Age and sex differences in the association between neighborhood socioeconomic environment and incident diabetes: Results from the diabetes location, environmental attributes and disparities (LEAD) network.

Objective: Worse neighborhood socioeconomic environment (NSEE) may contribute to an increased risk of type 2 diabetes (T2D). We examined whether the relationship between NSEE and T2D differs by sex and age in three study populations. Research design and methods: We conducted a harmonized analysis using data from three independent longitudinal study samples in the US: 1) the Veteran Administration Diabetes Risk (VADR) cohort, 2) the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, and 3) a case-control study of Geisinger electronic health records in Pennsylvania. We measured NSEE with a z-score sum of six census tract indicators within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). Community type-stratified models evaluated the likelihood of new diagnoses of T2D in each study sample using restricted cubic splines and quartiles of NSEE. Results: Across study samples, worse NSEE was associated with higher risk of T2D. We observed significant effect modification by sex and age, though evidence of effect modification varied by site and community type. Largely, stronger associations between worse NSEE and diabetes risk were found among women relative to men and among those less than age 45 in the VADR cohort. Similar modification by age group results were observed in the Geisinger sample in small town/suburban communities only and similar modification by sex was observed in REGARDS in lower density urban communities. Conclusions: The impact of NSEE on T2D risk may differ for males and females and by age group within different community types.

Evaluating Natural Experiments that Impact the Diabetes Epidemic: an Introduction to the NEXT-D3 Network.

PURPOSE OF REVIEW: Diabetes is an ongoing public health issue in the USA, and, despite progress, recent reports suggest acute and chronic diabetes complications are increasing. RECENT FINDINGS: The Natural Experiments for Translation in Diabetes 3.0 (NEXT-D3) Network is a 5-year research collaboration involving six academic centers (Harvard University, Northwestern University, Oregon Health & Science University, Tulane University, University of California Los Angeles, and University of California San Francisco) and two funding agencies (Centers for Disease Control and Prevention and National Institutes of Health) to address the gaps leading to persisting diabetes burdens. The network builds on previously funded networks, expanding to include type 2 diabetes (T2D) prevention and an emphasis on health equity. NEXT-D3 researchers use rigorous natural experiment study designs to evaluate impacts of naturally occurring programs and policies, with a focus on diabetes-related outcomes. NEXT-D3 projects address whether and to what extent federal or state legislative policies and health plan innovations affect T2D risk and diabetes treatment and outcomes in the USA; real-world effects of increased access to health insurance under the Affordable Care Act; and the effectiveness of interventions that reduce barriers to medication access (e.g., decreased or eliminated cost sharing for cardiometabolic medications and new medications such as SGLT-2 inhibitors for Medicaid patients). Overarching goals include (1) expanding generalizable knowledge about policies and programs to manage or prevent T2D and educate decision-makers and organizations and (2) generating evidence to guide the development of health equity goals to reduce disparities in T2D-related risk factors, treatment, and complications.

Proximity to freshwater blue space and type 2 diabetes onset: the importance of historical and economic context.

Salutogenic effects of living near aquatic areas (blue space) remain underexplored, particularly in non-coastal and non-urban areas. We evaluated associations of residential proximity to inland freshwater blue space with new onset type 2 diabetes (T2D) in central and northeast Pennsylvania, USA, using medical records to conduct a nested case-control study. T2D cases (n=15,888) were identified from diabetes diagnoses, medication orders, and laboratory test results and frequency-matched on age, sex, and encounter year to diabetes-free controls (n=79,435). We calculated distance from individual residences to the nearest lake, river, tributary, or large stream, and residence within the 100-year floodplain. Logistic regression models adjusted for community socioeconomic deprivation and other confounding variables and stratified by community type (townships [rural/suburban], boroughs [small towns], city census tracts). Compared to individuals living ≥1.25 miles from blue space, those within 0.25 miles had 8% and 17% higher odds of T2D onset in townships and boroughs, respectively. Among city residents, T2D odds were 38-39% higher for those living 0.25 to <0.75 miles from blue space. Residing within the floodplain was associated with 16% and 14% higher T2D odds in townships and boroughs. A post-hoc analysis demonstrated patterns of lower residential property values with nearer distance to the region's predominant waterbody, suggesting unmeasured confounding by socioeconomic disadvantage. This may explain our unexpected findings of higher T2D odds with closer proximity to blue space. Our findings highlight the importance of historic and economic context and interrelated factors such as flood risk and lack of waterfront development in blue space research.

Consumption of Foods Derived from Subsidized Crops Remains Associated with Cardiometabolic Risk: An Update on the Evidence Using the National Health and Nutrition Examination Survey 2009-2014.

In this study, we examined the associations between the consumption of foods derived from crops subsidized under the 2008 United States (US) Farm Bill and cardiometabolic risk factors and whether the magnitude of these associations has changed since the 2002 US Farm Bill. Four federal databases were used to estimate daily consumption of the top seven subsidized commodities (corn, soybeans, wheat, rice, sorghum, dairy, and livestock) and to calculate a subsidy score (0-1 scale) for Americans' daily dietary intake during 2009-2014, with a higher score indicative of a higher proportion of the diet derived from subsidized commodities. The cardiometabolic risk factors included obesity, abdominal adiposity, hypertension, dyslipidemia, and dysglycemia. Linear and logistic regression models were adjusted for age, sex, race/ethnicity, the poverty-income ratio, the smoking status, educational attainment, physical activity, and daily calorie intake. During 2009-2014, adults with the highest subsidy score had higher probabilities of obesity, abdominal adiposity, and dysglycemia compared to the lowest subsidy score. After the 2002 Farm Bill (measured using data from 2001-2006), the subsidy score decreased from 56% to 50% and associations between consuming a highly-subsidized diet and dysglycemia did not change (p = 0.54), whereas associations with obesity (p = 0.004) and abdominal adiposity (p = 0.002) significantly attenuated by more than half. The proportion of calories derived from subsidized food commodities continues to be associated with adverse cardiometabolic risk factors, though the relationship with obesity and abdominal adiposity has weakened in recent years.

The Diabetes Location, Environmental Attributes, and Disparities Network: Protocol for Nested Case Control and Cohort Studies, Rationale, and Baseline Characteristics.

BACKGROUND: Diabetes prevalence and incidence vary by neighborhood socioeconomic environment (NSEE) and geographic region in the United States. Identifying modifiable community factors driving type 2 diabetes disparities is essential to inform policy interventions that reduce the risk of type 2 diabetes. OBJECTIVE: This paper aims to describe the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a group funded by the Centers for Disease Control and Prevention to apply harmonized epidemiologic approaches across unique and geographically expansive data to identify community factors that contribute to type 2 diabetes risk. METHODS: The Diabetes LEAD Network is a collaboration of 3 study sites and a data coordinating center (Drexel University). The Geisinger and Johns Hopkins University study population includes 578,485 individuals receiving primary care at Geisinger, a health system serving a population representative of 37 counties in Pennsylvania. The New York University School of Medicine study population is a baseline cohort of 6,082,146 veterans who do not have diabetes and are receiving primary care through Veterans Affairs from every US county. The University of Alabama at Birmingham study population includes 11,199 participants who did not have diabetes at baseline from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort study with oversampling of participants from the Stroke Belt region. RESULTS: The Network has established a shared set of aims: evaluate mediation of the association of the NSEE with type 2 diabetes onset, evaluate effect modification of the association of NSEE with type 2 diabetes onset, assess the differential item functioning of community measures by geographic region and community type, and evaluate the impact of the spatial scale used to measure community factors. The Network has developed standardized approaches for measurement. CONCLUSIONS: The Network will provide insight into the community factors driving geographical disparities in type 2 diabetes risk and disseminate findings to stakeholders, providing guidance on policies to ameliorate geographic disparities in type 2 diabetes in the United States. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/21377.

