Applying systems thinking to identify enablers and challenges to scale-up interventions for hypertension and diabetes in low-income and middle-income countries: protocol for a longitudinal mixed-methods study.

INTRODUCTION: There is an urgent need to reduce the burden of non-communicable diseases (NCDs), particularly in low-and middle-income countries, where the greatest burden lies. Yet, there is little research concerning the specific issues involved in scaling up NCD interventions targeting low-resource settings. We propose to examine this gap in up to 27 collaborative projects, which were funded by the Global Alliance for Chronic Diseases (GACD) 2019 Scale Up Call, reflecting a total funding investment of approximately US$50 million. These projects represent diverse countries, contexts and adopt varied approaches and study designs to scale-up complex, evidence-based interventions to improve hypertension and diabetes outcomes. A systematic inquiry of these projects will provide necessary scientific insights into the enablers and challenges in the scale up of complex NCD interventions. METHODS AND ANALYSIS: We will apply systems thinking (a holistic approach to analyse the inter-relationship between constituent parts of scaleup interventions and the context in which the interventions are implemented) and adopt a longitudinal mixed-methods study design to explore the planning and early implementation phases of scale up projects. Data will be gathered at three time periods, namely, at planning (TP), initiation of implementation (T0) and 1-year postinitiation (T1). We will extract project-related data from secondary documents at TP and conduct multistakeholder qualitative interviews to gather data at T0 and T1. We will undertake descriptive statistical analysis of TP data and analyse T0 and T1 data using inductive thematic coding. The data extraction tool and interview guides were developed based on a literature review of scale-up frameworks. ETHICS AND DISSEMINATION: The current protocol was approved by the Monash University Human Research Ethics Committee (HREC number 23482). Informed consent will be obtained from all participants. The study findings will be disseminated through peer-reviewed publications and more broadly through the GACD network

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Applying systems thinking to identify enablers and challenges to scale-up interventions for hypertension and diabetes in low-income and middle-income countries: Protocol for a longitudinal mixed-methods study

Introduction There is an urgent need to reduce the burden of non-communicable diseases (NCDs), particularly in low-and middle-income countries, where the greatest burden lies. Yet, there is little research concerning the specific issues involved in scaling up NCD interventions targeting low-resource settings. We propose to examine this gap in up to 27 collaborative projects, which were funded by the Global Alliance for Chronic Diseases (GACD) 2019 Scale Up Call, reflecting a total funding investment of approximately US$50 million. These projects represent diverse countries, contexts and adopt varied approaches and study designs to scale-up complex, evidence-based interventions to improve hypertension and diabetes outcomes. A systematic inquiry of these projects will provide necessary scientific insights into the enablers and challenges in the scale up of complex NCD interventions. Methods and analysis We will apply systems thinking (a holistic approach to analyse the inter-relationship between constituent parts of scaleup interventions and the context in which the interventions are implemented) and adopt a longitudinal mixed-methods study design to explore the planning and early implementation phases of scale up projects. Data will be gathered at three time periods, namely, at planning (TP), initiation of implementation (T0) and 1-year postinitiation (T1). We will extract project-related data from secondary documents at TP and conduct multistakeholder qualitative interviews to gather data at T0 and T1. We will undertake descriptive statistical analysis of TP data and analyse T0 and T1 data using inductive thematic coding. The data extraction tool and interview guides were developed based on a literature review of scale-up frameworks. Ethics and dissemination The current protocol was approved by the Monash University Human Research Ethics Committee (HREC number 23482). Informed consent will be obtained from all participants. The study findings will be disseminated through peer-reviewed publications and more broadly through the GACD network.Fil: Ramani Chander, Anusha. Monash University; AustraliaFil: Joshi, Rohina. George Institute For Global Health; India. University of New South Wales; AustraliaFil: Van Olmen, Josefien. Universiteit Antwerp; BélgicaFil: Wouters, Edwin. Universiteit Antwerp; BélgicaFil: Delobelle, Peter. University of Cape Town; Sudáfrica. Vrije Unviversiteit Brussel; BélgicaFil: Vedanthan, Rajesh. Nyu Grossman School Of Medicine; Estados UnidosFil: Miranda, J Jaime. Universidad Peruana Cayetano Heredia; Perú. University of New South Wales; AustraliaFil: Oldenburg, Brian. La Trobe University; AustraliaFil: Sherwood, Stephen. University of Agriculture Wageningen; Países BajosFil: Rawal, Lal B.. Central Queensland University; AustraliaFil: Mash, Robert James. Stellenbosch University; SudáfricaFil: Irazola, Vilma Edith. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Martens, Monika. Universiteit Antwerp; Bélgica. Institute of Tropical Medicine; BélgicaFil: Lazo Porras, Maria. Universidad Peruana Cayetano Heredia; PerúFil: Liu, Hueiming. University of New South Wales; AustraliaFil: Agarwal, Gina. McMaster University; CanadáFil: Waqa, Gade. Fiji National University; FiyiFil: Soriano Marcolino, Milena. Universidade Federal de Minas Gerais; BrasilFil: Esandi, Maria Eugenia. Academia Nacional de Medicina de Buenos Aires; ArgentinaFil: Pinho Ribeiro, Antonio Luiz. Universidade Federal de Minas Gerais; BrasilFil: Probandari, Ari. Universitas Sebalas Maret; IndonesiaFil: González Salazar, Francisco. Universidad de Monterrey.; MéxicoFil: Shrestha, Abha. Kathmandu University School of Medical Sciences; Nepal. Dhulikhel Hospital; NepalFil: Sujarwoto, Sujarwoto. University of Brawijaya; IndonesiaFil: Levitt, Naomi. University of Cape Town; SudáfricaFil: Paredes, Myriam. Facultad Latinoamericana de Ciencias Sociales; EcuadorFil: Sugishita, Tomohiko. Tokyo Women's Medical University; JapónFil: Batal, Malek. University of Montreal; Canadá. Centre for Public Health Research; CanadáFil: Li, Yuan. The George Institute for Global Health at Peking University Health Science Centre; China. University of New South Wales; AustraliaFil: Beratarrechea, Andrea Gabriela. Instituto de Efectividad Clínica y Sanitaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

International audienceAbstract Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

: Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance