The SARS-CoV-2 pandemic has challenged healthcare systems worldwide. Uncertainty of transmission, limitations of physical healthcare system infrastructure and supplies as well as workforce shortages require dynamic adaption of resource deployment to manage rapidly evolving care demands, ideally based on real time data for the entire population. Moreover, shut down of traditional face-to-face care infrastructure requires rapid deployment of virtual health care options to avoid collapse of health organizations. The Alberta Electronic Health Record Information System is one of the largest population based comprehensive electronic medical record (EMR) installations. Alberta’s long standing solid telehealth hardware-, training-, provider remuneration- and legislation infrastructure has enabled quick transition to virtual healthcare. Virtual health services including asynchronous secure clinical communications, real-time virtual care via messaging, telephony or video conferencing  and ancillary functions like triage, scheduling, documentation and reporting, the previously established virtual hospital program with home monitoring, virtual health assessments, medication review, education and support for patients and families and coordination between family doctors, specialists and other health team members help to control viral transmission, protect healthcare personnel and save supplies. Moreover, rapid launch of online screening and triage tools to guide testing and isolation, online result sharing, infected patient and contact tracing including a smartphone exposure tracking application (ABTraceTogether), electronic best practice alerts and decision support tools, test and treatment order sets for standardized COVID-19 management, continuous access to population level real-time data to inform healthcare provider, public health and government decisions have become key factors in the management of a global crisis in Alberta. Uncertainty of transmission mode5, limitations of physical healthcare system infrastructure and supplies6 and workforce shortages8 require dynamic adaption of resource deployment to manage rapidly evolving care demands, ideally based on real time data for the entire population. Moreover, the social distancing9 based approach to flatten the disease-spread curve effectively shut down the traditional face-to-face care non-urgent delivery model aggravating the already existing overuse of emergency rooms and accelerating the collapse of health organizations.The outbreak of novel pneumonia of probably bat originHealthcare systems ahead of the digitalization curve, that have made the necessary investments into hardware-, training- and provider remuneration infrastructure prior to the pandemic can now enlist an important additional resource in their efforts to address the COVID-19 challenge.Alberta is home to more than 4.3 million people half of which live in two metropolitan areas, the Provincial capital Edmonton and the city of Calgary, whereas the remaining population spreads out over 600,000 square kilometers. All legal residents of Alberta are entitled to publicly funded and administered healthcare delivered by Alberta Health Services organized into five geographic zones. Alberta Health Services provides healthcare in 850 facilities of which 106 are acute care hospitals, five stand-alone psychiatric facilities, with 8,483 acute care beds, 27,163 continuing care beds/spaces, 249 community palliative and hospice beds and 2,772 addiction and mental health beds, the wholly-owned subsidiary Alberta Precision Laboratories plus equity partnership in 41 primary care networks. With 100,000 employees among them 8400 physicians Alberta Health Services is the largest employer in Alberta and fifth largest in Canada.10 dates back to 1997 and is jointly operated by Alberta’s Ministry of Health and Alberta Health Services. All available data items are catalogued in the Alberta Health Data Asset Directory and the Alberta Health Services Data Asset Inventory Summary12 Its main domains comprise access tools, repositories, registries, and infrastructure. Access Tools  allow users to browse and view health data across repositories, but hold no actual patient data. Repositories capture, store and maintain patient diagnostic, treatment, and care information. Registries capture, store, and provide data on places, identities, and events used by repositories and access tools for identification purposes. Infrastructure finally yet importantly, enables connection and transmission of health data.The Alberta Electronic Health Record Information System14 to implement the vision of one-patient-one-record. It is the central access point for comprehensive health information and delivery for patients and providers and replaced 1300 independent health information systems across the province. Connect Care15 is based on a highly customized version of EpiCare  to meet the needs of Alberta and Albertans. Wave 1 was rolled out in the Edmonton Zone and the remaining waves are expected to follow between 2020 and 202216.Connect Care was launched in November 201917.Alberta Health Services quickly developed a self-assessment tool to help citizens in Alberta determine whether they need to be tested, direct them to the appropriate test center and advise on self-isolation18.Healthcare workers, group home-, disability support- and shelter workers, police-, peace-, environmental health- and fish-and wildlife officers, correctional facility staff as well as service personnel in hospitals, clinics, and pharmacies are all at an increased risk. This targeted tool helps to prioritize groups at highest risk of local exposure and at-risk populations. It determines if testing, additional advice and/or self-isolation are required19.An additional online questionnaire was developed to determine fitness for work before arriving at the workplace so efficiency and exposure risk at local screening stations are reduced with screening personnel10 SARS-CoV-2 test results are available to all providers and patients in Alberta. The online screening tool data above is linked to the SARS-CoV-2 test results via the Alberta Health Care Number. If an Albertan tests positive for COVID-19, a contact tracer from Alberta Health Services gets in touch with the infected person using contact information provided at the testing center to determine others who may have been exposed to the infected person over the previous 21 days20 and encourage enrollment into the app enabled digital tracing program (see below).Through the Alberta Electronic Health Record Information SystemThe Connect Care system contains rapidly developed best practice alert and decision support modules that prompt providers to consider SARS-CoV-2 testing based on entered clinical data  or test result data . Providers are also asked to collect additional pandemic relevant data with structured questionnaires that links this information to the online tool screening tool data and test results if the patient underwent such screening prior to presentation to the healthcare system. This helps to refine the online test tools and later also study of the impact of the online screening. Moreover, Connect Care provides newly developed and continuously improved standardized diagnostic and treatment order sets for patients with suspected or established SARS-CoV-2 infections and COVID-19. This is particularly relevant for advanced pandemic stages where care has to be provided by medical professionals not primarily trained in internal medicine, pulmonology or critical care.21. It is based on mobile devices exchange of Bluetooth enabled secure encrypted tokens when another device with the app installed is detected nearby. Upon interaction with a contact tracer (see above) app users are encouraged to voluntarily upload the encrypted data from the app to Alberta Health Services and allow using that information to reach and warn other app users who have been within approximately 2 meters as determined by received signal strength indicator (RSSI) readings.20The Government of Alberta also deployed a mobile exposure contact tracing application22. The Alberta telemedicine standard of practice dates back to 201023. Advice bulletins on electronic communications & security of mobile devices24 and telemedicine25 have been kept up-to-date for more than a decade. With the advent of the SARS-CoV-2 pandemic professional bodies such as Alberta’s College of Physicians and Surgeons26 and the Alberta Medical Association27 provided additional advice and training while the Canadian Medical Protective Association covered medical legal aspects28 and cyber security29.It was estimated that between two and three million virtual visits took place between Canadians and their clinicians in 2019Virtual health services including asynchronous secure clinical communications, real-time virtual care via messaging, telephony or video conferencing  and the ancillary functions like triage, scheduling, documentation and reporting help control viral transmission, protect healthcare personnel and save supplies.Alberta Health Services operates several secure clinical communication channels including the Connect Care Secure Chat messaging system for patients and providers that is directly integrated into the electronic medical record and Secure Email.Real-Time virtual care is facilitated through integration of Zoom  technology with Connect Care. Zoom recording and live streaming for social media functions have been disabled.This enables electronic referrals through the online Alberta Referral Directory (including from referring providers outside the Connect Care environment), electronic triage, electronic visits, electronic consultations, video visits, and other virtual services that take advantage of the enterprise scheduling, decision-support, documentation and reporting capabilities of a fully integrated clinical information system. In addition, other conventional telehealth suites like Skype for Business  and Real Presence  are available. All technology is in compliance with the College of Physicians and Surgeons of Alberta guidelines on secure electronic communication and acceptable to the Office of the Privacy Commissioner of Alberta.Lastly, patients in Alberta can access many elements  of their own medical record online either through MyHealth Records in Netcare or MyChart in Connect Care.Due to the existing digital infrastructure, we were able to switch all clinical meetings like morning report, hand-over, weekend sign-out, radiology and rounds, but also our multidisciplinary conferences for transplant-, cancer- or inflammatory bowel disease patients within 24 h.30, which now pays off. The Edmonton Virtual Hospital for instance can deliver acute care in the home for individuals living with chronic or complex diseases provided by physicians, pharmacists, nurses and paramedics. This is accomplished through home monitoring, virtual health assessments, medication review, education and support for patients and families and coordination between family doctors, specialist doctors and other health team members. It can shorten hospital stays or avoid them all together, which reduces the risk of SARS-CoV-2 transmission for these often-frail patients and their providers.Alberta Health Services has previously invested into enhancing community care31 to support increased facilitation of service delivery through virtual means32.In addition to the existing telehealth billing codes, the Alberta Ministry of Health has made amendments to the Schedule of Medical BenefitsA networked integrated healthcare system adds to, or perhaps fully enables the digital advantage. Critical data like case volume, ICU