The value of process evaluation for public health interventions: field-case studies for non-communicable disease prevention and management in five countries.

Complex interventions are needed to effectively tackle non-communicable diseases. However, complex interventions can contain a mix of effective and ineffective actions. Process evaluation (PE) in public health research is of great value as it could clarify the mechanisms and contextual factors associ-ated with variation in the outcomes, better identify effective components, and inform adaptation of the intervention. The aim of this paper is to demonstrate the value of PE through five case studies that span the research cycle. The interven-tions include using digital health, salt reduction strategies, use of fixed dose combinations, and task shifting. Insights of the methods used, and the implications of the PE findings to the project, were discussed. PE of complex interventions can refute or confirm the hypothesized mechanisms of action, thereby enabling intervention refinement, and identifying implementation strategies that can address local contextual needs, so as to improve service delivery and public health outcomes.

Going digital: opportunities and barriers in the use of technology for health research.

Digital health refers to the use of novel information com-munication technologies in healthcare. The use of these technologies could positively impact public health and health outcomes of populations by generating timely data, and facili-tating the process of data collection, analysis, and knowledge translation. Using selected case studies, we aim to describe the opportunities and barriers in the use of technology applied to health-related research. We focus on three areas: strategies to generate new data using novel data collection methods, strategies to use and analyze existing data, and using digital health for health-related interventions. Exemplars from seven countries are provided to illustrate activity across these areas. Although the use of health-related technologies is increasing, challenges remain to support their adoption and scale-up -especially for under-served populations. Research using digital health approaches should take a user-centered design, actively working with the population of interest to maximize their uptake and effectiveness.

The role of colour and summary indicators in influencing front-of-pack food label effectiveness across seven countries.

OBJECTIVE: Many countries are considering the implementation of front-of-pack nutrition labels as a strategy to address high and increasing levels of overweight and obesity. A growing body of work demonstrates the superiority of labels that use colour and/or provide a summary indicator of product healthiness to enhance comprehension. However, previous studies have been confounded in determining the relative effectiveness of these two attributes by comparing labels that also differ in other ways. The present study tested labels that varied only on use of colour and/or reliance on a summary indicator across an international sample to provide unique insights into the relative importance of these attributes. DESIGN: Participants were randomised to see one of four variations of the Health Star Rating label that differed on the basis of use of colour and sole provision of a summary indicator. SETTING: Australia, Canada, China, India, New Zealand, the UK and the USA. PARTICIPANTS: Adults (n 7545) in seven countries were exposed to online choice tasks requiring them to select a preferred breakfast cereal and then nominate the healthiest cereal. RESULTS: Overall, the coloured versions, and particularly the one with just a summary indicator, outperformed the monochrome version that included nutrient-specific information. However, there were some differences by country, with results from Canada and China indicating superior outcomes for monochrome labels and those providing nutrient-specific information. CONCLUSIONS: The results highlight the importance of colour, but suggest that the introduction of front-of-pack nutrition labels should be preceded by country-specific formative testing to identify potential differences in outcomes.

Cardiovascular disease risk and comparison of different strategies for blood pressure management in rural India.

BACKGROUND: Non-optimal blood pressure (BP) levels are a major cause of disease burden globally. We describe current BP and treatment patterns in rural India and compare different approaches to BP lowering in this setting. METHODS: All individuals aged ≥40 years from 54 villages in a South Indian district were invited and 62,194 individuals (84%) participated in a cross-sectional study. Individual 10-year absolute cardiovascular disease (CVD) risk was estimated using WHO/ISH charts. Using known effects of treatment, proportions of events that would be averted under different paradigms of BP lowering therapy were estimated. RESULTS: After imputation of pre-treatment BP levels for participants on existing treatment, 76·9% (95% confidence interval, 75.7-78.0%), 5·3% (4.9-5.6%), and 17·8% (16.9-18.8%) of individuals had a 10-year CVD risk defined as low (< 20%), intermediate (20-29%), and high (≥30%, established CVD, or BP > 160/100 mmHg), respectively. Compared to the 19.6% (18.4-20.9%) of adults treated with current practice, a slightly higher or similar proportion would be treated using an intermediate (23·2% (22.0-24.3%)) or high (17·9% (16.9-18.8%) risk threshold for instituting BP lowering therapy and this would avert 87·2% (85.8-88.5%) and 62·7% (60.7-64.6%) more CVD events over ten years, respectively. These strategies were highly cost-effective relative to the current practice. CONCLUSION: In a rural Indian community, a substantial proportion of the population has elevated CVD risk. The more efficient and cost-effective clinical approach to BP lowering is to base treatment decisions on an estimate of an individual's short-term absolute CVD risk rather than with BP based strategy. CLINICAL TRIAL REGISTRATION: Clinical Trials Registry of India CTRI/2013/06/003753 , 14 June 2013.

