Impact of air pollution on stunting among children in Africa.

BACKGROUND: Undernutrition is a global public health crisis, causing nearly half of deaths for children under age 5 years. Little is known regarding the impact of air pollution in-utero and early childhood on health outcomes related to undernutrition. The aim of our study is to evaluate the association of prenatal and early-life exposure to PM2.5 and child malnutrition as captured by the height-for-age z-score (HAZ), and stunting in 32 countries in Africa. We also evaluated critical windows of susceptibility during pregnancy to each environmental risk. METHODS: We linked nationally representative anthropometric data from 58 Demographic and Health Surveys (DHS) (n = 264,207 children < 5 years of age) with the average in-utero PM2.5 concentrations derived from satellite imagery. We then estimated associations between PM2.5 and stunting and HAZ after controlling for child, mother and household factors, and trends in time and seasonality. RESULTS: We observed lower HAZ and increased stunting with higher in-utero PM2.5 exposure, with statistically significant associations observed for stunting (OR: 1.016 (95% CI: 1.002, 1.030), for a 10 µg/m3 increase). The associations observed were robust to various model specifications. Wald tests revealed that sex, wealth quintile and urban/rural were not significant effect modifiers of these associations. When evaluating associations between trimester-specific PM2.5 levels, we observed that associations between PM2.5 and stunting was the largest. CONCLUSIONS: This is one of the first studies for the African continent to investigate in-utero and early-life exposure to PM2.5 is an important marker of childhood undernutrition. Our results highlight that PM2.5 concentrations need to be urgently mitigated to help address undernutrition in children on the continent.

Is It the Timing? Short-Term Mobility and Coital Frequency in Agbogbloshie, Ghana.

Short-term mobility is often associated with increased sexual risk behavior. Mobile individuals often have higher rates of sexual risk behavior compared to non-mobile individuals, but the reasons why are not clear. Using monthly retrospective panel data from 202 men and 282 women in Agbogbloshie, Ghana, we tested whether short-term mobility was associated with changes in coital frequency, and whether the association was due to the act of travel in the given month (e.g., enabling higher risk behavior), the reason for travel, or an individual's travel propensity at other times in the year. Overnight travel specifically to visit family or friends, or for education, health, or other reasons, was associated with increased coital frequency for men. However, men with higher travel propensities had lower overall coital frequency and the act of traveling enabled more sex only for the most frequent male travelers. Men who seldom traveled had much higher coital frequency, but the act of traveling was not associated with additional sex acts. For women, travel for education, health, or other reasons increased coital frequency. Occasional female travelers had slightly more sex acts compared to non-mobile women, and the act of traveling for these women was associated with slight increases in coital frequency, supporting the enabling hypothesis. Highly mobile women had fewer sex acts per month on average. Our findings suggest that mobility characteristics measured on a broad temporal scale, as well as the reason for mobility, are important to understand the relationship between short-term mobility and sexual behavior.

Geographic Variation in Pneumonia and Influenza in Long-Term Care Facilities: A National Study.

There is large county-level geographic variation in pneumonia and influenza hospitalizations among short-stay and long-stay long-term care facility residents in the United States. Long-term care facilities in counties in the Southern and Midwestern regions had the highest rates of pneumonia and influenza from 2013 to 2015. Future research should identify reasons for these geographic differences.

The Fully Understanding Eating and Lifestyle Behaviors (FUEL) trial: Protocol for a cohort study harnessing digital health tools to phenotype dietary non-adherence behaviors during lifestyle intervention.

Objective: Lifestyle intervention can produce clinically significant weight loss and reduced disease risk/severity for many individuals with overweight/obesity. Dietary lapses, instances of non-adherence to the recommended dietary goal(s) in lifestyle intervention, are associated with less weight loss and higher energy intake. There are distinct "types" of dietary lapse (e.g., eating an off-plan food, eating a larger portion), and behavioral, psychosocial, and contextual mechanisms may differ across dietary lapse types. Some lapse types also appear to impact weight more than others. Elucidating clear lapse types thus has potential for understanding and improving adherence to lifestyle intervention. Methods: This 18-month observational cohort study will use real-time digital assessment tools within a multi-level factor analysis framework to uncover "lapse phenotypes" and understand their impact on clinical outcomes. Adults with overweight/obesity (n = 150) will participate in a 12-month online lifestyle intervention and 6-month weight loss maintenance period. Participants will complete 14-day lapse phenotyping assessment periods at baseline, 3, 6, 12, and 18 months in which smartphone surveys, wearable devices, and geolocation will assess dietary lapses and relevant phenotyping characteristics. Energy intake (via 24-h dietary recall) and weight will be collected at each assessment period. Results: This trial is ongoing; data collection began on 31 October 2022 and is scheduled to complete by February 2027. Conclusion: Results will inform novel precision tools to improve dietary adherence in lifestyle intervention, and support updated theoretical models of adherence behavior. Additionally, these phenotyping methods can likely be leveraged to better understand non-adherence to other health behavior interventions. Trial Registration: This study was prospectively registered https://clinicaltrials.gov/study/NCT05562427.

