Advertisement

BMC Public Health

, 19:1458 | Cite as

The moderating role of race/ethnicity and nativity in the relationship between perceived discrimination and overweight and obesity: results from the National Epidemiologic Survey on Alcohol and Related Conditions

  • Adolfo G. CuevasEmail author
  • Kasim Ortiz
  • Yusuf Ransome
Open Access
Research article
Part of the following topical collections:
  1. Health behavior, health promotion and society

Abstract

Background

The overweight/obesity epidemic is a public health issue in the United States (US), that disproportionately affect certain racial/ethnic minority groups. Perceived discrimination has been implicated as a health risk factor. However, research on race/ethnicity, perceived discrimination, and obesity has been mixed. Researchers suggest that perceptions of discrimination may be dependent upon nativity status. This study evaluated the role that nativity status and race/ethnicity play in the relationship between perceived discrimination and overweight/obesity.

Methods

We used Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (2004–2005) [N = 33,319]). Multinomial logistic regression assessed a three-way interaction (perceived discrimination × race/ethnicity × nativity) on overweight and obesity, adjusting for sociodemographic factors and health-related behaviors.

Results

The three-way interaction was significant for overweight [F (17, 49) = 3.35; p < 0.001] and obesity [F (17, 49) = 5.05; p < 0.001]. Among US-born individuals, US-born non-Hispanic Blacks had a decreased risk of being obese compared to US-born non-Hispanic Whites at mean levels of perceived discrimination [aRRR = 0.71; 95% CI (0.51–0.98); p = 0.04). Among foreign-born individuals, foreign-born South Americans had an increased risk of being overweight at mean levels of perceived discrimination compared to foreign-born non-Hispanic Whites [aRRR = 8.07; 95% CI (1.68–38.77); p = 0.01], whereas foreign-born Dominicans had a decreased risk of being obese compared to foreign-born non-Hispanic Whites [aRRR = 0.05; 95% CI (0.01–0.20); p < 0.001].

Conclusion

Perceived racial discrimination is a risk factor for overweight/obesity for certain groups. Race/ethnicity and nativity may play important roles in the relationship between perceived discrimination and overweight/obesity. Future research is needed to identify the behavioral and psychological pathways that link perceived discrimination and overweight/obesity.

Keywords

Race/ethnicity Discrimination Nativity Obesity 

Abbreviations

BMI

Body mass index

CI

Confidence Intervals

EOD

Experiences of Discrimination

NESARC

National Epidemiologic Survey on Alcohol and Related Conditions

RRR

Relative risk ratio

SES

Socioeconomic status

US

United States

Introduction

The overweight/obesity epidemic has been a persistent public health issue in the US, disproportionately affecting certain racial/ethnic minority groups [1, 2]. Non-Hispanic Blacks and Hispanics/Latinos have higher prevalence of overweight/obesity compared to non-Hispanic Whites [2], which places them at a greater risk for obesity-related diseases, such as hypertension, coronary heart disease, and stroke [1, 3, 4, 5, 6]. There is also evidence that individuals who are overweight are at increased risk of cardiovascular disease risk [7] and are more likely to become obese over time [8]. Nevertheless, these aggregate data mask important variations in overweight/obesity based on nativity status. Limited evidence shows that US-born individuals, across race/ethnicity, have significantly higher obesity prevalence compared to their foreign-born counterparts [9, 10]. For instance, US-born Blacks are approximately 2.5 times more likely to be obese than foreign-born Blacks, whereas US-born Whites and US-born Hispanics are each 1.4 times more likely to be obese compared to their foreign-born counterparts [10].

The etiology of obesity and obesity disparities is multifactorial, reflecting a complex interaction of biobehavioral and socioenvironmental factors [7]. For instance, there is evidence that genetic markers, such as a variant in FTO (rs9939609) independently increases obesity susceptibility [7]. Other factors, such as physical inactivity and poor dietary behaviors, interact together to further increase risk of obesity [7, 11, 12]. Racial/ethnic minorities generally engage in less physical activity and consume fewer fruits and vegetables than Whites [13]. These obesity-related behaviors are thought to contribute to racial/ethnic disparities in obesity [14]. Given that racial/ethnic minorities are disproportionately at the lower end of the socioeconomic strata as compared to Whites, researchers have suggested racial/ethnic differences in obesity may simply be a function of underlying differences in socioeconomic status, via differences in social environments that facilitate healthy dietary and exercise behaviors [15, 16, 17].

Studies have found, however, that the association between SES and obesity varies by race/ethnicity and that ethnic/racial differences in obesity are not fully explained by SES [15, 18, 19, 20]. Moreover, despite foreign-born individuals disproportionately being at the lower end of the SES strata, they display better health, lower mortality, and lower obesity rates than their US-born counterparts who tend to have higher levels of income and education [10, 21, 22, 23, 24, 25]. While US-born individuals engage in different health behaviors (e.g., dietary intake and physical activity) compared with foreign-born, even after adjusting for health behavior and SES, differences in nativity status persist [10].

Stress can increase the risk of overweight and obesity through psychological means [26, 27]. For example, greater reports of stressful life events are associated with increased reports of depressive symptoms [28]. There is compelling evidence that depression increases the risk of obesity [29]. Stress can also increase the risk of overweight and obesity through behavioral pathways. Animal and human studies show that stress can induce cravings for high sugar and high fat foods [30]. Moreover, stress can reduce effort to engage in physical activity [31].

Perceived discrimination operate like other stressors, in that they are life-long and cumulative and can lead to illness and disease [32, 33, 34]. Growing attention has been given to the ways in which race/ethnicity-related aspects of social experiences, particularly perceived discrimination, may increase the risk of obesity [35, 36, 37]. Findings pertaining to the relationship between discrimination and obesity, however, have been mixed. For example, Molina and colleagues found that among 602 Latino adults living in Lawrence, MA, those who reported greater general perceived discrimination were more likely to have higher BMI and waist circumference, even after adjusting for sociodemographic factors, physical activity, and stressful life events. In a multi-racial/ethnic sample of 3105 adults, greater reports of discrimination (both racial and non-racial) were associated with increased abdominal obesity, but only among ethnic Whites (e.g., Irish, Jewish, Polish) [37]. Lewis and colleagues found that, among White and Black women (N = 402; 45% African-American, 55% Caucasian), greater reports of general discrimination were associated with higher amounts of visceral fat, but the association did not vary by race [38]. Vines and colleagues found that, among 447 Black women, perceived racism was inversely associated with lower levels of waist-to-hip ratio [39].