and regular bed capacity at facility-, city-, and are level can be tracked across an entire population without insurance-, health management organization- or institutional boundaries. Emergencies can be managed through a central command structure. Task forces for personal protective equipment, infection, prevention and control and supply management are easily appointed. Critical information can be shared in real time with the entire healthcare system., Policies are implemented everywhere and disaster planning can make optimal use of existing resources including deployment of medical staff across different facilities with city- and zone wide service and backup service schedules as well as privilege extensions as they are ultimately provided by a single payer.33 in healthcare, which began some 15 years ago34. Through this crisis we are rethinking our traditional doctor-patient relationship, some elements of which will evolve towards a virtual care provider35. Of course, the successful management of a global health crisis does not exclusively depend on the digitalization level of the healthcare system. However, highly digitalized healthcare systems employing networked electronic medical record systems with real time data collection, result sharing and decision support tools, can improve active surveillance, timely case finding, effective isolation, testing, tracing of every contact in containment and enforce social distancing, all of which have been identified by the WHO Strategic and Technical Advisory Group for Infectious Hazards as key factors to control the COVID-19 pandemic36.The SARS-CoV-2 pandemic accelerates the digital revolution38 and ethical39 challenge is to balance40 individual’s interest in privacy42 with the societal need to use large volumes of digital health and mobility data43 to successfully take on the pandemic challenge45. Government overreach46 or criminal abuse of programming loop holes in increasingly deployed tracing apps, especially in non-democratic countries are a real concern. Another prominent example are the encryption flaws in the widely used Zoom video conferencing software  and transmission of meeting encryption keys through China, exposed by the University of Toronto in April 202047.Rising concerns of cyber security with broad financially driven exploitation of personal data by tech companies, criminal infiltration of networked infrastructure and government systems, repeated major data breaches in our increasingly digitally connected world have led jurisdictions like the European Union to pass legislation for tighter regulation  and better protection of citizens’ right to informational self-determination. The legal48 along with the required training, human resources and investment in academic research, to further refine it, the hurdles for countries with a lower United Nations Human Development Index (HDI)49 are often insurmountable, considering that some parts of the world are still in the process of building basic technical infrastructure like functional electric grids or internet connectivity to accommodate such systems.Whereas governments and health system operators in many Western jurisdictions will hopefully expedite building and expanding a digital medicine infrastructure


Regulatory approval of biosimilars predominantly relies on biosimilarity assessments of quality attributes (QAs), particularly the potentially critical QAs (pCQAs) that may affect the clinical profile. However, a limited understanding exists concerning how EU regulators reflect the biosimilarity assessments of (pC)QAs in European public assessment reports (EPARs) by different stakeholders. The type and extent of information on QAs and pCQAs in EPARs were evaluated for seven adalimumab biosimilars. Seventy-seven QAs, including 31 pCQAs, were classified and assessed for type  and extent (biosimilarity interpretation and/or test results) of information in EPARs. Reporting on the QAs (35–75%) varied between EPARs, where the most emphasis was placed on pCQAs (65–87%). Functional attributes (54% QAs and 92% pCQAs) were reported more frequently than structural attributes (8% QAs and 22% pCQAs). About 50%  of pCQAs were consistently reported in all EPARs. Regulators often provided biosimilarity interpretation  but rarely include test results . Minor differences in structural attributes, commonly in glycoforms and charge variants, were often observed in adalimumab biosimilars but did not affect the functions and clinical profile. Despite the variability in reporting QAs in EPARs, the minor observed differences were largely quantitative and not essentially meaningful for the overall conclusion of biosimilarity of the seven adalimumab biosimilars. After pThe leading regulatory and health authorities in highly regulated markets, such as the European Medicines Agency (EMA), the United States Food and Drug Administration (US FDA), and the World Health Organization (WHO), have established frameworks and guidelines for the development, assessment, and approval of biosimilars ,6,7,8. BQuality attributes are measurable molecular characteristics that describe the physical, chemical, biological, and microbiological properties of a drug molecule . Some QA® by AbbVie Corporation, USA, has the largest number of biosimilars approved in the EU market. Adalimumab is an anti-tumor necrosis factor-α (TNF-α) monoclonal antibody that prevents the interaction of TNF-α with its receptors and is indicated for the treatment of various immune-mediated inflammatory diseases ..47].similar included wording such as “same,” “match,” “(highly) similar,” “comparable,” and “consistent”.Biosimilarity interpretation was defined as reported (yes) if the EPAR contained keywords demarcating the regulatory interpretation of the biosimilarity of a QA and pCQA as identical, similar, or having minor differences. The interpretation of Test results were defined as reported (yes) if the EPAR included the quantitative or qualitative acceptance criteria of a given QA and pCQA, which included the numerical limits, range, and distribution, as shown in the examples in The frequency of the reported QAs and pCQAs stratified by structural and functional attributes was used to express the consistency in reporting the QAs and pCQAs of adalimumab biosimilars by EU regulators in EPARs. A QA and pCQA was considered to be consistently reported if EU regulators describe it in all included EPARs. The proportion of reported QAs and pCQAs for the four reporting categories see  was calcIn conclusion, we found variations in the frequency of reported QAs between EPARs of adalimumab biosimilars. The minor differences in the identified QAs did not affect functions and clinical performance and seem to be largely quantitative differences and not essentially meaningful for the overall conclusion of biosimilarity.In line with our hypothesis, the pCQAs, specifically functional pCQAs, were reported most frequently and consistently in EPARs, as these reflect the MoA and can potentially affect the clinical profile. Greater consistency could be applied in reporting of QAs with more emphasis on pCQAs in EPARs, which could improve the understanding of the relationship between QAs and the clinical profile, which may positively contribute to adopting biosimilars in clinical practice.


Improvements in health cannot occur without cutting-edge research informing the design and implementation of health programmes and policies, highlighting the need for qualified and capable researchers and institutions in countries where disease burden is high and resources are limited.Research capacity strengthening efforts in low- and middle-income countries have included provision of training scholarships for postgraduate degrees, often in high-income countries, internships at research universities/centres, short courses, as well as involvement with research groups for hands-on experience, among others. The HRP Alliance provides opportunities for developing local research capacity in sexual and reproductive health and rights through institutions based in low- and middle-income countries linked with ongoing and past collaborative studies. It is a network of HRP research partner institutions, World Health Organization (WHO) country and regional offices, WHO special programmes and partnerships, and WHO collaborating centres.It is through the HRP Alliance that HRP seeks to improve population health by strengthening local research capacity in sexual and reproductive health across the globe, with focus in low- and middle-income countries, in alignment with WHO’s quest of promoting healthier populations. Improvements in health cannot occur without cutting-edge research informing the design and implementation of health programmes and policies. Evidence generated in-country is necessary to shape and add relevance to national research and policy agendas –3. This Research capacity strengthening (RCS) efforts in LMICs have included provision of training scholarships for postgraduate degrees, often in high-income countries, internships at research universities/centres, short courses, as well as involvement with research groups for hands-on experience, among others –7. Thesehttps://www.who.int/reproductivehealth/hrp_alliance/en/). It is a network of HRP research partner institutions, WHO country and regional offices, WHO special programmes and partnerships, and WHO collaborating centres. It is through the HRP Alliance that HRP seeks to improve population health by strengthening local research capacity in SRHR across the globe, with focus in LMICs, in alignment with WHO’s quest of promoting healthier populations [The HRP Alliance, created in 2016 as part of the UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP) , provideulations .  Fig. ;Tailored support to country research institutions in the development and implementation of research studies and the production of scientific publications;Leadership in knowledge transfer activities that contribute to ensuring the implementation of WHO recommendations for policy and practice;Collaborative grant proposals among several hubs or institutions supported by the hubs using the HRP Alliance network to leverage experience and expertise;Enabled collaborations among HRP Alliance fellows for specific research projects;Response to health emergencies through SRHR research to improve rapid health system response and local research capacity.At the core of the HRP Alliance are regional RCS “hubs,” selected through an open competitive process that considers experience in SRHR RCS and capacity to provide regional leadership in RCS. These hubs, based in Brazil, Burkina Faso, Ghana, Kenya, Pakistan, Thailand, and Viet Nam,Since inception, the HRP Alliance has trained over 700 participants from LMICs through 30 workshops and courses and is supporting over 60 researchers obtain a master’s or doctoral degree, some of whom have been involved in the local implementation of HRP multi-country studies –17 and iThe HRP Alliance model for RCS is one among many, but it holds the unique characteristic of allowing for the development and building of research capacity of individuals and institutions through the engagement and leadership of research institutions located in LMICs. This model has the potential, by supporting RCS activities through institutions located in the regions of interest, to prevent future brain drain of qualified researchers by building capacity and offering viable opportunities for implementing research in their home countries. This paper serves as a blueprint of what the HRP Alliance has set out to do and to be held accountable to its mandate.Additional file 1. Version de l'article en français - versão do artigo em português - versión del artículo en español


