Antenatal care quality and detection of risk among pregnant women: An observational study in Ethiopia, India, Kenya, and South Africa.

BACKGROUND: Antenatal care (ANC) is an essential platform to improve maternal and newborn health (MNH). While several articles have described the content of ANC in low- and middle-income countries (LMICs), few have investigated the quality of detection and management of pregnancy risk factors during ANC. It remains unclear whether women with pregnancy risk factors receive targeted management and additional ANC. METHODS AND FINDINGS: This observational study uses baseline data from the MNH eCohort study conducted in 8 sites in Ethiopia, India, Kenya, and South Africa from April 2023 to January 2024. A total of 4,068 pregnant women seeking ANC for the first time in their pregnancy were surveyed. We built country-specific ANC completeness indices that measured provision of 16 to 22 recommended clinical actions in 5 domains: physical examinations, diagnostic tests, history taking and screening, counselling, and treatment and prevention. We investigated whether women with pregnancy risks tended to receive higher quality care and we assessed the quality of detection and management of 7 concurrent illnesses and pregnancy risk factors (anemia, undernutrition, obesity, chronic illnesses, depression, prior obstetric complications, and danger signs). ANC completeness ranged from 43% in Ethiopia, 66% in Kenya, 73% in India, and 76% in South Africa, with large gaps in history taking, screening, and counselling. Most women in Ethiopia, Kenya, and South Africa initiated ANC in second or third trimesters. We used country-specific multivariable mixed-effects linear regression models to investigate factors associated with ANC completeness. Models included individual demographics, health status, presence of risk factors, health facility characteristics, and fixed effects for the study site. We found that some facility characteristics (staffing, patient volume, structural readiness) were associated with variation in ANC completeness. In contrast, pregnancy risk factors were only associated with a 1.7 percentage points increase in ANC completeness (95% confidence interval 0.3, 3.0, p-value 0.014) in Kenya only. Poor self-reported health was associated with higher ANC completeness in India and South Africa and with lower ANC completeness in Ethiopia. Some concurrent illnesses and risk factors were overlooked during the ANC visit. Between 0% and 6% of undernourished women were prescribed food supplementation and only 1% to 3% of women with depression were referred to a mental health provider or prescribed antidepressants. Only 36% to 73% of women who had previously experienced an obstetric complication (a miscarriage, preterm birth, stillbirth, or newborn death) discussed their obstetric history with the provider during the first ANC visit. Although we aimed to validate self-reported information on health status and content of care with data from health cards, our findings may be affected by recall or other information biases. CONCLUSIONS: In this study, we observed gaps in adherence to ANC standards, particularly for women in need of specialized management. Strategies to maximize the potential health benefits of ANC should target women at risk of poor pregnancy outcomes and improve early initiation of ANC in the first trimester.

Measuring people's views on health system performance: Design and development of the People's Voice Survey.

Todd Lewis and co-authors discuss development and use of the People's Voice Survey for health system assessment.

Snacking Behavior and Association with Metabolic Risk Factors in Adults from North and South India.

BACKGROUND: Snacks are increasingly contributing to daily diets around the world. Studies from high-income countries have demonstrated the link between snack consumption and metabolic risk factors, but there are very few studies from low- and middle-income countries. OBJECTIVES: The objective of this study was to assess snack behavior and its associations with metabolic risk factors in Indian adults. METHODS: Adults from the UDAY study (October 2018-February 2019, n = 8762) from rural and urban Sonipat (North) and Vizag (South) India were studied for snack consumption (food frequency questionnaire), demographic factors, including age, sex, etc. and metabolic risk factors, including BMI, waist circumference, fat percentage, plasma glucose, and blood pressure. We compared snack consumption by categories of sociodemographic factors (Mann-Whitney U test, Kruskal-Wallis test) and studied the likelihood for metabolic risk (logistic regression analysis). RESULTS: Half of the study participants were women and resided in rural locations. Savory snacks were the most preferred; 50% of the participants consumed them 3-5 times/wk. Participants preferred to purchase out-of-home prepared snacks and eat them at home (86.6%) while watching television (69.4%) or with family/friends (49.3%). The reasons for snacking were hunger, craving, liking, and availability. Snack consumption was higher in Vizag (56.6%) than in Sonipat (43.4%), among women (55.5%) than men (44.5%), and the wealthiest; it was similar in rural-urban locations. Frequent consumers of snacks had 2 times higher likelihood for having obesity (OR: 2.22; 95% CI: 1.51, 3.27) central obesity (OR: 2.35; 95% CI: 1.60, 3.45), and higher fat percentage (OR: 1.92; 95% CI: 1.31, 2.82) and higher fasting glucose levels (r=0.12 (0.07-0.18) than consumers who consumed snacks rarely (all P ≤ 0.05). CONCLUSIONS: Snack (savory and sweet) consumption was high among adults from sexes in both urban and rural locations of north and south India. This was associated with higher risk of obesity. There is a need to improve the food environment by promoting policies for ensuring healthier food options to reduce snacking and associated metabolic risk.

Food insecurity and its determinants among adults in North and South India.

BACKGROUND: Food insecurity is a major public health problem worldwide. In India, there are limited food insecurity assessment studies using a conventionally accepted method like the Food Insecurity Experience Scale (FIES), developed by the Food and Agricultural Organization (FAO). This study aims to measure food insecurity using the FIES and explore its determinants and association with body mass index (BMI) among Indian adults.  METHODS: In a cross-sectional study, we used FIES to measure food security in a sample of 9005 adults residing in North and South India. Using questionnaires, socio-demographic factors, dietary intake and food security data were collected. The dietary diversity scores (FAO-IDDS) and food insecurity scores (FAO-FIES) were calculated. Body size was measured and BMI was calculated.  RESULTS: The mean age of the study participants was 52.4 years (± 11.7); half were women and half resided in rural areas. Around 10% of the participants reported having experienced (mild or moderate or severe) food insecurity between October 2018 and February 2019. Dietary diversity (measured by FAO's Individual Dietary Diversity Scores, IDDS) was low and half of the participants consumed ≤ 3 food groups/day. The mean BMI was 24.7 kg/m2. In the multivariate analysis, a lower IDDS and BMI were associated with a higher FIES. The place of residence, gender and wealth index were important determinants of FIES, with those residing in South India, women and those belonging to the poorest wealth index reporting higher food insecurity. CONCLUSION: Food security is understudied in India. Our study adds important evidence to the literature. Despite having marginal food insecurity, high prevalence of low diet quality, especially among women, is disconcerting. Similar studies at the national level are warranted to determine the food insecurity situation comprehensively in India and plan appropriate policy actions to address it effectively, to attain the key Sustainable Development Goals (SDG).

A cluster randomized controlled trial of an electronic decision-support system to enhance antenatal care services in pregnancy at primary healthcare level in Telangana, India: trial protocol.

BACKGROUND: India contributes 15% of the total global maternal mortality burden. An increasing proportion of these deaths are due to Pregnancy Induced Hypertension (PIH), Gestational Diabetes Mellitus (GDM), and anaemia. This study aims to evaluate the effectiveness of a tablet-based electronic decision-support system (EDSS) to enhance routine antenatal care (ANC) and improve the screening and management of PIH, GDM, and anaemia in pregnancy in primary healthcare facilities of Telangana, India. The EDSS will work at two levels of primary health facilities and is customized for three cadres of healthcare providers - Auxiliary Nurse Midwifes (ANMs), staff nurses, and physicians (Medical Officers). METHODS: This will be a cluster randomized controlled trial involving 66 clusters with a total of 1320 women in both the intervention and control arms. Each cluster will include three health facilities-one Primary Health Centre (PHC) and two linked sub-centers (SC). In the facilities under the intervention arm, ANMs, staff nurses, and Medical Officers will use the EDSS while providing ANC for all pregnant women. Facilities in the control arm will continue to provide ANC services using the existing standard of care in Telangana. The primary outcome is ANC quality, measured as provision of a composite of four selected ANC components (measurement of blood pressure, blood glucose, hemoglobin levels, and conducting a urinary dipstick test) by the healthcare providers per visit, observed over two visits. Trained field research staff will collect outcome data via an observation checklist. DISCUSSION: To our knowledge, this is the first trial in India to evaluate an EDSS, targeted to enhance the quality of ANC and improve the screening and management of PIH, GDM, and anaemia, for multiple levels of health facilities and several cadres of healthcare providers. If effective, insights from the trial on the feasibility and cost of implementing the EDSS can inform potential national scale-up. Lessons learned from this trial will also inform recommendations for designing and upscaling similar mHealth interventions in other low and middle-income countries. CLINICALTRIALS: gov, NCT03700034, registered 9 Oct 2018, https://www. CLINICALTRIALS: gov/ct2/show/NCT03700034 CTRI, CTRI/2019/01/016857, registered on 3 Mar 2019, http://www.ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=28627&EncHid=&modid=&compid=%27,%2728627det%27.

Dietary patterns in North and South India: a comparison with EAT-Lancet dietary recommendations.

BACKGROUND: Environmentally sustainable diets are represented in the EAT-Lancet recommendations developed by the Lancet Commission on Planetary Health in 2019. Very few studies have compared Indian diets with the EAT-Lancet recommendations. The present study performed such a comparison using primary dietary consumption data from adults in north and south India. METHODS: Data from 8762 adults (52.4 ± 11.7 years) residing in Sonipat and Vizag India were collected on sociodemographic characteristics, wealth index (household assets) and dietary intake (food frequency questionnaire: nine food groups). The quantity consumed and energy from each food group was compared with the EAT-Lancet recommendations. We investigated the likelihood of deficit or excess in consumption compared to the EAT-Lancet recommendations by different sociodemographic factors. RESULTS: Half of the participants were women and half resided in rural areas. Vegetables and fruits were consumed in lower quantity, whereas dairy and added fats were consumed in higher quantity than recommended by the EAT-Lancet recommendations. For whole grains, female gender and poorest wealth index were the factors associated with deficit or no consumption, whereas, for vegetables and fruits, it was poorest wealth index and residence in rural areas (p < 0.05, all). Rural residence and poorest wealth index were associated with excess consumption of dairy and added fats (p < 0.05, all). CONCLUSIONS: The diets of the study participants were mainly plant-based, and high in dairy but lacking in nutrient-rich foods such as vegetables and fruits. Appropriate policy actions for making healthy sustainable diets and micronutrient-rich foods available and affordable to all with a particular focus on the poor and rural populations are warranted.

Prevalence of chronic obstructive pulmonary disease and chronic bronchitis in eight countries: a systematic review and meta-analysis.

Objective: To estimate the prevalence of chronic obstructive pulmonary disease (COPD) and chronic bronchitis in eight countries in South Asia through a systematic review and meta-analysis. Methods: We searched MEDLINE® Complete, Web of Science, Embase®, Scopus, CINAHL and reference lists of screened studies for research on the prevalence of COPD and chronic bronchitis in South Asian countries published between January 1990 and February 2021. We used standardized diagnostic criteria for definitions of COPD and chronic bronchitis. Two reviewers undertook study screening, full-text review, quality appraisal and data extraction. Findings: Of 1529 studies retrieved, 43 met the inclusion criteria: 32 provided data from India; four from Bangladesh; three from Nepal; two from Pakistan; and two from both India and Sri Lanka. Twenty-six studies used standardized diagnostic definitions and 19 were included in the meta-analysis. The estimated pooled prevalence of COPD was 11.1% (95% confidence interval, CI: 7.4-14.8%), using the Global Initiative for Chronic Obstructive Lung Disease fixed criteria and 8.0% (95% CI: 5.6-10.4%) using the lower limit of normal criteria. The prevalence of COPD was highest in north India (19.4%) and Bangladesh (13.5%) and in men. The estimated pooled prevalence of chronic bronchitis was 5.0% (95% CI: 4.1-6.0%) in India and 3.6% (95% CI: 3.1-4.0%) in Pakistan. Conclusion: Included countries have a high prevalence of COPD although it varied by geographical area and study characteristics. Future research in South Asia should use standardized diagnostic criteria to examine the contribution of setting-specific risk factors to inform prevention and control strategies.

Measuring the quality of antenatal care in a context of high utilisation: evidence from Telangana, India.

BACKGROUND: Antenatal care coverage has dramatically increased in many low-and middle-income settings, including in the state of Telangana, India. However, there is increasing evidence of shortfalls in the quality of care women receive during their pregnancies. This study aims to examine dimensions of antenatal care quality in Telangana, India using four primary and secondary data sources. METHODS: Data from two secondary statewide data sources (National Family Health Survey (NFHS-5), 2019-21; Health Management Information System (HMIS), 2019-20) and two primary data sources (a facility survey in 19 primary health centres and sub-centres in selected districts of Telangana; and observations of 36 antenatal care consultations at these facilities) were descriptively analysed. RESULTS: NFHS-5 data showed about 73% of women in Telangana received all six assessed antenatal care components during pregnancy. HMIS data showed high coverage of antenatal care visits but differences in levels of screening, with high coverage of haemoglobin tests for anaemia but low coverage of testing for gestational diabetes and syphilis. The facility survey found missing equipment for several key antenatal care services. Antenatal care observations found blood pressure measurement and physical examinations had high coverage and were generally performed correctly. There were substantial deficiencies in symptom checking and communication between the woman and provider. Women were asked if they had any questions in 22% of consultations. Only one woman was asked about her mental health. Counselling of women on at least one of the ten items relating to birth preparedness and on at least one of six danger signs occurred in 58% and 36% of consultations, respectively. CONCLUSION: Despite high coverage of antenatal care services and some essential maternal and foetal assessments, substantial quality gaps remained, particularly in communication between healthcare providers and pregnant women and in availability of key services. Progress towards achieving high quality in both content and experience of antenatal care requires addressing service gaps and developing better measures to capture and improve women's experiences of care.

Burden, patterns, and impact of multimorbidity in North India: findings from a rural population-based study.

AIM: To estimate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among a young rural population. METHODS: We conducted a cross-sectional survey among participants aged ≥30 years in rural Punjab, North India, from Jan 2019 to April 2019. Multimorbidity was defined as the coexistence of ≥two conditions using a 14-condition tool validated in India. We also calculated a multimorbidity-weighted index (MWI), which provides a weight to each disease based on its impact on physical functioning. Logistic regression was conducted to evaluate the association with sociodemographic variables, mental health (PHQ-9), physical functioning (ADL scale), and self-rated health (SRH). RESULTS: We analyzed data from 3213 adults [Mean age 51.5 (±13), 54% women]. Prevalence of single chronic condition, multimorbidity, and MWI was 28.6, 18% and - 1.9 respectively. Age, higher wealth index and ever use alcohol were significantly associated with multimorbidity. Overall, 2.8% of respondents had limited physical functioning, 2.1% had depression, and 61.5% reported low SRH. Poorer health outcomes were more prevalent among the elderly, women, less educated, and those having lower wealth index and multimorbidity, were found to be significantly associated with poor health outcomes. CONCLUSIONS: The burden of multimorbidity was high in this young rural population, which portends significant adverse effects on their health and quality of life. The Indian health system should be reconfigured to address this emerging health priority holistically, by adopting a more integrated and sustainable model of care.

Improving care for hypertension and diabetes in india by addition of clinical decision support system and task shifting in the national NCD program: I-TREC model of care.

BACKGROUND: The growing burden of hypertension and diabetes is one of the major public health challenges being faced by the health system in India. Clinical Decision Support Systems (CDSS) that assist with tailoring evidence-based management approaches combined with task-shifting from more specialized to less specialized providers may together enhance the impact of a program. We sought to integrate a technology "CDSS" and a strategy "Task-shifting" within the Government of India's (GoI) Non-Communicable Diseases (NCD) System under the Comprehensive Primary Health Care (CPHC) initiative to enhance the program's impact to address the growing burden of hypertension and diabetes in India. METHODS: We developed a model of care "I-TREC" entirely calibrated for implementation within the current health system across all facility types (Primary Health Centre, Community Health Centre, and District Hospital) in a block in Shaheed Bhagat Singh (SBS) Nagar district of Punjab, India. We undertook an academic-community partnership to incorporate the combination of a CDSS with task-shifting into the GoI CPHC-NCD system, a platform that assists healthcare providers to record patient information for routine NCD care. Academic partners developed clinical algorithms, a revised clinic workflow, and provider training modules with iterative collaboration and consultation with government and technology partners to incorporate CDSS within the existing system. DISCUSSION: The CDSS-enabled GoI CPHC-NCD system provides evidence-based recommendations for hypertension and diabetes; threshold-based prompts to assure referral mechanism across health facilities; integrated patient database, and care coordination through workflow management and dashboard alerts. To enable efficient implementation, modifications were made in the patient workflow and the fulcrum of the use of technology shifted from physician to nurse. CONCLUSION: Designed to be applicable nationwide, the I-TREC model of care is being piloted in a block in the state of Punjab, India. Learnings from I-TREC will provide a roadmap to other public health experts to integrate and adapt their interventions at the national level. TRIAL REGISTRATION: CTRI/2020/01/022723.

Health, psychosocial, and economic impacts of the COVID-19 pandemic on people with chronic conditions in India: a mixed methods study.

BACKGROUND: People with chronic conditions are disproportionately prone to be affected by the COVID-19 pandemic but there are limited data documenting this. We aimed to assess the health, psychosocial and economic impacts of the COVID-19 pandemic on people with chronic conditions in India. METHODS: Between July 29, to September 12, 2020, we telephonically surveyed adults (n = 2335) with chronic conditions across four sites in India. Data on participants' demographic, socio-economic status, comorbidities, access to health care, treatment satisfaction, self-care behaviors, employment, and income were collected using pre-tested questionnaires. We performed multivariable logistic regression analysis to examine the factors associated with difficulty in accessing medicines and worsening of diabetes or hypertension symptoms. Further, a diverse sample of 40 participants completed qualitative interviews that focused on eliciting patient's experiences during the COVID-19 lockdowns and data analyzed using thematic analysis. RESULTS: One thousand seven hundred thirty-four individuals completed the survey (response rate = 74%). The mean (SD) age of respondents was 57.8 years (11.3) and 50% were men. During the COVID-19 lockdowns in India, 83% of participants reported difficulty in accessing healthcare, 17% faced difficulties in accessing medicines, 59% reported loss of income, 38% lost jobs, and 28% reduced fruit and vegetable consumption. In the final-adjusted regression model, rural residence (OR, 95%CI: 4.01,2.90-5.53), having diabetes (2.42, 1.81-3.25) and hypertension (1.70,1.27-2.27), and loss of income (2.30,1.62-3.26) were significantly associated with difficulty in accessing medicines. Further, difficulties in accessing medicines (3.67,2.52-5.35), and job loss (1.90,1.25-2.89) were associated with worsening of diabetes or hypertension symptoms. Qualitative data suggest most participants experienced psychosocial distress due to loss of job or income and had difficulties in accessing in-patient services. CONCLUSION: People with chronic conditions, particularly among poor, rural, and marginalized populations, have experienced difficulties in accessing healthcare and been severely affected both socially and financially by the COVID-19 pandemic.

A model for national assessment of barriers for implementing digital technology interventions to improve hypertension management in the public health care system in India.

BACKGROUND: There is substantial interest in leveraging digital health technology to support hypertension management in low- and middle-income countries such as India. The potential for healthcare infrastructure and broader context to support such initiatives in India has not been examined. We evaluated existing healthcare infrastructure to support digital health interventions and examined epidemiologic, socioeconomic, and geographical contextual correlates of healthcare infrastructure in 544 districts covering 29 states and union territories across India. METHODS: The study was a cross-sectional analysis of India's Fourth District Level Household and Facility Survey (DLHS-4; 2012-2014), the most up-to-date nationally representative district-level healthcare infrastructure data. Facilities were the unit of analysis, and analyses accounted for clustering within states. The main outcome was healthcare system infrastructural context to implement hypertension management programs. Domains included diagnostics (functional BP instrument), medications (anti-hypertensive medication in stock), essential clinical staff (e.g., staff nurse, medical officer, pharmacist), and IT specific infrastructure (regular power supply, internet connection, computer availability). Descriptive analysis was conducted for infrastructure indicators based on the Indian Public Health Standards, and logistic regression was conducted to estimate the association between epidemiologic and geographical context (exposures) and the composite measure of healthcare system. RESULTS: Data from 32,215 government facilities were analyzed. Among lowest-tier subcenters, 30% had some IT infrastructure, while at the highest-tier district hospitals, 92% possessed IT infrastructure. At mid-tier primary health centres and community health centres, IT infrastructure availability was 28 and 51%, respectively. For all but sub-centres, the availability of essential staff was lower than the availability of IT infrastructure. For all but district hospitals, higher levels of blood pressure, body mass index, and urban residents were correlated with more favorable infrastructure. By region, districts in Western India tended towards having the best prepared health facilities. CONCLUSIONS: IT infrastructure to support digital health interventions is more frequently lacking at lower and mid-tier healthcare facilities compared with apex facilities in India. Gaps were generally larger for staffing than physical infrastructure, suggesting that beyond IT infrastructure, shortages in essential staff impose significant constraints to the adoption of digital health interventions. These data provide early benchmarks for state- and district-level planning.

The Integrated Tracking, Referral, and Electronic Decision Support, and Care Coordination (I-TREC) program: scalable strategies for the management of hypertension and diabetes within the government healthcare system of India.

BACKGROUND: Hypertension and diabetes are among the most common and deadly chronic conditions globally. In India, most adults with these conditions remain undiagnosed, untreated, or poorly treated and uncontrolled. Innovative and scalable approaches to deliver proven-effective strategies for medical and lifestyle management of these conditions are needed. METHODS: The overall goal of this implementation science study is to evaluate the Integrated Tracking, Referral, Electronic decision support, and Care coordination (I-TREC) program. I-TREC leverages information technology (IT) to manage hypertension and diabetes in adults aged ≥30 years across the hierarchy of Indian public healthcare facilities. The I-TREC program combines multiple evidence-based interventions: an electronic case record form (eCRF) to consolidate and track patient information and referrals across the publicly-funded healthcare system; an electronic clinical decision support system (CDSS) to assist clinicians to provide tailored guideline-based care to patients; a revised workflow to ensure coordinated care within and across facilities; and enhanced training for physicians and nurses regarding non-communicable disease (NCD) medical content and lifestyle management. The program will be implemented and evaluated in a predominantly rural district of Punjab, India. The evaluation will employ a quasi-experimental design with mixed methods data collection. Evaluation indicators assess changes in the continuum of care for hypertension and diabetes and are grounded in the Reach, Effectiveness, Adoption Implementation, and Maintenance (RE-AIM) framework. Data will be triangulated from multiple sources, including community surveys, health facility assessments, stakeholder interviews, and patient-level data from the I-TREC program's electronic database. DISCUSSION: I-TREC consolidates previously proven strategies for improved management of hypertension and diabetes at single-levels of the healthcare system into a scalable model for coordinated care delivery across all levels of the healthcare system hierarchy. Findings have the potential to inform best practices to ultimately deliver quality public-sector hypertension and diabetes care across India. TRIAL REGISTRATION: The study is registered with Clinical Trials Registry of India (registration number CTRI/2020/01/022723 ). The study was registered prior to the launch of the intervention on 13 January 2020. The current version of protocol is version 2 dated 6 June 2018.

Regional and socio-demographic variation in laboratory-based predictions of 10-year cardiovascular disease risk among adults in north and south India.

OBJECTIVE: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in India. There is no laboratory-based CVD risk data among Indians from different regions and backgrounds. This study estimated laboratory-based 10-year CVD risk across different population sub-groups. METHODS: Data from UDAY derived from cross-sectional surveys of rural and urban populations of northern (Haryana) and southern (Andhra Pradesh) India were analysed. World Health Organization/International Society of Hypertension laboratory-based equations calculated 10-year CVD risk among participants without CVD history. Wilcoxon rank sum test analyzed average CVD risk across subgroups. Chi-square test compared population proportions in different CVD risk categories. Regression analysis assessed the association between CVD risk and participant characteristics. RESULTS: The mean (SD) age of the participants (n = 8448) was 53.2 (9.2) years. Males in Haryana had increased CVD risk compared to those in Andhra Pradesh (p < 0.01). In both states, female gender was shown to have a protective effect on CVD risk (p < 0.01). Age correlated with increased risk (p < 0.01). Education level did not affect CVD risk however employment status may have. Hypertension, diabetes, hyperlipidemia, smoking, and insufficient exercise were associated with increased CVD risk (p < 0.01). Residence (urban versus rural) and wealth index did not largely affect CVD risk. CONCLUSION: Minor differences exist in the distribution of laboratory-based CVD risk across Indian population cohorts. CVD risk was similar in urban wealthy participants and rural poor and working-class communities in northern and southern India. Public health efforts need to target all major segments of the Indian population to curb the CVD epidemic.

