Disparities in Health Care Coverage Among U.S. Born and Mexican/Central American Born Labor Workers in the U.S

An Observational Study Quantifying the Disproportionate Impact of COVID-19 Among Immigrant Adults, 2021 California Health Interview Survey

OBJECTIVE

Substantial data on COVID-19-related morbidity and mortality among medically underserved populations are available, yet data on the social impact of the COVID-19 pandemic among immigrants in the United States are limited. We identified COVID-19-related health and social disparities among US immigrants.

METHODS

We analyzed predictors of COVID-19-related health and social outcomes (including ever had or thought had COVID-19, vaccine uptake, risk-reduction behaviors, job loss, childcare difficulties, and difficulty paying rent) during the pandemic by citizenship status, using data from the 2021 California Health Interview Survey. The overall sample size included 24 453 US-born citizens, naturalized citizens, and noncitizens aged ≥18 years. We examined relationships between sociodemographic variables, including immigration-related factors, and COVID-19-related health and social outcomes using descriptive, bivariate, and multivariate logistic regression analysis.

RESULTS

When accounting for sociodemographic characteristics, noncitizens had higher odds than naturalized and US-born citizens of experiencing challenges during the COVID-19 pandemic, including difficulty paying rent (adjusted odds ratio [aOR] = 1.54; 95% CI, 1.47-2.42) and job loss (aOR = 1.43; 95%, CI, 1.14-1.79). At the bivariate level, noncitizens had the highest rate of ever had or thought had COVID-19 (24.7%) compared with US-born citizens (20.8%) and naturalized citizens (16.8%; all P < .001). Noncitizens also had a significantly higher likelihood of risk-reduction behaviors (eg, always wearing a face covering, getting vaccinated if available) than US-born citizens (P < .001).

CONCLUSION

These findings reveal the disproportionate impact of the COVID-19 pandemic among noncitizens and reflect limited socioeconomic resources, limited access to health care, and precarious employment among noncitizens in California during the pandemic. Citizenship status should be considered a critical immigration-related factor when examining disparities among immigrant populations.

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

BACKGROUND

There is no recognized gold standard method for estimating the number of individuals with substance use disorders (SUDs) seeking help within a given geographical area. This presents a challenge to policy makers in the effective deployment of resources for the treatment of SUDs. Internet search queries related to help seeking for SUDs using Google Trends may represent a low-cost, real-time, and data-driven infoveillance tool to address this shortfall in information.

OBJECTIVE

This paper assesses the feasibility of using search query data related to help seeking for SUDs as an indicator of unmet treatment needs, demand for treatment, and predictor of the health harms related to unmet treatment needs. We explore a continuum of hypotheses to account for different outcomes that might be expected to occur depending on the demand for treatment relative to the system capacity and the timing of help seeking in relation to trajectories of substance use and behavior change.

METHODS

We used negative binomial regression models to examine temporal trends in the annual SUD help-seeking internet search queries from Google Trends by US state for cocaine, methamphetamine, opioids, cannabis, and alcohol from 2010 to 2020. To validate the value of these data for surveillance purposes, we then used negative binomial regression models to investigate the relationship between SUD help-seeking searches and state-level outcomes across the continuum of care (including lack of care). We started by looking at associations with self-reported treatment need using data from the National Survey on Drug Use and Health, a national survey of the US general population. Next, we explored associations with treatment admission rates from the Treatment Episode Data Set, a national data system on SUD treatment facilities. Finally, we studied associations with state-level rates of people experiencing and dying from an opioid overdose, using data from the Agency for Healthcare Research and Quality and the CDC WONDER database.

RESULTS

Statistically significant differences in help-seeking searches were observed over time between 2010 and 2020 (based on P<.05 for the corresponding Wald tests). We were able to identify outlier states for each drug over time (eg, West Virginia for both opioids and methamphetamine), indicating significantly higher help-seeking behaviors compared to national trends. Results from our validation analyses across different outcomes showed positive, statistically significant associations for the models relating to treatment need for alcohol use, treatment admissions for opioid and methamphetamine use, emergency department visits related to opioid use, and opioid overdose mortality data (based on regression coefficients having P≤.05).

CONCLUSIONS

This study demonstrates the clear potential for using internet search queries from Google Trends as an infoveillance tool to predict the demand for substance use treatment spatially and temporally, especially for opioid use disorders.

Advocating for Equitable Healthcare for the Undocumented Immigrant

ABSTRACT

Despite the healthcare community's increased efforts to reduce health disparities in the United States, undocumented immigrants (UIs) remain one of the highest at-risk populations. Health and public policies, societal and healthcare worker bias, and fear of deportation are among barriers to healthcare access, resulting in increasingly poor health and health outcomes. Christian nurses, guided by biblical principles and the American Nurses Association's Code of Ethics for Nurses, can advocate for UIs' healthcare needs by supporting and promoting more inclusive institutional and government policies.

Challenging federal exclusion: Immigrant safety, health, and healthcare access in sanctuary cities

As the United States (U.S.) continues to prioritize federal immigration enforcement, subnational localities increasingly enact their own immigration policies. Cities limiting cooperation with federal immigration enforcement are commonly referred to as sanctuary cities, which aim to improve immigrant safety and wellbeing. Yet, little is known about how these cities accomplish this beyond immigration enforcement non-cooperation. We draw from qualitative interviews with 54 organizational workers in Seattle, Washington and Boston, Massachusetts. Our findings illuminate lingering challenges immigrants face within sanctuary cities and demonstrate how organizational workers mitigate the shortcomings of sanctuary policies to addressing broad definitions of safety and health by enacting their own sanctuary practices.

Disparities of health service for the poor in the coastal area: does Universal health coverage reduce disparities?

Background & Objective: Poor people, in general, get poor quality of health services. The situation is very much worsening for the poor who live in the remote areas in the coastal belt of Bangladesh as health care facilities and services are often less complete, farther away, and therefore most costly to reach than in urban hospitals and physician. Ensure of better health service for the poor, it is essential to examine the effectiveness of Universal Health Coverage (UHC). This study sets its objectives to evaluate the health service for the poor in the coastal area of Bangladesh and develop an approach of management strategy. Methods: This study followed a two-stage cluster sampling technique and carried out a household survey through the open-ended questionnaire. In addition, the study applied the logistic regression model to generate empirically supported assessments. Results: Result from the disparity rate ratio (DRR) revealed that there is a big health care disparity of different income groups like poor and rich. Furthermore, results from the model demonstrated that Medicaid, Medicare, Social Health Insurance, Telemedicine and Capitation under the provision Universal Health Coverage (UHC) are statistically significant compared to reduce the health care disparity. Conclusion: UHC becomes a critical issue for improved and quality health care system for all the groups especially, the poor in coastal Bangladesh. This study showed that Medicaid, Medicare and Social Health Insurance and Capitation perform well to provide better health care facilities for all.