The global nutrition transition and increased consumption of sugar-sweetened beverages and ultra-processed snacks have contributed to increasing rates of child obesity and dental caries in developing countries. In Nepal, where child malnutrition rates are high, the relationship between malnutrition and dental caries is poorly understood. This cross-sectional study aims to assess this relationship among a convenience sample of 273 children age six months to less than 12 years in three communities in Nepal, using parent/caregiver interviews, child dental exams, and anthropometric measurements. Fisher’s exact test and independent t-tests examined associations between dietary practices and severe caries and between severe caries and malnutrition, respectively. Children consumed sugar-sweetened beverages and processed snacks frequently: 80% consumed tea with sugar, 60% consumed sweet snacks, and 65% consumed processed savory snacks daily. Overall, 74% of children had untreated tooth decay, and 21% exhibited stunting malnutrition, 14% were underweight, and 6% presented wasting. Significant associations were found between daily consumption of sweets and processed snacks with severe caries and between severe caries and poorer nutritional status. These findings underscore the need to incorporate nutrition and oral health promotion and dental treatment into maternal–child health services and schools and to strengthen policies to reduce children’s access to junk food. The global “nutrition transition” describes the shift from a traditional, whole-food diet to a highly-processed diet high in sugar, fat, and salt, often referred to as the “Western diet” . Over reDental caries, the most prevalent chronic disease of childhood, is driven by exposure to dietary sugars. Metabolized within the dental biofilm, these sugars create a state of imbalance where net demineralization of the tooth structure occurs. That process, when left unchecked, will lead to cavitation and then chronic infection of the pulp space and surrounding tissues ,12,13. CSugar consumption is a common risk factor for dental caries, malnutrition, and obesity ,24,28. TThis is a cross-sectional study of dietary practices, nutritional status, and oral health in a convenience sample of 273 Nepali children aged six months to 12 years, conducted in December 2016. Participants were recruited by our local partner organization, Jevaia Foundation, a Nepal-based non-governmental organization working with the Ministry of Health to build a system of community-based dental care in rural Nepal. Participating villages were selected based on the interest, needs, and working capacity of Jevaia Foundation. All families with children from six months to 12 years of age from two rural villages (Puranchaur and Hansapur) and one urban community (Pokhara City) in the Kaski district of Nepal were invited to participate in a community dental health camp. Camp activities included data collection followed by nutrition and oral health education, distribution of toothbrushes and fluoride toothpaste, fluoride varnish application, and referral to dental treatment as needed. This study received ethical approval by the University of California, Berkeley Committee for Protection of Human Subjects (#2010-06-1655), University of California, San Francisco Human Research Protection Program by inter-institutional reliance (#2493-UCSF), and the Nepal Health Research Council (#420/2016).Trained Jevaia field staff, who were experienced in conducting oral health promotion in Nepal, provided verbal explanation of the study to participating parents/caregivers and children, obtained written informed consent from adults for their own and their children’s participation, and obtained verbal assent from children according to their developmental ability. Field staff interviewed parents/caregivers regarding family demographic characteristics, maternal and child dietary and oral health practices, dental symptoms, and access to dental care . InterviTo assess children’s consumption of snack foods and beverages associated with dental caries, parents were asked about the frequency of their child’s consumption of milk, soda, tea with sugar, sweet snacks, and processed savory snacks. Sweet snacks were defined as sweets, candy, and chocolate, and processed savory snacks were defined as chips and biscuits. For each food or beverage, parents were asked to estimate their child’s frequency of consumption within six categories: Never, Every 2–3 Weeks, Once a Week, 2–3 Times a Week, Daily, and 2–3 Times a Day. Frequency of consumption of milk, soda, tea with sugar, sweets, and processed snacks comprised the predictor variables for the association between dietary consumption and severe caries.Three indices for severe caries were used as the outcome variables for the association between diet and severe caries and predictor variables for the association between severe caries and malnutrition: (1) Severe Early Childhood Caries (S-ECC), for children with primary dentition (<6 years), defined by any caries in children <3 years, dmft score >4 at age 3, dmft score >5 at age 4, dmft score >6 at age 5, or any dmft in the maxillary anterior incisors . (2) TheChild nutritional status was determined by the World Health Organization (WHO) growth reference standards for children ,42. WHO Descriptive data were examined using frequencies with mean and standard deviation (SD) for family demographic characteristics, and the responses were stratified by age for child nutrition and oral health characteristics. The responses assessing diet consumption were consolidated into Rarely or Never (combining Never and Every 2–3 Weeks), Weekly (combining Once a Week and 2-3 Times a Week), and Daily (combining Daily and 2–3 Times a Day). The association between frequency of dietary consumption and severe caries  was examined by applying Fisher’s exact test, a procedure used for small sample statistics with cells less than a value of 5 . IndepenFamily demographic information is presented in Child nutrition and oral health characteristics by age are summarized in This exploratory study examined the diet-related risk factors for severe tooth decay and the association between severe tooth decay and nutritional status in a convenience sample of Nepali children. The traditional diet in the areas of Nepal where the study was conducted is rice with lentils and vegetables , and traditional snacks include corn or popped corn, roasted soybeans, beaten rice, and foods made from locally grown grains such as wheat and millet . The majFor children under six years with primary dentition, severe early childhood caries was associated with frequent milk consumption as well as frequent consumption of sugary drinks (SSBs and sugar tea) and snacks (sweet and processed). It appears that younger children who never consumed milk experienced a greater frequency of severe caries than those who consumed milk daily or weekly. At the same time, children who consumed sugary beverages and junk food on a daily or weekly basis had a greater frequency of severe caries than those who never consumed these products. For older children (who had mixed dentition), severe caries was associated only with frequent consumption of sweet and processed snacks. These findings suggest that frequent consumption of sweet and processed snacks may be hazardous to the oral health of children of all ages and that sugar-sweetened beverages as well as non-nutritious snacks may be particularly hazardous to children’s oral health in early childhood. This finding aligns with existing evidence that primary teeth are particularly susceptible to rapid progression of caries due to their smaller size and bulbous shape which creates a larger surface area to volume ratio, thinner enamel, and generally poorer oral hygiene in early childhood ,46. AddiIn this study population, caries was observed to begin in the first two years of life and increased steadily in frequency and severity over early childhood. Tooth eruption began as early as six months of age, with the first sign of tooth decay at 12 months of age. At age seven, the mean dmft+DMFT (5.9) and the frequency of pufa+PUFA (58%) were at their highest. The decline in mean dmft+DMFT and pufa+PUFA frequency starting after age seven is likely due to the normal exfoliation of primary teeth that were decayed. From infancy to age 12, the majority of children (74%) had tooth decay, but it was the approximately 1/3 of children with severe caries who were at significantly increased risk for the adverse impact of caries on their nutritional status.While the frequency of malnutrition in this sample was lower than that in other studies , the ratWhile the maternal-child health field and child malnutrition literature has continued to focus on poverty, insufficient macro- and micro-nutrients, and infectious diseases as the main contributors to child malnutrition, the possible contributions of excessive sugar consumption and dental caries have not been acknowledged . There nThis study has limitations including the use of a cross-sectional analysis to identify associations but cannot demonstration causation. The use of a convenience sample may not be generalizable to the entire population, and a small sample size limits the power of the statistical analysis and the ability to conduct multivariable analysis that can control for confounding. Analysis of severe caries is also limited by the aggregation of dmft and DMFT in children with mixed dentition. Furthermore, this study assessed dental caries as a primary outcome and exposure and did not include a complete oral hygiene evaluation. Oral hygiene was evaluated by self-report yet we did not assess toothpaste usage, plaque scores, or gingival inflammation. Moreover, the use of broad age ranges for analyzing the association between dietary consumption and severe caries and malnutrition limits the ability to make conclusions about these relationships in narrower age strata. In addition, due to the limited time available for interviews, the questionnaire addressed a small number of caries-related snack foods and beverages, rather than a comprehensive dietary assessment, which could have provided greater dietary detail. Finally, dietary behaviors as reported by parents/caregivers may have underestimated children’s consumption of junk food due to acceptability bias or lack of awareness of their children’s consumption outside of parental supervision. Despite these limitations, this exploratory study is useful for providing a foundation to inform further hypothesis formation about caries and malnutrition in Nepal. Future research should use more robust sampling and statistical methodology to better understand the directionality of sugar consumption, caries, and nutrition-related disease among Nepali children.This cross-sectional study of the nutrition and oral health of Nepali children aged six months to less than 12 years demonstrated a high prevalence of the daily consumption of junk food and sugar-sweetened beverages, significant associations between the frequency of junk food consumption and severe dental caries, and significant associations between severe dental caries and the risk for malnutrition. Maternal–child health programs, early childhood education, and schools should incorporate combined nutrition and oral health interventions to promote the traditional diet, oral hygiene, and dental screening and treatment, as well as advocacy for policies to limit the marketing of unhealthy products to children to ensure that children’s environments promote good nutrition and oral health.


