prevention and care services. A strong focus on implementation and process evaluation will identify the likely scalability and sustainability of these interventions.