Developing consensus measures for global programs: lessons from the Global Alliance for Chronic Diseases Hypertension research program.

BACKGROUND: The imperative to improve global health has prompted transnational research partnerships to investigate common health issues on a larger scale. The Global Alliance for Chronic Diseases (GACD) is an alliance of national research funding agencies. To enhance research funded by GACD members, this study aimed to standardise data collection methods across the 15 GACD hypertension research teams and evaluate the uptake of these standardised measurements. Furthermore we describe concerns and difficulties associated with the data harmonisation process highlighted and debated during annual meetings of the GACD funded investigators. With these concerns and issues in mind, a working group comprising representatives from the 15 studies iteratively identified and proposed a set of common measures for inclusion in each of the teams' data collection plans. One year later all teams were asked which consensus measures had been implemented. RESULTS: Important issues were identified during the data harmonisation process relating to data ownership, sharing methodologies and ethical concerns. Measures were assessed across eight domains; demographic; dietary; clinical and anthropometric; medical history; hypertension knowledge; physical activity; behavioural (smoking and alcohol); and biochemical domains. Identifying validated measures relevant across a variety of settings presented some difficulties. The resulting GACD hypertension data dictionary comprises 67 consensus measures. Of the 14 responding teams, only two teams were including more than 50 consensus variables, five teams were including between 25 and 50 consensus variables and four teams were including between 6 and 24 consensus variables, one team did not provide details of the variables collected and two teams did not include any of the consensus variables as the project had already commenced or the measures were not relevant to their study. CONCLUSIONS: Deriving consensus measures across diverse research projects and contexts was challenging. The major barrier to their implementation was related to the time taken to develop and present these measures. Inclusion of consensus measures into future funding announcements would facilitate researchers integrating these measures within application protocols. We suggest that adoption of consensus measures developed here, across the field of hypertension, would help advance the science in this area, allowing for more comparable data sets and generalizable inferences.

What is the optimal recall period for verbal autopsies? Validation study based on repeat interviews in three populations.

BACKGROUND: One key contextual feature in Verbal Autopsy (VA) is the time between death and survey administration, or recall period. This study quantified the effect of recall period on VA performance by using a paired dataset in which two VAs were administered for a single decedent. METHODS: This study used information from the Population Health Metrics Research Consortium (PHMRC) Study, which collected VAs for "gold standard" cases where cause of death (COD) was supported by clinical criteria. This study repeated VA interviews within 3-52 months of death in PHMRC study sites in Andhra Pradesh, India, and Bohol and Manila, Philippines. The final dataset included 2113 deaths interviewed twice and with recall periods ranging from 0 to 52 months. COD was assigned by the Tariff method and its accuracy determined by comparison with the gold standard COD. RESULTS: The probability of a correct diagnosis of COD decreased by 0.55 % per month in the period after death. Site of data collection and survey module also affected the probability of Tariff Method correctly assigning a COD. The probability of a correct diagnosis in VAs collected 3-11 months after death will, on average, be 95.9 % of that in VAs collected within 3 months of death. CONCLUSIONS: These findings suggest that collecting VAs within 3 months of death may improve the quality of the information collected, taking the need for a period of mourning into account. This study substantiates the WHO recommendation that it is reasonable to collect VAs up to 1 year after death providing it is accepted that probability of a correct diagnosis is likely to decline month by month during this period.