Exemplars,” studies success factors among these countries with a lens toward replicability.Several countries have notably reduced childhood stunting relative to economic growth over the past 15–20 y. The Exemplars in Stunting Reduction project, or “Exemplars studies.This paper details the standardized mixed-methods framework for studying determinants of childhood stunting reduction applied in Exemplar countries, evidence-based frameworks, mixed methodologies , effective research partnerships, case study process and timeline, and data triangulation and corroboration are presented.An expert technical advisory group (TAG), criteria for identifying Exemplars research activities. A systematic review of published peer-reviewed and grey literature was undertaken, along with in-depth policy and program analysis of nutrition-specific and -sensitive investments. Both descriptive and advanced quantitative analysis was undertaken . Qualitative data collection using in-depth interviews and focus groups was conducted with national and community stakeholders  to understand country experiences. The case study process was iterative, and all research outputs were triangulated to develop the stunting reduction narrative for each country. Findings were shared with country experts for weigh-in and corroboration through dissemination events.Experts in health, nutrition, and evaluation methods were selected at the study outset to provide technical support to all phases of research (TAG). Exemplar countries were selected by the TAG, who considered quantitative data  and qualitative insights . Experienced country research partners were selected and an inception meeting with stakeholder consultations was held to launch research and garner support. Evidence-based conceptual frameworks underpinned all Exemplars research uses a mixed-methods framework for studying positive outliers that can be applied across diverse health and development outcomes. These hExemplars in stunting reduction country case studies. Our framework is based on the broad Exemplars in Global Health approach for studies of positive outliers (Supplementary Appendix 1) . This paper presents an overview of methods; therefore, ethical review was not required.This methods paper introduces our standardized mixed-methods framework applied across all Exemplars project, we assembled a technical advisory group (TAG) of global experts in health, nutrition, and evaluation methods (Supplementary Appendix 2). Experts represented a range of sectors, including academia, donor, and nongovernmental organization (NGO) communities, and included representation from the World Bank, the Bill & Melinda Gates Foundation (BMGF) and International Food Policy Research Institute (IFPRI). The TAG was established to ensure Exemplars research was scientifically robust, current and relevant to diverse stakeholders, and utilizing valid cutting-edge methodologies and tools. Specifically, the TAG provided technical inputs and support through all phases of Exemplars research, including country selection, methodology design and implementation, and result interpretations and inferences, as well as partnered communication and dissemination activities. The TAG convened in-person or remotely multiple times throughout the year as required.At the outset of the Exemplars largely focused on highlighting positive outliers in the 2000 to 2015 period. Our systematic country selection process aimed to identify true exemplars  or “positive outliers.” To this end, the process of selecting case study countries involved plotting the compound annual growth rate (CAGR) in absolute stunting prevalence as a function of the CAGR in gross domestic product (GDP) per capita. We also found no difference in country ranking with sensitivity analyses using gross national income (GNI) per capita instead of GDP and average annual percentage point change (AAPC) instead of CAGR. We stratified analyses by World Bank income groups  to compare countries within similar income bands (1) steep declines in stunting rates over time and/or 2) high CAGR in stunting prevalence relative to CAGR in GDP per capita. In other words, those countries that demonstrated greater reductions in stunting prevalence while experiencing relatively smaller increases in GDP per capita were ideal candidates for case study selection.Given accelerated under-5 stunting prevalence reduction globally and in several LMICs after the year 2000, me bands . Using tSupplementary Appendix 3. Countries ranked in the bottom left quadrant are the closest to exemplar status; a total of 13 countries were shortlisted by the TAG in this manner . The TAG also considered additional factors such as the total population of each country (minimum threshold of 5 million), variability across income bands and geographic region, physical accessibility/country security, feasibility of case study activities , and the existence of local contacts and potential partners. Using these criteria, a total of 5 countries were selected for phase 1 of the Exemplars project  in Toronto, Canada. Identifying country co–principal investigators and collaborating with local research teams, however, was critical to each study. We selected academic partners with experience in diverse disciplines related to child stunting, such as public health, nutrition, maternal and child health, demography, and public finance and economics. Research partners for each Exemplar findings, and identifying strategic partnerships and opportunities for dissemination.Our country partners were pivotal in all stages of the research; specifically, they lead the qualitative data collection and program/policy analysis, and provided support to the systematic literature review and quantitative analyses. Research partners also coordinated and facilitated an inception meeting at a central location that was attended by >20 national experts across sectors including government , academia, UN agencies, the World Bank, the WHO, NGOs , and frontline workers , among other child nutrition interest groups. These study launching events aimed to proactively engage key stakeholders in all planned aspects of the study, including but not limited to identifying datasets, locating policy and program documents, discussing methodology, identifying participants for qualitative inquiry, increasing awareness and ownership of Exemplars, we adapted the framework to study determinants of childhood stunting reduction  (90 (19) aExemplars research and its purpose in our work are summarized in Key methods used in Exemplars analysis did not duplicate but rather enhanced the existing understanding of stunting in each country. We used standard systematic review methodology . We searched >15 online search engines  and multiple grey literature sources, including government and UN websites, among others. Three broad categories of search terms were used: stunting, child, and country. We searched for literature in all languages published after 1990. Articles were title and abstract screened for relevance, and standardized inclusion and exclusion criteria were applied across countries; see Supplementary Appendix Figure 4 for the example flow diagram from Senegal.Each case study started with a systematic review of published and unpublished literature synthesizing information on contextual factors, national and subnational interventions, policies, strategies, programs, and initiatives that may have contributed to stunting reduction in the country. The systematic review was critical for understanding the current state of knowledge on stunting in each country, for informing study methodology and potential data sources, for identifying knowledge gaps, and for corroborating (or contrasting) our results. This step was pivotal in ensuring Exemplar studies were the demographic and health surveys (DHSs) and multiple indicator cluster surveys (MICSs). These nationally representative household surveys utilize comparable, standardized methods to gather data for a wide range of indicators in the areas of population, health, and nutrition  independently ranked each variable strength from 1 to 5, and an unweighted mean was calculated. Using this method, variable strength ranged from 2/5 to 5/5, with an average strength score of 3.7/5, which suggested that indicators in Exemplars studies were of adequate quality on average but that interpretations of analysis should be made with caution, particularly for those based on lower-ranking variables .The main study outcomes were child HAZ and stunting calculated using WHO child growth standards . The hieExemplars research are summarized in Appendix 1 (1) analyzing the gap  between extreme groups over time; 2) stunting prevalence for the least educated, most educated, or middle groups; and 3) changes in stunting prevalence for any group over time. We analyzed both relative and absolute changes in stunting prevalence for each geographic region by calculating the compound annual growth rate and AAPC, respectively. Both metrics provide value and selection of one compared with the other should depend on research interest. In Peru, for instance, departments  that had the highest reduction in stunting prevalence according to CAGR were slightly different than those identified with AAPC; our selection of “top performing” regions was based on a composite of those that ranked high in absolute and relative change.Descriptive analysis methods used in pendix 1 , 