Socioeconomic Status and Current Cigarette Smoking Status: Immigrants’ Diminished Returns

Extensive theoretical and empirical work has established the strong effects of socioeconomic status (SES) indicators such as education and income on health outcomes.1-3 High education and income are associated with higher happiness4 and lower risk of depression,5 anxiety,6 suicide,7 distress,8,9 and substance use.10,11 In contrast, immigration is associated with lower SES, poor health, and substance use.12-15 Marginalized and non-marginalized groups, however, show health effects of SES indicators such as education and income unequally.16-22 According to the Marginalizationrelated Diminished Returns (MDRs) theory, 23,24 the effects of education,25 income,26-30 employment,31,32 and marital status on mental health,33,34 physical health,35-38 and health behaviors25,39-41 are weaker for minority groups than the majority group. This pattern has been established for Blacks,17,18 Hispanics,26,42 Asian Americans,43 Native Americans,10 and the LGBT community.44-46 For example, high SES LGBT individuals remain at high risk of loss of mental well-being,44 obesity,46 and smoking.45 According to the MDRs literature, minority status may reduce the health returns of education,35 income,26-30 occupation,31,32 and marital status47; however, it is yet unknown if the same MDRs can also be seen for immigrants. That is, it is unclear if immigrants and non-immigrants similarly gain health from their SES resources such as education and income. Similar to other sources of marginalization, namely race,33 ethnicity,26,40 and sexual orientation,44-46 immigrants are pushed to the margin of the host society. Given the immigration rules and regulations, border control laws, and the xenophobia pervasive in our society, immigrants are commonly discriminated against and are treated as secondclass citizens.48-52 In this study, the National Health Interview Survey (NHIS), a nationally representative study, was used to compare immigrants and non-immigrants for the effects of education http://ijtmgh.com Int J Travel Med Glob Health. 2020 June;8(2):66-72 doi 10.34172/ijtmgh.2020.11 TMGH IInternational Journal of Travel Medicine and Global Health J

and income on the current cigarette smoking status of adults in the United States. As suggested by MDRs, immigration was considered as a social identity and social status that reflects marginalization. Thus, weaker effects of education and income on current cigarette smoking of immigrant than non-immigrant people were expected, similar to the pattern observed for Blacks, Hispanics, Asian Americans, Native Americans, and the LGBT community.

Methods
This is a cross-sectional study. 2015 NHIS data was used. The NHIS is the primary source of information regarding the physical health status of American adults 18 years or older. The NHIS sample is composed of US residents who are civilian, non-institutionalized people. The current analysis is limited to adults.

Participants and Sampling
The NHIS used a multi-stage clustered/stratified random sampling: First was to sample 428 primary sampling units (PSUs) drawn from 1900 geographically defined PSUs. All the 50 US states and the District of Columbia had representative PSUs in the sample. The PSUs were either a metropolitan statistical area, a single county, or a small group of contiguous counties. For this analysis, only data from adults was used.

Process
The data is collected by the National Center for Health Statistics (NCHS), which is a part of the Centers for Disease Control and Prevention (CDC). The US Census Bureau collects the data. Data is collected via face-to-face interviews in participants' households. On some occasions, this face-toface interview is followed or replaced by a telephone interview.

Participants
The total sample in this study was 14,149 adults who were either immigrants (n = 1977; 14.0%) or non-immigrants (n=12 166; 86.0%). People could be of any race/ethnicity to be included in this study. The study had no exclusion criteria.

Measures Predictor
Education. Education is shown to be in 4 categorical levels in Tables 1 and 2 though. Income. Annual income was self-reported. This variable was measured as a continuous variable in dollars. For the current analysis, however, a dichotomous variable with a cut-off point of 35 000 USD was used. Individuals with high income were coded as one, and those with lower income were coded as 0.
Moderator Immigration status. Nativity was self-reported. All participants were asked if they were born in the US. The responses were coded 1 for immigrants and 0 for non-immigrants.

Covariates
Demographic factors included age, gender, region, race, ethnicity, education, marital status, and employment. Age (years) was a continuous variable. Gender was a dichotomous measure (male = 1, female = 0). Participants indicated their region as being either the Northeast, Midwest, South, or West. Participants self-identified their race and ethnicity, both of which were operationalized as categorical variables. Race was White only (reference category), Black/African American only, Native American/Alaska Native only, Asian only, multiple race, and race group not releasable (masked or missing). Ethnicity was Hispanics = 1, non-Hispanics = 0 (reference category). Participants were asked about the number of years of schooling. Marital status was a dichotomous variable with married coded as 1. Employment status was a dichotomous variable with employed coded as 1.

Dependent Variable
Current Cigarette Smoking. Current cigarette smoking status was the outcome. Smoking status was self-reported. Current cigarette smokers were defined as those who had smoked at least 100 cigarettes, were a smoker at the time of the survey, and reported smoking daily.

Statistical Analyses
Given the NHIS's multi-stage sampling design, SPSS 23.0 (IBM Inc., NY, USA) was applied for data analysis. Using SPSS, adjustments were made for the NHIS survey weights due to the design variables (strata, clusters, and non-response). Taylor series linearization was applied for the re-estimation of standard errors (SE). Weighted means and frequencies were used for descriptive statistics. For multivariable analyses, four logistic regression models were applied. In these models, education and income were the independent variables; current cigarette smoking status was the dependent variable; and demographic factors and race, ethnicity, and region were the control variables. Immigration status was the moderator. The first two models were calculated in the pooled sample that included both immigrants and non-immigrants. Model 1 did not include immigration by education and income interaction terms. Model 2, however, included immigration by education and income interaction terms. Model 3 and Model 4 were performed in non-immigrants and immigrants, respectively. Adjusted odds ratio (OR), 95% confidence intervals (CI), SE, and P values were reported. A P value of less than 0.05 was considered significant.