As research continues to document the relationship between perceived discrimination and obesity, greater attention is needed on the heterogeneity within racial/ethnic groups. Brondolo and colleagues [40] suggest that perception of discrimination, particularly among racial/ethnic minority groups, may be dependent on an individual’s membership to other social identity groups. Nativity status is one group membership that can influence perception of discrimination. Because foreign-born individuals are typically born and raised in a society where their racial/ethnic group is the majority, they may have had fewer experiences of discrimination based on their race/ethnicity in their country of origin. Latino/Hispanic immigrants, in particular, are from countries with distinct social construction of race. Going back to colonialism, Latinos with phenotypes of African descent were the lowest in the social hierarchy, followed by those of indigenous descent; while those who were phenotypically European held political, social, and economic power [41]. Much of these inequalities persist and manifest in Latin American countries today in overt and subtle ways, with darker skin and African phenotypic features being perceived as less desirable, while lighter skin and European phenotypic features perceived more favorably [41]. This form of discrimination (i.e., colorism) may be more salient to Hispanic/Latino immigrants living in the US than discrimination based on their race/ethnicity. Moreover, Hispanic/Latino immigrants living in the US experience unique stressors, like acculturative stress (i.e., the psychological impact of adapting to a new culture) [42], which may be a more immediate threat to the self than racial/ethnic discrimination. US-born individuals, on the other hand, are exposed to more discussions and studies of race and racism, which can potentially make them more adept at recognizing racial/ethnic bias in the US [40, 43, 44]. For US-born racial/ethnic minorities, in particular, race/ethnicity may be a more salient source of individuals’ perceptions of discriminatory treatment than other social identities as they recognize that their social and economic conditions are shaped by institutional and interpersonal discrimination [45, 46].

In a study of 1454 urban-dwelling Asian and Black adults, U.S.-born individuals reported more race-related stigmatization and exclusion than foreign-born individuals. In a community-based study of 185 US-born and 114 foreign-born Black pregnant women, US-born Black pregnant women reported greater prevalence of personal racism and group racism compared to foreign-born Black pregnant women. Another study found that found greater reporting of discrimination (e.g., being treated with less courtesy than other people; being treated with less respect than other people) among US-born Latinos (47% vs. 25%) compared to foreign-born Latinos [47].

Perceived discrimination and its obesogenic sequelae are potentially obscured, without considering the intersection of race/ethnicity and nativity status. The effects of discrimination on overweight/obesity may be stronger for certain groups. A better understanding of the association between perceived discrimination and overweight status/obesity will allow us to identify those most vulnerable to discrimination. Using a multi-racial/ethnic, population-based sample of adults, we examined the interrelationship between racial/ethnic perceived discrimination, race/ethnicity, and nativity status on overweight/obesity. We hypothesize that the association between racial/ethnic perceived discrimination and overweight/obesity is stronger for US-born racial/ethnic minorities.

Methods

We used data from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) [2004–2005] [48], which is a population-representative survey of United States adults living in noninstitutionalized settings. Trained interviewers utilized computer-assisted personal interviews to capture health outcomes, behavioral factors, and psychiatric disorders of respondents > 18 years of age [49]. NESARC data are weighted to adjust for the probabilities of selecting households, selecting one person per household, oversampling and nonresponse. There was also an oversampling of young adults (18–24 years old) and non-Hispanic Blacks and Hispanics/Latinos to ensure appropriate representation of racial and ethnic subgroups and to obtain reliable statistical estimation in these subpopulations [50]. Wave 2 involved re-interviews of 34,653 Wave 1 participants, resulting in a cumulative response rate of 70.2%. NESARC received ethical approval from the U.S. Census Bureau and the U.S. Office of Management and Budget [49]. The final sample for the current analyses included N = 32,747 respondents. This study was approved by the Institutional Review Board at Harvard T.H. Chan School of Public Health.

Anthropometric measures

Trained interviewers administered survey-based measures and measured the respondent’s height and weight. The primary outcomes were overweight and obesity based on Body Mass Index (BMI). BMI was calculated based on measured height and weight, and values were categorized as follows: a) underweight/normal [BMI ≤ 25]; b) overweight [25.1 ≥ BMI ≤ 30]; and c) obese [BMI ≥ 30.1]. This coding follows previously utilized assessments of weight statuses using NESARC [51].

Perceived racial discrimination

We measured perceived racial discrimination using the validated Experiences of Discrimination (EOD) instrument [52]. Respondents were asked how often in the past year they had “been prevented from doing something, or been hassled or made to feel inferior in any of the following situations because of your race, ethnicity, or color.” The EOD asks respondents whether they have experienced racial discrimination in nine different social context, including work, school, housing, and with the police and courts. Participants were given the option of 0 = Never, 1 = Once, 2 = Two or three times, or 3 = Four or more times.

Race/ethnicity

We took full advantage of NESARC’s oversampling of racial minority populations and included Hispanic/Latino subgroups. Race/ethnicity was coded as follows: non-Hispanic White (reference), non-Hispanic Black, Mexican American, Cuban American, Puerto Rican, Central American, South American, Dominican, and non-Hispanic Other.

Nativity

Nativity was assessed using the following question: “Were you born in the United States”, for which respondents were provided yes/no response option.

Covariates

Due to their known relationship with either overweight/obesity or racial discrimination [53, 54, 55, 56], we included the following socio-demographic covariates in the adjusted regression models: gender (male/female), educational attainment (less than high school, high school diploma/general education degree, some college/bachelor’s degree, graduate education), age (18–98 years of age); personal income (less than/equal to $19 K, $20 K- $35 K, $36 K - $70 K, more than $70 K), marital status [married/cohabitating, widowed/divorced/separated, never married), current smoking status (yes/no), and census region.

Statistical analyses

First, we present sociodemographic characteristics of our study sample; wherein we conducted Rao-Scott X2 tests on categorical variables, comparing demographic markers across weight statuses. We then deployed multinomial logistic regressions to examine the three-way interaction (perceived discrimination × race/ethnicity × nativity) on overweight/obesity, adjusting for all covariates. Results of the regression models are reported using relative risk ratios (RRRs) with corresponding 95% confidence intervals (CI). All analyses were conducted using Stata 14.2 software, taking into consideration complex survey design of the NESARC, using Stata’s svy: mlogit suite of commands [57].

Results

A total of 32,747 participants were included in the main analyses, of whom 9947 (28.34%) were obese, 11,329 (33.97%) were overweight, and 12,159 (37.68%) were normal or underweight (see Table 1). The average age of the sample was 45.08 years old. Less than half of the participants were male (47.92%). Non-Hispanic Whites had a greater proportion of normal weight/underweight than overweight and obese. For the other race/ethnicity groups, the weight distributions were relatively the same. Among men, the highest percentage of respondents were in the overweight group, whereas for women, the majority were found in the underweight/normal weight group. A greater proportion of non-smokers and smokers were normal weight/underweight than overweight and obese. Among US-born individuals, US-born non-Hispanic Blacks (M = 1.24; SE = 0.01) reported the highest level of discrimination compared to other US-born groups. Among foreign-born individuals, foreign-born Dominicans and non-Hispanic other had the reported the highest level of discrimination compared to other foreign-born groups (see Table 2).
Table 1

Weighted Descriptive Demographics by Weight Statuses: National Epidemiological Survey of Alcohol & Related Conditions (2003–2004); N = 32,747

 

Normal/underweight %

Overweight %

Obese %

p-value

Race/Ethnicity

   

< 0.01

 Non-Hispanic White

28.04%

24.17%

19.39%

 

 Non-Hispanic Black

3.17%

3.65%

4.47%

 

 Mexican

1.74%

2.49%

2.14%

 

 Cuban

0.16%

0.19%

0.13%

 

 Puerto Rican

0.37%

0.55%

0.39%

 

 Central American

0.44%

0.52%

0.31%

 

 South American

0.28%

0.29%

0.15%

 

 Dominican

0.10%

0.09%

0.07%

 

 Non-Hispanic Other

3.42%

1.97%

1.29%

 

Marital Status

   

< 0.01

 Married

22.57%

22.93%

18.31%

 

 Widowed/Divorce

7.49%

6.14%

5.36%

 

 Never Married/Single

7.62%

4.90%

4.67%

 

Gender

   

0.06

 Male

14.53%

19.49%

13.18%

 

 Female

23.16%

14.48%

15.16%

 

Educational Attainment

   

< 0.01

 Less than High School

4.68%

4.87%

4.57%

 

 High School Diploma/GED

9.27%

9.50%

8.82%

 

 Some College/College Graduate

17.77%

15.06%

12.25%

 

 Graduate School

5.97%

4.54%

2.70%

 

Income

   

< 0.01

 Less than $20,000

14.02%

9.95%

9.85%

 

 $20,000 – $35,999

11.71%

11.02%

9.10%

 

 $36,000 – $70,999

8.27%

8.83%

6.88%

 

 $71,000+

3.58%

4.18%

2.52%

 

Current Smoking Status

   

< 0.01

 No

28.60%

26.66%

22.69%

 

 Yes

9.03%

7.34%

5.68%

 

Nativity

   

< 0.01

 U.S. Born

31.91%

28.87%

25.32%

 

 Foreign-Born

5.77%

5.11%

3.03%

 

Census Region

   

0.08

 Northeast

6.70%

5.99%

5.06%

 

 Midwest

6.77%

6.34%

5.42%

 

 South

14.33%

13.00%

11.08%

 

 West

9.89%

8.64%

6.79%

 
 

M (SE)

M (SE)

M (SE)

 

Discrimination (0–5)

1.08 (0.004)

1.08 (0.004)

1.09 (0.004)

< 0.01

Age

44.44 (0.250)

46.17 (0.234)

44.72 (0.225)

< 0.01

Table 2

Multinomial Logistic Regression: Racial Discrimination Levels, Results Stratified by Race/Ethnicity & Nativity: National Epidemiological Survey of Alcohol & Related Conditions – Wave 2 (2003–2004; N = 32,747)

Race/ethnicity

US-born

P-value

 Non-Hispanic White

1.04 (0.002)

0.01

 Non-Hispanic Black

1.24 (0.01)

 

 Mexican American

1.19 (0.02)

 

 Cuban

1.10 (0.03)

 

 Puerto Rican

1.19 (0.02)

 

 Central American

1.09 (0.03)

 

 South American

1.06 (0.02)

 

 Dominican

1.16 (0.05)

 

 Non-Hispanic Other

1.11 (0.02)

 
 

Foreign-born

 

 Non-Hispanic White

1.11 (0.01)

0.01

 Non-Hispanic Black

1.17 (0.03)

 

 Mexican American

1.13 (0.01)

 

 Cuban

1.06 (0.02)

 

 Puerto Rican

1.14 (0.03)

 

 Central American

1.12 (0.02)

 

 South American

1.19 (0.04)

 

 Dominican

1.21 (0.10)

 

 Non-Hispanic Other

1.21 (0.02)

 

Main effects

In assessing the interaction between race/ethnicity and perceived discrimination, Dominicans [aRRR = 0.04; 95% CI (0.01–0.15); p = 0.001] and non-Hispanic Other respondents [aRRR = 0.50; 95% CI (0.30–0.84); p = 0.019) reporting greater perceived discrimination indicated a decreased relative risk of identifying as obese compared to their normal weight counterparts. When assessing the main effect of perceived discrimination and nativity, foreign-born respondents reporting greater perceived discrimination indicated a decreased relative risk of both overweight [aRRR = 0.64; 95% CI (0.51–0.82); p = 0.001] and obese [aRRR = 0.50; 95% CI (0.35–0.70); p = 0.001] compared to their U.S.-born counterparts. Table 3 provides estimates of interaction main effects of perceived discrimination and race/ethnicity and nativity respectively.
Table 3

Multinomial Logistic Regression Analysis of Weight Statuses Impacted by Racial Discrimination: National Epidemiological Survey of Alcohol & Related Conditions – Wave 2 (2003–2004; N = 32,747)

 

Overweight vs. Normal/Underweight

RRR 95% CI

Obese vs. Normal/Underweight

RRR 95% CI

Interactions

Race/Ethnicity*Racial Discrimination

 Non-Hispanic White (ref)

1.00

1.00

 Non-Hispanic Black

0.81 [0.60–1.11]

0.78 [0.56–1.08]

 Mexican

0.92 [0.65–1.30]

0.65 [0.41–1.04]

 Cuban

1.18 [0.42–3.29]

1.45 [0.61–3.43]

 Puerto Rican

0.63 [0.31–1.28]

1.02 [0.51–2.03]

 Central American

1.37 [0.56–3.36]

0.86 [0.37–2.02]

 South American

2.38 [1.16–4.90]

1.20 [0.47–3.11]

 Dominican

0.39 [0.11–1.41]

0.04*** [0.01–0.15]

 Non-Hispanic Other

0.99 [0.62–1.57]

0.50** [0.30–0.84]

Nativity*Racial Discrimination

 U.S. Born (ref)

1.00

1.00

 Foreign Born

0.64*** [0.51–0.82]

0.50*** [0.35–0.70]