28–35. pendix 1 , 30. As 1) whole-population shifts in HAZ plot; 2) changes in mean HAZ across surveys, to examine whether reductions in growth faltering were occurring for the entire spectrum of children in that age group; and 3) changes in skewness and kurtosis of the curve, to explore inequalities in the growth-faltering spectrum. See example illustrations for Ethiopia in Supplementary Appendix 8.We generated child HAZ kernel density plots for all under-5 children and stratified for children aged <6, 6–23, and >24 mo. Such analyses enabled inferences regarding 1) the curve's intercept, which reveals the intergenerational susceptibility of child undernutrition or the extent to which a mother's nutrition leads to small babies at birth; and 2) the postnatal growth-faltering process, which is typically steepest between 6 and 24 mo, after which it tapers off. Child growth curves, or “Victora curves,” show predicted child HAZ that has been estimated from smoothed local polynomial regressions plotted against child age , 37. SeeExemplars study undertook 2 sets of complementary multivariable analyses that aimed to answer the same research question . The linear regression based on panel datasets uses a difference-in-difference analysis framework in which interactions of time with covariables are used to assess factors impacting HAZ decline  to identify the nutrition-specific and -sensitive key events  that may have contributed to a reduction in child stunting; 2) to understand the main success factors and challenges of relevant nutrition-specific and -sensitive facilitators of key events ; 3) to identify important contextual factors that have functioned as enablers or drivers of national-level stunting change; and 4) to document community-level perspectives and experiences on the stunting transition by consulting childcare workers and mothers of young children.The qualitative component of We undertook 3 independent research activities to inform study objectives. At the first stage, national stakeholders  were interviewed to provide insight and expertise on objectives 1, 2, and 3. This top-down approach aimed to solicit macro-level perspectives and experiences in health and nutrition in each country. To understand how individuals in the community received and implemented major nutrition-specific and -sensitive policy and program events, as well as their experiences in the nutritional transition as a whole, we consulted childcare workers in the community  and the mothers of young children. These latter 2 research activities largely informed objectives 3 and 4 and also shed light on objective 2.Supplementary Appendix 10. Data were analyzed using thematic analysis aligning with the basic, underlying, and immediate causes of child undernutrition. Methods detailed for the Exemplars studies are provided in the respective papers in this supplement.Primary qualitative data collection methods involved conducting in-depth interviews (IDI) with key informants at national and community levels (10–20 participants), and focus group discussions (FGD) with mothers in communities (2–12 focus groups with 10–15 participants each). Our conceptual framework informed design of the IDI and FGD guides, as well as analysis and interpretation of the qualitative data. Our qualitative data collection tools were also informed by existing literature and nutrition questionnaires; for example, the IFPRI's nutrition-focused qualitative data collection toolkit was consulted and relevant tools were adapted to our research objectives as appropriate . Our appExemplars studies are provided in the respective papers in this supplement.We assembled a timeline of key nutrition-specific and -sensitive laws, acts, and regulations; policies, strategies, and plans; and programs in each country through an iterative approach drawing on several of the above methods. Starting with a desk review of literature identified through our systematic approach, a suggested timeline was proposed by SickKids researchers and the country research team. This timeline was shared with national expert stakeholders to obtain their corroboration and insight on any missing initiatives. After reviewing additional literature and specific policy and program documents as suggested by experts, a second iteration of the timeline was proposed. This process ensued until consensus was reached between all research partners and experts. For each initiative, we thoroughly examined published and unpublished documents to track down the information displayed in Exemplars studies was to iteratively use data from each research activity to derive and contextualize key results. Evidence-based inferences supported by our analyses were first proposed by SickKids research leads, and then subsequent iterations were added on with country partners and subject matter experts and contrasted with the literature to develop the final narrative. This thorough process of weighing the existing literature with empirical data and analysis and expert insight ensured that inferences on causality and determined pathways of change were plausible and rooted in rigorous analysis.A final and critical step of Exemplar studies have been presented sequentially in this paper, it should be noted that, in practice, activities occurred in tandem. This parallel approach was effective in honing our methodology as we used emergent results from one research activity to inform processes and inferences of others. Similarly, learnings from earlier case studies performed in earlier countries were used to streamline methods for subsequent studies. In general, case studies ensued as follows: 1) preparation of preliminary literature review, policy and program snapshot, and descriptive quantitative analysis; 2) attendance at a study inception meeting in each country to present the study background and approach and consult key stakeholders; 3) developing and implementing methods for systematic review and qualitative, quantitative, and policy and program review work; 4) completion of research and development of final study results; and 5) sharing of findings and country expert consultation to iterate on inferences. Each Exemplar research study took about 1 to 1.5 y to complete, and all 5 phase 1 studies were completed between 2017 and 2019.Though the 4 research activities used in Exemplars approach exercised a range of activities, including a systematic literature review, qualitative inquiry with diverse national- and community-level stakeholders, robust quantitative analyses, and policy and program mapping and an exploration of financial allocations, to paint a holistic picture of stunting decline in each country. Though mixed-methods research for studying determinants and drivers of nutritional improvements is not new, our approach improves upon the existing literature in several ways  had child anthropometry data with >20% flagged/implausible values. Paper 3 of this supplement sheds additional light on anthropometry quality and metrics for its evaluation.Several study limitations should also be noted . Data peThere was generally a limited scope of ecological variables available for our assessment, and several important domains were not quantifiable even through area-level predictors, like food security, agriculture production, etc.We were not able to quantitatively examine several drivers due to the challenges posed in measuring such phenomena  and limitations of data availability for several programs . Our mapping of financial data pertaining to nutrition-specific and -sensitive initiatives may be incomplete, considering that we reported only data we could obtain from stakeholders and the published literature. Significant limitations in national health expenditure data and the financial allocations for specific programs highlight a gap in our understanding of the investment, implementation, and scale of these efforts.We were also not able to conduct age-stratified analyses for all countries, particularly for children <6 mo of age, due to limited statistical power and/or meaningful HAZ change over time in these populations. Thus, we could have missed important age-specific HAZ determinants . Another limitation pertains to confounding. Although we adjusted for confounding variables in the quantitative analyses, some residual confounding may remain from unmeasured confounders or poorly estimated variables. Interactions between different factors within and between the different hierarchical levels may also affect the results, although due to measurement challenges they were not assessed. Given the reliance on cross-sectional survey datasets for quantitative analyses, causal inference was challenging and interpretations had to be made with caution.Participant recall, high staff turnover, and poor institutional memory were also limitations of the qualitative inquiry.Exemplars mixed-methods approach for studying determinants of childhood stunting decline over a 15–20-y period in countries that have made significant progress. Despite limitations in data, the approach brings several strengths for building a comprehensive and rigorous narrative of change. In scaling up efforts to reduce morbidity and premature mortality among mothers and children globally, we hope such mixed-methods research approaches can become commonplace in studying health and development outcomes.This paper presented the nqaa152_Supplemental_FileClick here for additional data file.


