The Association Between Immigration Status and Office-based Medical Provider Visits for Cancer Patients in the United States

Climate-related migration and population health: social science-oriented dynamic simulation model

BACKGROUND

Social science models find the ecological impacts of climate change (EICC) contribute to internal migration in developing countries and, less so, international migration. Projections expect massive climate-related migration in this century. Nascent research calls to study health, migration, population, and armed conflict potential together, accounting for EICC and other factors. System science offers a way: develop a dynamic simulation model (DSM). We aim to validate the feasibility and usefulness of a pilot DSM intended to serve as a proof-of-concept and a basis for identifying model extensions to make it less simplified and more realistic.

METHODS

Studies have separately examined essential parts. Our DSM integrates their results and computes composites of health problems (HP), health care (HC), non-EICC environmental health problems (EP), and environmental health services (ES) by origin site and by immigrants and natives in a destination site, and conflict risk and intensity per area. The exogenous variables include composites of EICC, sociopolitical, economic, and other factors. We simulate the model for synthetic input values and conduct sensitivity analyses.

RESULTS

The simulation results refer to generic origin and destination sites anywhere on Earth. The effects' sizes are likely inaccurate from a real-world view, as our input values are synthetic. Their signs and dynamics are plausible, internally consistent, and, like the sizes, respond logically in sensitivity analyses. Climate migration may harm public health in a host area even with perfect HC/ES qualities and full access; and no HP spillovers across groups, conflict, EICC, and EP. Deviations from these conditions may worsen everyone's health. We consider adaptation options.

CONCLUSIONS

This work shows we can start developing DSMs to understand climate migration and public health by examining each case with its own inputs. Validation of our pilot model suggests we can use it as intended. We lay a path to making it more realistic for policy analysis.

Association of Cancer History and Health Care Utilization Among Female Immigrants Using NHANES 2007-2016 Data

BACKGROUND

Despite health disparities in preventive care among adult female immigrants, the extent to which their health service utilization is influenced by a cancer history remains largely unknown.

METHODS

Using Andersen's behavioral model, 2007-2016 National Health and Nutrition Examination Survey data were analyzed to examine the influence of a cancer history on health service utilization among adult immigrant women. Multivariate logistic regression models assessed factors related to past year health care utilization, operationalized as an outpatient doctor's visit and an inpatient overnight hospital stay.

RESULTS

Once other factors were considered, a past cancer history increased the likelihood of a past year inpatient overnight hospital stay, but was not associated with a past year outpatient doctor's visit.

DISCUSSION

An outpatient doctor's visit for adult female immigrant cancer survivors would provide an opportunity for essential preventive health services. They must be educated about the importance of ongoing outpatient care for cancer surveillance and health maintenance.

Immigration factors and potentially avoidable hospitalizations in Canada

Objective

Estimate the effect of immigration characteristics on the risk of a hospitalization for an ambulatory care sensitive condition (ACSC).

Research design

We analyzed data on the Canadian resident adult population aged 18 to 74 years who responded to the 2006 long form Census. The Census data were linked to the Canadian Institute for Health Information (CIHI)’s Discharge Abstract Database (DAD) for fiscal years 2006–2007, 2007–2008, and 2008–2009. We conducted a logistic regression on the binary variable we created for an ACSC admission.

Measures

The CIHI definition of ACSC hospitalizations was used to identify potentially avoidable hospitalizations in the DAD. Immigration factors analyzed included years in Canada, ethnic origin, and ability to speak one of the official languages.

Results

There were 3,342,450 respondents aged between 18 and 74. Using the Canadian at birth as our reference population, recent immigrants (up to five years in Canada) had lower odds of an ACSC hospitalization, regardless of their ethnic origins, with the exception of immigrants from Oceania and from other North American countries for whom the effect was not significant. The protective effect was still present in children of immigrants (AOR=0.89). Immigrants from the Caribbean, from Southern, Eastern, and Western Europe, as well as those from East Asia had lower odds across categories of time spent in Canada. The protective effect was stronger in immigrants from East Asia and lower in those of Oceanic and other North American countries.

Conclusions

Our results suggest that the healthy immigrant effect dissipates with time in Canada but remains even in children of immigrants. The protective effect differs depending on the ethnic origin of the immigrant.

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Immigrants generally arrive in a country with a higher health status than that of the local population.

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Immigrants and children of immigrants have lower odds of having an ACSC hospitalization are lower than Canadians at birth.

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Odds of an ACSC hospitalization vary depending on immigration characteristics such as the ethnic origin and the time lived in Canada.

Self-reported healthcare provider utilization across United States Midwestern households

Understanding the relationships between health care provider usage and demographics of patients is necessary for the development of educational materials, outreach information, and programs targeting individuals who may benefit from services. This analysis identified relationships between health care provider usage and individual's demographics. A sample of Midwestern U.S. respondents (n = 1265) was obtained through the use of an online survey distributed February 12-26, 2016 and was targeted to be representative of the population of the Midwestern states sampled in terms of sex, age, income, and state of residence. Specific factors identified as significant in contributing to provider usage (in the past five years) differed across the eleven provider types studied. In the most commonly used practitioners (the general or primary physician), relationships between provider usage and age, income, health insurance coverage status, and having children in the household were identified. Furthermore, significant (and positive) correlations were identified between the usage of various practitioners; reporting the use of one type of practitioner studied was correlated positively with reporting the use of another type of health care provider studied in this analysis. This analysis provides insight into the relationships between health care provider usage and demographics of individuals, which can aid in the development of educational materials, outreach programs, and policy development.