Racism, Diminished Returns of Socioeconomic Resources, and Black Middle-Income Children’s Health Paradox—Reply

Diarrhea, soil-transmitted helminth infection and malnutrition are leading causes of child mortality in low- and middle-income countries (LMICs). To reduce the prevalence of these diseases, effective interventions for adequate water, sanitation, and hygiene (WaSH) should be implemented. This paper describes the design of a cluster-randomized controlled trial that will compare the efficacy of four school-based WaSH interventions for improving children’s health literacy, handwashing, and nutrition. Interventions consisted of (1) WaSH policy reinforcement; (2) low-, medium-, or high-volume health education; (3) hygiene supplies; and (4) WaSH facilities (e.g., toilets, urinals, handwashing basins) improvements. We randomly allocated school clusters from the intervention arm to one of four groups to compare with schools from the control arm. Primary outcomes were: children’s health literacy, physical growth, nutrition status, and handwashing prevalence. Secondary outcomes were: children’s self-reported health status and history of extreme hunger, satisfaction with WaSH facilities, and school restrooms’ WaSH adequacy. We will measure differences in pre- and post-intervention outcomes and compare these differences between control and intervention arms. This research protocol can be a blueprint for future school-based WaSH intervention studies to be conducted in LMICs. Study protocols were approved by the ethics committees of the University of Bonn, Germany, and the University of the Philippines Manila. This trial was retroactively registered, ID number: DRKS00021623.

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Global Network for Women's and Children's Health Research: probable causes of stillbirth in low- and middle-income countries using a prospectively defined classification system

BJOG An International Journal of Obstetrics & Gynaecology ◽

10.1111/1471-0528.14493 ◽

2017 ◽

Vol 125 (2) ◽

pp. 131-138 ◽

Cited By ~ 24

Author(s):

EM McClure ◽

A Garces ◽

S Saleem ◽

JL Moore ◽

CL Bose ◽

...

Keyword(s):

Classification System ◽

Health Research ◽

Children's Health ◽

Global Network ◽

Children’S Health ◽

Middle Income ◽

Middle Income Countries ◽

Low And Middle Income

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AI for Improving Children’s Health: A Community Case Study

Frontiers in Artificial Intelligence ◽

10.3389/frai.2020.544972 ◽

2021 ◽

Vol 3 ◽

Author(s):

Aakash Ganju ◽

Srini Satyan ◽

Vatsal Tanna ◽

Sonia Rebecca Menezes

Keyword(s):

Health Care ◽

Digital Health ◽

Healthcare Delivery ◽

Health Resources ◽

Heterogeneous Data ◽

Mobile App ◽

Children's Health ◽

Children’S Health ◽

Middle Income ◽

Predictive Algorithms

The Indian health care system lacks the infrastructure to meet the health care demands of the country. Physician and nurse availability is 30 and 50% below WHO recommendations, respectively, and has led to a steep imbalance between the demand for health care and the infrastructure available to support it. Among other concerns, India still struggles with challenges like undernutrition, with 38% of children under the age of five being underweight. Despite these challenges, technological advancements, mobile phone ubiquity and rising patient awareness offers a huge opportunity for artificial intelligence to enable efficient healthcare delivery, by improved targeting of constrained resources. The Saathealth mobile app provides low-middle income parents of young children nflwith interactive children’s health, nutrition and development content in the form of an entertaining video series, a gamified quiz journey and targeted notifications. The app iteratively evolves the user journey based on dynamic data and predictive algorithms, empowering a shift from reactive to proactive care. Saathealth users have registered over 500,000 sessions and over 200 million seconds on-app engagement over a year, comparing favorably with engagement on other digital health interventions in underserved communities. We have used valuable app analytics data and insights from our 45,000 users to build scalable, predictive models that were validated for specific use cases. Using the Random Forest model with heterogeneous data allowed us to predict user churn with a 93% accuracy. Predicting user lifetimes on the mobile app for preliminary insights gave us an RMSE of 25.09 days and an R2 value of 0.91, reflecting closely correlated predictions. These predictive algorithms allow us to incentivize users with optimized offers and omni-channel nudges, to increase engagement with content as well as other targeted online and offline behaviors. The algorithms also optimize the effectiveness of our intervention by augmenting personalized experiences and directing limited health resources toward populations that are most resistant to digital first interventions. These and similar AI powered algorithms will allow us to lengthen and deepen the lifetime relationship with our health consumers, making more of them effective, proactive participants in improving children’s health, nutrition and early cognitive development.

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Promoting women’s and children’s health through community groups in low-income and middle-income countries: a mixed-methods systematic review of mechanisms, enablers and barriers

BMJ Global Health ◽

10.1136/bmjgh-2019-001972 ◽

2019 ◽

Vol 4 (6) ◽

pp. e001972 ◽

Cited By ~ 6

Author(s):

Lu Gram ◽

Adam Fitchett ◽

Asma Ashraf ◽

Nayreen Daruwalla ◽

David Osrin

Keyword(s):

Systematic Review ◽

Mixed Methods ◽

Low Income ◽

Interaction Analysis ◽

Children's Health ◽

Children’S Health ◽

Community Mobilisation ◽

Community Groups ◽

Middle Income ◽

Barriers To Health

IntroductionCommunity mobilisation through group activities has been used to improve women’s and children’s health in a range of low-income and middle-income contexts, but the mechanisms through which it works deserve greater consideration. We did a mixed-methods systematic review of mechanisms, enablers and barriers to the promotion of women’s and children’s health in community mobilisation interventions.MethodsWe searched for theoretical and empirical peer-reviewed articles between January 2000 and November 2018. First, we extracted and collated proposed mechanisms, enablers and barriers into categories. Second, we extracted and synthesised evidence for them using narrative synthesis. We assessed risk of bias with adapted Downs and Black and Critical Appraisal Skills Programme checklists. We assigned confidence grades to each proposed mechanism, enabler and barrier.Results78 articles met the inclusion criteria, of which 39 described interventions based on a participatory group education model, 19 described community-led structural interventions to promote sexual health in marginalised populations and 20 concerned other types of intervention or multiple interventions at once. We did not have high confidence in any mechanism, enabler or barrier. Two out of 15 proposed mechanisms and 10 out of 12 proposed enablers and barriers reached medium confidence. A few studies provided direct evidence relating proposed mechanisms, enablers or barriers to health behaviours or health outcomes. Only two studies presented mediation or interaction analysis for a proposed mechanism, enabler or barrier.ConclusionWe uncovered multiple proposed mechanisms, enablers and barriers to health promotion through community groups, but much work remains to provide a robust evidence base for proposed mechanisms, enablers and barriers.PROSPERO registration numberCRD42018093695.

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