Key considerations for the future of mental health epidemiology.

Psychiatric epidemiology has led to substantial progress in our understanding of the causes of mental health disorders. The increasing sophistication of etiologic psychiatric research has been accompanied by a greater focus on the biological and genetic causes of psychiatric disorders, to some extent diverging from field's early focus on the burden of poor mental health due to a breadth of social and economic conditions. We argue that the moment is ripe for advancing a mental health epidemiology that can reconnect the field to these earlier-and still central-concerns, while retaining the strengths of psychiatric epidemiology. Embracing five considerations can help advance the evolving field of mental health epidemiology. First, conceptually, an ambitious vision for the future of the field necessitates investment in refining our definitions and methodologies. Second, there is a need for a renewed focus on the macrosocial determinants of mental health. Third, a deeper engagement with mental health inequities should be central to our scholarship. Fourth, the field would benefit from a more deliberate assessment of the mechanisms leading to adverse mental health outcomes, which can then be used to inform novel interventions. Finally, realizing this future is contingent upon a wholesale commitment to studying population mental health globally.

Pandemic stressors and mental health indicators in eight countries.

PURPOSE: The Covid-19 pandemic has exacted a significant physical, financial, social, and emotional toll on populations throughout the world. This study aimed to document the association between pandemic stressors and mental health during the pandemic across countries that differ in cultural, geographic, economic, and demographic factors. METHODS: We administered an online survey randomly in Brazil, China, Germany, Egypt, India, Indonesia, Nigeria, and the United States from September 2020 to November 2020. This survey included questions on Covid-19-related stressors as well as the Patient Health Questionnaire-2 and the Primary Care PTSD Checklist to screen for depression and post-traumatic stress disorder (PTSD) symptoms, respectively. We performed bivariable and multivariable regression analyses to assess the prevalence and odds ratios of overall depression symptoms and probable PTSD and in relation to stressors across countries. RESULTS: Among 8754 respondents, 28.9% (95% CI 27.5-30.0%) experienced depression symptoms, and 5.1% (95% CI 4.5-6.0%) experienced probable PTSD. The highest prevalence of depression symptoms was in Egypt (41.3%, 95% CI 37.6-45.0%) and lowest in the United States (24.9%, 95% CI 22.3-27.7%). The highest prevalence of probable PTSD was in Brazil (7.3%, 95% CI 5.6-9.4%) and the lowest in China (1.2%, 95% CI 0.7-2.0%). Overall, experiencing six or more Covid-19-related stressors was associated with both depression symptoms (OR 1.90, 95% CI 1.46-2.48) and probable PTSD (OR 13.8, 95% CI 9.66-19.6). CONCLUSION: The association between pandemic related stressors and the burden of adverse mental health indicators early in the Covid-19 pandemic transcended geographic, economic, cultural, and demographic differences between countries. The short-term and long-term impacts of the pandemic on mental health should be incorporated in efforts to tackle the consequences of Covid-19.

Assets and depression in U.S. adults during the COVID-19 pandemic: a systematic review.

PURPOSE: Mental health is shaped by social and economic contexts, which were altered during the COVID-19 pandemic. No study has systematically reviewed the literature on the relation between different assets and depression during the COVID-19 pandemic. METHODS: We conducted a systematic review of the literature on financial (e.g. income/savings), physical (e.g., home ownership), and social (e.g., marital status, educational attainment) assets and depression in U.S. adults. For each asset type, we created binary comparisons to report on the direction of the relationship and described if each study reported insignificant, positive, negative, or mixed associations. RESULTS: Among the 41 articles identified, we found that income was the most studied asset (n=34), followed by education (n=25), marital status (n=18), home ownership (n=5), and savings (n=4). 88%, 100%, and 100% of articles reported a significant association of higher income, home ownership, and higher savings, respectively, with less depression. The association between marital status and education with depression was more nuanced: 72% (13 of 18) studies showed that unmarried persons had greater risk of depression than married or cohabitating persons and 52% (13 of 25) of studies reported no significant difference in depression across educational groups. CONCLUSION: This work adds to the literature a deeper understanding of how different assets relate to depression. In the context of largescale traumatic events, policies that maintain and protect access to social, physical, and financial assets may help to protect mental health.

Symptoms of Posttraumatic Stress During the COVID-19 Pandemic in the Governmental Public Health Workforce and General Population.

We aimed to estimate the prevalence of COVID-19-related posttraumatic stress symptoms (PTSS) in the governmental public health workforce and in US adults, assess differences in reporting PTSS within subgroups, and evaluate whether frontline workers reported higher levels of PTSS than persons in other jobs. We used data from 2 nationally representative studies: the 2021 Public Health Workforce Interests and Needs Survey (PH WINS) and the COVID-19 and Life Stressors Impact on Mental Health and Well-being (CLIMB) study. Our study found that the state and local governmental public health workforce was more likely to report PTSS than the general adult population. Almost a quarter of public health agency employees (24.7%) and 21.1% of adults reported at least 3 symptoms of posttraumatic stress. Differences in levels of PTSS appeared within demographic groups for both samples. Personal care and service frontline workers had 4.3 times the odds of reporting symptoms of posttraumatic stress than non-frontline workers.

Depression and PTSD among Houston Residents who Experienced Hurricane Harvey and COVID-19: Implications for Urban Areas Affected by Multiple Disasters.

Little is known about the combined impact of the COVID-19 pandemic and other major disasters on mental health. Hurricane Harvey hit the Gulf Coast in 2017, resulting in substantial costs, significant levels of displacement, and approximately 100 deaths, and was followed in 2020 by the COVID-19 pandemic. We randomly sampled 1167 Houstonians from 88 designated super-neighborhoods and surveyed them about their demographics, event-specific traumas and stressors, and symptoms of current depression and post-traumatic stress disorder (PTSD). We estimated the prevalence of depression (5.8%) and PTSD (12.6%) more than three years after Hurricane Harvey, and assessed the relative influence of event-specific stressors and traumas on current mental health. Overall, we observed evidence for two key findings that are salient for residents of urban environments in the context of multiple disasters. First, stressors were primary influences on depression, whereas both stressors and traumas influenced PTSD. Second, the influences of stressors and traumas on depression and PTSD symptoms faded with time.

Invited Commentary: Toward a Better Understanding of Disparities in Overdose Mortality.

The United States has been in the grip of an epidemic of drug overdose mortality for the past few decades, and deaths from drug overdose increased dramatically during the coronavirus disease 2019 pandemic. Townsend et al. (Am J Epidemiol. 2022;191(4):599-612) add to the growing literature highlighting the steep rise of drug overdose mortality among racial and ethnic minorities in the country. Using data from National Center for Health Statistics death certificates and employing principles of small-area estimation and a Bayesian hierarchical model to stabilize the estimates of smaller racial/ethnic groups and states, the authors found that combinations of opioid/stimulant drug overdose deaths saw a steep increase among racial and ethnic minorities, particularly Black Americans, between 2007 and 2019. The results from their analysis highlight the need to change the narrative around opioid deaths, to invest in targeted policies that address the growing burden of drug overdose faced by racial/ethnic minorities, and the importance of using innovative methods to address limitations to data disaggregation. The paper also demonstrates the importance of a holistic view of the challenges to the health of the American public.

How an outbreak became a pandemic: a chronological analysis of crucial junctures and international obligations in the early months of the COVID-19 pandemic.

Understanding the spread of SARS-CoV-2, how and when evidence emerged, and the timing of local, national, regional, and global responses is essential to establish how an outbreak became a pandemic and to prepare for future health threats. With that aim, the Independent Panel for Pandemic Preparedness and Response has developed a chronology of events, actions, and recommendations, from December, 2019, when the first cases of COVID-19 were identified in China, to the end of March, 2020, by which time the outbreak had spread extensively worldwide and had been characterised as a pandemic. Datapoints are based on two literature reviews, WHO documents and correspondence, submissions to the Panel, and an expert verification process. The retrospective analysis of the chronology shows a dedicated initial response by WHO and some national governments, but also aspects of the response that could have been quicker, including outbreak notifications under the International Health Regulations (IHR), presumption and confirmation of human-to-human transmission of SARS-CoV-2, declaration of a Public Health Emergency of International Concern, and, most importantly, the public health response of many national governments. The chronology also shows that some countries, largely those with previous experience with similar outbreaks, reacted quickly, even ahead of WHO alerts, and were more successful in initially containing the virus. Mapping actions against IHR obligations, the chronology shows where efficiency and accountability could be improved at local, national, and international levels to more quickly alert and contain health threats in the future. In particular, these improvements include necessary reforms to international law and governance for pandemic preparedness and response, including the IHR and a potential framework convention on pandemic preparedness and response.

Food, Big Data, and Decision-making: a Scoping Review-the 3-D Commission.

Food is an important determinant of health, featuring prominently in the Sustainable Development Goals. The term "big data" is seldom used in relation to food, partly because food data are scattered across different sectors. The increasing availability of food-related data presents an opportunity to glean new insights on food and food systems. These insights may enhance the quality of products and services and improve decision-making on optimizing food availability, all to the end of producing better health. Yet, knowledge gaps remain about the unique opportunities and challenges linked to big data on food and their use in decision-making. This scoping review explored the available literature linking food with big data and decision-making, using the following research question: What is the current literature on data about food, and how are these data used in decision-making? We searched PubMed until 29 February 2020 and Embase, Web of Sciences, and the Cochrane Database of Systematic Reviews until 8 March 2020. We included studies written in English and conducted narrative analyses to identify relevant themes from included studies. Sixteen studies fulfilled our eligibility criteria, including big data analyses, modelling studies, and reviews. These studies described the added value of using big data and how evidence from big data had or can be used for decision-making, as well as challenges and opportunities for such use. The majority of the included studies examined the link between food and big data, while hypothesizing of how these insights could inform decision-making, including policies, interventions, programs, and financing. There were only two examples wherein big data on food informed decision-making directly. The review highlights several false dichotomies in how the subject is approached in the literature and the importance of context, both between and within countries, in shaping the availability and types of data that can be used as meaningful evidence to inform decision-making. This review shows the paucity of research around the intersection of food, big data, and decision-making, as well as the potential in using big data on food systems to the end of informing decisions to improve the health of populations. Future research and decision-making around health systems can benefit from examining the full spectrum of perspectives on the subject. Future research and decision-making around health systems can also employ the steadfast embrace of technology, which will potentially reduce disparities in big data availability, to the end of improving the health of populations.

Energy, Data, and Decision-Making: a Scoping Review-the 3D Commission.

Access to energy is an important social determinant of health, and expanding the availability of affordable, clean energy is one of the Sustainable Development Goals. It has been argued that climate mitigation policies can, if well-designed in response to contextual factors, also achieve environmental, economic, and social progress, but otherwise pose risks to economic inequity generally and health inequity specifically. Decisions around such policies are hampered by data gaps, particularly in low- and middle-income countries (LMICs) and among vulnerable populations in high-income countries (HICs). The rise of "big data" offers the potential to address some of these gaps. This scoping review sought to explore the literature linking energy, big data, health, and decision-making.Literature searches in PubMed, Embase, and Web of Science were conducted. English language articles up to April 1, 2020, were included. Pre-agreed study characteristics including geographic location, data collected, and study design were extracted and presented descriptively, and a qualitative thematic analysis was performed on the articles using NVivo.Thirty-nine articles fulfilled eligibility criteria. These included a combination of review articles and research articles using primary or secondary data sources. The articles described health and economic effects of a wide range of energy types and uses, and attempted to model effects of a range of technological and policy innovations, in a variety of geographic contexts. Key themes identified in our analysis included the link between energy consumption and economic development, the role of inequality in understanding and predicting harms and benefits associated with energy production and use, the lack of available data on LMICs in general, and on the local contexts within them in particular. Examples of using "big data," and areas in which the articles themselves described challenges with data limitations, were identified.The findings of this scoping review demonstrate the challenges decision-makers face in achieving energy efficiency gains and reducing emissions, while avoiding the exacerbation of existing inequities. Understanding how to maximize gains in energy efficiency and uptake of new technologies requires a deeper understanding of how work and life is shaped by socioeconomic inequalities between and within countries. This is particularly the case for LMICs and in local contexts where few data are currently available, and for whom existing evidence may not be directly applicable. Big data approaches may offer some value in tracking the uptake of new approaches, provide greater data granularity, and help compensate for evidence gaps in low resource settings.