The paradox of verbal autopsy in cause of death assignment: symptom question unreliability but predictive accuracy.

BACKGROUND: We believe that it is important that governments understand the reliability of the mortality data which they have at their disposable to guide policy debates. In many instances, verbal autopsy (VA) will be the only source of mortality data for populations, yet little is known about how the accuracy of VA diagnoses is affected by the reliability of the symptom responses. We previously described the effect of the duration of time between death and VA administration on VA validity. In this paper, using the same dataset, we assess the relationship between the reliability and completeness of symptom responses and the reliability and accuracy of cause of death (COD) prediction. METHODS: The study was based on VAs in the Population Health Metrics Research Consortium (PHMRC) VA Validation Dataset from study sites in Bohol and Manila, Philippines and Andhra Pradesh, India. The initial interview was repeated within 3-52 months of death. Question responses were assessed for reliability and completeness between the two survey rounds. COD was predicted by Tariff Method. RESULTS: A sample of 4226 VAs was collected for 2113 decedents, including 1394 adults, 349 children, and 370 neonates. Mean question reliability was unexpectedly low (kappa = 0.447): 42.5 % of responses positive at the first interview were negative at the second, and 47.9 % of responses positive at the second had been negative at the first. Question reliability was greater for the short form of the PHMRC instrument (kappa = 0.497) and when analyzed at the level of the individual decedent (kappa = 0.610). Reliability at the level of the individual decedent was associated with COD predictive reliability and predictive accuracy. CONCLUSIONS: Families give coherent accounts of events leading to death but the details vary from interview to interview for the same case. Accounts are accurate but inconsistent; different subsets of symptoms are identified on each occasion. However, there are sufficient accurate and consistent subsets of symptoms to enable the Tariff Method to assign a COD. Questions which contributed most to COD prediction were also the most reliable and consistent across repeat interviews; these have been included in the short form VA questionnaire. Accuracy and reliability of diagnosis for an individual death depend on the quality of interview. This has considerable implications for the progressive roll out of VAs into civil registration and vital statistics (CRVS) systems.

A shortened verbal autopsy instrument for use in routine mortality surveillance systems.

BACKGROUND: Verbal autopsy (VA) is recognized as the only feasible alternative to comprehensive medical certification of deaths in settings with no or unreliable vital registration systems. However, a barrier to its use by national registration systems has been the amount of time and cost needed for data collection. Therefore, a short VA instrument (VAI) is needed. In this paper we describe a shortened version of the VAI developed for the Population Health Metrics Research Consortium (PHMRC) Gold Standard Verbal Autopsy Validation Study using a systematic approach. METHODS: We used data from the PHMRC validation study. Using the Tariff 2.0 method, we first established a rank order of individual questions in the PHMRC VAI according to their importance in predicting causes of death. Second, we reduced the size of the instrument by dropping questions in reverse order of their importance. We assessed the predictive performance of the instrument as questions were removed at the individual level by calculating chance-corrected concordance and at the population level with cause-specific mortality fraction (CSMF) accuracy. Finally, the optimum size of the shortened instrument was determined using a first derivative analysis of the decline in performance as the size of the VA instrument decreased for adults, children, and neonates. RESULTS: The full PHMRC VAI had 183, 127, and 149 questions for adult, child, and neonatal deaths, respectively. The shortened instrument developed had 109, 69, and 67 questions, respectively, representing a decrease in the total number of questions of 40-55%. The shortened instrument, with text, showed non-significant declines in CSMF accuracy from the full instrument with text of 0.4%, 0.0%, and 0.6% for the adult, child, and neonatal modules, respectively. CONCLUSIONS: We developed a shortened VAI using a systematic approach, and assessed its performance when administered using hand-held electronic tablets and analyzed using Tariff 2.0. The length of a VA questionnaire was shortened by almost 50% without a significant drop in performance. The shortened VAI developed reduces the burden of time and resources required for data collection and analysis of cause of death data in civil registration systems.