The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR): Unique 1.4 M patient Electronic Health Record cohort.

BACKGROUND: The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016. RESULTS: Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset. CONCLUSIONS: LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM. IMPLICATIONS: Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design. LEVEL OF EVIDENCE: While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.

Cost-effectiveness of Diabetes Prevention Interventions Targeting High-risk Individuals and Whole Populations: A Systematic Review.

OBJECTIVE: We conducted a systematic review of studies evaluating the cost-effectiveness (CE) of interventions to prevent type 2 diabetes (T2D) among high-risk individuals and whole populations. RESEARCH DESIGN AND METHODS: Interventions targeting high-risk individuals are those that identify people at high risk of developing T2D and then treat them with either lifestyle or metformin interventions. Population-based prevention strategies are those that focus on the whole population regardless of the level of risk, creating public health impact through policy implementation, campaigns, and other environmental strategies. We systematically searched seven electronic databases for studies published in English between 2008 and 2017. We grouped lifestyle interventions targeting high-risk individuals by delivery method and personnel type. We used the median incremental cost-effectiveness ratio (ICER), measured in cost per quality-adjusted life year (QALY) or cost saved to measure the CE of interventions. We used the $50,000/QALY threshold to determine whether an intervention was cost-effective or not. ICERs are reported in 2017 U.S. dollars. RESULTS: Our review included 39 studies: 28 on interventions targeting high-risk individuals and 11 targeting whole populations. Both lifestyle and metformin interventions in high-risk individuals were cost-effective from a health care system or a societal perspective, with median ICERs of $12,510/QALY and $17,089/QALY, respectively, compared with no intervention. Among lifestyle interventions, those that followed a Diabetes Prevention Program (DPP) curriculum had a median ICER of $6,212/QALY, while those that did not follow a DPP curriculum had a median ICER of $13,228/QALY. Compared with lifestyle interventions delivered one-on-one or by a health professional, those offered in a group setting or provided by a combination of health professionals and lay health workers had lower ICERs. Among population-based interventions, taxing sugar-sweetened beverages was cost-saving from both the health care system and governmental perspectives. Evaluations of other population-based interventions-including fruit and vegetable subsidies, community-based education programs, and modifications to the built environment-showed inconsistent results. CONCLUSIONS: Most of the T2D prevention interventions included in our review were found to be either cost-effective or cost-saving. Our findings may help decision makers set priorities and allocate resources for T2D prevention in real-world settings.

Cost-effectiveness of Interventions to Manage Diabetes: Has the Evidence Changed Since 2008?