Use of Data to Understand the Social Determinants of Depression in Two Middle-Income Countries: the 3-D Commission.

Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression.This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y).Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government's outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators.

Data, Social Determinants, and Better Decision-making for Health: the 3-D Commission.

More than a decade after the World Health Organization Commission on the Social Determinants of Health (SDoH), it is becoming widely accepted that social and economic factors, including but not limited to education, energy, income, race, ethnicity, and housing, are important drivers of health in populations. Despite this understanding, in most contexts, social determinants are not central to local, national, or global decision-making. Greater clarity in conceptualizing social determinants, and more specificity in measuring them, can move us forward towards better incorporating social determinants in decision-making for health. In this paper, first, we summarize the evolution of the social framing of health. Second, we describe how the social determinants are conceptualized and contextualized differently at the global, national, and local levels. With this, we seek to demonstrate the importance of analyzing and understanding SDoH relative to the contexts in which they are experienced. Third, we problematize the gap in data across contexts on different dimensions of social determinants and describe data that could be curated to better understand the influence of social determinants at the local and national levels. Fourth, we describe the necessity of using data to understand social determinants and inform decision-making to improve health. Our overall goal is to provide a path for our collective understanding of the foundational causes of health, facilitated by advances in data access and quality, and realized through improved decision-making.

Data Sources for Understanding the Social Determinants of Health: Examples from Two Middle-Income Countries: the 3-D Commission.

The expansion in the scope, scale, and sources of data on the wider social determinants of health (SDH) in the last decades could bridge gaps in information available for decision-making. However, challenges remain in making data widely available, accessible, and useful towards improving population health. While traditional, government-supported data sources and comparable data are most often used to characterize social determinants, there are still capacity and management constraints on data availability and use. Conversely, privately held data may not be shared. This study reviews and discusses the nature, sources, and uses of data on SDH, with illustrations from two middle-income countries: Kenya and the Philippines. The review highlights opportunities presented by new data sources, including the use of big data technologies, to capture data on social determinants that can be useful to inform population health. We conducted a search between October 2010 and September 2020 for grey and scientific publications on social determinants using a search strategy in PubMed and a manual snowball search. We assessed data sources and the data environment in both Kenya and the Philippines. We found limited evidence of the use of new sources of data to study the wider SDH, as most of the studies available used traditional sources. There was also no evidence of qualitative big data being used. Kenya has more publications using new data sources, except on the labor determinant, than the Philippines. The Philippines has a more consistent distribution of the use of new data sources across the HEALTHY determinants than Kenya, where there is greater variation of the number of publications across determinants. The results suggest that both countries use limited SDH data from new data sources. This limited use could be due to a number of factors including the absence of standardized indicators of SDH, inadequate trust and acceptability of data collection methods, and limited infrastructure to pool, analyze, and translate data.

Housing as a Social Determinant of Health: Evidence from Singapore, the UK, and Kenya: the 3-D Commission.

Housing is a paradigmatic example of a social determinant of health, as it influences and is influenced by structural determinants, such as social, macroeconomic, and public policies, politics, education, income, and ethnicity/race, all intersecting to shaping the health and well-being of populations. It can therefore be argued that housing policy is critically linked to health policy. However, the extent to which this linkage is understood and addressed in public policies is limited and highly diverse across and within countries. This analysis seeks to describe the linkages between housing policies and health and well-being using examples from three countries at different levels of the wealth spectrum: Singapore, the UK, and Kenya.We conducted a comparative policy analysis across three country contexts (Singapore, the UK, and Kenya) to document the extent to which housing policies address health and well-being, highlighting commonalities and differences among them. To guide our analysis, we used the United Nations (UN) definition of adequate housing as it offers a broad framework to analyze the impact of housing on health and well-being.The anatomy of housing policies has a strong correlation to the provision of adequate housing across Singapore, the UK, and Kenya, especially for vulnerable groups. The paper demonstrates that contextual factors including population composition (i.e., aging versus youthful), political ideologies, legal frameworks (i.e., welfare versus market-based provision of housing), and presence (or absence) of adequate, quality, timely, reliable, robust data systems for decision-making, which are taken up by stakeholders/state, have strong implications of the type of housing policies developed and implemented, in turn directly and indirectly impacting the overall health and well-being of populations.This analysis demonstrates the value of viewing housing policies as public health policies that could significantly impact the health and well-being of populations, especially vulnerable groups. Moreover, the findings highlight the importance of the Health in All Policies approach to facilitate integrated policy responses to address social determinants of health such as housing. This is more critical than ever, given the context of the global pandemic that has led to worsening overall health and well-being.

