Provision of Onsite Prenatal Care Services at U.S. Federally Qualified Health Centers

Associations of Sociodemographic and Neighborhood Vulnerability With Cardiovascular Health in Midlife Women in the United States

BACKGROUND: Many women have suboptimal cardiovascular health (CVH), which declines during midlife. Few studies have characterized CVH across the menopausal transition or identified its sociodemographic and neighborhood determinants. METHODS: We analyzed a prospective cohort of women in eastern Massachusetts enrolled during pregnancy (1999–2002) and followed to midlife (2019–2024). Exposures included household income, education, race and ethnicity, and neighborhood Social Vulnerability Index (categorized from very low [<20th percentile] to very high [≥80th percentile]; higher categories=greater neighborhood vulnerability). Women self-reported their menopause status using questionnaires. Using Life’s Essential 8, we derived CVH scores (0–100 points; higher score=better CVH) at 3-, 8-, 13-, 18-, and 23-year follow-up visits. Linear spline mixed-effect models examined associations of sociodemographics and neighborhood Social Vulnerability Index with differences in CVH across different menopause stages (premenopause, perimenopause, and postmenopause). RESULTS: Among 1200 women (mean enrollment age, 32.1 years; 67.5% Non-Hispanic White), 15.4% had household incomes ≤$40 000/y, 8.8% had ≤high school education, and 17.4% resided in very high Social Vulnerability Index neighborhoods. After covariate adjustment, women with lower income, lower education, or identifying as Non-Hispanic Black exhibited lower CVH across follow-up. Independent of individual sociodemographics, continued residence in vulnerable neighborhoods over time was associated with lower CVH and unfavorable CVH trajectories across follow-up. For example, residence in very high (versus very low) Social Vulnerability Index neighborhoods from enrollment to 3-year follow-up corresponded to mean CVH differences of −6.7 (95% CI, −12.3 to −1.2) at 3-year, −9.8 (95% CI, −15.6 to −4.0) at 8-year, −8.9 (95% CI, −13.9 to −3.9) at 13-year, −6.7 (95% CI, −12.9 to −0.5) at 18-year, and −7.2 (95% CI, −12.5 to −1.9) at 23-year follow-up, and with faster CVH score decline during premenopause (−0.62 points/y; 95% CI, −1.22 to −0.02). CONCLUSIONS: Women from disadvantaged sociodemographic backgrounds or residing in vulnerable neighborhoods exhibit poorer CVH across the menopausal transition, highlighting opportunities to optimize long-term CVH and mitigate cardiovascular disease risk.

Genetic Determinants of Macronutrient Intake Are Associated With Specific Food Intake in Youth: A Cohort Study Across Childhood and Adolescence

OBJECTIVE. We examined associations of polygenic scores (PS) for macronutrient intake with food intake and cardiometabolic outcomes during childhood and ad

Most Community Health Centers Provide Prenatal Care, But One-Third Still Lack Services | HPHCI: Department of Population Medicine

Boston, MA—A new national study provides the first comprehensive look at prenatal care services offered by federally qualified health centers (FQHCs), revealing that while these safety-net providers play a critical role in caring for low-income and racially diverse pregnant populations, significant gaps in access remain.

Information Forklift Certified Organizations

Agentic development as a process, not a product, and other expensive failures of understanding

Vertical Federated Learning: Concepts, Advances, and Challenges

Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with different features about the same set of users jointly train machine learning models without exposing their raw data or model parameters. Motivated by the rapid growth in VFL research and real-world applications, we provide a comprehensive review of the concept and algorithms of VFL, as well as current advances and challenges in various aspects, including effectiveness, efficiency, and privacy. We provide an exhaustive categorization for VFL settings and privacy-preserving protocols and comprehensively analyze the privacy attacks and defense strategies for each protocol. In the end, we propose a unified framework, termed VFLow, which considers the VFL problem under communication, computation, privacy, as well as effectiveness and fairness constraints. Finally, we review the most recent advances in industrial applications, highlighting open challenges and future directions for VFL.