OBJECTIVE: To synthesize updated evidence on the cost-effectiveness (CE) of interventions to manage diabetes, its complications, and comorbidities. RESEARCH DESIGN AND METHODS: We conducted a systematic literature review of studies from high-income countries evaluating the CE of diabetes management interventions recommended by the American Diabetes Association (ADA) and published in English between June 2008 and July 2017. We also incorporated studies from a previous CE review from the period 1985-2008. We classified the interventions based on their strength of evidence (strong, supportive, or uncertain) and levels of CE: cost-saving (more health benefit at a lower cost), very cost-effective (≤$25,000 per life year gained [LYG] or quality-adjusted life year [QALY]), cost-effective ($25,001-$50,000 per LYG or QALY), marginally cost-effective ($50,001-$100,000 per LYG or QALY), or not cost-effective (>$100,000 per LYG or QALY). Costs were measured in 2017 U.S. dollars. RESULTS: Seventy-three new studies met our inclusion criteria. These were combined with 49 studies from the previous review to yield 122 studies over the period 1985-2017. A large majority of the ADA-recommended interventions remain cost-effective. Specifically, we found strong evidence that the following ADA-recommended interventions are cost-saving or very cost-effective: In the cost-saving category are 1) ACE inhibitor (ACEI)/angiotensin receptor blocker (ARB) therapy for intensive hypertension management compared with standard hypertension management, 2) ACEI/ARB therapy to prevent chronic kidney disease and/or end-stage renal disease in people with albuminuria compared with no ACEI/ARB therapy, 3) comprehensive foot care and patient education to prevent and treat foot ulcers among those at moderate/high risk of developing foot ulcers, 4) telemedicine for diabetic retinopathy screening compared with office screening, and 5) bariatric surgery compared with no surgery for individuals with type 2 diabetes (T2D) and obesity (BMI ≥30 kg/m2). In the very cost-effective category are 1) intensive glycemic management (targeting A1C <7%) compared with conventional glycemic management (targeting an A1C level of 8-10%) for individuals with newly diagnosed T2D, 2) multicomponent interventions (involving behavior change/education and pharmacological therapy targeting hyperglycemia, hypertension, dyslipidemia, microalbuminuria, nephropathy/retinopathy, secondary prevention of cardiovascular disease with aspirin) compared with usual care, 3) statin therapy compared with no statin therapy for individuals with T2D and history of cardiovascular disease, 4) diabetes self-management education and support compared with usual care, 5) T2D screening every 3 years starting at age 45 years compared with no screening, 6) integrated, patient-centered care compared with usual care, 7) smoking cessation compared with no smoking cessation, 8) daily aspirin use as primary prevention for cardiovascular complications compared with usual care, 9) self-monitoring of blood glucose three times per day compared with once per day among those using insulin, 10) intensive glycemic management compared with conventional insulin therapy for T2D among adults aged ≥50 years, and 11) collaborative care for depression compared with usual care. CONCLUSIONS: Complementing professional treatment recommendations, our systematic review provides an updated understanding of the potential value of interventions to manage diabetes and its complications and can assist clinicians and payers in prioritizing interventions and health care resources.

Using natural experimental studies to guide public health action: turning the evidence-based medicine paradigm on its head.

Despite smaller effect sizes, interventions delivered at population level to prevent non-communicable diseases generally have greater reach, impact and equity than those delivered to high-risk groups. Nevertheless, how to shift population behaviour patterns in this way remains one of the greatest uncertainties for research and policy. Evidence about behaviour change interventions that are easier to evaluate tends to overshadow that for population-wide and system-wide approaches that generate and sustain healthier behaviours. Population health interventions are often implemented as natural experiments, which makes their evaluation more complex and unpredictable than a typical randomised controlled trial (RCT). We discuss the growing importance of evaluating natural experiments and their distinctive contribution to the evidence for public health policy. We contrast the established evidence-based practice pathway, in which RCTs generate 'definitive' evidence for particular interventions, with a practice-based evidence pathway in which evaluation can help adjust the compass bearing of existing policy. We propose that intervention studies should focus on reducing critical uncertainties, that non-randomised study designs should be embraced rather than tolerated and that a more nuanced approach to appraising the utility of diverse types of evidence is required. The complex evidence needed to guide public health action is not necessarily the same as that which is needed to provide an unbiased effect size estimate. The practice-based evidence pathway is neither inferior nor merely the best available when all else fails. It is often the only way to generate meaningful evidence to address critical questions about investing in population health interventions.

Advancing Measurement of Diabetes at the Population Level.

PURPOSE: The measurement and estimation of diabetes in populations guides resource allocation, health priorities, and can influence practice and future research. To provide a critical reflection on current diabetes surveillance, we provide in-depth discussion about how upstream determinants, prevalence, incidence, and downstream impacts of diabetes are measured in the USA, and the challenges in obtaining valid, accurate, and precise estimates. FINDINGS: Current estimates of the burden of diabetes risk are obtained through national surveys, health systems data, registries, and administrative data. Several methodological nuances influence accurate estimates of the population-level burden of diabetes, including biases in selection and response rates, representation of population subgroups, accuracy of reporting of diabetes status, variation in biochemical testing, and definitions of diabetes used by investigators. Technological innovations and analytical approaches (e.g., data linkage to outcomes data like the National Death Index) may help address some, but not all, of these concerns, and additional methodological advances and validation are still needed. Current surveillance efforts are imperfect, but measures consistently collected and analyzed over several decades enable useful comparisons over time. In addition, we proposed that focused subsampling, use of technology, data linkages, and innovative sensitivity analyses can substantially advance population-level estimation.