Implementation of Maternal and Newborn Health Mobile Phone E-Cohorts to Track Longitudinal Care Quality in Low- and Middle-Income Countries.

BACKGROUND: The maternal and newborn health (MNH) eCohort is a new mixed-mode (in-person and phone) longitudinal survey aiming to provide data on novel and undermeasured dimensions of quality along the MNH continuum of care. We describe implementation experiences and lessons learned in Ethiopia, India, Kenya, and South Africa to inform future longitudinal mobile phone-based studies on health system quality. METHODS: To document the implementation approach and lesson learned, we engaged numerous stakeholders and conducted data reviews, debriefs, and a workshop with participants from all collaborative research organizations. RESULTS: The MNH eCohorts enrolled women during their first antenatal care visit in 2 sentinel sites in Ethiopia, India, Kenya, and South Africa. In India, a site with better health outcomes and a site with poorer outcomes were chosen. In the remaining countries, an urban site and a rural site were chosen. Enrollment facilities reflect care-seeking patterns according to local health information data across public and private facilities and primary and secondary levels. Data collectors had a range of educational and experience profiles, and phone data collection was completed by the same enumerators in some countries and outsourced to data collection firms in others. Adequate infrastructure (including Internet and mobile phone coverage) was essential to implementation. Although follow-up is ongoing in India and South Africa, the eCohort retained 89%-90% of participants throughout the entire pregnancy and 78%-81% until 3 months postpartum in Ethiopia and Kenya, respectively. CONCLUSIONS: The MNH eCohort is a complex and long survey. Careful and thoughtful implementation demonstrates that it is a useful tool to gather data on health system quality and continuity and on changes in user experience over the continuum of care. Findings from the eCohort related to care and system competence and user experience will be valuable to program managers and policymakers alike.

User-reported quality of care: findings from the first round of the People's Voice Survey in 14 countries.

High-quality care is essential for improving health outcomes, although many health systems struggle to maintain good quality. We use data from the People's Voice Survey-a nationally representative survey conducted in 14 high-income, middle-income, and low-income countries-to describe user-reported quality of most recent health care in the past 12 months. We described ratings for 14 measures of care competence, system competence, and user experience and assessed the relationship between visit quality factors and user recommendation of the facility. We disaggregated the data by high-need and underserved groups. The proportion of respondents rating their most recent visit as high quality ranged from 25% in Laos to 74% in the USA. The mean facility recommendation score was 7·7 out of 10. Individuals with high needs or who are underserved reported lower-quality services on average across countries. Countries with high health expenditure per capita tended to have better care ratings than countries with low health expenditure. Visit quality factors explained a high proportion of variation in facility recommendations relative to facility or demographic factors. These results show that user-reported quality is low but increases with high national health expenditure. Elevating care quality will require monitoring and improvements on multiple dimensions of care quality, especially in public systems.

The path to universal health coverage in five African and Asian countries: examining the association between insurance status and health-care use.

Despite major efforts to achieve universal health coverage (UHC), progress has lagged in many African and Asian countries. A key strategy pursued by many countries is the use of health insurance to increase access and affordability. However, evidence on insurance coverage and on the association between insurance and UHC is mixed. We analysed nationally representative cross-sectional data collected between 2022 and 2023 in Ethiopia, Kenya, South Africa, India, and Laos. We described public and private insurance coverage by sociodemographic factors and used logistic regression to examine the associations between insurance status and seven health-care use outcomes. Health insurance coverage ranged from 25% in India to 100% in Laos. The share of private insurance ranged from 1% in Ethiopia to 13% in South Africa. Relative to the population with private insurance, the uninsured population had reduced odds of health-care use (adjusted odds ratio 0·68, 95% CI 0·50-0·94), cardiovascular examinations (0·63, 0·47-0·85), eye and dental examinations (0·54, 0·42-0·70), and ability to get or afford care (0·64, 0·48-0·86); private insurance was not associated with unmet need, mental health care, and cancer screening. Relative to private insurance, public insurance was associated with reduced odds of health-care use (0·60, 0·43-0·82), mental health care (0·50, 0·31-0·80), cardiovascular examinations (0·62, 0·46-0·84), and eye and dental examinations (0·50, 0·38-0·65). Results were highly heterogeneous across countries. Public health insurance appears to be only weakly associated with access to health services in the countries studied. Further research is needed to improve understanding of these associations and to identify the most effective financing strategies to achieve UHC.