Isopod Site

Pillbugs, sowbugs, roly-polies and woodlice, collectively referred to as isopods, are land-dwelling crustaceans that feed on decaying organic matter.

Humanitarian Governance

This review examines humanitarian governance, defined as the increasingly organized and internationalized attempt to save the lives, enhance the welfare, and reduce the suffering of the world's most vulnerable populations. Political scientists and international relations scholars are only now beginning to explain this rapidly growing global governance of humanity, which is particularly evident in the developing literatures on humanitarian intervention, emergency relief, peacebuilding, and refugee protection. As they increasingly engage this relatively unexplored area of global life, political scientists are using the familiar analytics of the global governance literature to explain the origins, design, and effectiveness of this collective activity. This essay, though, interjects an alternative perspective, one that draws from critical theory, to widen the research agenda of the study of humanitarian governance. Specifically, the essay raises six central questions: What kind of world is being imagined and produced? What accounts for the tremendous growth of humanitarian governance over the last century? Who governs? How is humanitarian governance organized and accomplished? What are the principal techniques of control? By what authority do humanitarians govern and what do they do with that authority?

Uncovering Coordinated Networks on Social Media: Methods and Case Studies

Coordinated campaigns are used to influence and manipulate social media platforms and their users, a critical challenge to the free exchange of information online. Here we introduce a general, unsupervised network-based methodology to uncover groups of accounts that are likely coordinated. The proposed method constructs coordination networks based on arbitrary behavioral traces shared among accounts. We present five case studies of influence campaigns, four of which in the diverse contexts of U.S. elections, Hong Kong protests, the Syrian civil war, and cryptocurrency manipulation. In each of these cases, we detect networks of coordinated Twitter accounts by examining their identities, images, hashtag sequences, retweets, or temporal patterns. The proposed approach proves to be broadly applicable to uncover different kinds of coordination across information warfare scenarios.

A General Method to Find Highly Coordinating Communities in Social Media through Inferred Interaction Links

Political misinformation, astroturfing and organised trolling are online malicious behaviours with significant real-world effects. Many previous approaches examining these phenomena have focused on broad campaigns rather than the small groups responsible for instigating or sustaining them. To reveal latent (i.e., hidden) networks of cooperating accounts, we propose a novel temporal window approach that relies on account interactions and metadata alone. It detects groups of accounts engaging in various behaviours that, in concert, come to execute different goal-based strategies, a number of which we describe. The approach relies upon a pipeline that extracts relevant elements from social media posts, infers connections between accounts based on criteria matching the coordination strategies to build an undirected weighted network of accounts, which is then mined for communities exhibiting high levels of evidence of coordination using a novel community extraction method. We address the temporal aspect of the data by using a windowing mechanism, which may be suitable for near real-time application. We further highlight consistent coordination with a sliding frame across multiple windows and application of a decay factor. Our approach is compared with other recent similar processing approaches and community detection methods and is validated against two relevant datasets with ground truth data, using content, temporal, and network analyses, as well as with the design, training and application of three one-class classifiers built using the ground truth; its utility is furthermore demonstrated in two case studies of contentious online discussions.

Exposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election

Coordinated information operations remain a persistent challenge on social media, despite platform efforts to curb them. While previous research has primarily f

Data of 600,000 Gaza households exposed in WFP cyber-attack

With over 2 million people registered in Gaza, it may be the largest-known breach of humanitarian beneficiary data to date.

The Signal Code: A Human Rights Approach to Information During Crisis | Harvard Humanitarian Initiative

The Signal Code is the result of a six month study by the Signal Program on Human Security and Technology at the Harvard Humanitarian Initiative (HHI) at the Harvard T.H. Chan School of Public Health to identify what human rights people have to information during disasters. The Signal Code identifies five rights from multiple sources of international human rights and humanitarian law and standards that already exist and apply to humanitarian information activities (HIAs).