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Anemia in children remains a public health concern in developing countries. In Cambodia, the prevalence of anemia among children decreased slightly from 55.2% in 2014 to 49% in 2019. We examined descriptively temporal and geospatial trends of anemia and used logistic regression to analyze potential associations between individual and household characteristics and anemia among children aged 6-59 months using data from the Cambodia Demographic and Health Survey (CDHS) for 2005, 2010, and 2014. Survey weights were applied to account for the complex survey design of the CDHS. We used logistic regression to assess factors associated with anemia among children aged 6-59 months. The prevalence of anemia among children decreased from 62.2% in 2005 to 56.6% in 2014. The proportion of the Cambodian child population with anemia was highest in Pursat (84.3%) for 2005, Kampong Thom (67%) for 2010, and Preah Vihear and Steung Treng (68.6%) for 2014, respectively. Factors independently associated with increased odds of having anemia included children with mothers who were anemic (adjusted odds ratio (AOR) =1.77, 95% CI: 1.58 - 1.97); children who were male (AOR=1.20, 95% CI: 1.07 - 1.33), underweight (AOR=1.24, 95% CI: 1.14 - 1.57), stunted (AOR=1.24, 95% CI: 1.09 - 1.41), or had a recent episode of fever (AOR=1.16, 95% CI: 1.03 - 1.31). Children had decreased odds of having anemia if they were aged 12-23 months (AOR=0.68; 95% CI: 0.55 -0.86), 24-35 months (AOR=0.21; 95% CI: 0.17 - 0.26), 36-47 months (AOR=0.17; 95% CI: 0.13 - 0.21) or aged 48-59 months (AOR=0.15; 95% CI: 0.12 - 0.19) compared to infants; they were also less likely to have anemia if they were from a wealthier household (AOR=0.64; 95% CI: 0.50 - 0.84), and children who took drugs for the intestinal parasite were decreased by 14% (AOR = 0.86; 95% CI: 0.89-0.93) than those who did not take drugs. Anemia remains highly prevalent among children aged 6-59 months in Cambodia. Public health interventions and policies to alleviate anemia should be prioritized to address these factors.

COVID-19 is associated with one of the largest disturbances to life in the 21st century. To quell disease spread, governments implemented lockdowns that likely created hardships for house-holds. To improve knowledge of consequences, we examine how the pandemic period was associ-ated with household hardships and assess factors associated with these hardships. We conducted a cross-sectional study using quasi-Poisson regression to examine factors associated with house-hold hardships. Data were collected between August and September of 2021 from a random sam-ple of 880 households living in a Health and Demographic Surveillance System (HDSS) located in the Harari Region and the District of Kersa, both in Ethiopia. Having a head of household with no education, residing in a rural area, larger household size, lower income and/or wealth, and community responses to COVID-19 including lockdowns and travel restrictions were inde-pendently associated with experiencing household hardships. Our results identify characteristics of groups at-risk for food insecurity during the pan-demic; households that were already strug-gling prior to the onset of the pandemic were at greatest risk of adverse consequences during the pandemic period. These findings may inform future efforts to mitigate the consequences of COVID-19 and future disease out-breaks.

Anemia is a major public health problem for thirty-two million pregnant women worldwide. Anemia during pregnancy is a leading cause of child low birth weight, preterm birth, and perinatal/neonatal mortality. Pregnant women are at higher risk of anemia due to micronutrient deficiencies, hemoglobinopathies, infections, socio-demographic and behavioral factors. This study aimed to: 1) assess temporal and geospatial trends of anemia in Cambodia and 2) identify factors associated with anemia among pregnant women aged 15-49 years old in Cambodia. We analyzed data from the Cambodia Demographic and Health Survey (CDHS) for 2005, 2010, and 2014. Data were pooled across the three survey years for all pregnant women aged 15-49 years. Survey weights were applied to account for the complex survey design of the CDHS. Descriptive statistics were estimated for key sociodemographic characteristics of the study population. We used logistic regressions to assess factors associated with anemia among pregnant women aged 15-49 years old. Anemia in pregnant women aged 15-49 in Cambodia decreased from 56% in 2005 to 53% in 2014. With the highest in Preah Vihear and Stung Treng provinces (74.3%), in Kratie province (73%), and in Prey Veng (65.4%) in 2005, 2010, and 2014 respectively. Compared to pregnant women from the wealthiest households, women from poorest households were more likely to have anemia (AOR = 2.8; 95% CI: 1.76-4.9). Pregnant women from coastal regions were almost twice as likely of having anemia (AOR = 1.9; 95% CI: 1.2-3.0). Pregnant women were more likely anemic if they were in their 2nd trimester (AOR = 2.6; 95% CI: 1.9-3.6) or 3rd trimester (AOR = 1.6 95% CI: 1.2-2.3). Anemia remains highly prevalent among pregnant women in Cambodia. Public health interventions and policies to alleviate anemia should be prioritized and shaped to address these factors.