Integrating Social Determinants in Decision-Making Processes for Health: Insights from Conceptual Frameworks-the 3-D Commission.

The inclusion of social determinants of health offers a more comprehensive lens to fully appreciate and effectively address health. However, decision-makers across sectors still struggle to appropriately recognise and act upon these determinants, as illustrated by the ongoing COVID-19 pandemic. Consequently, improving the health of populations remains challenging. This paper seeks to draw insights from the literature to better understand decision-making processes affecting health and the potential to integrate data on social determinants. We summarised commonly cited conceptual approaches across all stages of the policy process, from agenda-setting to evaluation. Nine conceptual approaches were identified, including two frameworks, two models and five theories. From across the selected literature, it became clear that the context, the actors and the type of the health issue are critical variables in decision-making for health, a process that by nature is a dynamic and adaptable one. The majority of these conceptual approaches implicitly suggest a possible role for data on social determinants of health in decision-making. We suggest two main avenues to make the link more explicit: the use of data in giving health problems the appropriate visibility and credibility they require and the use of social determinants of health as a broader framing to more effectively attract the attention of a diverse group of decision-makers with the power to allocate resources. Social determinants of health present opportunities for decision-making, which can target modifiable factors influencing health-i.e. interventions to improve or reduce risks to population health. Future work is needed to build on this review and propose an improved, people-centred and evidence-informed decision-making tool that strongly and explicitly integrates data on social determinants of health.

Improving Decision-Making for Population Health in Nonhealth Sectors in Urban Environments: the Example of the Transportation Sector in Three Megacities-the 3-D Commission.

Noncommunicable diseases (NCDs) represent a significant global public health burden. As more countries experience both epidemiologic transition and increasing urbanization, it is clear that we need approaches to mitigate the growing burden of NCDs. Large and growing urban environments play an important role in shaping risk factors that influence NCDs, pointing to the ineluctable need to engage sectors beyond the health sector in these settings if we are to improve health. By way of one example, the transportation sector plays a critical role in building and sustaining health outcomes in urban environments in general and in megacities in particular. We conducted a qualitative comparative case study design. We compared Bus Rapid Transit (BRT) policies in 3 megacities-Lagos (Africa), Bogotá (South America), and Beijing (Asia). We examined the extent to which data on the social determinants of health, equity considerations, and multisectoral approaches were incorporated into local politics and the decision-making processes surrounding BRT. We found that all three megacities paid inadequate attention to health in their agenda-setting, despite having considerable healthy transportation policies in principle. BRT system policies have the opportunity to improve lifestyle choices for NCDs through a focus on safe, affordable, and effective forms of transportation. There are opportunities to improve decision-making for health by involving more available data for health, building on existing infrastructures, building stronger political leadership and commitments, and establishing formal frameworks to improve multisectoral collaborations within megacities. Future research will benefit from addressing the political and bureaucratic processes of using health data when designing public transportation services, the political and social obstacles involved, and the cross-national lessons that can be learned from other megacities.

Taking the Long View: COVID-19 Priorities for the Biden Administration.

The COVID-19 pandemic transformed the American political landscape, influencing the course of the 2020 election and creating an urgent policy priority for the new administration. The Biden-Harris plan for beating COVID-19 represents a practicable, technically competent plan to contain the pandemic, one that will serve the country well in the months ahead. The authors suggest that the United States would also benefit from an even bolder set of aspirations-reframing the national conversation on COVID-19, embedding equity in all health decision making, strengthening the social safety net, and changing how we talk about health-as part of the national response to COVID-19. This would represent a genuine step forward in the US approach to health, informed by the systemic flaws COVID-19 exposed, and would realize benefits from the pandemic moment that in turn would propel national health forward for the rest of the century.