The maternal and newborn health eCohort to track longitudinal care quality: study protocol and survey development.

The MNH eCohort was developed to fill gaps in maternal and newborn health (MNH) care quality measurement. In this paper, we describe the survey development process, recruitment strategy, data collection procedures, survey content and plans for analysis of the data generated by the study. We also compare the survey content to that of existing multi-country tools on MNH care quality. The eCohort is a longitudinal mixed-mode (in-person and phone) survey that will recruit women in health facilities at their first antenatal care (ANC) visit. Women will be followed via phone survey until 10-12 weeks postpartum. User-reported information will be complemented with data from physical health assessments at baseline and endline, extraction from MNH cards, and a brief facility survey. The final MNH eCohort instrument is centered around six key domains of high-quality health systems including competent care (content of ANC, delivery, and postnatal care for the mother and newborn), competent systems (prevention and detection, timely care, continuity, integration), user experience, health outcomes, confidence in the health system, and economic outcomes. The eCohort combines the maternal and newborn experience and, due to its longitudinal nature, will allow for quality assessment according to specific risks that evolve throughout the pregnancy and postpartum period. Detailed information on medical and obstetric history and current health status of respondents and newborns will allow us to determine whether women and newborns at risk are receiving needed care. The MNH eCohort will answer novel questions to guide health system improvements and to fill data gaps in implementing countries.

Added knowledge: The MNH eCohort will answer novel questions and provide information on undermeasured dimensions of MNH care quality included continuity of care, system competence, and user experience.Global health impact for policy and action: The data generated will inform policy makers to develop strategies to improve adherence to standards of care and quality for mothers and newborns.

Health system quality and COVID-19 vaccination: a cross-sectional analysis in 14 countries.

The social and behavioural determinants of COVID-19 vaccination have been described previously. However, little is known about how vaccinated people use and rate their health system. We used surveys conducted in 14 countries to study the health system correlates of COVID-19 vaccination. Country-specific logistic regression models were adjusted for respondent age, education, income, chronic illness, history of COVID-19, urban residence, and minority ethnic, racial, or linguistic group. Estimates were summarised across countries using random effects meta-analysis. Vaccination coverage with at least two or three doses ranged from 29% in India to 85% in Peru. Greater health-care use, having a regular and high-quality provider, and receiving other preventive health services were positively associated with vaccination. Confidence in the health system and government also increased the odds of vaccination. By contrast, having unmet health-care needs or experiencing discrimination or a medical mistake decreased the odds of vaccination. Associations between health system predictors and vaccination tended to be stronger in high-income countries and in countries with the most COVID-19-related deaths. Access to quality health systems might affect vaccine decisions. Building strong primary care systems and ensuring a baseline level of quality that is affordable for all should be central to pandemic preparedness strategies.

Agricultural and Socioeconomic Factors Associated with Farmer Household Dietary Diversity in India: A Comparative Study of Visakhapatnam and Sonipat.

Using primary data from 479 farmer households, this study examined the associations between agricultural and socioeconomic factors and farmer household dietary diversity in Visakhapatnam and Sonipat. Cropping intensity was positively associated with farmers' household dietary diversity score (HDDS), suggesting that higher cropping intensity may expand the gross cropped area and improve food security among subsistence farmers. Distance to food markets was also significantly associated with farmer HDDS, which suggests that market integration with rural households can improve farmer HDDS in Visakhapatnam. In Sonipat, wealth index had a positive association with farmer HDDS, targeting the income pathway by improving farmer HDDS in this region. Considering the relative contribution of these factors, distance to food markets, cropping intensity, and crop diversity were the three most important factors affecting farmer HDDS in Visakhapatnam, whereas wealth index, cropping intensity, and distance to food markets emerged as the top three important factors contributing to farmer HDDS in Sonipat. Our study concludes that the associations between agricultural and socioeconomic factors and farmer HDDS are complex but context- and location-specific; therefore, considering the site- and context-specific circumstances, different connections to HDDS in India can be found to better support policy priorities on the ground.