The computer vision technique has been rapidly adopted in cow lameness detection research due to its noncontact characteristic and moderate price. This paper attempted to summarize the research progress of computer vision in the detection of lameness. Computer vision lameness detection systems are not popular on farms, and the accuracy and applicability still need to be improved. This paper discusses the problems and development prospects of this technique from three aspects: detection methods, verification methods and application implementation. The paper aims to provide the reader with a summary of the literature and the latest advances in the field of computer vision detection of lameness in dairy cows. Dairy cow lameness not only adversely affects dairy cow welfare and reduces dairy production but also degrades the reproductive capacity and increases the mortality rate ,2,3. AccThis high lameness rate has a large impact on the dairy economy ,11. LameLameness leads to behavioral changes in dairy cows when walking , as the Automated lameness detection could provide useful cow- and herd-level information to address an information gap, particularly regarding mild and moderately lame cows . The autThe purpose of this paper was to review the development and research of the computer vision-based lameness detection technique for dairy cows, providing references and suggestions for future research approaches, as well as the development of computer vision-based lameness automatic detection systems, by analyzing the existing methods and technologies used in lameness detection. This paper is divided into four parts: In part 1, the main studies used in lameness detection (based on 2D computer vision) are reviewed and introduced, including the image processing, feature selection, classification and evaluation methods. Part 2 introduces the lameness detection techniques based on newer types of cameras, including 3D and thermal infrared cameras, as well as their advantages and disadvantages and a comparison with the 2D detection methods. Part 3 briefly introduces other sensors for lameness detection used in the current research and analyzes the inspiration behind other detection technologies for the study of computer vision-based lameness detection. Finally, the findings of this review are presented in Part 4. Part 5 summarizes the article and discusses computer vision-based lameness detection from three aspects—namely, research methods, verification methods and practical applications—to provide ideas and references for future research on lameness detection.https://scholar.google.com/), Web of Knowledge (http://wokinfo.com/) and Science Direct (https://www.sciencedirect.com/). This review includes peer-reviewed articles (132 articles) published between January 1989 and September 2020. The key words lameness, automated, lameness classification, lameness detection, computer vision, image processing, locomotion scoring, dairy, and cattle in various combinations were entered into Google Scholar  and optimized the classification performance by multiple consecutive measurements using 3D video . Four coInfrared thermography (IRT) is a noninvasive, non-radiation, rapidly evolving diagnostic method, and it can measure the surface temperature of an object . Since hOther research on the detection of lameness in dairy cattle has focused mainly on changes in movement , changesCompared with computer vision detection methods, contact sensors have several advantages, including easier data acquisition, stronger mapping relationships between the data and lameness characteristics and simpler research and decision-making methods. These studies also reveal some deficiencies in the computer vision-based techniques for detecting cow lameness. One of the most important deficiencies is that a computer vision technique cannot accurately obtain the characteristic information of cows through image processing, and errors in image processing lead to errors in characteristic information and then affect the judgment involved in the decision-making of lameness detection. However, due to the noncontact information acquisition method and the detection method being similar to the locomotion score system, this technique is worthy of being studied. Therefore, in the next chapter, we discuss the development of a cow lameness-detection technique based on computer vision.Lameness remains an important problem for dairy farming. Due to the great difficulty and cost of the manual detection of lameness, it is necessary to accurately and automatically detect the lameness of cows. The main advantages of lameness detection in cows based on computer vision methods are that these methods are cheap and noncontact ; howeverLocomotion scores and foot pathologies are usually used as the reference standards for the validation of automatic lameness detection systems (ALDSs) . The curToday’s lameness detection research typically uses professional observations as the validation data for research results; however, lameness is a process, rather than a binary characteristic  ,31. ThusAlthough the methods of cow lameness detection based on computer vision have been studied for many years, they have not been widely applied. An automatic lameness detection system must be effective, reliable and feasible . Based oThe result of the survey “Why are automatic cow lameness detection systems not popular?” shows that “before automatic detection cow lameness systems can be applied in practice, low-cost systems with high-detection performance must be available” . The cosCompared with manual detection, despite that the automatic detection system has equipment costs, the returns from automated lameness detection may still be worthwhile . HoweverRegarding the detection ability of cow lameness systems based on computer vision, farm staffs are primarily concerned with the false-positive percentage, the missed lameness percentage and the accuracy of the indication regarding which leg exhibits lameness . AnotherIn addition to the system costs and detection ability, some additional problems affect the deployment of these systems. For example, 2D camera images are disturbed by illumination conditions and background changes and have strict requirements for placement and positioning. When long-term and continuous measurements are needed , environComputer vision-based technologies used for cow lameness detection have the advantages of a noncontact application and moderate prices, which can effectively classify lameness according to the walking status of dairy cows to improve the welfare of dairy cows and reduce economic losses. This paper aimed to provide an overview of the results in this field of research. It classified these techniques according to the types of cameras used in the computer vision systems, including 2D, 3D and thermal infrared cameras. Since different types of cameras can provide different images of cows, the research methods are also different. We separately reviewed their key steps in lameness detection, including feature selection, the feature acquisition technique and lameness detection method, since most research was focused on these steps. At the same time, this paper compared and discussed the advantages and disadvantages of the different types of cameras used in lameness detection systems. In the study of a computer vision detection technique for dairy cows, there were still some problems and obstacles in the detection effects and application. This paper discussed the problems and development prospects of this technique from three aspects: detection methods, verification methods and application implementation. Development aimed at the application and popularization of the computer vision lameness detection system for dairy cows still faces technical problems and limitations related to its application on farms, which requires further exploration and research.


The association between socioeconomic status and health/healthcare related outcomes across the life course is well established; however, the specific mechanisms that underlie this complex association are not well understood. There have been calls in the health disparities literature for greater explication of the socioeconomic factors associated with differential outcomes for racial/ethnic minorities and socioeconomic groups. Recent research offers an expanded notion of socioeconomic circumstances by including indicators of financial hardship; however, there has been little conceptual and measurement clarity for gerontology research. To fill this gap, we conducted a scoping review of how financial hardship has been defined and measured in research with older adults. Using an adapted version of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) protocol, N=25 articles were identified through the following indexes: PubMed, CINAHL, PsycInfo, Sociological Abstracts, and Embase. Articles were included if they were published after January 1, 2000, published in the United States, and conducted with adults aged 50 and older. Our study found neither a consistently used term for nor a definition of the financial hardship experience; however, two key domains were consistently measured across studies with older adults: food insecurity and medical expenses were measured in N=9 and N=13 studies, respectively. Greater conceptual and measurement clarity in research on financial hardship among older adults helps to unpack the complex ways in which socioeconomic circumstance are experienced, make comparisons across studies measuring the financial hardship experience, and to identify the specific aspects of financial hardship for intervention.


Knowledge regarding late effects  in survivors of adolescent and young adult (AYA) acute lymphoblastic leukemia (ALL) is lacking.Using the population-based California Cancer Registry linked with California hospitalization data, we evaluated late effects in 1069 AYAs (aged 15–39 years) diagnosed with ALL in California between 1995 and 2012 and surviving a minimum of 3 years from diagnosis.The estimated 10-year cumulative incidence of subsequent endocrine disease  and cardiac disease  were strikingly high; avascular necrosis , liver disease , respiratory disease , seizure and/or stroke , renal disease , and second neoplasms  were estimated to occur at 10 years with the reported frequencies. Multivariable analyses including the entire patient cohort demonstrated that public or no insurance (vs private and/or military insurance) and receipt of hematopoietic cell transplantation were independently associated with the occurrence of all late effects considered. In multivariable analyses limited to the 766 AYAs who were not transplanted, we continued to find a statistically significant association between public and no insurance and the occurrence of all late effects. Frontline regimen type (pediatric vs adult) was not statistically significantly associated with any of the late effect categories.This large population-based analysis is among the first to describe late effects in survivors of AYA ALL. The strong association between insurance type and late effects suggests that AYAs with public or no insurance may have reduced access to survivorship care following completion of ALL therapy. As the survival of adolescents and young adults (AYAs) with acute lymphoblastic leukemia (ALL) improves, a greater focus on late effects and survivorship issues is increasingly necessary. The medical conditions and subsequent neoplasms (hereafter referred to as late effects) that develop following the successful treatment of ALL in children have been captured and described through a variety of registries, including the Childhood Cancer Survivor Study (CCSS) . No suchThe treatment landscape of AYA ALL has evolved over the past 2 decades. Although novel targeted immunotherapies and cellular therapies are now routinely used in relapsed or refractory ALL, multiagent chemotherapy remains the backbone of AYA ALL treatment . AYA ALLTo begin to fill these gaps in current knowledge, we conducted an observational study evaluating late effects in survivors of AYA ALL across the state of California. Using population-based data, we additionally describe associations between late effects and AYA sociodemographics and ALL therapies, including frontline regimen type, in a large cohort of AYA ALL survivors.International Classification of Diseases (ICD) for Oncology, 3rd edition, codes 9826, 9835, 9836, 9811-9818, and 9837. The CCR is California’s population-based cancer surveillance system, which is composed of 3 National Cancer Institute Surveillance Epidemiology and End Results registries. The CCR has been state mandated to collect reports on incident cancers diagnosed in California since 1988. Patients surviving less than 3 years from diagnosis were excluded from the study