Clinical-Community Partnerships to Identify Patients With Food Insecurity and Address Food Needs.

INTRODUCTION: More than 42 million people in the United States are food insecure. Although some health care entities are addressing food insecurity among patients because of associations with disease risk and management, little is known about the components of these initiatives. METHODS: The Systematic Screening and Assessment Method was used to conduct a landscape assessment of US health care entity-based programs that screen patients for food insecurity and connect them with food resources. A network of food insecurity researchers, experts, and practitioners identified 57 programs, 22 of which met the inclusion criteria of being health care entities that 1) screen patients for food insecurity, 2) link patients to food resources, and 3) target patients including adults aged 50 years or older (a focus of this assessment). Data on key features of each program were abstracted from documentation and telephone interviews. RESULTS: Most programs (n = 13) focus on patients with chronic disease, and most (n = 12) partner with food banks. Common interventions include referrals to or a list of food resources (n = 19), case managers who navigate patients to resources (n = 15), assistance with federal benefit applications (n = 14), patient education and skill building (n = 13), and distribution of fruit and vegetable vouchers redeemable at farmers markets (n = 8). Most programs (n = 14) routinely screen all patients. CONCLUSION: The programs reviewed use various strategies to screen patients, including older adults, for food insecurity and to connect them to food resources. Research is needed on program effectiveness in improving patient outcomes. Such evidence can be used to inform the investments of potential stakeholders, including health care entities, community organizations, and insurers.

The contribution of subsidized food commodities to total energy intake among US adults.

OBJECTIVE: The contribution of subsidized food commodities to total food consumption is unknown. We estimated the proportion of individual energy intake from food commodities receiving the largest subsidies from 1995 to 2010 (corn, soyabeans, wheat, rice, sorghum, dairy and livestock). DESIGN: Integrating information from three federal databases (MyPyramid Equivalents, Food Intakes Converted to Retail Commodities, and What We Eat in America) with data from the 2001-2006 National Health and Nutrition Examination Surveys, we computed a Subsidy Score representing the percentage of total energy intake from subsidized commodities. We examined the score's distribution and the probability of having a 'high' (≥70th percentile) v. 'low' (≤30th percentile) score, across the population and subgroups, using multivariate logistic regression. SETTING: Community-dwelling adults in the USA. SUBJECTS: Participants (n 11 811) aged 18-64 years. RESULTS: Median Subsidy Score was 56·7 % (interquartile range 47·2-65·4 %). Younger, less educated, poorer, and Mexican Americans had higher scores. After controlling for covariates, age, education and income remained independently associated with the score: compared with individuals aged 55-64 years, individuals aged 18-24 years had a 50 % higher probability of having a high score (P<0·0001). Individuals reporting less than high-school education had 21 % higher probability of having a high score than individuals reporting college completion or higher (P=0·003); individuals in the lowest tertile of income had an 11 % higher probability of having a high score compared with individuals in the highest tertile (P=0·02). CONCLUSIONS: Over 50 % of energy in US diets is derived from federally subsidized commodities.

Non-communicable diseases in South Asia: contemporary perspectives.

