Operationalizing Structural Racism - Dennis et al
racism on Asian Americans, Na- Conflict of Interest Divide. New York: NYU Press; 2008.
tive Pacific Islanders, and Native No conflicts of interest to report. 13. Bonilla-Silva E, Dietrich DR. The Latin
Hawaiians. This gap merits fur- Author Contributions
ther population-specific research. Research concept and design: Den- Americanization of Racial Stratification
nis, Wilbur; Acquisition of data: Den- in the U.S. In: Hall RE, ed. Racism in
Conclusion nis, Chung, Lodge, Martinez, Wilbur; the 21st Century: An Empirical Analysis
Data analysis and interpretation: Den- of Skin Color. New York, NY: Springer
We outline a framework for op- nis, Chung, Lodge, Martinez, Wilbur; New York; 2008:151-170, https://doi.
erationalizing structural racism as Manuscript draft: Dennis, Chung, Lodge, org/10.1007/978-0-387-79098-5_9
it relates to health disparities re- Martinez, Wilbur; Administrative: Dennis, 14. Bailey ZD, Krieger N, Agénor M, Graves
search in the United States. Care- Chung, Lodge, Martinez, Wilbur; Supervi- J, Linos N, Bassett MT. Structural rac-
fully considering the experiences of sion: Dennis ism and health inequities in the USA:
different racial and ethnic popula- References evidence and interventions. Lancet.
tions across time is important for 2017;389(10077):1453-1463. https://doi.
generating a literature that captures 1. Phelan JC, Link BG. Is racism a fundamen- org/10.1016/S0140-6736(17)30569-X
the varying effects of structural rac- tal cause of inequalities in health? Annu Rev PMID:28402827
ism on health both historically and Sociol. 2015;41(1):311-330. https://doi. 15. Dunbar-Ortiz R. An Indigenous Peoples’
today. The framework presented org/10.1146/annurev-soc-073014-112305 History of the United States. Boston: Beacon
here should help future scholars Press; 2014.
across disciplines identify and ques- 2. Groos M, Wallace M, Hardeman R, 16. Kovich H. Rural Matters - Coronavi-
tion important laws, policies, and Theall KP. Measuring inequity: a system- rus and the Navajo Nation. N Engl J
norms that have differentially con- atic review of methods used to quantify Med. 2020;383(2):105-107. https://
strained opportunities for health structural racism. J Health Dispar Res Pract. doi.org/10.1056/NEJMp2012114
across racial and ethnic groups. 2018;11(2):Article 13. https://digitalschol- PMID:32329970
arship.unlv.edu/jhdrp/vol11/iss2/13 17. Sequist TD. The disproportionate impact
Acknowledgments of COVID-19 on communities of color.
The authors wish to thank Robert A. 3. Omi M, Winant H. Racial Formation in N Engl J Med Catalyst. July, 2020. https://
Hummer for his thoughtful feedback on the United States. 3rd ed. New York, NY: catalyst.nejm.org/doi/full/10.1056/
this commentary. This work was supported Routledge; 2015. CAT.20.0370
by the Population Research Infrastructure 18. Hine DC, Hine WC, Harrold S. The
Program (P2CHD050924), the Population 4. Williams DR, Lawrence JA, Davis African-American Odyssey. Vol I, 4th ed.
Research Training Grant (T32HD007168) BA. Racism and health: evidence and Upper Saddle River, New Jersey: Pearson
and the Interdisciplinary Training in needed research. Annu Rev Public Health. Prentice Hall; 2008.
Life Course Research Training Grant 2019;40:105-125. https://doi.org/10.1146/ 19. Wilkins DE, Lomawaima TK. Uneven
(T32HD091058) awarded to the Uni- annurev-publhealth-040218-043750 Ground: American Indian Sovereignty and
versity of North Carolina at Chapel Hill Federal Law. Norman: University of Okla-
by the Eunice Kennedy Shriver National 5. Bonilla-Silva E. Rethinking racism: toward homa Press; 2001.