cohort.We identified patients aged 15 to 39 years at the time of ALL diagnosis between January 1, 1995, and December 31, 2012, in the California Cancer Registry (CCR) using the seeICD, 9th Revision (ICD-9) and the ICD, 10th Revision (ICD-10).Identified patients were linked to the Office of Statewide Health Planning and Development (OSHPD) patient hospital discharge records through a probabilistic linkage that matched on social security number, date of birth, sex, and zip code. Patients who did not link to the OSHPD file  were excluded see. OSHPD cWe obtained patient characteristics and treatment information from CCR including age at diagnosis, sex, race and ethnicity, health insurance at diagnosis or initial treatment, neighborhood socioeconomic status (SES) tertile, treatment facility, physician specialty (pediatric vs adult oncologist), cranial irradiation treatment (CRT), and frontline regimen type. We considered publicly insured and uninsured patients together in the analyses because prior evaluations demonstrated that most AYAs who obtain public insurance at diagnosis were either uninsured or had intermittent public insurance just prior to diagnosis, and therefore the small number of uninsured AYA cancer patients in the cancer registry likely reflects retroactive enrollment in Medicaid at cancer diagnosis ,10. PrivICD-9 and ICD-10 discharge diagnosis codes  characterized baseline patient, hospital, and treatment attributes. We used nonparametric methods that account for death as a competing risk to calculate cumulative incidence (CMI) and associated 95% confidence intervals (CIs) of developing a late effect 3 or more years after diagnosis . For CMIP value of less than .05. The proportional hazards assumption was assessed numerically based on cumulative sums of Martingale residuals and visually by plotting the log of negative log of the Kaplan-Meier estimates vs the log of time for all predictor variables. Variables that violated this assumption  were included as stratifying variables. Correlation of variables in the models was assessed using chi-square tests. Multivariable models for late effects were adjusted for race and ethnicity, sex, health insurance, diagnosis year, neighborhood SES, and radiation. All models (seeP < .001); thus, models in the entire cohort included transplant, but not frontline, regimen. We also evaluated late effects separately in patients who did not undergo transplant . All statistical tests were 2-sided, and a The final study cohort included 1069 AYA patients (aged 15-39 years at diagnosis) with ALL diagnosed between 1995 and 2012 in California who survived at least 3 years following diagnosis and were successfully identified in both the CCR and the OSHPD databases . BaselinThe estimated 5- and 10-year CMI of late effects are depicted in Multivariable analysis including the entire study cohort (n = 1069) demonstrated that public or no health insurance (vs private/military) and receipt of HCT were statistically significantly and independently associated with every late effect considered in this study . StatistMultivariable analysis among patients who were not transplanted (n = 766) similarly revealed public or no health insurance (vs private/military) to be statistically and independently associated with all late effects . This anFinally, a separate multivariable analysis among transplanted patients (n = 303) demonstrated that in this cohort, neighborhood SES was associated with a higher risk of all late effects considered , with AYThe spectacular success of childhood ALL has resulted not only from the careful development of effective therapeutic regimens but also from the methodical tracking and reporting of late effects following successful leukemia treatment. As the therapeutic management of AYA ALL evolves and more closely mirrors the pediatric approach, it is anticipated that a greater proportion of patients will become long-term survivors of AYA ALL. It is therefore increasingly important to more clearly ascertain the burden of late effects in this cancer survivor population. In this population-based analysis of survivors of AYA ALL across California, we demonstrate that the cumulative incidence of cardiac diseases (17%), endocrine diseases (28.7%), and AVN (9.6%) is estimated to be strikingly high at 10 years following diagnosis, and the incidence of SN was 1.4%. Further, we found that the development of late effects across all organ systems was statistically significantly and independently increased in uninsured or publicly insured survivors and AYAs who had undergone HCT.In 2013, the Institute of Medicine  convened a workshop focused on addressing the needs of AYA cancer patients, which identified a critical gap in adequate research related to late effects following AYA cancers . AlthougIn the current study, we aimed to describe late effects across organ systems and SN in patients who have survived at least 3 years following a diagnosis of AYA ALL and to evaluate associations between baseline sociodemographics and general treatment approaches with late effects. It is useful to examine our findings relative to late effects described in survivors of childhood ALL but challenging because of substantial differences in patient cohorts, follow-up time, and methodologies across studies. For example, the CCSS uses a survey-based assessment tool to track late effects, whereas we used a combination of cancer registry and hospitalization data. In a CCSS analysis with longer follow-up of survivors of childhood and adolescent ALL (younger than age 21 years at diagnosis) reported by Turcotte and colleagues . The CCSIt is well known that exposures to certain therapeutic agents and modalities influence the development of late effects following cancer therapy. Although children with ALL are routinely treated with multiagent pediatric ALL therapeutic backbones that incorporate substantial cumulative doses of steroids, vincristine, asparaginase, and intrathecal chemotherapy, AYAs may be treated with these pediatric-type ALL regimens or with adult-type ALL regimens, which generally include more anthracyclines and alkylating agents . It has In contrast, we found that receipt of HCT was strongly associated with the development of late effects across all categories. Perhaps most marked was the increase in a 10-year cumulative incidence of SN with HCT (4% vs 0.3%). This is particularly striking because this dataset does not include nonmelanoma skin cancers, which have been previously reported as among the most frequent SN following HCT . The assThe use of population-based registries to approximate the incidence of late effects following cancer therapy has inherent strengths and limitations. Our analysis included linked statewide cancer registry and hospitalization data, which allowed us to evaluate important sociodemographic and cancer treatment details, as well as SN and late effects warranting hospitalization. However, we were only able to abstract the initial frontline regimen administered and were unable to detail the cumulative doses of specific therapeutic agents, including radiation therapy delivered outside the central nervous system. We also relied on diagnosis codes for late effects and were unable to capture diagnoses occurring during clinic visits, potentially underestimating the burden of late effects in our population. Similarly, we were unable to capture late effects that were diagnosed outside of the state of California. Additional studies are required to fully capture the burden of late effects that do not result in hospitalizations and those occurring on a national level. We were also unable to capture cytogenetic and molecular leukemic features at diagnosis, as well as lifestyle factors and survivorship plans that may influence late effects. Finally, the median follow-up time of 8.2 years is not long enough to assess the full burden of late effects in survivors of AYA ALL. It is well known that certain complications, including SN, may occur decades after the completion of therapy ,30,31.In conclusion, this study provides a large population-based description of late effects in survivors of AYA ALL. Given the nascent literature describing late effects, particularly in older AYAs treated in adult oncology settings, these data offer valuable insight into the burden of late effects in this vulnerable survivor population. Prospective population-based studies with longer follow-up would further inform the development of AYA-specific survivorship guidelines.This work was supported in part by Servier Pharmaceuticals. The collection of cancer incidence data used in this study was supported by the California Department of Public Health pursuant to California Health and Safety Code Section 103885; Centers for Disease Control and Prevention’s National Program of Cancer Registries, under cooperative agreement 5NU58DP006344; the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program under contract HHSN261201800032I awarded to the University of California, San Francisco, contract HHSN261201800015I awarded to the University of Southern California, and contract HHSN261201800009I awarded to the Public Health Institute.Role of the funder: The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; and the decision to submit the manuscript for publication.Disclaimers: The ideas and opinions expressed herein are those of the author(s) and do not necessarily reflect the opinions of the State of California, Department of Public Health, the National Cancer Institute, and the Centers for Disease Control and Prevention or their contractors and subcontractors.Disclosures: Lori Muffly reports consulting fees for Kite and Pfizer and research support from Servier and Adaptive. Frances Maguire, Qian Li, Vanessa Kennedy, and Theresa Keegan report no conflicts of interest.pkaa025_Supplementary_DataClick here for additional data file.


Population health is influenced by interactions between environmental determinants, which are captured by dimensions and indicators. This study aims to systematically review key environmental determinants and respective dimensions and indicators, relevant to evaluate population health in urban settings, and to understand their potential implications into policies.A search of literature published between 2008 and 2018 was conducted in PubMed, Web of Science, Scopus and SciELO Portugal databases, on studies with evidence on association between an environmental determinant and a health outcome in urban contexts. Health determinants, dimensions and indicators researched in the selected studies were synthetized, and associations analyzed. An independent assessment of quality of the studies was performed. Key conclusions and policy recommendations were extracted to build a framework to analyze environment related population health and policies in urban settings.Ninety four studies of varied methodological approaches and quality met the inclusion criteria. The review identified positive associations between all environmental determinants -socioeconomic, built environment, natural environment, healthcare, behaviors, and health outcomes - overall mortality and morbidity, in urban settings. Improvements in income, education, air quality, occupation status, mobility and smoking habits indicators have positive impact in overall mortality and chronic diseases morbidity indicators. Initiatives to improve population health in which policymakers can be more evidence-informed include socioeconomic, natural environment and built environment determinants.There is scope and need to further explore which environmental determinants and dimensions most contribute to population health to create a series of robust evidence-based measures to better inform urban planning policies. Assuring the health of the public goes beyond focusing on the health status of individuals; it requires a population health approach. Population health refers to “health outcomes and their distribution in a population. These outcomes are achieved by patterns of health determinants” . Recent The impact of urban settings on population health has been increasing as more people live in cities and towns than in rural areas , 16. As An integrated and holistic overview is necessary to facilitate a systematic examination of population health and its multiple environmental determinants in urban contexts, so that it is possible to track new evidence , 25 and Therefore, we conducted a systematic review of literature to identify which key environmental determinants  and respective dimensions and indicators  are associated with human health outcomes, entailing overall mortality and morbidity, in urban settings. The review enables an informed discussion about relevant environmental health determinants, dimensions, and indicators for urban settings and how these factors