INTRODUCTION: Non-communicable diseases (NCDs) such as metabolic, cardiovascular, cancers, injuries and mental health disorders are increasingly contributing to the disease burden in South Asia, in light of demographic and epidemiologic transitions in the region. Home to one-quarter of the world's population, the region is also an important priority area for meeting global health targets. In this review, we describe the current burden of and trends in four common NCDs (cardiovascular disease, diabetes, cancer and chronic obstructive pulmonary disease) in South Asia. SOURCES OF DATA: The 2010 Global Burden of Disease Study supplemented with the peer-reviewed literature and reports by international agencies and national governments. AREAS OF AGREEMENT: The burden of NCDs in South Asia is rising at a rate that exceeds global increases in these conditions. Shifts in leading risk factors-particularly dietary habits, tobacco use and high blood pressure-are thought to underlie the mounting burden of death and disability due to NCDs. Improvements in life expectancy, increasing socioeconomic development and urbanization in South Asia are expected to lead to further escalation of NCDs. AREAS OF CONTROVERSY: Although NCD burdens are currently largest among affluent groups in South Asia, many adverse risk factors are concentrated among the poor, portending a future increase in disease burden among lower income individuals. GROWING POINTS: There continues to be a notable lack of national surveillance data to document the distribution and trends in NCDs in the region. Similarly, economic studies and policy initiatives addressing NCD burdens are still in their infancy. AREAS TIMELY FOR DEVELOPING RESEARCH: Opportunities for innovative structural and behavioral interventions that promote maintenance of healthy lifestyles-such as moderate caloric intake, adequate physical activity and avoidance of tobacco-in the context of socioeconomic development are abundant. Testing of health care infrastructure and systems that best provide low-cost and effective detection and treatment of NCDs is a priority for policy researchers.

Do we produce enough fruits and vegetables to meet global health need?

BACKGROUND: Low fruit and vegetable (FV) intake is a leading risk factor for chronic disease globally, but much of the world's population does not consume the recommended servings of FV daily. It remains unknown whether global supply of FV is sufficient to meet current and growing population needs. We sought to determine whether supply of FV is sufficient to meet current and growing population needs, globally and in individual countries. METHODS AND FINDINGS: We used global data on agricultural production and population size to compare supply of FV in 2009 with population need, globally and in individual countries. We found that the global supply of FV falls, on average, 22% short of population need according to nutrition recommendations (supply:need ratio: 0.78 [Range: 0.05-2.01]). This ratio varies widely by country income level, with a median supply:need ratio of 0.42 and 1.02 in low-income and high-income countries, respectively. A sensitivity analysis accounting for need-side food wastage showed similar insufficiency, to a slightly greater extent (global supply:need ratio: 0.66, varying from 0.37 [low-income countries] to 0.77 [high-income countries]). Using agricultural production and population projections, we also estimated supply and need for FV for 2025 and 2050. Assuming medium fertility and projected growth in agricultural production, the global supply:need ratio for FV increases slightly to 0.81 by 2025 and to 0.88 by 2050, with similar patterns seen across country income levels. In a sensitivity analysis assuming no change from current levels of FV production, the global supply:need ratio for FV decreases to 0.66 by 2025 and to 0.57 by 2050. CONCLUSION: The global nutrition and agricultural communities need to find innovative ways to increase FV production and consumption to meet population health needs, particularly in low-income countries.

Open access: academic publishing and its implications for knowledge equity in Kenya.

Traditional, subscription-based scientific publishing has its limitations: often, articles are inaccessible to the majority of researchers in low- and middle-income countries (LMICs), where journal subscriptions or one-time access fees are cost-prohibitive. Open access (OA) publishing, in which journals provide online access to articles free of charge, breaks this barrier and allows unrestricted access to scientific and scholarly information to researchers all over the globe. At the same time, one major limitation to OA is a high publishing cost that is placed on authors. Following recent developments to OA publishing policies in the UK and even LMICs, this article highlights the current status and future challenges of OA in Africa. We place particular emphasis on Kenya, where multidisciplinary efforts to improve access have been established. We note that these efforts in Kenya can be further strengthened and potentially replicated in other African countries, with the goal of elevating the visibility of African research and improving access for African researchers to global research, and, ultimately, bring social and economic benefits to the region. We (1) offer recommendations for overcoming the challenges of implementing OA in Africa and (2) call for urgent action by African governments to follow the suit of high-income countries like the UK and Australia, mandating OA for publicly-funded research in their region and supporting future research into how OA might bring social and economic benefits to Africa.