All models are adjusted by age(y), personal income, marital status, smoking status, educational attainment, drinking status

a RRR = Relative Risk Ratios

b 95% CI = 95% Confidence Interval

*0.10; **0.050; ***0.001

Three-way interaction

The three-way interaction was significant [F (32, 34) = 3.10; p < 0.001], as well as that for the overweight [F (17, 49) = 3.35; p < 0.001] and obese [F (17, 49) = 5.05; p < 0.001] categories respectively. We present nativity-stratified results of the interaction between perceived discrimination and race/ethnicity to compare and contrast the moderating effects of race/ethnicity and perceived discrimination on overweight/obesity (see Table 4). Results indicate that at mean levels of perceived discrimination, US-born non-Hispanic Blacks had a decreased risk of being obese compared to US-born non-Hispanic Whites [aRRR = 0.71; 95% CI (0.51–0.98); p = 0.04). Among foreign-born individuals, foreign-born South Americans had an increased risk of being overweight at mean levels of perceived discrimination [aRRR = 8.07; 95% CI (1.68–38.77); p = 0.01], whereas foreign-born Dominicans who reported greater perceived discrimination were at a decreased risk of being obese compared to foreign-born non-Hispanic Whites [aRRR = 0.05; 95% CI (0.01–0.20); p < 0.001].
Table 4

Multinomial Logistic Regression: Weight Statuses Impacted by Racial Discrimination, Results Stratified by Nativity: National Epidemiological Survey of Alcohol & Related Conditions – Wave 2 (2003–2004; N = 32,747)

 

Overweight vs. Normal/Underweight

RRRa 95%CIb

Obese vs. Normal/Underweight

RRR 95% CI

Overweight vs. Normal/Underweight

RRR 95% CI

Obese vs. Normal/Underweight

RRR 95% CI

Nativity-Stratified Models

U.S. Born

Foreign-Born

Race/ethnicity*Racial Discrimination

 Non-Hispanic White

1.00

1.00

1.00

1.00

 Non-Hispanic Black

0.76 [0.54–1.07]

0.71** [0.51–0.98]

2.52 [0.57–11.13]

1.73 [0.64–4.69]

 Mexican American

0.98 [0.63–1.56]

0.78 [0.48–1.27]

2.78 [0.65–11.92]

0.57 [0.16–2.07]

 Cuban

2.06 [0.18–23.18]

2.67 [0.33–21.55]

3.94 [0.47–33.08]

1.52 [0.33–7.07]

 Puerto Rican

0.72 [0.22–2.36]

1.66 [0.62–4.45]

2.22 [0.46–10.64]

0.76 [0.21–2.74]

 Central American

3.16 [0.72–13.92]

0.63 [0.07–5.56]

2.99 [0.58–15.48]

1.19 [0.28–5.01]

 South American

1.73 [0.15–20.26]

0.02 [0.00–4.14]

8.07* [1.68–38.77]

1.63 [0.33–7.93]

 Dominican

4.11 [0.02 – N/A]

0.06 [0.00–38.50]

1.25 [0.24–6.64]

0.05*** [0.01–0.20]

 Non-Hispanic Other

1.55 [0.81–2.97]

1.07 [0.56–2.03]

3.03 [0.61–14.96]

0.49 [0.13–1.81]

All models are adjusted by age(y), personal income, marital status, smoking status, educational attainment [Foreign-born models also adjust for length of time in the U.S.]

a RRR = Relative Risk Ratios

b 95%CI = 95% Confidence Interval

*0.10; **0.050; ***0.001

Discussion

To the best of our knowledge, this was the first study to examine the interaction between perceived discrimination, race/ethnicity, nativity on overweight/obesity across a multiracial/ethnic sample of adults. We found a three-way interaction between perceived discrimination, race/ethnicity, and nativity status on obesity. Contrary to our expectations, we found that, at mean levels of perceived discrimination, US-born non-Hispanic Blacks had lower risk of being obese compared to US-born non-Hispanic Whites. Nevertheless, other studies have found similar results. For example, Vines and colleagues found that higher perceived racism was associated with a lower waist-to-hip ratio among African American women [39]. Another study found that greater discrimination was associated with poor physical functioning for White women, but not for Black Women [58]. Vines and colleagues also found a negative indirect effect of discrimination on physical health through self-esteem for White women only. Some researchers speculate that the awareness of discrimination may serve as a protective factor for non-Hispanic Blacks. Versey and Curtin [58] suggest that Whites are more likely to devalue the self as a consequence of unfair treatment, whereas Blacks may attribute experiences of unfair treatment to an unjust system rather than the self, which in turn can be protective to adverse health effects [58]. Contrary to Jackson et al.’s suggestion that Blacks may engage in unhealthy behaviors as stress coping strategies [59], it may also be the case that US born non-Hispanic Blacks may engage in healthy coping activities (e.g., exercise) that leads to some healthy outcomes, such as lower weight gain [39]. Further research is needed to examine the mechanism by which perceived discrimination may lead to lower obesity among US born non-Hispanic Blacks [53].

It is important to mention that US-born non-Hispanic Blacks still have higher rates of overweight/obesity compared to US-born non-Hispanic Whites [2]. There might be other psychosocial stressors that increase the risk of obesity for US-born non-Hispanic Blacks. US-born non-Hispanic Blacks report experiencing greater exposure to common stressors (e.g., financial strain, relationship problems) concurrent with greater exposure to race-related stressors (e.g., racial discrimination) than their White counterparts [60, 61]. A recent study shows that greater cumulative exposure to a wide range of stressors is associated with greater odds of obesity [35]. Future research needs to consider wider range of psychosocial stressors that may concurrently increase the risk of overweight/obesity for US-born racial/ethnic minority groups.

Compared to foreign-born non-Hispanic Whites, we found that foreign-born South Americans had higher risk of being overweight, whereas foreign-born Dominicans had lower risk of being obese at mean levels of perceived discrimination. Differences in migration patterns and sociopolitical histories, particularly among Hispanics/Latinos, may play a role in how foreign-born immigrants perceive and respond to unfair treatment attributed to race/ethnicity. The reasons for migration can affect how immigrants interact with their social environment [62]. Due to political and economic insecurity, large waves of Dominican immigrants have obtained permanent residency in the US [63, 64]. Dominican immigrants in the US suffer from high unemployment rates and other social barriers, such as poor access to care [65]. While racial discrimination may be a part of foreign-born Dominicans’ lived experiences, other stressors (e.g., employment stress) may play more prominent roles in their daily lives. Therefore, the health effects of discrimination may not be as potent compared to other groups. The inverse relationship between discrimination and obesity may also reflect unique coping behaviors to discrimination for Dominicans. However, very little research has examined coping behaviors within this Hispanic/Latino subgroup. Future research is needed to examine how Dominicans cope with race-related stressors like discrimination.