Institute of Child Health and Human a structural interpretation. Am Sociol 20. Cerasano HE. The Indian Health Service:
Development. Additionally, this work was Rev. 1997;62(3):465-480. https://doi. barriers to health care and strategies for
supported by the Biostatistics for Research org/10.2307/2657316 improvement. Georget J Poverty Law Policy.
in Environmental Health Training Grant 2017;24(3):421-439.
(T32ES007018) awarded to the Univer- 6. Mills CW. The Racial Contract. Ithaca, NY: 21. Native American Rights Fund. Trigger
sity of North Carolina at Chapel Hill by Cornell University Press; 1999. Points: Current State of Research on History,
the National Institute of Environmental Impacts, and Healing Related to the United
Health Sciences. This content is solely the 7. Powell JA. Structural Racism: Building States’ Indian Industrial/Boarding School
responsibility of the authors and does not upon the Insights of John Calmore. N C Policy. Boulder, Colorado: Native American
necessarily represent the official views of LAW Rev. 2008;86(3):791. Rights Fund; 2019:1-104.
the National Institutes of Health. 22. Lindsay BC. Murder State: California’s
8. Reskin B. The race discrimination Native American Genocide, 1846-1873.
system. Annu Rev Sociol. 2012;38(1):17- Lincoln, Nebraska: University of Nebraska
35. https://doi.org/10.1146/annurev- Press; 2012. https://doi.org/10.2307/j.
soc-071811-145508 ctt1d9nqs3
23. Title II: Assisted Housing for Indians and
9. Pincus F. Discrimination comes Alaska Natives. Public Law 100-358. Statute
in many forms: individual, institu- 102 676, Code 42 U.S.C. 1437aa. June 29,
tional, and structural. Am Behav Sci. 1988.
1996;40(2):186-194. https://doi. 24. McCollum Letter Urges Greater Army Corps
org/10.1177/0002764296040002009 Consultation with Standing Rock Sioux on
Dakota Access Pipeline. Press Release. Sep-
10. Angermeyer MC, Matschinger H, Link BG, tember 14, 2016. Last accessed December
Schomerus G. Public attitudes regarding 14, 2020 from https://mccollum.house.gov/
individual and structural discrimination: press-release/mccollum-urges-further-army-
two sides of the same coin? Soc Sci Med. corps-consultation-standing-rock-sioux-
2014;103:60-66. https://doi.org/10.1016/j. dakota-access
socscimed.2013.11.014 PMID:24507911 25. Warhol L. Creating official language policy
11. Yancey G. Who Is White? Latinos, Asians,
and the New Black/Nonblack Divide. Boul-
der, CO: Lynne Rienner Publishers; 2003.
12. O’Brien E. The Racial Middle; Latinos and
Asian Americans Living beyond the Racial
Ethnicity & Disease, Volume 31, Supplement 1, 2021 309
Created for free by https://foxyutils.com
Operationalizing Structural Racism - Dennis et al
from local practice: the example of the Na-
tive American Languages Act 1990/1992.
Lang Policy. 2012;11(3):235-252. https://
doi.org/10.1007/s10993-012-9248-5
26. Staurowsky EJ. “You know, we are all
Indian”: exploring white power and
privilege in reactions to the NCAA Na-
tive American mascot policy. J Sport Soc
Issues. 2007;31(1):61-76. https://doi.