Suicide deaths in rural Andhra Pradesh--a cause for global health action.

OBJECTIVES: To determine the proportion of deaths attributable to suicides in rural Andhra Pradesh, India over a 4-year period using a verbal autopsy method. METHODS: Deaths occurring in 45 villages (population 185,629) were documented over a 4-year period from 2003 to 2007 by non-physician healthcare workers trained in the use of a verbal autopsy tool. Causes of death were assigned by physicians trained in the International Classification of Diseases, version 10. All data were entered and processed electronically using a secure study website. RESULTS: Verbal autopsies were completed for 98.2% (5786) of the deaths (5895) recorded. The crude death rate was 8.0/1000. 4.8% (95% CI 4.3-5.4) of all deaths were suicides, giving a suicide rate of 37.5/100,000 population. Forty-three percent of suicides occurred in the age group 15-29 years, and 62% were in men. In the younger age groups (10-29 years), suicides by women (56%) were more common than by men (44%). Poisoning (40%) was the most common method of self-harm followed by hanging (12%). CONCLUSION: The suicide rate in this part of rural Andhra Pradesh is three times higher than the national average of 11.2/100,000, but is in line with that reported in the Million Death Study. There is an urgent need to develop strategies targeted at young individuals to prevent deaths by suicide in India.

Engineering a mobile health tool for resource-poor settings to assess and manage cardiovascular disease risk: SMARThealth study.

BACKGROUND: The incidence of chronic diseases in low- and middle-income countries is rapidly increasing both in urban and rural regions. A major challenge for health systems globally is to develop innovative solutions for the prevention and control of these diseases. This paper discusses the development and pilot testing of SMARTHealth, a mobile-based, point-of-care Clinical Decision Support (CDS) tool to assess and manage cardiovascular disease (CVD) risk in resource-constrained settings. Through pilot testing, the preliminary acceptability, utility, and efficiency of the CDS tool was obtained. METHODS: The CDS tool was part of an mHealth system comprising a mobile application that consisted of an evidence-based risk prediction and management algorithm, and a server-side electronic medical record system. Through an agile development process and user-centred design approach, key features of the mobile application that fitted the requirements of the end users and environment were obtained. A comprehensive analytics framework facilitated a data-driven approach to investigate four areas, namely, system efficiency, end-user variability, manual data entry errors, and usefulness of point-of-care management recommendations to the healthcare worker. A four-point Likert scale was used at the end of every risk assessment to gauge ease-of-use of the system. RESULTS: The system was field-tested with eleven village healthcare workers and three Primary Health Centre doctors, who screened a total of 292 adults aged 40 years and above. 34% of participants screened by health workers were identified by the CDS tool to be high CVD risk and referred to a doctor. In-depth analysis of user interactions found the CDS tool feasible for use and easily integrable into the workflow of healthcare workers. Following completion of the pilot, further technical enhancements were implemented to improve uptake of the mHealth platform. It will then be evaluated for effectiveness and cost-effectiveness in a cluster randomized controlled trial involving 54 southern Indian villages and over 16000 individuals at high CVD risk. CONCLUSIONS: An evidence-based CVD risk prediction and management tool was used to develop an mHealth platform in rural India for CVD screening and management with proper engagement of health care providers and local communities. With over a third of screened participants being high risk, there is a need to demonstrate the clinical impact of the mHealth platform so that it could contribute to improved CVD detection in high risk low resource settings.

Heart failure care in low- and middle-income countries: a systematic review and meta-analysis.