South Americans have differing migration patterns compared to Dominicans. They are more likely to enter the U.S. as professionals through employment-based visas [66]. Employment may expose South American immigrants to more instances of racial/ethnic discrimination in different social contexts (e.g., workplace, healthcare). This new stressor may influence foreign-born South Americans to engage in health-compromising coping behaviors. For instance, there is compelling evidence that poor sleep quality predict the development of obesity [67, 68, 69]. Limited research shows that ethnic discrimination is associated with daytime sleepiness, and short and long sleep duration among Hispanic/Latinos [70]. Individuals of South American background report shorter sleep durations and higher levels of sleepiness compared to other Hispanic/Latino subgroups [71]. It may be that exposure to discrimination may have a greater effect on obesity-related risk factors for South American immigrants. Nevertheless, future research is needed to better understand how nativity status may affect the relationship between perceived discrimination and obesity-related behaviors for this group.

There are limitations to consider in our study. We only had access to Wave 2 NESARC data and so this preliminary study was cross-sectional, which precludes the assumptions of causal associations between discrimination and obesity. It may be that those who are obese are more likely to experience racial/ethnic discrimination. However, Hunte found that everyday discrimination predicted an increase in waist circumference over time [36]. Our study examined only one aspect of discrimination. We used the Experiences of Discrimination scale, which captures discriminatory experiences that are acute and apparent [52]. It may be that acute forms of racial discrimination may have a greater influence overweight/obesity risk for certain groups, whereas chronic, more subtle forms of unfair treatment may be more deleterious to health for others [72]. Future studies should examine the effects that acute and chronic forms of discrimination may have on overweight/obesity across racial/ethnic groups. Discrimination may increase the risk of obesity through behavioral and psychological pathways [54]. The ways in which individuals respond to stressors may depend on their membership to racial/ethnic groups and nativity status. Future studies should examine the effects of discrimination on obesity-related behaviors (e.g., diet, sleep, physical activity) and how they may differ based on race/ethnicity and nativity. In addition, we only measured one aspect of acculturation (i.e., nativity). Acculturation is multidimensional construct and different acculturation process (e.g., degree to which one endorses the culture of the host country) may interact with social experiences and health differently [73]. Examining different aspects of acculturation (e.g., psychological acculturation, language use) would allow researchers to better understand immigrants’ experiences with discrimination.

Along with conceptual limitations, there are also methodological limitations to consider. The confidence intervals for some racial/ethnic groups, such as US-born Dominicans, were wide, which is indicative of the small sample sizes in the study. Our findings need to be replicated with larger sample sizes to better measure the association between discrimination and obesity. In addition, we did not adjust for urban/rural place of residence. Studies find the perception of discrimination and rates of obesity vary by urbanization [74, 75, 76]. Non-Whites are majorities in most urban counties [77], which may influence perception of discrimination for Whites and non-Whites. Future research should consider the level of urbanization in the relationship between perceived discrimination and obesity. Finally, this study used a single measure of adiposity (i.e., BMI) to assess obesity. While it is a reliable and valid measure that is commonly used to assess obesity-related morbidity and mortality [78, 79, 80], further research using additional adiposity measures would allow us to better capture obesity disparities and factors that help explain existing differences.

Conclusion

Perceived discrimination may be a risk factor for obesity. Nativity status and race/ethnicity may play key roles in the relationship between perceived discrimination and overweight/obesity. Greater perceived discrimination was associated with lower risk of obesity among US-born non-Hispanic Blacks, whereas greater discrimination was associated with higher risk of overweight for foreign-born South Americans and lower risk of obesity among foreign-born Dominicans. More research is needed to identify the pathways that may link perceived discrimination to obesity among these groups. Perceived discrimination remains a significant stressor for racial/ethnic minorities and contributes to overall racial/ethnic health disparities. Psychosocial interventions aimed at reducing discrimination-related stress might help to reduce the obesogenic consequences of discrimination.

Notes

Acknowledgements

Not applicable.

Authors’ contributions

AGC contributed to the conceptualization and writing of the manuscript; KO assisted with analyses, writing of the manuscript, and interpretation of the results; YR assisted with interpretation of the results and writing of the manuscript. All authors have read and approved the manuscript.

Funding

This project was partially supported by the National Institute of Health 3R25CA057711. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. The development of the manuscript was partially supported by Cancer Disparities Research Network/Geographic Management Program (GMaP) Region 4 funded by 3 P30 CA006927-52S2 and CTSI Mentored Career Development Award (KL2 TR002545). The funders did not influence the design of the study and collection, analysis, nor the interpretation of data and writing the manuscript.

Ethics approval and consent to participate

De-identified data for this study were obtained after completing an internal data use agreement with the National Epidemiologic Survey on Alcohol and Related Conditions committee. This study was approved by the Institutional Review Board at Harvard T.H. Chan School of Public Health.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References