Role of students in global health delivery.

What role do students have in global health activities? On one hand, students have much to offer, including innovative ideas, fresh knowledge and perspective, and inspiring energy. At the same time, students lack technical credentials and may drain resources from host communities. Here, we examine the dynamic, contemporary roles of students in global health activities, including health delivery. We focus on 3 themes that guide engagement: (1) fostering an enabling policy environment (eg, toward greater health equity); (2) understanding and working within the local context and governments' needs; and (3) leading bidirectional partnerships. We next study the implications of short-term exposure and long-term engagement programs. We conclude with 4 recommendations on how to better equip students to engage in the next frontier of global health education and future action.

Misalignment between perceptions and actual global burden of disease: evidence from the US population.

Significant funding of health programs in low-income countries comes from external sources, mainly private donors and national development agencies of high-income countries. How these external funds are allocated remains a subject of ongoing debate, as studies have revealed that external funding may misalign with the underlying disease burden. One determinant of the priorities set by both private donors and development agencies is the perceptions of populations living in high-income countries about which diseases are legitimate for global health intervention. While research has been conducted on the priorities expressed by recipient communities, relatively less has been done to assess those of the donating country. To investigate people's beliefs about the disease burden in high-income countries, we compared publicly available data from U.S. surveys of people's perceptions of the leading causes of death in developing countries against measures of the actual disease burden from the World Health Organization. We found little correlation between the U.S. public's perception and the actual disease burden, measured as either mortality or disability-adjusted life years. While there is potential for reverse causality, so that donor programs drive public perceptions, these findings suggest that increasing the general population's awareness of the true global disease burden could help better align global health funding with population health needs.

Finding a policy solution to India's diabetes epidemic.

In India, thirty-five million people have diabetes-a number expected to more than double by 2025, disproportionately affecting working-age people. The economic impact of this increase could be devastating to India's emerging economy. In this paper we discuss drivers of the epidemic, analyze current policies and practices in India, and conclude with recommendations, focusing on multisectoral and international collaboration. We see these recommendations as providing a blueprint for addressing diabetes in India by illuminating opportunities and barriers for policymakers and others.

Brief assessment of motor function: reliability and concurrent validity of the Gross Motor Scale.

OBJECTIVE: The Brief Assessment of Motor Function (BAMF) is a series of 10-point ordinal scales developed for rapid description of gross motor, fine motor, and oral motor performance. We examined interrater and intrarater reliability and concurrent validity of the BAMF Gross Motor Scale. DESIGN: This validation study included 48 children (age, 5 mo to 17 yr) with a wide range of gross motor capability. Ten children with varied diagnoses participated in the reliability study. For concurrent validity, the BAMF performance of 38 children with osteogenesis imperfecta was compared with scores on the Peabody Developmental Motor Scales, laboratory gait analysis, and manual muscle testing. RESULTS: Reliability values for intraclass correlations were 0.996 (interrater) and 1.00 (intrarater). Significant relationships were identified between the BAMF and gait speed ( r = 0.68, P < 0.0001), stride length (r = 0.71, P < 0.0001), duration of double-limb support ( r = -0.40, P < 0.03), number of weak muscles (r = -0.74, P< 0.0001), and the Peabody Developmental Motor Scales (r = 0.95, P < 0.0001). Number of weak muscles was the strongest predictor of BAMF score R2 = 0.5080, F = 24.77, P < 0.0001). CONCLUSIONS: The BAMF demonstrates good reliability for children with a range of diagnoses and acceptable concurrent validity with gross motor development, muscle strength, and formal gait assessment in children with osteogenesis imperfecta.