The ``Community Recovery after a Natural Disaster: A Survey of Communities Affected by Mt. Merapi Eruptions'' data that are described herein were gathered 16 months after the 2010 Mt. Merapi volcanic eruptions in Central Java, Indonesia. Data collection was organized as a pilot effort to document victim experiences of the disaster; including disaster preparation, mitigation, and recovery. Three-stage clustered random sampling was conducted to create a sample that was representative of varying levels of destruction experienced by victims of the eruptions as well as one that included respondents who were still living in a disaster shelter, who had returned to their previous community, and who had moved on to a new community. By drawing respondents from 10 different villages or shelter communities, a total respondent sample of 400 was collected.

Over the past 20 years, many of the low and middle-income countries (LMICs) of South and Southeast Asia have experienced dramatic increases in the number and availability of inexpensive motorcycles. Juxtapose this trend, unequal access to health care remains a significant concern, as people continue to die from treatable conditions. With calls to improve geographic accessibility, ongoing research continues to examine interventions (e.g., mHealth) that may help geographically isolated individuals access health care that is often located in more urbanized regions of LMICs. In this study, I examine motorcycles as a heretofore under recognized mode of transportation in LMICs that may function as a distance demolishing determinant of health care access. Results suggest that motorcycles substantially reduce the rural penalty in which both geographic distance and household finances are perceived as a major problems for accessing health care in these regions.

Geographic isolation and spatial inequality are growing issues for most countries. However, distance-demolishing technologies have been proposed as a solution of overcoming geographic barriers associated with geographic penalties. This research uses the rapid and widespread adoption of inexpensive motorcycles in Vietnam as a case study of how distance-demolishing technologies can improve household well-being. Utilising panel data from the 2004, 2006 and 2008 Vietnamese Household Living Standard Surveys, this research uses propensity score matching to isolate the effect that the introduction of a motorcycle has on household income. Our results show that new motorcycle ownership reduces spatial isolation penalties and significantly improves household well-being in Vietnam. In addition, marginalised populations, such as female-headed households and rural households, receive relatively larger returns from a new motorcycle. Our findings suggest that distance-demolishing technologies can contribute to the reduction of spatial inequality by helping households overcome both geographic and social barriers.

Migration is a standard survival strategy in the context of disasters. While prior studies have examined factors associated with return migration following disasters, an area that remains relatively underexplored is whether moving home to one&rsquo, s original community results in improved health and well-being compared to other options such as deciding to move on. In the present study, our objective is to explore whether return migration, compared to other migration options, results in superior improvements to mental health. We draw upon data from a cross-sectional pilot study conducted 16 months after a series of volcanic eruptions in Merapi, Indonesia. Using ordinal logistic regression, we find that compared to respondents who were still displaced (reference category), respondents who had &ldquo, moved home&rdquo, were proportionally more likely to report good mental health (proportional odds ratios (POR) = 2.02 [95% CI = 1.05, 3.91]) compared to average or poor mental health. Likewise, respondents who had &ldquo, moved on&rdquo, were proportionally more likely to report good mental health (POR = 2.64 [95% CI = 0.96, 7.77]. The results suggest that while moving home was an improvement from being displaced, it may have been better to move on, as this yielded superior associations with self-reported mental health.