BACKGROUND: Heart failure places a significant burden on patients and health systems in high-income countries. However, information about its burden in low- and middle-income countries (LMICs) is scant. We thus set out to review both published and unpublished information on the presentation, causes, management, and outcomes of heart failure in LMICs. METHODS AND FINDINGS: Medline, Embase, Global Health Database, and World Health Organization regional databases were searched for studies from LMICs published between 1 January 1995 and 30 March 2014. Additional unpublished data were requested from investigators and international heart failure experts. We identified 42 studies that provided relevant information on acute hospital care (25 LMICs; 232,550 patients) and 11 studies on the management of chronic heart failure in primary care or outpatient settings (14 LMICs; 5,358 patients). The mean age of patients studied ranged from 42 y in Cameroon and Ghana to 75 y in Argentina, and mean age in studies largely correlated with the human development index of the country in which they were conducted (r = 0.71, p<0.001). Overall, ischaemic heart disease was the main reported cause of heart failure in all regions except Africa and the Americas, where hypertension was predominant. Taking both those managed acutely in hospital and those in non-acute outpatient or community settings together, 57% (95% confidence interval [CI]: 49%-64%) of patients were treated with angiotensin-converting enzyme inhibitors, 34% (95% CI: 28%-41%) with beta-blockers, and 32% (95% CI: 25%-39%) with mineralocorticoid receptor antagonists. Mean inpatient stay was 10 d, ranging from 3 d in India to 23 d in China. Acute heart failure accounted for 2.2% (range: 0.3%-7.7%) of total hospital admissions, and mean in-hospital mortality was 8% (95% CI: 6%-10%). There was substantial variation between studies (p<0.001 across all variables), and most data were from urban tertiary referral centres. Only one population-based study assessing incidence and/or prevalence of heart failure was identified. CONCLUSIONS: The presentation, underlying causes, management, and outcomes of heart failure vary substantially across LMICs. On average, the use of evidence-based medications tends to be suboptimal. Better strategies for heart failure surveillance and management in LMICs are needed. Please see later in the article for the Editors' Summary.

Using verbal autopsy to measure causes of death: the comparative performance of existing methods.

BACKGROUND: Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. METHODS: We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. RESULTS: Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. CONCLUSIONS: Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.

Comparability of HbA1c and lipids measured with dried blood spot versus venous samples: a systematic review and meta-analysis.

BACKGROUND: Levels of haemoglobin A1c (HbA1c) and blood lipids are important determinants of risk in patients with diabetes. Standard analysis methods based upon venous blood samples can be logistically challenging in resource-poor settings where much of the diabetes epidemic is occurring. Dried blood spots (DBS) provide a simple alternative method for sample collection but the comparability of data from analyses based on DBS is not well established. METHODS: We conducted a systematic review and meta-analysis to define the association of findings for HbA1c and blood lipids for analyses based upon standard methods compared to DBS. The Cochrane, Embase and Medline databases were searched for relevant reports and summary regression lines were estimated. RESULTS: 705 abstracts were found by the initial electronic search with 6 further reports identified by manual review of the full papers. 16 studies provided data for one or more outcomes of interest. There was a close agreement between the results for HbA1c assays based on venous and DBS samples (DBS = 0.9858venous + 0.3809), except for assays based upon affinity chromatography. Significant adjustment was required for assays of total cholesterol (DBS = 0.6807venous + 1.151) but results for triglycerides (DBS = 0.9557venous + 0.1427) were directly comparable. CONCLUSIONS: For HbA1c and selected blood lipids, assays based on DBS samples are clearly associated with assays based on standard venous samples. There are, however, significant uncertainties about the nature of these associations and there is a need for standardisation of the sample collection, transportation, storage and analysis methods before the technique can be considered mainstream. This should be a research priority because better elucidation of metabolic risks in resource poor settings, where venous sampling is infeasible, will be key to addressing the global epidemic of cardiovascular diseases.

Implementation of mobile-health technology is associated with five-year survival among individuals in rural areas of Indonesia.