interrelate and how they may be tackled through policies defined for the urban context.den). A representation of the environmental determinants and dimensions relevant to evaluate population health in urban settings is depicted in Fig. This review was conducted according to the recommendations from the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) . A systeThe period covered in the search was from 2008 to 2018 and the following syntax was used: (#1)  AND (#2) (city OR cities OR town OR “metropolitan area” OR “urban environment”[Title/Abstract]) AND (#3) (indicators OR determinants [Title/Abstract]).As inclusion criteria each study had to: (1) be written in English or Portuguese; (2) report a quantitative relationship between at least one environmental determinant, and one health outcome and (3) population health should be analyzed in urban settings at city level, council or metropolitan area .The exclusion criteria were: (1) specific populations as migrants or indigenous populations or population living in slums; (2) genetic studies or studies using animal models, as well as studies evaluating the applications of tools or indexes and studies comparing rural and urban environments; (3) qualitative studies, systematic reviews and meta-analyses and (4) studies that were only published in abstract form. Although, we recognize the value of grey literature, in the current systematic review this form of publication was not considered due to potential risk of bias.Two authors (MS and JM) independently screened all included titles and abstracts of the entire list of studies identified and reviewed full texts of articles that met predetermined inclusion criteria.All the references identified through the search were uploaded into citation manager software ENDNOTE  and duplicates were removed. Data extracted for each publication was organized by environmental determinant, grouped by category of heath outcome and included: author and date, aim of the study, study population, study design, association measure, dimension and respective indicators, and type of relation between indicator and health outcome . Key conclusions and policy recommendations were extracted to inform the construction of a final framework to analyze environment related population health in urban settings. Discrepancies were solved through a review by a third coauthor (AM).The visualization of the relationships between environmental determinants dimensions and health outcomes evidenced in the extracted data was made using Sankey diagram  overall mortality, 2) morbidity related to birth outcomes , 3) morbidity related with overall chronic diseases outcomes  , 4) morbEnvironmental determinants were divided in socioeconomic status, natural environment, built environment, healthcare, and behaviors. Health outcomes were divided into 5 major categories: 1) overall mortality, 2) morbidity related to birth outcomes , 3) morbidity related with overall chronic diseases outcomes  , 4) morbOut of the sample of 94 studies, the largest number of included studies were published between 2012 and 2016. Predominantly the referred studies analyzed the impact of an environmental determinant and/or dimension making use of more than one indicator; and more than half focused on adult populations (18–64-years-old). Most of the studies had a cross-sectional (56%) and cohort (37%) design and the association measures were mainly odds ratio, relative risk, β coefficient and prevalence ratio.positive (+), if a desirable improvement in the indicator was associated with an improvement of population health , or if a population subgroup is associated with higher population health ; negative (−), if a desirable improvement in the indicator was associated with a deterioration of population health , or if a population subgroup is associated with worse population health ;The 94 studies explored 24-paired associations between 45 indicators  and the 5 categories of health outcomes. The multilevel mapping Sankey diagram displayed in Fig. Such cases of positive or negative associations are presented in Tables 1, 3, 5, 7, 9 in Additional file Looking into specific environmental health determinants, from the 57 studies evaluating the impact of socioeconomic determinant, 81 indicators showed association with population health. All improvements in socioeconomic determinant indicators were found to positively impact population health.Of the 36 indicators used to understand the relationship between natural environment and population health, obtained from 18 studies, the evidence showed that increases in the quality of water and decreases in all air pollution and noise indicators are associated with improved on overall mortality, birth outcomes, chronic diseases  and mental disorders.Results from the 18 indicators of built environment show that improvements in mobility and green spaces would improve population health related with overall mortality, birth complications, chronic diseases, mental disorders and obesity outcomes. Sanitation and safety improvements are associated with improvements in birth outcomes, mental disorders, and obesity outcomes.Only 5 studies assessed the healthcare determinant showing that increases in hospital supply and infrastructures have positive associations with overall mortality, while dental care use and health infrastructures showed null associations with any health outcome.Among health behaviors determinant, from the 21 indicators referred in the 14 studies included, improvements in human behavior indicators translated into improved population health but no association was found with birth outcomes and morbidity related with HIV and respiratory diseases.Contrasting with the initial framework defined for analysis, there was no study assessing the impact of soil indicators, housing indicators and health insurance indicators on mortality and morbidity outcomes. From the reviewed studies, 78% of the studies were found to have overall high risk of bias  with risk of bias being mainly attributed to issues in outcome assessment. Most of the studies were performed with populations from USA, Brazil, and Europe. This predominance can be explained by the fact that the most urbanized regions include Northern America (82% living in urban areas in 2014), Latin America (80%), and Europe (73%). African and Asian countries remain mostly rural, with 40 and 48% of their respective populations living in urban areas .Our strict inclusion criteria guaranteed that only studies assessing a clear relationship between an environmental determinant and an outcome were included. This was to objectively appraise that relationship, as well as the risk of bias and facilitate the interpretation of the evidence to increase validity of results and constancy across the data extraction.The evidence presented in the studies included in this systematic review demonstrated the importance of understanding the complex interdependency of health, society, socioeconomic condition, built and natural environment –37, as wThe overall findings suggest that socioeconomic determinant have been the most studied area, evidencing strong and consistent associations with all health outcomes appraised in this review. Lorenzoni (2019) and Pickett (2015) , 39 show2, SO2, O3, total suspended particles (TSP)) and noise levels  resulted in lower rates of mortality, as well as in decreased numbers of birth complications, chronic diseases such as cardiovascular, cancer and respiratory, and mental outcomes. In general, the studies reviewed evaluated separately the impact of air pollution and noise on health supporting the evidence that environmental noise should be considered an independent risk factor to health separated from air pollution [The constant need to monitor the state of the natural environment to check if the international targets are being achieved and if policy actions are having the desired effects  can explollution , 42. Anoollution . In factollution  there isollution . There hollution . Within ollution . Green sollution , 49. Addollution , increasollution , 51, 52.ollution , 54 showThe evidence about relationship between behavior indicators and population health shows many positive associations, especially in studies in which improvements in more than one indicator of behavior were analyzed - improvements in behavior-related indicators should improve health outcomes like mortality, chronic diseases, mental and obesity disorders.Lastly, a scarce number of studies reported the relationship between healthcare indicators and mortality outcomes - evidence was reported only in American and Brazilian populations and showed a positive association between improvements in hospital care and improvements on population health.Jia (2017)  suggestsOverall mortality and chronic diseases morbidity were the most studied outcomes in the reviewed studies. Associations with all the determinants evaluated were found, as well as for mental outcomes. Obesity outcomes appear as the fourth health consequence in population health more influenced by environmental determinants, followed by birth outcomes. Within all the outcomes included in chronic diseases, HIV indicators were referred to be influenced only by socioeconomic indicators. Given that, the number of individuals newly infected with HIV has declined over the years but some groups remain at high risk , this caEvidence also showed that different measures to assess overall morbidity were used among the literature and in fact it may be a cofounding aspect that can generate divergences. To overcome this divergence, disability-adjusted life years (DALYs) or other health related quality of life metrics can be used to define and quantify the burden of disease, so as to measure the gap between current health status and an ideal situation free of disease and while combining mortality and morbidity indicators .The health of people living in cities is deeply determined by their living conditions. While there are considerable inequalities across regions, there are also inequalities within cities among various dimensions. The health challenges that need to be tackled to reduce population health inequities in urban environments are different from the ones found in rural environments in terms of, for example, air quality or access to health infrastructures, and must be analyzed differently . These gOur results from the framework Fig.  are consThis review has several strengths. As the main aim of this review is to report on associations, not to prove or refute causality, it presents an analysis of a wide and exhaustive range of influences between environmental determinants and health outcomes in urban settings. This urban settings focus enables an up to date identification of potential risks to population health. Although 25% of the reviewed studies were from Portuguese-speaking countries, the limitation to only select English and Portuguese written studies could have limited the evidence appraised in this review and to introduce a geographic location bias. Also, cities are spatially dynamic and can include suburban areas or slums contributing to the inherent complexity in mapping and in evaluating the quality of the heterogeneous data. Different populations, different methods and measures of evaluation, from the included studies and the variability of existing definitions of each determinant/dimension and outcome that were not standardized as might be expected may contribute to a misclassification bias. This heterogeneity should be considered when interpreting the high risk of bias of the reviewed studies. To minimize these issues, only peer review publications were included, and grey literature was excluded for the analysis.Our results provide a comprehensive synthesis of environment health determinants and indicators, outcomes and of associations between determinants and outcomes in urban settings, as well as identifies important gaps and methodological limitations in this field of research. Environmental health indices should be redesigned to reach consensus on definitions and measurements and to be meaningful to planners, policymakers, and researchers.Ultimately, this review helps to identify those aspects of a city that influences and contribute to improve population health and suggests a hierarchy of determinants where actions to improve them should be taken to promote population health in urban settings.Future work should look to improve flexible tools capable of evaluate modifications in environmental health determinants related to population health taking into account the dynamic of the urban setting to help target action areas, allocate resources and provide information to improve interventions and policies and to support decision making about health services and urban planning policies.Additional file 1.Additional file 2.