  1. 1.
    Flegal KM, Kruszon-Moran D, Carroll MD, Fryar CD, Ogden CL. Trends in obesity among adults in the United States, 2005 to 2014. JAMA. 2016;315(21):2284–91.  https://doi.org/10.1001/jama.2016.6458.CrossRefPubMedGoogle Scholar
  2. 2.
    Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 2006;295(13):1549–55.  https://doi.org/10.1001/jama.295.13.1549.CrossRefPubMedGoogle Scholar
  3. 3.
    Vucenik I, Stains JP. Obesity and cancer risk: evidence, mechanisms, and recommendations. Ann N Y Acad Sci. 2012;1271(1):37–43.  https://doi.org/10.1111/j.1749-6632.2012.06750.x.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Arteaga CL, Adamson PC, Engelman JA, et al. AACR Cancer Progress report 2014. Clin Cancer Res. 2014;20(19 Supplement):S1–S112.  https://doi.org/10.1158/1078-0432.CCR-14-2123.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Zhang H, Rodriguez-Monguio R. Racial disparities in the risk of developing obesity-related diseases: a cross-sectional study. Ethn Dis. 2012;22(3):308–16.PubMedGoogle Scholar
  6. 6.
    Spanakis EK, Golden SH. Race/Ethnic Difference in Diabetes and Diabetic Complications. Curr Diab Rep. 2013;13(6).  https://doi.org/10.1007/s11892-013-0421-9.CrossRefGoogle Scholar
  7. 7.
    Hruby A, Hu FB. The epidemiology of obesity: a big picture. PharmacoEconomics. 2015;33(7):673–89.  https://doi.org/10.1007/s40273-014-0243-x.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Zilanawala A, Davis-Kean P, Nazroo J, Sacker A, Simonton S, Kelly Y. Race/ethnic disparities in early childhood BMI, obesity and overweight in the United Kingdom and United States. Int J Obes. 2015;39(3):520–9.  https://doi.org/10.1038/ijo.2014.171.CrossRefGoogle Scholar
  9. 9.
    Krueger PM, Coleman-Minahan K, Rooks RN. Race/ethnicity, nativity and trends in BMI among U.S. adults. Obesity. 2014;22(7):1739–46.  https://doi.org/10.1002/oby.20744.CrossRefPubMedGoogle Scholar
  10. 10.
    Wen M, Kowaleski-Jones L, Fan JX. Ethnic-immigrant disparities in Total and abdominal obesity in the US. Am J Health Behav. 2013;37(6):807–18.  https://doi.org/10.5993/AJHB.37.6.10.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Ledoux TA, Hingle MD, Baranowski T. Relationship of fruit and vegetable intake with adiposity: a systematic review. Obes Rev Off J Int Assoc Study Obes. 2011;12(5):e143–50.  https://doi.org/10.1111/j.1467-789X.2010.00786.x.CrossRefGoogle Scholar
  12. 12.
    Wiklund P. The role of physical activity and exercise in obesity and weight management: time for critical appraisal. J Sport Health Sci. 2016;5(2):151–4.  https://doi.org/10.1016/j.jshs.2016.04.001.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    August KJ, Sorkin DH. Racial/ethnic disparities in exercise and dietary behaviors of middle-aged and older adults. J Gen Intern Med. 2011;26(3):245–50.  https://doi.org/10.1007/s11606-010-1514-7.CrossRefPubMedGoogle Scholar
  14. 14.
    Anderson NB, Bulatao RA, Cohen B, National Research Council (US) Panel on Race E. Racial/Ethnic Disparities in Health Behaviors: A Challenge to Current Assumptions: National Academies Press (US); 2004. https://www.ncbi.nlm.nih.gov/books/NBK25518/. Accessed 19 Feb 2019
  15. 15.
    Wang Y, Beydoun MA. The obesity epidemic in the United States—gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a systematic review and meta-regression analysis. Epidemiol Rev. 2007;29(1):6–28.  https://doi.org/10.1093/epirev/mxm007.CrossRefPubMedGoogle Scholar
  16. 16.
    Wen M, Fan JX, Kowaleski-Jones L, Wan N. Rural-urban disparities in obesity prevalence among working age adults in the United States: exploring the mechanisms. Am J Health Promot AJHP. 2018;32(2):400–8.  https://doi.org/10.1177/0890117116689488.CrossRefPubMedGoogle Scholar
  17. 17.
    Lundeen EA. Obesity Prevalence Among Adults Living in Metropolitan and Nonmetropolitan Counties — United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67.  https://doi.org/10.15585/mmwr.mm6723a1.CrossRefGoogle Scholar
  18. 18.
    Ogden CL, Fakhouri TH, Carroll MD, et al. Prevalence of Obesity Among Adults, by Household Income and Education — United States, 2011–2014. MMWR Morb Mortal Wkly Rep. 2017;66(50):1369–73.  https://doi.org/10.15585/mmwr.mm6650a1.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Fradkin C, Wallander JL, Elliott MN, Tortolero S, Cuccaro P, Schuster MA. Associations between socioeconomic status and obesity in diverse, young adolescents: variation across race/ethnicity and gender. Health Psychol Off J Div Health Psychol Am Psychol Assoc. 2015;34(1):1–9.  https://doi.org/10.1037/hea0000099.CrossRefGoogle Scholar
  20. 20.
    Sánchez-Vaznaugh EV, Kawachi I, Subramanian SV, Sánchez BN, Acevedo-Garcia D. Do socioeconomic gradients in body mass index vary by race/ethnicity, gender, and birthplace? Am J Epidemiol. 2009;169(9):1102–12.  https://doi.org/10.1093/aje/kwp027.CrossRefPubMedGoogle Scholar
  21. 21.
    Antecol H, Bedard K. Unhealthy assimilation: why do immigrants converge to American health status levels? Demography. 2006;43(2):337–60.  https://doi.org/10.1353/dem.2006.0011.CrossRefPubMedGoogle Scholar
  22. 22.
    Cagney KA, Browning CR, Wallace DM. The Latino paradox in neighborhood context: the case of asthma and other respiratory conditions. Am J Public Health. 2007;97(5):919–25.  https://doi.org/10.2105/AJPH.2005.071472.CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Vega WA, Rodriguez MA, Gruskin E. Health disparities in the Latino population. Epidemiol Rev. 2009;31(1):99–112.  https://doi.org/10.1093/epirev/mxp008.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Eschbach K, Stimpson JP, Kuo Y-F, Goodwin JS. Mortality of foreign-born and US-born Hispanic adults at younger ages: a reexamination of recent patterns. Am J Public Health. 2007;97(7):1297–304.  https://doi.org/10.2105/AJPH.2006.094193.CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Pinheiro PS, Callahan KE, Gomez SL, et al. High cancer mortality for US-born Latinos: evidence from California and Texas. BMC Cancer. 2017;17.  https://doi.org/10.1186/s12885-017-3469-0.
  26. 26.
    Tomiyama AJ. Stress and obesity. Annu Rev Psychol. 2019;70:703–18.CrossRefGoogle Scholar
  27. 27.
    Ouakinin SRS, Barreira DP, Gois CJ. Depression and obesity: integrating the role of stress, neuroendocrine dysfunction and inflammatory pathways. Front Endocrinol. 2018;9.  https://doi.org/10.3389/fendo.2018.00431.
  28. 28.
    Hammen C. Stress and depression. Annu Rev Clin Psychol. 2004;1(1):293–319.  https://doi.org/10.1146/annurev.clinpsy.1.102803.143938.CrossRefGoogle Scholar