Incorporating geographical factors with artificial neural networks to predict reference values of erythrocyte sedimentation rate.

BACKGROUND: The measurement of the Erythrocyte Sedimentation Rate (ESR) value is a standard procedure performed during a typical blood test. In order to formulate a unified standard of establishing reference ESR values, this paper presents a novel prediction model in which local normal ESR values and corresponding geographical factors are used to predict reference ESR values using multi-layer feed-forward artificial neural networks (ANN). METHODS AND FINDINGS: Local normal ESR values were obtained from hospital data, while geographical factors that include altitude, sunshine hours, relative humidity, temperature and precipitation were obtained from the National Geographical Data Information Centre in China.The results show that predicted values are statistically in agreement with measured values. Model results exhibit significant agreement between training data and test data. Consequently, the model is used to predict the unseen local reference ESR values. CONCLUSIONS: Reference ESR values can be established with geographical factors by using artificial intelligence techniques. ANN is an effective method for simulating and predicting reference ESR values because of its ability to model nonlinear and complex relationships.

A Conceptual Approach towards Improving Monitoring of Living Conditions for Populations Affected by Desertification, Land Degradation, and Drought.

Addressing the global challenges of desertification, land degradation, and drought (DLDD), and their impacts on achieving sustainable development goals for coupled human-environmental systems is a key component of the 2030 Agenda for Sustainable Development. In particular, Sustainable Development Goal (SDG) 15.3 aims to, "by 2030, combat desertification, restore degraded land and soil, including land affected by desertification, drought and floods, and strive to achieve a land degradation-neutral world". Addressing this challenge is essential for improving the livelihoods of those most affected by DLDD and for safeguarding against the most extreme effects of climate change. This paper introduces a conceptual framework for improved monitoring of DLDD in the context of United Nations Convention to Combat Desertification (UNCCD) Strategic Objective 2 (SO2) and its expected impacts: food security and adequate access to water for people in affected areas are improved; the livelihoods of people in affected areas are improved and diversified; local people, especially women and youth, are empowered and participate in decision-making processes in combating DLDD; and migration forced by desertification and land degradation is substantially reduced. While it is critical to develop methods and tools for assessing DLDD, work is needed first to provide a conceptual roadmap of the human dimensions of vulnerability in relation to DLDD, especially when attempting to create a globally standardized monitoring approach.

Healthcare accessibility in preconflict Syria: a comparative spatial analysis.

INTRODUCTION: There is scarce information about the allocation of health resources in Syria. Pre-existing inequalities were further intensified after the 2011 conflict which displaced over 50% of the population. This study provides an analysis of health inequalities in Syria focusing on spatial access to public hospitals and employs data from 2010, just prior to the outbreak of conflict. Establishing a preconflict snapshot of the health system could serve as a helpful baseline assessment for future studies to measure the impact of the conflict on the health system. Such information could also offer systematic data to guide postconflict reconstruction efforts. METHODS: We compared two methods to quantify the inpatient bed access: provider to population ratio (PPR) and two-step floating catchment area (2SFCA) method. We compared PPR calculated at the governorate level with population weighted 2SFCA score calculated at a resolution of 2 km by 2 km. We then aggregated at the governorate level, tested multiple catchment sizes and calculated Gini coefficient for each governorate. RESULTS: We found high inequality in access to public hospitals across and within governorates, especially in the north and eastern regions, where all governorates ranked in the lowest two quintiles using both PPR and 2SFCA. Relatively small governorates in the west and the south had higher spatial access and less inequality. Testing variability in catchment size showed that even at 125 km catchment, 65% of the country had accessibility below national average. CONCLUSION: Methodologically, the use of 2SFCA provided more nuanced insights about hospital bed allocation than PPR. 2SFCA was able to account for the cross-boundary effect and road network quality. Realistic representation of health accessibility is possible in data-scarce settings such as Syria and could be adapted to assess health access inequalities in conflict and postconflict settings.

Robust relationship between ambient air pollution and infant mortality in India.