There is an urgent need to focus on implementing cost-effective health interventions and policies to reduce the burden of cardiovascular disease in Indonesia. This study aims to evaluate whether a mobile technology-supported primary health care intervention, compared with usual care, would reduce the risk of all-cause mortality among people in rural Indonesia. Data were collected from 11,098 participants in four intervention villages and 10,981 participants in four control villages in Malang district, Indonesia. The baseline data were collected in 2016. All the participants were followed for five years, and the mortality data were recorded. Cox proportional hazard model was used to examine the association between the intervention and the risk of all-cause mortality, adjusted for the covariates, including age, gender, educational attainment, employment and marital status, obesity and the presence of diabetes mellitus. During the five-year follow-up, 275 participants died in intervention villages, compared with 362 in control villages. Participants residing in intervention villages were at 18% (95%CI = 4 to 30) lower risk of all-cause mortality. Higher education attainment and being married are associated with lower risks of all-cause mortality among respondents who lived in the control villages, but not among those living in the intervention villages. A mobile technology-supported primary health care intervention had the potential to improve the five-year survival among people living in villages in an upper-middle income country.

Rationale, Design, and Intervention Development of a Mobile Health-Led Primary Care Program for Management of Type 2 Diabetes in Rural Thailand: Protocol for a SMARThealth Diabetes Study.

BACKGROUND: Noncommunicable diseases (NCDs), particularly diabetes and chronic kidney diseases, pose a significant health burden in Thailand, especially among socioeconomically disadvantaged populations. The existing primary health care system faces challenges in providing optimal care for NCDs due to inadequate primary care workforce. The SMARThealth program offers a technology-based solution to enhance NCD management through task-sharing among nonphysician health care workers. OBJECTIVE: This study aims to adapt and implement the SMARThealth Diabetes program in rural Thailand to improve diabetes management. The main objectives are to (1) adapt, validate, and integrate the SMARThealth Diabetes program for improving the management of type 2 diabetes mellitus at the primary health care level; and (2) to determine the feasibility and acceptability of the SMARThealth Diabetes program in rural communities of Thailand. METHODS: A pragmatic, type 2 hybrid effectiveness or implementation, parallel-group cluster randomized controlled trial of 12 months duration and involving 51 subdistrict health offices in rural communities of Kamphaeng Phet province, Thailand, will be conducted. The intervention arm will receive the SMARThealth Diabetes program, including workforce restructuring, clinical decision support system, and continuous performance monitoring, while the control arm will continue with usual practice. Data will be collected using the SMARThealth platform and will be stored on a server in Thailand. The primary outcome measure will be the change in mean hemoglobin A1c (HbA1c) measured at randomization and 12 months from randomization between the intervention and control clusters. Secondary outcomes will include the difference in change in albuminuria status, estimated glomerular filtration rate, systolic blood pressure, and low-density lipoprotein cholesterol level. The analysis for change in HbA1c between baseline and end of study will be performed using linear mixed models. Any imbalances between the 2 arms will be addressed by sensitivity analyses. Additionally, a mixed methods process evaluation will be conducted to assess the implementation process, that will include in-depth interviews and focus group discussions, in addition to the quantitative data collected during the implementation process. The qualitative data will be thematically analyzed to explore factors that promote or inhibit the implementation and maintenance of the program. RESULTS: The data collection commenced in November 2022, and the results will be ready for publication by the first quarter of 2025. Effectiveness of the intervention package will be assessed by change in mean HbA1c measures, and detailed feasibility, barriers, and enablers for the implementation of the intervention will be documented through a detailed process evaluation. CONCLUSIONS: The study protocol outlines a novel approach to enhancing diabetes management in rural Thailand through digital technology-based interventions that will facilitate task-sharing among health care workers. This can help inform future strategies for improving NCD care in low-resource settings globally. TRIAL REGISTRATION: Thai Clinical Trials Registry TCTR20200322006; https://www.thaiclinicaltrials.org/show/TCTR20200322006. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59266.

Global lessons on delivery of primary healthcare services for people with non-communicable diseases: convergent mixed methods.