  29. 29.
    Luppino FS, de Wit LM, Bouvy PF, et al. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry. 2010;67(3):220–9.  https://doi.org/10.1001/archgenpsychiatry.2010.2.CrossRefPubMedGoogle Scholar
  30. 30.
    Novelle MG, Diéguez C. Food addiction and binge eating: lessons learned from animal models. Nutrients. 2018;10(1):71.CrossRefGoogle Scholar
  31. 31.
    Stults-Kolehmainen MA, Sinha R. The effects of stress on physical activity and exercise. Sports Med Auckl NZ. 2014;44(1):81–121.  https://doi.org/10.1007/s40279-013-0090-5.CrossRefGoogle Scholar
  32. 32.
    Cuevas AG, Williams DR, Albert MA. Psychosocial factors and hypertension: a review of the literature. Cardiol Clin. 2017;35(2):223–30.  https://doi.org/10.1016/j.ccl.2016.12.004.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Paradies Y, Ben J, Denson N, et al. Racism as a determinant of health: a systematic review and meta-analysis. PLoS One. 2015;10(9):e0138511.  https://doi.org/10.1371/journal.pone.0138511.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Williams DR, Priest N, Anderson N. Understanding associations between race, socioeconomic status and health: patterns and prospects. Health Psychol Off J Div Health Psychol Am Psychol Assoc. 2016;35(4):407–11.  https://doi.org/10.1037/hea0000242.CrossRefGoogle Scholar
  35. 35.
    Cuevas AG, Chen R, Thurber KA, Slopen N, Williams DR. Psychosocial stress and overweight and obesity: findings from the Chicago community adult health study. Ann Behav Med. 2019.  https://doi.org/10.1093/abm/kaz008.CrossRefGoogle Scholar
  36. 36.
    Hunte HER. Association between perceived interpersonal everyday discrimination and waist circumference over a 9-year period in the midlife development in the United States cohort study. Am J Epidemiol. 2011;173(11):1232–9.  https://doi.org/10.1093/aje/kwq463.CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Hunte HER, Williams DR. The association between perceived discrimination and obesity in a population-based multiracial and multiethnic adult sample. Am J Public Health. 2009;99(7):1285–92.  https://doi.org/10.2105/AJPH.2007.128090.CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Lewis TT, Kravitz HM, Janssen I, Powell LH. Self-reported experiences of discrimination and visceral fat in middle-aged African-American and Caucasian women. Am J Epidemiol. 2011;173(11):1223–31.  https://doi.org/10.1093/aje/kwq466.CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Vines AI, Baird DD, Stevens J, Hertz-Picciotto I, Light KC, McNeilly M. Associations of abdominal fat with perceived racism and passive emotional responses to racism in African American women. Am J Public Health. 2007;97(3):526–30.  https://doi.org/10.2105/AJPH.2005.080663.CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Brondolo E, Rahim R, Grimaldi S, Ashraf A, Bui N, Schwartz J. Place of birth effects on self-reported discrimination: variations by type of discrimination. Int J Intercult Relat IJIR. 2015;49:212–22.  https://doi.org/10.1016/j.ijintrel.2015.10.001.CrossRefPubMedGoogle Scholar
  41. 41.
    Araujo-Dawson B. Understanding the complexities of skin color, perceptions of race, and discrimination among Cubans, Dominicans, and Puerto Ricans. Hisp J Behav Sci. 2015;37(2):243–56.  https://doi.org/10.1177/0739986314560850.CrossRefGoogle Scholar
  42. 42.
    Smart JF, Smart DW. Acculturative stress: the experience of the Hispanic immigrant. Couns Psychol. 1995;23(1):25–42.  https://doi.org/10.1177/0011000095231003.CrossRefGoogle Scholar
  43. 43.
    Arellano-Morales L, Roesch SC, Gallo LC, et al. Prevalence and correlates of perceived ethnic discrimination in the Hispanic community health study/study of Latinos sociocultural ancillary study. J Lat Psychol. 2015;3(3):160–76.  https://doi.org/10.1037/lat0000040.CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Deaux K, Bikmen N, Gilkes A, et al. Becoming American: stereotype threat effects in afro-Caribbean immigrant groups. Soc Psychol Q. 2007;70(4):384–404.CrossRefGoogle Scholar
  45. 45.
    Bonnie RJ, Stroud C, Breiner H, et al. Diversity and the Effects of Bias and Discrimination on Young Adults’ Health and Well-Being. National Academies Press (US); 2015. https://www.ncbi.nlm.nih.gov/books/NBK284777/. Accessed 13 Apr 2019.
  46. 46.
    Burt CH, Simons RL, Gibbons FX. Racial discrimination, ethnic-racial socialization, and crime: a micro-sociological model of risk and resilience. Am Sociol Rev. 2012;77(4):648–77.  https://doi.org/10.1177/0003122412448648.CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Pérez DJ, Fortuna L, Alegria M. Prevalence and correlates of everyday discrimination among U.S. Latinos. J Community Psychol. 2008;36(4):421–33.  https://doi.org/10.1002/jcop.20221.CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Hasin DS, Grant BF. The National Epidemiologic Survey on alcohol and related conditions (NESARC) waves 1 and 2: review and summary of findings. Soc Psychiatry Psychiatr Epidemiol. 2015;50(11):1609–40.  https://doi.org/10.1007/s00127-015-1088-0.CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    National Institutes of Health. National Institute on Alcohol Abuse and Alcoholism (September 2010). Alcohol use and alcohol use disorders in the United States, a 3-year follow-up: Main findings from the 2004–2005 wave 2 National Epidemiologic Survey on alcohol and related conditions (NESARC). US Alcohol Epidemiol Data Ref Man. 2010;8(2).Google Scholar
  50. 50.
    Ruan WJ, Goldstein RB, Chou SP, et al. The alcohol use disorder and associated disabilities interview schedule-IV (AUDADIS-IV): reliability of new psychiatric diagnostic modules and risk factors in a general population sample. Drug Alcohol Depend. 2008;92(1–3):27–36.  https://doi.org/10.1016/j.drugalcdep.2007.06.001.CrossRefPubMedGoogle Scholar
  51. 51.
    Udo T, Purcell K, Grilo CM. Perceived weight discrimination and chronic medical conditions in adults with overweight and obesity. Int J Clin Pract. 2016;70(12):1003–11.  https://doi.org/10.1111/ijcp.12902.CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Krieger N, Smith K, Naishadham D, Hartman C, Barbeau EM. Experiences of discrimination: validity and reliability of a self-report measure for population health research on racism and health. Soc Sci Med. 2005;61(7):1576–96.  https://doi.org/10.1016/j.socscimed.2005.03.006.CrossRefPubMedGoogle Scholar
  53. 53.