Disasters are associated strongly with forced migration. Indeed, migration is a standard survival strategy for those facing disruptions of this kind. Such is the case with Mt. Merapi, Indonesia, where a series of eruptions occurred in 2010. Mechanisms related to forced migration in such scenarios are fairly well understood, yet it remains less clear what factors may influence return migration. Given local interest in facilitating resettlement out of hazardous areas as a means of risk reduction, our objective in this study is to explore the extent to which recovery aid may create incentives for households to move on rather than move home. Specifically, we explore whether the influence of recovery aid varied by whether it was: financial vs. another type of aid; provided by a government agency or NGO versus a social network; and/or distributed with other types of recovery aid. We use data from a cross-sectional pilot study and multinomial logistic regression models to explore the influence of aid on migration status. Of the various forms of aid considered, financial recovery aid was consistently associated with moving on. The combination of financial recovery aid with remittances resulted in an association with having moved on that was even stronger than just receiving financial recovery aid. Ultimately, analyses of “aid packages” suggest that a combination of aid was relatively more effective in fostering resettlement, suggesting that while other forms of aid may not have been sufficient to increase resettlement by themselves, they may enhance the effect of financial recovery aid.

To what extent does community experience differ between low–context and high–context societies? Prior literature theorizes that community experience consists of two separate, yet highly related concepts: community attachment, an individual's general rootedness to a place, and community satisfaction, how well an individual's community meets their societal needs. We test this conceptualization of community experience across communities in the United States and two Southeast Asian nations: Thailand and Vietnam. We argue that Southeast Asian nations constitute “high–context” societies with relatively high social integration and solidarity while the United States is more individualized and less socially integrated and thus constitutes a “low–context” society. Our results provide empirical evidence that individuals’ experience of community varies between low– and high–context societies. These results demonstrate that cultural context continues to matter in regards to the lived experience of community and researchers need to remain vigilant in accounting for such differences as they seek to examine the concept of community more broadly.