OBJECTIVE: To extract key lessons on primary healthcare (PHC) service delivery strategies for non-communicable diseases (NCD) from the work of researchers funded by the Global Alliance for Chronic Diseases (GACD). DESIGN: A convergent mixed methods study that extracted data using a standardised template from research projects funded by the GACD that focused on PHC. The strategies implemented in these studies were mapped onto the PHC Performance Initiative framework. Semistructured qualitative interviews were conducted with researchers from purposefully selected projects to understand the strategies and contextual factors in more depth. SETTING: PHC contexts from low or middle-income countries (LMIC) as well as vulnerable groups within high-income countries. Projects came from all regions of the world, particularly East Asia and Pacific, sub-Saharan Africa, South Asia, Latin America and Caribbean. PARTICIPANTS: The study extracted data on 84 research projects and interviewed researchers from 16 research projects. RESULTS: Research projects came from all regions of the world, and mainly focused on diabetes (35.3%), hypertension (28.3%) and mental health (27.6%). Mapped onto the PHC Performance Initiative framework: 49.4% focused on high-quality PHC (particularly the comprehensiveness of NCD care, 41.2%); 41.2% on the availability of PHC services (particularly the competence of healthcare workers, 36.5%); 35.3% on population health management (particularly community-based services, 35.3%); 34.1% on facility organisation and management (particularly team-based care, 20.0%) and 31.8% on access (particularly digital technology, 23.5%). Most common strategies were task shifting and training to improve the comprehensiveness of NCD care through community-based services. Contextual factors related to inputs: infrastructure, equipment and medication, workforce (particularly community health workers), finances, health information systems and digital technology. CONCLUSION: Key strategies and contextual factors to improve PHC service delivery for NCDs in LMICs were identified. These strategies should combine with other strategies to strengthen the PHC system as a whole, while improving care for NCDs.

Mental Health Care Support in Rural India: A Cluster Randomized Clinical Trial.

Importance: More than 150 million people in India need mental health care but few have access to affordable care, especially in rural areas. Objective: To determine whether a multifaceted intervention involving a digital health care model along with a community-based antistigma campaign leads to reduced depression risk and lower mental health-related stigma among adults residing in rural India. Design, Setting, and Participants: This parallel, cluster randomized, usual care-controlled trial was conducted from September 2020 to December 2021 with blinded follow-up assessments at 3, 6, and 12 months at 44 rural primary health centers across 3 districts in Haryana and Andhra Pradesh states in India. Adults aged 18 years and older at high risk of depression or self-harm defined by either a Patient Health Questionnaire-9 item (PHQ-9) score of 10 or greater, a Generalized Anxiety Disorder-7 item (GAD-7) score of 10 or greater, or a score of 2 or greater on the self-harm/suicide risk question on the PHQ-9. A second cohort of adults not at high risk were selected randomly from the remaining screened population. Data were cleaned and analyzed from April 2022 to February 2023. Interventions: The 12-month intervention included a community-based antistigma campaign involving all participants and a digital mental health intervention involving only participants at high risk. Primary health care workers were trained to identify and manage participants at high risk using the Mental Health Gap Action Programme guidelines from the World Health Organization. Main Outcomes and Measures: The 2 coprimary outcomes assessed at 12 months were mean PHQ-9 scores in the high-risk cohort and mean behavior scores in the combined high-risk and non-high-risk cohorts using the Mental Health Knowledge, Attitude, and Behavior scale. Results: Altogether, 9928 participants were recruited (3365 at high risk and 6563 not at high risk; 5638 [57%] female and 4290 [43%] male; mean [SD] age, 43 [16] years) with 9057 (91.2%) followed up at 12 months. Mean PHQ-9 scores at 12 months for the high-risk cohort were lower in the intervention vs control groups (2.77 vs 4.48; mean difference, -1.71; 95% CI, -2.53 to -0.89; P < .001). The remission rate in the high-risk cohort (PHQ-9 and GAD-7 scores <5 and no risk of self-harm) was higher in the intervention vs control group (74.7% vs 50.6%; odds ratio [OR], 2.88; 95% CI, 1.53 to 5.42; P = .001). Across both cohorts, there was no difference in 12-month behavior scores in the intervention vs control group (17.39 vs 17.74; mean difference, -0.35; 95% CI, -1.11 to 0.41; P = .36). Conclusions and Relevance: A multifaceted intervention was effective in reducing depression risk but did not improve intended help-seeking behaviors for mental illness. Trial Registration: Clinical Trial Registry India: CTRI/2018/08/015355.