    Williams DR, Mohammed SA. Discrimination and racial disparities in health: evidence and needed research. J Behav Med. 2009;32(1):20.  https://doi.org/10.1007/s10865-008-9185-0.CrossRefPubMedGoogle Scholar
  54. 54.
    Pascoe EA, Smart RL. Perceived discrimination and health: a meta-analytic review. Psychol Bull. 2009;135(4):531–54.  https://doi.org/10.1037/a0016059.CrossRefPubMedPubMedCentralGoogle Scholar
  55. 55.
    Kim G, Parmelee P, Bryant AN, et al. Geographic region matters in the relation between perceived racial discrimination and psychiatric disorders among black older adults. The Gerontologist. 2017;57(6):1142–7.  https://doi.org/10.1093/geront/gnw129.CrossRefPubMedGoogle Scholar
  56. 56.
    Lawless MH, Harrison KA, Grandits GA, Eberly LE, Allen SS. Perceived stress and smoking-related behaviors and symptomatology in male and female smokers. Addict Behav. 2015;51:80–3.  https://doi.org/10.1016/j.addbeh.2015.07.011.CrossRefPubMedPubMedCentralGoogle Scholar
  57. 57.
    StataCorp. Stata Statistical Software: Release 14. College Station; 2015.Google Scholar
  58. 58.
    Versey HS, Curtin N. The differential impact of discrimination on health among black and white women. Soc Sci Res. 2016;57:99–115.  https://doi.org/10.1016/j.ssresearch.2015.12.012.CrossRefPubMedGoogle Scholar
  59. 59.
    Jackson JS, Knight KM, Rafferty JA. Race and unhealthy behaviors: chronic stress, the HPA Axis, and physical and mental health disparities over the life course. Am J Public Health. 2010;100(5):933–9.  https://doi.org/10.2105/AJPH.2008.143446.CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Sternthal MJ, Slopen N, Williams DR. Racial disparities in health: how much does stress really matter? Bois Rev Soc Sci Res Race. 2011;8(01):95–113.  https://doi.org/10.1017/S1742058X11000087.CrossRefGoogle Scholar
  61. 61.
    Slopen N, Williams DR. Discrimination, other psychosocial stressors, and self-reported sleep duration and difficulties. Sleep. 2014;37(1):147–56.  https://doi.org/10.5665/sleep.3326.CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Schwartz SJ, Salas-Wright CP, Pérez-Gómez A, et al. Cultural stress and psychological symptoms in recent Venezuelan immigrants to the United States and Colombia. Int J Intercult Relat. 2018;67:25–34.CrossRefGoogle Scholar
  63. 63.
    Rytina N. Estimates of the legal permanent resident population in 2008. Off Immigr Stat Policy Dir US Dep Homel Secur. 2009; http://www.dhs.gov/xlibrary/assets/statistics/publications/lpr_pe_2007.Pdf.
  64. 64.
    Hoffnung-Garskof J. A tale of two cities: Santo Domingo and New York after 1950: Princeton University Press; 2010.Google Scholar
  65. 65.
    Oropesa RS, Jensen L. Dominican immigrants and discrimination in a new destination: the case of Reading, Pennsylvania*. City Community. 2010;9(3):274–98.  https://doi.org/10.1111/j.1540-6040.2010.01330.x.CrossRefPubMedPubMedCentralGoogle Scholar
  66. 66.
    Fuligni AJ, Perreira KM. Immigration and adaptation. Handb US Lat Psychol Dev Community-Based Perspect. 2009:99–113.Google Scholar
  67. 67.
    Bayon V, Leger D, Gomez-Merino D, Vecchierini M-F, Chennaoui M. Sleep debt and obesity. Ann Med. 2014;46(5):264–72.  https://doi.org/10.3109/07853890.2014.931103.CrossRefPubMedGoogle Scholar
  68. 68.
    Zimberg IZ, Dâmaso A, Del Re M, et al. Short sleep duration and obesity: mechanisms and future perspectives. Cell Biochem Funct. 2012;30(6):524–9.  https://doi.org/10.1002/cbf.2832.CrossRefPubMedGoogle Scholar
  69. 69.
    Beccuti G, Pannain S. Sleep and obesity. Curr Opin Clin Nutr Metab Care. 2011;14(4):402–12.  https://doi.org/10.1097/MCO.0b013e3283479109.CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    Alcántara C, Patel SR, Carnethon M, et al. Stress and sleep: results from the Hispanic community health study/study of Latinos sociocultural ancillary study. SSM - Popul Health. 2017;3:713–21.  https://doi.org/10.1016/j.ssmph.2017.08.004.CrossRefPubMedPubMedCentralGoogle Scholar
  71. 71.
    Redline S, Sotres-Alvarez D, Loredo J, et al. Sleep-disordered breathing in Hispanic/Latino individuals of diverse backgrounds. The Hispanic community health study/study of Latinos. Am J Respir Crit Care Med. 2014;189(3):335–44.  https://doi.org/10.1164/rccm.201309-1735OC.CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.
    Williams DR. Race, socioeconomic status, and health: the added effects of racism and discrimination. Ann N Y Acad Sci. 1999;896:173–88.CrossRefGoogle Scholar
  73. 73.
    Abraído-Lanza AF, Echeverría SE, Flórez KR. Latino immigrants, acculturation, and health: promising new directions in research. Annu Rev Public Health. 2016;37(1):219–36.  https://doi.org/10.1146/annurev-publhealth-032315-021545.CrossRefPubMedPubMedCentralGoogle Scholar
  74. 74.
    Patten E. The black-white and urban-rural divides in perceptions of racial fairness. Pew Res Cent. 2013.Google Scholar
  75. 75.
    Befort CA, Nazir N, Perri MG. Prevalence of obesity among adults from rural and urban areas of the United States: findings from NHANES (2005–2008). J Rural Health Off J Am Rural Health Assoc Natl Rural Health Care Assoc. 2012;28(4):392–7.  https://doi.org/10.1111/j.1748-0361.2012.00411.x.CrossRefGoogle Scholar
  76. 76.
    National Public Radio (NPR) the RWJF and the Harvard TH Chan School of Public Health. Discrimination in America: Experiences and Views of African Americans. 2017.Google Scholar
  77. 77.
    Pew Research Center. Demographic and economic trends in urban, suburban and rural communities | Pew Research Center. 2018. https://www.pewsocialtrends.org/2018/05/22/demographic-and-economic-trends-in-urban-suburban-and-rural-communities/. Accessed 13 Apr 2019.Google Scholar
  78. 78.
    Stein CJ, Colditz GA. The epidemic of obesity. J Clin Endocrinol Metab. 2004;89(6):2522–5.  https://doi.org/10.1210/jc.2004-0288.CrossRefPubMedGoogle Scholar
  79. 79.
    Rothman KJ. BMI-related errors in the measurement of obesity. Int J Obes. 2008;32(S3):ijo200887.  https://doi.org/10.1038/ijo.2008.87.CrossRefGoogle Scholar
  80. 80.
    US Preventive Services Task Force. Screening for obesity in adults: recommendations and rationale. Ann Intern Med. 2003;139(11):930.CrossRefGoogle Scholar

Copyright information

© The Author(s). 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  1. 1.Department of Community HealthTufts UniversityMedfordUSA
  2. 2.Department of Sociology & CriminologyUniversity of New MexicoAlbuquerqueUSA
  3. 3.Department of Social & Behavioral SciencesYale School of Public HealthNew HavenUSA

Personalised recommendations