Cervical and Breast Cancer Screening Among Mexican Migrant Women, 2013

The next phases of the Migrante Project: Study protocol to expand an observatory of migrant health on the Mexico-U.S. border

Background

Mexican migrants traveling across the Mexico-United States (U.S.) border region represent a large, highly mobile, and socially vulnerable subset of Mexican nationals. Population-level health data for this group is hard to obtain given their geographic dispersion, mobility, and largely unauthorized status in the U.S. Over the last 14 years, the Migrante Project has implemented a unique migration framework and novel methodological approach to generate population-level estimates of disease burden and healthcare access for migrants traversing the Mexico-U.S. border. This paper describes the rationale and history of the Migrante Project and the protocol for the next phases of the project.

Methods/design

In the next phases, two probability, face-to-face surveys of Mexican migrant flows will be conducted at key crossing points in Tijuana, Ciudad Juarez, and Matamoros (N = 1,200 each). Both survey waves will obtain data on demographics, migration history, health status, health care access, COVID-19 history, and from biometric tests. In addition, the first survey will focus on non-communicable disease (NCD), while the second will dive deeper into mental health and substance use. The project will also pilot test the feasibility of a longitudinal dimension with 90 survey respondents that will be re-interviewed by phone 6 months after completing the face-to-face baseline survey.

Discussion

Interview and biometric data from the Migrante project will help to characterize health care access and health status and identify variations in NCD-related outcomes, mental health, and substance use across migration phases. The results will also set the basis for a future longitudinal extension of this migrant health observatory. Analyses of previous Migrante data, paired with data from these upcoming phases, can shed light on the impact of health care and immigration policies on migrants' health and inform policy and programmatic responses to improve migrant health in sending, transit, and receiving communities.

Comparison of Cervical Levels of Interleukins-6 and -8 in Patients with and without Cervical Intraepithelial Neoplasia

Introduction:

Interleukins-6 and -8 are two pro-inflammatory cytokines increasing in serum and local levels under malignant conditions. There are limited evidences on the association between cervical level of these two factors and cervical intraepithelial neoplasia (CIN). So, this study aimed to explore the association between cervical levels of IL-6 and IL-8 with cervical premalignant lesions.

Methods:

The present case-control study was conducted on married women undergone Pap smear for routine screening in two groups as the group with CIN (n=100) and the healthy control group (n=100). Cervical secretions were collected using sterile swab and the levels of IL-8 and IL-6 were measured by enzyme-linked immunosorbent assay (ELISA). The obtained data were analyzed by SPSS software.

Results:

The mean cervical IL-6 level was 568.66±594.62 pg/ml in the patients with CIN and 212.7±213.9 pg/ml in the controls (P <0.001). The cervical IL-8 levels in the case and control groups were measured to be 1320.43±876.5 pg/ml and 1053.59±747.64 pg/ml, respectively (p=0.02). By modifying the confounding size effect of the age and marital duration, it was determined that cervical levels of IL-6 and IL-8 were both associated with CIN.

Conclusion:

Our results showed that the cervical levels of IL-6 and IL-8 are associated with CIN independent of age and marital duration.

Community-based participatory design of a community health worker breast cancer training intervention for South Florida Latinx farmworkers

OBJECTIVE

Community health worker (CHW)-led education is an important strategy to increase awareness and access to breast cancer screening in medically-underserved communities. This study aimed to develop a context-specific, culturally-appropriate training intervention for South Florida CHWs to educate Latinx immigrant farmworkers on breast cancer and early detection.

METHODS

A community-based participatory research (CBPR) study, conducted 2017-2019, informed the design of a training curriculum for CHWs and educational dissemination materials. Twenty-two CHWs were trained and knowledge gains were measuring using a one-group pre-and post-test design. Triangulated evaluation consisted of field observations of CHW-client interactions, CHW self-reports, and rapid assessment surveys of community members.

RESULTS

A community stakeholder-informed breast cancer training curriculum resulted in significant, sustained breast cancer knowledge gains among CHWs when comparing pre-, post-, and 4-6 month post-training follow-up test scores. Field observations of educational material dissemination, CHW self-reported evaluations, and community rapid assessment surveys at three health fairs demonstrated this was an effective strategy to engage female Latinx farmworkers in breast cancer education.

CONCLUSIONS

Community and key stakeholder participation in the development of a breast cancer educational intervention allowed for tailored design priorities around knowledge-based content, comprehensiveness, relevance, appropriateness, and ease of dissemination to community members. This model of participatory CHW training intervention design can enable future train-the-trainer approaches to disseminate and scale-up evidence-based health education interventions.

Forecasting Participants in the All Women Count! Mammography Program

INTRODUCTION

The All Women Count! (AWC!) program is a no-cost breast and cervical cancer screening program for qualifying women in South Dakota. Our study aimed to identify counties with similar socioeconomic characteristics and to estimate the number of women who will use the program for the next 5 years.

METHODS

We used AWC! data and sociodemographic predictor variables (eg, poverty level [percentage of the population with an annual income at or below 200% of the Federal Poverty Level], median income) and a mixture of Gaussian regression time series models to perform clustering and forecasting simultaneously. Model selection was performed by using Bayesian information criterion (BIC). Forecasting of the predictor variables was done by using an autoregressive integrated moving average model.

RESULTS

By using BIC, we identified 5 clusters showing the groups of South Dakota counties with similar characteristics in terms of predictor variables and the number of participants. The mixture model identified groups of counties with increasing or decreasing trends in participation and forecast averages per cluster.

CONCLUSION

The mixture of regression time series model used in this study allowed for the identification of similar counties and provided a forecasting model for future years. Although several predictors contributed to program participation, we believe our forecasting analysis by county may provide useful information to improve the implementation of the AWC! program by informing program managers on the expected number of participants in the next 5 years. This, in turn, will help in data-driven resource allocation.