The efficacy of interventions to prevent type 2 diabetes among women with recent gestational diabetes mellitus-A living systematic review and meta-analysis.

BACKGROUND: While previously considered a transient condition, with no lasting adverse impact, gestational diabetes mellitus (GDM) is now a well-established risk factor for developing type 2 diabetes mellitus (T2DM). The risk of developing T2DM appears to be particularly high in the first few years after childbirth, providing a compelling case for early intervention. This review provides an up-to-date systematic review and meta-analysis to assess the effectiveness of interventions to reduce incidence of T2DM in women with a recent history of GDM. METHODS: The search was conducted on October 20, 2023 with an annual surveillance planned for the next 5 years to maintain a living systematic review. The inclusion criteria were randomized controlled trials of any type in women within 5 years of GDM-complicated pregnancy that reported outcomes of T2DM diagnosis or measures of dysglycemia with a follow-up of at least 12 months. RESULTS: Seventeen studies met our inclusion criteria and have been included in this review. There were 3 pharmacological and 14 lifestyle interventions. Intervention was not associated with significant reduction in the primary outcome of T2DM (risk ratio, 0.78; 95% confidence interval [CI]: 0.43-1.41; p = 0.41; I2 = 79%) compared with the control group (placebo or usual care). However, meta-analysis of the four studies reporting hazard ratios suggested a reduction in diabetes incidence (hazard ratio, 0.68; 95% CI: 0.48-0.97; p = 0.03; I2 = 31%). CONCLUSION: This review provides equivocal evidence about the efficacy of interventions to reduce the risk of T2DM in women within 5 years of GDM-complicated pregnancy and highlights the need for further studies, including pharmacotherapy.

Antenatal oral glucose tolerance test abnormalities in the prediction of future risk of postpartum diabetes in women with gestational diabetes: Results from the LIVING study.

OBJECTIVES: To explore associations between type and number of abnormal glucose values on antenatal oral glucose tolerance test (OGTT) with postpartum diabetes in South Asian women diagnosed with gestational diabetes (GDM) using International Association of the Diabetes and Pregnancy Study Groups criteria. METHODS: This post-hoc evaluation of the Lifestyle Intervention IN Gestational Diabetes (LIVING) study, a randomized controlled trial, was conducted among women with GDM in the index pregnancy, across 19 centers in Bangladesh, India, and Sri Lanka. Postpartum diabetes (outcome) was defined on OGTT, using American Diabetes Association (ADA) criteria. RESULTS: We report data on 1468 women with GDM, aged 30.9 (5.0) years, and with median (interquartile range) follow-up period of 1.8 (1.4-2.4) years after childbirth following the index pregnancy. We found diabetes in 213 (14.5%) women with an incidence of 8.7 (7.6-10.0)/100 women-years. The lowest incidence rate was 3.8/100 women years, in those with an isolated fasting plasma glucose (FPG) abnormality, and highest was 19.0/100 women years in participants with three abnormal values. The adjusted hazard ratios for two and three abnormal values compared to one abnormal value were 1.73 (95% confidence interval [CI], 1.18-2.54; p = .005) and 3.56 (95% CI, 2.46-5.16; p < .001) respectively. The adjusted hazard ratio for the combined (combination of fasting and postglucose load) abnormalities was 2.61 (95% CI, 1.70-4.00; p < .001), compared to isolated abnormal FPG. CONCLUSIONS: Risk of diabetes varied significantly depending upon the type and number of abnormal values on antenatal OGTT. These data may inform future precision medicine approaches such as risk prediction models in identifying women at higher risk and may guide future targeted interventions.