org/10.1177/0193723506296825
27. Cunningham PJ. Access to care in the
Indian Health Service. Health Aff (Mill-
wood). 1993;12(3):224-233. https://
doi.org/10.1377/hlthaff.12.3.224
PMID:8244235
28. Indian Health Care Improvement Act, 25
U.S.C. 1601-1672. Last accessed December
14, 2020 from https://www.ihs.gov/ihcia/
29. Eliassen M. Indian Child Welfare Act. In:
Cousins LH, ed. Encyclopedia of Human Ser-
vices and Diversity. Vol 1. Thousand Oaks,
CA: SAGE Publications, Inc; 2014:701-
702,
310 Ethnicity & Disease, Volume 31, Supplement 1, 2021
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Original Report Structural Racism and Immigrant
Health: Exploring the Association
Between Wage Theft, Mental Health,
and Injury among Latino Day Laborers
Maria Eugenia Fernández-Esquer, PhD1; Lynn N. Ibekwe, MPH1;
Rosalia Guerrero-Luera, MBA2; Yesmel A. King, MA1;
Casey P. Durand, PhD1; John S. Atkinson, DrPH1
Background: Although wage theft has been Introduction workers never report or pursue ac-
discussed primarily as a labor and human tion against their employer. Though
rights issue, it can be conceptualized as an Wage theft, defined as purpose- wage theft is a common labor law
issue of structural racism with important fully withholding payment or the violation experienced by US work-
consequences for immigrant health. underpayment of wages for com- ers, those most likely to experience
Objectives: The objectives of this study pleted work,1,2 is typically discussed it include low-income and racial/
were to: 1) identify sociodemographic, as a labor and human rights issue ethnic minority workers such as
employment, and stress-related characteris- but is also a manifestation of struc- Latino day laborers (LDLs).1,2 For
tics that increase Latino day laborers’ odds tural racism with serious implica- LDLs, wage theft is only possible
of experiencing wage theft; 2) assess the tions for health among immigrant because of racist beliefs that individ-
association between wage theft and serious workers. According to the Eco- uals who lack legal documentation
work-related injury; 3) assess the association nomic Policy Institute, wage theft is are of inferior status and therefore,
between wage theft and three indicators of experienced by millions of workers rightfully excluded from society.3,4
mental health—depression, social isolation, in the United States and costs ap-
and alcohol use—as a function of wage proximately $15 billion a year in Wage Theft and Latino Day
theft; and 4) assess serious work-related lost income,2 an estimate likely sub- Laborers
injury as a function of wage theft controlling stantially lower than the exact dollar Latino day laborers represent
for mental health. amount stolen each year given most an informal and often unregulated
Methods: Secondary data analyses were
based on survey data collected from 331 jury incidents. Thus, our basic premise was 2 Department of Management, Policy, and
Latino day laborers between November partially supported: wage theft may act as a Community Health, The University of
2013 and July 2014. Regression analyses stressor that stems from conditions, in part, Texas Health Science Center at Houston
were conducted to test the relationships reflecting structural racism, making work- (UTHealth) School of Public Health,
described above. ers vulnerable to poorer health. Ethn Dis. Houston, TX
Results: Approximately 25% of participants 2021;31(Suppl 1):345-356; doi:10.18865/
reported experiencing wage theft and ed.31.S1.345 Address correspondence to Maria Eugenia
20% reported serious work-related injury. Fernández-Esquer, The University of Texas
Wage theft was associated with working in Keywords: Latino Immigrants; Day Labor- Health Science Center at Houston School of
construction and was initially associated ers; Wage Theft; Injury; Structural Racism Public Health, Center for Health Promotion
with work-related injury. Wage theft was not and Prevention Research, 7000 Fannin
significantly associated with mental health 1 Department of Health Promotion and Street, Suite 2518, Houston, TX 77030;
indicators. The association between wage Behavioral Sciences, The University of [email protected]
theft and injury became non-significant Texas Health Science Center at Houston
when controlling for the mental health (UTHealth) School of Public Health,
variables. Houston, TX
Conclusions: The hardship and stress
associated with wage theft incidents may
ultimately lead to more frequent injury. Al-
though we expected an association of wage
theft with mental health, we found vulner-
ability to physical health as indicated by in-
Ethnicity & Disease, Volume 31, Supplement 1, 2021 345
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
workforce who are particularly vul- value the work and worth of Latino as they pertain to minimum wage,
nerable to labor abuses and wage immigrants.4,8 LDLs’ experiences give cover to the practice of wage
theft due to the interaction between of discrimination, undocumented theft and further contributes to
individual (eg, sociodemographic status, threats of deportation, and LDLs’ systemic discrimination.2,9,14
and employment characteristics) job loss from employers are also the Several labor laws created to help
and structural (eg, criminalization byproducts of a legal and social sys- protect US workers—notably those
and devaluation of immigrants) fac- tem that tacitly allows LDLs to be- established through the Fair Labor
tors that make them targets of ex- come the victims of wage theft.8-10 Standards Act of 19382,6,14—histori-
ploitation.4,5 At the individual level, cally excluded people of color by ex-
limited education, low English profi- Wage Theft and Structural plicitly excluding occupations over-
ciency, and lack of knowledge about Racism whelmingly made up by this group
labor laws make them vulnerable to (eg, agricultural, domestic). While
Structural racism is defined as some of these legal barriers have
Though wage theft is “the macro level systems, social forc- been lifted to increase access to pro-
a common labor law es, institutions, ideologies, and pro- tections for people of color, Latinos
violation experienced by cesses that interact with one another remain some of the least protected
US workers, those most to generate and reinforce inequities workers in the United States.15,16
likely to experience it among racial/ethnic groups.”11,12 In
include low-income and this system, dominant groups re- Wage Theft and Health
racial/ethnic minority ceive social, economic, and politi-
workers such as Latino day cal advantages, while non-dominant Although several forms of struc-
laborers (LDLs).1,2 groups, such as Latinos, receive less tural racism have been linked to neg-
favorable treatment often manifest- ative health outcomes,11,13 only a few
exploitation, as these factors have ed as social oppression and econom- studies have explored the relation-
been associated with increased re- ic disadvantage (eg, wage theft).13 ship between wage theft and health.
ports of minimum wage violations.6 It is within such an environment of These studies are qualitative in na-
Employment characteristics such differential treatment that US labor ture and suggest that wage theft is
as industry category, company size, and immigration laws foster the sys- a major stressor commonly reported
and payments of wages in cash have tematic practice of wage theft expe- by LDLs and that wage theft is linked
also been found to be strong predic- rienced by LDLs.3,4 The presumed or to maladaptive health behaviors and
tors of wage theft.7 These individual real undocumented status of LDLs indicators of poor mental and physi-
and work characteristics do not exist often place them in a marginalized cal health.4,8,17-21 For example, the
in a vacuum, as they are connected position, where they experience seminal work of Walter et al21 illus-
by macro structural forces that de- social exclusion and the presump- trated how the mental well-being of
tion that they are not entitled to immigrant workers is closely tied to
basic rights.4 Being undocumented their self-image as economic provid-
represents more than an immigra- ers. Thus, workers who lose income
tion status category, as it is a socio- due to wage theft, not only report
political condition characterized by economic loss but also report feel-
instability, insecurity, and hyper- ings of worthlessness and depres-
vigilance that shapes every aspect sion as a result of this type of abuse.
of life for those who are forced to Negi’s18,19 extensive ethnographic
live under the specter of illegality.3 work illustrates the connection be-
Other structural disadvantages tween wage theft and mental health.
such as weak enforcement and the She has noted that abuses of worker
limited scope of existing labor laws rights, including wage theft, have a
346 Ethnicity & Disease, Volume 31, Supplement 1, 2021
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
negative effect on the mental health States is higher for Latinos than sion and binge drinking.18,28 Thus,
of LDLs.18,19 Depression and anxiety for non-Latino workers (excluding the very need for a job and the fear
often result from this experience, as transportation incidents) and high- of losing it contributes to their in-
wage theft deprives these workers er for foreign-born Latino work- creased risk for injury,29 and wage
of income slated for their families, ers than US-born Latino workers.23 theft likely exacerbates this risk.
often leading the workers to isolate While there are no studies that While the evidence is limited,
themselves and to abuse alcohol and establish a direct association be- the above findings suggest that
other substances.18 The stress cre- tween wage theft and injury, LDLs wage theft is a commonly experi-
ated by wage theft is exacerbated have reported wage theft as a major enced and pernicious problem that
by the sense of powerlessness that source of stress at work that may affects LDLs’ economic well-being
comes from an irregular immigra- contribute to their vulnerability to and may adversely impact their
tion status and the resulting per- injury.24 Economic pressures and health. To our knowledge, studies
ceived inability to seek justice.8,19 competition for a limited number of that identify individual-level pre-
Workplace injury, which often jobs, particularly at corners with a dictors of wage theft or examine
co-occurs with wage theft in the large labor pool,25 may push LDLs the association between wage theft
context of hazardous work condi- to take more hazardous jobs from and health among LDLs are rare.
tions, is a serious health problem employers willing to exploit their Such evidence could strengthen
among LDLs.18,22 One in five LDLs economic needs.26,27 Wage theft and existing research on day labor-
report experiencing a work-related the fear or actual experience of a se- ers and other Latino immigrants’
injury.4 In fact, the US Bureau of La- rious injury have a negative impact susceptibility to wage theft and its
bor Statistics reports that the work- on mental health, as these threats co-occurring health consequences,
related fatality rate in the United may increase LDLs levels of depres- which in turn can inform individ-
SES WAGE DEPRESSION SEVERE
WORK THEFT INJURY
DEPORT ISOLATION
ALCOHOL
USE
Figure 1. Relationship of wage theft with sociodemographic and work characteristics, deportation stress, mental health, and
injury
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
ual and policy level interventions lots) or locations where they fre- in a two-day interviewer training,
to assist this vulnerable population. quently look for work in the Hous- guided by a manual of procedures.
Thus, the purpose of this study ton metropolitan area. A total of They administered the survey on
was to: 1) identify sociodemograph- 38 corners were identified and ob- site at each corner location, which
ic, employment, and stress-related served between November 2013 and lasted between 45 and 60 minutes
characteristics that increase LDLs’ July 2014. Corners were stratified per interview. All participants pro-
odds of experiencing wage theft; by size (ie, labor pool density) as vided verbal consent prior to the
2) assess the association between determined by the average number interview and were given the op-
wage theft and serious work-related of Latino day laborers observed on tion to discontinue the interview
injury; 3) assess the association be- location. Corners were classified as or complete it at a later time if they
tween wage theft and three indica- small (≤ 20 LDLs observed), me- needed to participate in daily hir-
tors of mental health—depression, dium (21–44 observed), and large ing activities. Upon survey comple-
social isolation, and alcohol use—as (≥ 45 observed). To ensure adequate tion, participants were compensated
a function of wage theft; and 4) as- representation of corner size during with a $20 gift card and received
sess serious work-related injury as a data collection, we set recruitment a copy of their informed consent
function of wage theft controlling quotas of 60 LDLs from small cor- and a list of community resources.
for mental health. These aims are ners, 90 from medium corners, and
depicted in presented in Figure 1. 150 from large corners. Sample size Survey Content and Measures
and power considerations for this
pilot study were based on the ability Sociodemographic and em-
M ethods to establish feasibility, acceptability, ployment characteristics mea-
and initial outcomes for an injury sured in the survey included age,
prevention program. Thus, we sys- years of school, country of origin,
Our current study represents tematically surveyed all identified language(s) spoken, marital status,
a secondary data analysis based corners and assessed initial trends in number of children supported fi-
on survey data collected for a pi- injury rates and its social, occupa- nancially, time living in the Unit-
lot community-based program to tional, and demographic correlates. ed States, time looking for work
reduce workplace injury among The corner survey was adminis- on the corners, and most frequent
Latino day laborers.30 The parent tered via face-to-face interview to job performed in the last year.
study was approved to interview 331 individuals and completed over Three scales assessed participants’
adult Latino males (aged ≥21 years) the course of 10 weeks, beginning mental health. Depression in the
by the Committee for the Protec- in mid-November 2013. Participant previous week was measured using
tion of Human Subjects at The eligibility criteria included: a) being the sum of the seven-item Center
University of Texas Health Science aged ≥21 years; b) self-identifying for Epidemiological Studies-De-
Center at Houston. Key method- as Hispanic or Latino; and c) pres- pression (CES-D) scale.31 A sample
ological aspects of the parent study ently looking for work on corners. item was, “In the last week…, how
pertaining to this article are pre- All eligible individuals who agreed often would you say... You felt that
sented below and full study details to participate were included in the everything you did was an effort?”
are found in an earlier article.30 study until sample quotas were met Responses could range from 1 =
or exceeded for each corner size. not at all to 4 = a lot. Chronbach’s
Study Setting and Participant α for the depression scale was .83.