Descriptive Statistics
The total sample in this study was 14 149 immigrant and nonimmigrant American adults 55+ years old. Table 3 depicts the descriptive statistics of the participants overall and based on nativity. Table 1 shows the results of two logistic regressions in the pooled sample with education and income as the predictors and current cigarette smoking status as the outcome (dependent variable). Model 1 included only the main effects of education and income; however, Model 2 added the interaction terms between immigration status, education, and income. Based on Model 1, high education and income were linked to lower odds of current cigarette smoking. Model 2, however, revealed statistically significant interactions between education and income with immigration status on current cigarette smoking status of adults. The model suggested that the protective effects of education and income against current cigarette smoking status were smaller for immigrant than non-immigrant adults (Table 1). Table 2 shows the results of one logistic regression on non-immigrants (Model 3) and one logistic regression in immigrants (Model 4). In these models, education and income were the predictors, and current cigarette smoking status was the outcome (dependent variable). Based on Model 3, high education levels and income were associated with lower odds of current cigarette smoking for non-immigrant adults. Model 4 did not show protective effects of most education levels and income on current cigarette smoking for immigrant adults ( Table 2).

Discussion
Education and income were associated with lower odds of current cigarette smoking status of adults. These effects, however, were larger for non-immigrants than immigrants.
Marginalization, broadly defined, reduces the health return of education and income among other SES indicators. This is supported by the observations that Blacks, 33 Hispanics, 26,40 Asian Americans, 43 Native Americans, 10 and people of the LGBT community 46 show MDRs. If any type of marginalization reduces the health gains that follow SES indicators such as education and income, similar patterns should be expected for immigrants. [48][49][50][51][52] Societal and structural factors such as social stratification, residential segregation, labor market discrimination, and low availability of resources in urban areas may all suggest that immigrants may be less likely to benefit from their education and income fully.
As education and income improve, tobacco use reduces, but less for immigrants than non-immigrants. This finding is an extension of previous literature on MDRs 23,24 on diminishing returns of education, 35 income, [26][27][28][29][30] occupation, 31,32 and marital status 47 on a wide range of mental health outcomes  58 and exercise, 13 Finally, MDRs are seen for physical health outcomes such as obesity, 35,36 self-rated health, 26,34,53 chronic diseases, 28,29,37 disability, 59 and mortality. 38 Not only educational attainment 34 and income, 28 but also occupation, 38 and marital status 47 all generate less health for the majority than marginalized people. Social marginalization, regardless of its type, whether it is based on race, 60 ethnicity, 26,40 sexual orientation, [44][45][46] or immigration are consistently associated with less health gain from income and other SES indicators. 60 The robust and consistent nature of the MDRs shifts the blame from the marginalized people to the society that reduces the gain of all vulnerable and disadvantaged groups. Thus, these patterns suggest that the MDRs are due to the function and structure of society. US social institutions treat people differentially based on their color, race, ethnicity, class, heritage, and nativity, resulting in systemic marginalization of non-majority groups. Such marginalization reduces people's chances for enjoying full participation and full benefits from resources that are available to them. The racism, xenophobia, and nationalism embedded in the social fabric of the US society reduce immigrants, LGBTs, and racial and ethnic minorities' ability to fully leverage their human capital and turn it into tangible outcomes. As a result, they show less than expected benefits in the presence of education, income, and other SES resources. 23,24 Implications To undo MDRs, bold policies are needed that can equalize the health return of education and income as well as other SES indicator cross groups. Such policies should go beyond equal access to education and income and focus on equality in the returns of SES indicators across social groups. Specific policies and programs should help immigrants to more effectively mobilize and leverage their education and income to gain tangible outcomes. Ways by which the purchasing power of immigrants can be enhanced should be studied in future research.

Limitations
The current results should be interpreted with the methodological limitations in mind. First, any cross-sectional study is limited in drawing causal inferences. It cannot be ruled out that excessive health problems influence social mobility and the ability to generate educational mobility and income. Thus, reverse causality cannot be ruled out in this study. Thus, the results should be interpreted not as causation, but as association. Moreover the mechanisms by which MDRs of education and income emerge were not studied. The lower purchasing power of income for immigrants may be the mechanism. Access to the country of origin was not available; nor did we control for type of occupation, wealth, assets, or parental education. Future research should replicate and validate these findings using longitudinal data with a more comprehensive list of measures on nativity, country of origin, and other SES indicators. Future research may also include contextual factors such as neighborhoods' ethnic composition, SES, or density of resources as factors that may cause MDRs. It is likely that highly educated and high-income immigrants report poor mental health, because they need to spend more time on the job or they face extra stress to gain such education and income. Finally, there is a need to compare immigrants from Asia, Africa, and Latino countries, as each culture may adopt US culture differently.

Conclusion
While education and income reduce the odds of current cigarette smoking status of American adults, these influences are weaker for immigrants than non-immigrants. Thus, tobacco use disparities in immigrants are beyond SES inequalities and also diminishing marginal returns of SES indicators such as education and income for immigrants. To eliminate health inequalities that impact immigrants, it is essential to recognize and address MDRs-related inequalities that endure across all SES levels.

Conflict of Interest Disclosures
The author declares no conflicts of interest.

Ethical Approval
All participants signed written consent forms. The NHIS protocol was approved by the CDC Instructional Review

What Is Already Known?
High education and income are associated with lower odds of current cigarette smoking; however, these effects may vary across population sub-groups.

What This Study Adds?
In line with the marginalization-related diminished returns, education and income generate less protection against cigarette smoking for immigrants than non-immigrants in the United States. As a result, we may observe a higher than expected prevalence of smokers among highly educated and high-income immigrants.