IN 2014, SCIENCE AND SCIENCE TRANSLATIONAL MEDICINE JOINED FORCES TO PRODUCE an important special issue on global health, which suggested that existing tools can deliver big payoffs ([ 1 ][1]). The special issue assessed plateauing budgets for global health; the effectiveness of large-scale global health projects; evidence for reduction in global mortality and gender inequities; the scope and trends of the global burden of disease; delivery and coverage of essential global health products; models for integrating research, capacity building, and service with global health education in medicine, public health, and engineering; the growing role of mobile health (mHealth) for universal health coverage; responses to global health crises; emerging and evolving infectious diseases; and a proposed global map of health research and development. To assess how well global health partnerships for research and education are working, we subsequently undertook a survey of all North American university members of the Consortium of Universities for Global Health (CUGH) and a concurrent survey of their international partner institutions in lower- and middle-income countries. Survey participation rates were high, including 82 North American universities (81% of all 2015 CUGH members) and 47 international partner institutions, (77% of the partner institutions with contact information identified by North American universities). Sample interviews of participants from the North American and international institutions helped to define key themes and contributed to a framework for future global health research and education partnerships. The survey results, published 1 April 2016, are available here ([ 2 ][2]). Some of the key cross-cutting findings are listed below. (i) The most common types of partnerships include collaborative research (reported by 94% of North American and 80% of international institutions) followed by various types of educational programs (especially for North American students) and health systems development (for 69% of international institutions). (ii) High levels of perceived equity and mutual benefits by North American and international institutions. (iii) The strongest perceived partnership benefits were from research collaborations and student knowledge acquisition. (iv) The most important source of funding for North American institutions was the university itself, followed by the U.S. National Institutes of Health (NIH) other federal funds [including the President’s Emergency Plan for AIDS Relief (PEPFAR)], and then foundations and private donors. International partners also depended not only on funding from the North American universities, but equally on foundations, international nongovernmental organizations (NGOs), United Nations agencies, international research agencies, and other donors. (v) Factors other than funding that correlated with perceived benefits from partnerships for North American universities included being part of larger institutional partnerships, and for international institutions, correlated with the level of North American universities’ student preparation. (vi) The following areas indicated correctible problems in the collaborations: 20% of North American universities and international institutions reported poor or only fair collaboration in establishing mutual goals; more than 30% of North American universities and international institutions reported poor or only fair collaboration in monitoring and evaluation; and 34% of North American universities and more than 40% of international institutions reported only fair or poor feedback and communication with their partners. A 10-step framework for success of global health programs was developed from the surveys, interviews, and literature review. These steps included identifying champions and a core team; developing a strategic plan; obtaining institutional support and baseline funding; developing future leaders; guiding student enthusiasm and expectations; monitoring and evaluation; systematic communication; and building cross-university interdisciplinary networks. The survey findings document the perceived importance of several collaborative activities—in particular, investments from the North American universities, which are particularly important in the success of global health partnerships—and also identify collaborative activities in need of improvement. The most common collaborations included research as well as education and training, and the findings indicate the potential synergies between global health research and training programs. 1. [↵][3]1. B. Jasny, 2. L. Roberts, 3. M. Enserink, 4. O. Smith , What works. Science 345, 1256–1257 (2014). [OpenUrl][4][Abstract/FREE Full Text][5] 2. [↵][6]J. A. Muir, J. Farley, A. Osterman, S. E. Hawes, K. Martin, J. S. Morrison, K. K. Holmes, Global health programs and partnerships: Evidence of mutual benefit and equity. A Report of the CSIS Global Health Policy Center, Rowman & Littlefield, April 2016. [1]: #ref-1 [2]: #ref-2 [3]: #xref-ref-1-1 "View reference 1 in text" [4]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DJasny%26rft.auinit1%253DB.%26rft.volume%253D345%26rft.issue%253D6202%26rft.spage%253D1256%26rft.epage%253D1257%26rft.atitle%253DWhat%2Bworks%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.345.6202.1256%26rft_id%253Dinfo%253Apmid%252F25214599%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [5]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjEzOiIzNDUvNjIwMi8xMjU2IjtzOjQ6ImF0b20iO3M6MzA6Ii9zY2l0cmFuc21lZC84LzMzNC8zMzRlZDQuYXRvbSI7fXM6ODoiZnJhZ21lbnQiO3M6MDoiIjt9 [6]: #xref-ref-2-1 "View reference 2 in text"

Studies of resource selection form the basis for much of our understanding of wildlife habitat requirements, and resource selection functions (RSFs), which predict relative probability of use, have been proposed as a unifying concept for analysis and interpretation of wildlife habitat data. Logistic regression that contrasts used and available or unused resource units is one of the most common analyses for developing RSFs. Recently, resource utilization functions (RUFs) have been developed, which also predict probability of use. Unlike RSFs, however, RUFs are based on a continuous metric of space use summarized by a utilization distribution. Although both RSFs and RUFs predict space use, a direct comparison of these 2 modeling approaches is lacking. We compared performance of RSFs and RUFs by applying both approaches to location data for 75 Rocky Mountain elk (Cervus elaphus) and 39 mule deer (Odocoileus hemionus) collected at the Starkey Experimental Forest and Range in northeastern Oregon, USA. We evaluated differences in maps of predicted probability of use, relative ranking of habitat variables, and predictive power between the 2 models. For elk, 3 habitat variables were statistically significant (P < 0.05) in the RSF, whereas 7 variables were significant in the RUF. Maps of predicted probability of use differed substantially between the 2 models for elk, as did the relative ranking of habitat variables. For mule deer, 4 variables were significant in the RSF, whereas 6 were significant in the RUF, and maps of predicted probability of use were similar between models. In addition, distance to water was the top-ranked variable in both models for mule deer. Although space use by both species was predicted most accurately by the RSF based on cross-validation, differences in predictive power between models were more substantial for elk than mule deer. To maximize accuracy and utility of predictive wildlife-habitat models, managers must be aware of the relative strengths and weaknesses of different modeling techniques. We conclude that although RUFs represent a substantial advance in resource selection theory, techniques available for generating RUFs remain underdeveloped and, as a result, RUFs sometimes predict less accurately than models derived using more conventional techniques.