Social determinants of health, data science, and decision-making: Forging a transdisciplinary synthesis.

Sandro Galea and co-authors discuss a forthcoming Collection on data science and social determinants of health.

Claiming Health as a Public Good in the Post-COVID-19 Era.

The global response to COVID-19 has been uneven and disappointing in the vast majority of countries. The United States has borne the largest absolute burden of disease globally, as COVID-19 exploited pre-existing poor population health among Americans to spread rapidly, with devastating consequences. Why does the country that spends the most on healthcare in the world have one of the worst responses to COVID-19? We argue that this is because the United States conception of health is predominantly focused on healthcare, an overwhelming investment in developing drugs and treatments, and an underinvestment in the foundational conditions that keep people healthy. COVID-19 has exposed the limits of this approach to health. In order to prevent COVID-19 and future such pandemics, we must create the conditions that can keep population-level health threats at bay. This means addressing the conditions that shape health, including economics, employment, community networks, racial disparities, how we treat older adults, and the physical layout of our communities. To do so means acknowledging health as a public good, as a transnational project with countries working together to build a healthier world. It also means acknowledging that everyone has a right to health. These aspirations should become core to the global community's health aspirations in the post-COVID-19 era.

Child labor and health: a systematic literature review of the impacts of child labor on child's health in low- and middle-income countries.

OBJECTIVE: To summarize current evidence on the impacts of child labor on physical and mental health. METHODS: We searched PubMed and ScienceDirect for studies that included participants aged 18 years or less, conducted in low- and middle-income countries (LMICs), and reported quantitative data. Two independent reviewers conducted data extraction and assessment of study quality. RESULTS: A total of 25 studies were identified, the majority of which were cross-sectional. Child labor was found to be associated with a number of adverse health outcomes, including but not limited to poor growth, malnutrition, higher incidence of infectious and system-specific diseases, behavioral and emotional disorders, and decreased coping efficacy. Quality of included studies was rated as fair to good. CONCLUSION AND RECOMMENDATIONS: Child labor remains a major public health concern in LMICs, being associated with adverse physical and mental health outcomes. Current efforts against child labor need to be revisited, at least in LMICs. Further studies following a longitudinal design, and using common methods to assess the health impact of child labor in different country contexts would inform policy making.

Operationalization of patients' rights in Sudan: Quantifying nurses' knowledge.

BACKGROUND: Promoting patients' rights is essential for defining the standards of clinical services within a country. Given their responsibilities, nurses can be the primary target for research to investigate the issue of patients' rights within a healthcare system. As such, assessing the knowledge of nurses about patients' rights is an essential step toward improving the quality of healthcare in limited resource settings like Sudan. OBJECTIVES: We aimed to assess the level of knowledge about patients' rights among the nursing staff at Friendship Teaching Hospital in Sudan. METHODS: This hospital-based cross-sectional study was carried out at the Friendship Teaching Hospital in Sudan. We surveyed the totality of nurses (95) at the hospital using an amended survey. The data were analyzed in SPSS software using descriptive and inferential statistics. ETHICAL CONSIDERATION: The study was approved by the Research Unit of Khartoum Ministry of Health and the Hospital administration. All respondents gave verbal consent prior to participating in the study. RESULTS: Only 48.4% of the participants knew about the existence of the Sudanese Charter of patients' rights. Nonetheless, our analysis found that 65.8% of nurses had acceptable level of knowledge (scored more than 75% of the total knowledge score) of patients' rights, and none of the participant scored less than 50% of the total knowledge score. Finally, we found no statistical association between the knowledge score and demographic data, educational level, whether the participant knows about the existence of the Charter or not and a number of other factors. CONCLUSION: Nurses' lack of knowledge about the existence of the Sudanese Charter of patients' rights adopted in 2009 rights confirms the need for further efforts by Ministry of Health to promote the document. Furthermore, further research is needed to investigate the disconnect between nurses' lack of knowledge about the existence of the charter and their awareness of the rights within the charter as well as the actual implementation of rights.