BACKGROUND: Ambient exposure to fine particulate matter (PM2.5) is one of the top global health concerns. We estimate the associations between in-utero and perinatal exposure to PM2.5 and infant, neonatal and postneonatal mortality in India. We evaluate the sensitivity of this association to two widely-used exposure assessments. METHOD: We linked nationally representative anthropometric data from India's 2015-2016 Demographic and Health Survey (n = 259,627 children under five across 640 districts of India) with satellite-based PM2.5 concentrations during the month of birth of each child. We then estimated the associations between PM2.5 from each dataset and child mortality, after controlling for child, mother and household factors including trends in time and seasonality. We examined if factors: urban/rural, sex, wealth quintile and state modified the associations derived from the two datasets using Wald tests. RESULTS: We found evidence that PM2.5 impacts infant mortality primarily through neonatal mortality. The estimated association between neonatal mortality and PM2.5 in trimester 3 was OR: 1.016 (95% CI: 1.003, 1.030) for every 10 µg/m3 increase in exposure. This association was robust to the exposure assessment used. Child sex was a significant effect modifier, with PM2.5 impacting mortality in infant girls more than boys. CONCLUSIONS: Our results revealed a robust association between ambient exposure to PM2.5 in the latter period of pregnancy and early life with infant and neonatal mortality in India. Urgent air pollution management plans are needed to improve infant mortality in India.

Quantifying clinic transfers among people living with HIV in the Western Cape, South Africa: a retrospective spatial analysis.

OBJECTIVES: For persons living with HIV (PLWH) in long-term care, clinic transfers are common and influence sustained engagement in HIV care, as they are associated with significant time out-of-care, low CD4 count, and unsuppressed viral load on re-entry. Despite the geospatial nature of clinic transfers, there exist limited data on the geospatial trends of clinic transfers to guide intervention development. In this study, we investigate the geospatial characteristics and trends of clinic transfers among PLWH on antiretroviral therapy (ART) in the Western Cape Province of South Africa. DESIGN: Retrospective spatial analysis. SETTING: PLWH who initiated ART treatment between 2012 and 2016 in South Africa's Western Cape Province were followed from ART initiation to their last visit prior to 2017. Deidentified electronic medical records from all public clinical, pharmacy, and laboratory visits in the Western Cape were linked across space and time using a unique patient identifier number. PARTICIPANTS: 4176 ART initiators in South Africa (68% women). METHODS: We defined a clinic transfer as any switch between health facilities that occurred on different days and measured the distance between facilities using geodesic distance. We constructed network flow maps to evaluate geospatial trends in clinic transfers over time, both for individuals' first transfer and overall. RESULTS: Two-thirds of ART initiators transferred health facilities at least once during follow-up. Median distance between all clinic transfer origins and destinations among participants was 8.6 km. Participant transfers were heavily clustered around Cape Town. There was a positive association between time on ART and clinic transfer distance, both among participants' first transfers and overall. CONCLUSION: This study is among the first to examine geospatial trends in clinic transfers over time among PLWH. Our results make clear that clinic transfers are common and can cluster in urban areas, necessitating better integrated health information systems and HIV care.

Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement.

Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psychosocial, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisions to be based on the strongest science possible, transparency and clarity in reporting in spatial lifecourse epidemiologic studies is essential. A task force supported by the International Initiative on Spatial Lifecourse Epidemiology (ISLE) identified a need for guidance in this area and developed a Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) Statement. The aim is to provide a checklist of recommendations to improve and make more consistent reporting of spatial lifecourse epidemiologic studies. The STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement for cohort studies was identified as an appropriate starting point to provide initial items to consider for inclusion. Reporting standards for spatial data and methods were then integrated to form a single comprehensive checklist of reporting recommendations. The strength of our approach has been our international and multidisciplinary team of content experts and contributors who represent a wide range of relevant scientific conventions, and our adherence to international norms for the development of reporting guidelines. As spatial, location-based, and artificial intelligence technologies used in spatial lifecourse epidemiology continue to evolve at a rapid pace, it will be necessary to revisit and adapt the ISLE-ReSt at least every 2-3 years from its release.

Indoor and Outdoor Air Pollution and Lung Cancer in New Hampshire and Vermont.

Indoor and outdoor air pollution is known to contribute to increased lung cancer incidence. This study is the first to address the contribution of home heating fuel and geographical course particulate matter (PM10) concentrations to lung cancer rates in New Hampshire, U.S. First, Pearson correlation analysis and Geographically weighted regression were used to investigate spatial relationships between outdoor PM10 and lung cancer rates. While the aforementioned analyses did not indicate a significant contribution of PM10 to lung cancer in the state, there was a trend towards a significant association in the northern and southwestern regions of the state. Second, case-control data were used to estimate the contributions of indoor pollution and second hand smoke to risk of lung cancer with adjustment for confounders. Increased risk was found among those who used wood or coal to heat their homes for more than 10 winters before the age of 18, with a significant increase in risk per winter. Resulting data suggest that further investigation of the relationship between heating-related air pollution levels and lung cancer risk is needed.