Selection Interview Procedures Social isolation was measured
as the sum of two items used previ-
We recruited Latino day laborers Four Latino day laborers and ously as part of a scale developed to
at corners (ie, street corners, home two bilingual Latinas familiar with measure adaptation in a sample of
improvement and convenience the LDL community participated LDLs.32 The two items were: “Could
stores, parks, bus stops, parking
348 Ethnicity & Disease, Volume 31, Supplement 1, 2021
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
Table 1. Characteristics of the study sample (N=331) N Range Mean SD
324 43.6
Age (years) 330 21.7 – 73.8 7.6 10.2
Last year went to school 327 0 – 18.0 12.8 3.8
Time in the US (years) 331 .08 – 53.0 3.7 9.9
Time on the corners (years) 330 .02 – 27.0 1.8 4.5
Number of children support financially 331 0 – 8.0 4.9 1.7
Deportation stress 330 2.0 – 8.0 13.7 2.0
Depression 330 7.0 – 27.0 5.4 4.0
Social isolation 2.0 – 8.0 1.6
N Percent
Country of origin 15 4.5
US (Puerto Rico) 135 40.8
Mexico 153 46.2
Central America 28 8.5
Other Latin American country
106 32.0
Marital status 173 52.3
Single 52 15.7
Married or living with a partner
Separated/divorced/widowed 292 88.2
39 11.8
Spoken language
Primary language Spanish or other non-English language 107 32.3
English equally with or better than Spanish 224 67.7
Most frequent job in last year 76 23.0
Other 152 45.9
Construction 103 31.1
Corner size 138 41.9
Small 85 25.8
Medium 73 22.2
Large 21 6.4
12 3.6
Past year alcohol use
Never 249 75.5
Monthly or less 81 24.5
2 – 4 times a month
2 – 3 times a week 264 79.8
4 or more times a week 67 20.2
Experienced wage theft
No
Yes
Experienced past year injury
No
Yes
you tell me how often you miss your in the past-year was measured on sured using two items from the
family and friends in your country a five-point scale: 1 = never; 2 = previously mentioned adaptation
of origin?” and “Could you tell me monthly or less; 3 = 2 to 4 times a scale: “Could you tell me how of-
how often you need someone to talk month; 4 = 2 to 3 times a week; 5 = 4 ten you worry about being deport-
to?” Responses ranged from 1 = nev- or more times a week. It was treated ed?” and “Could you tell me how
er to 4 = always. The Pearson cor- as a continuous variable. Scale scores often you worry about family and
relation between the two items was were missing if an item was missing. friends being deported?” Responses
.27 (P<.001). Alcohol use frequency Deportation stress was mea- ranged from 1 = never to 4 = al-
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
ways. The two items were summed. health,33 was assessed by asking par- tics’ criteria for “work-related re-
The Pearson correlation between ticipants, “In the past year, have you cordable cases,” this was defined as,
the two items was .59 (P<.001). had a serious injury or illness related “an injury or illness for which you
Serious work-related injury, an to your job as a day laborer?” Based missed work because of it; you felt
indicator of physical (occupational) on the US Bureau of Labor Statis- you should not have gone to work
Table 2. Adjusted logistic regression results for predictors of wage theft; wage theft as a predictor of injury; wage theft as
predictor of injury controlling for mental health
A. Predictors of wage theft B. Wage theft as a C. Wage theft as a
predictor of Injury predictor of injury
controlling for mental
health
AOR (95% CI) P AOR (95% CI) P AOR (95% CI) P
Sociodemographics 1.00 (.97 – 1.03) .990 .99 (.96 – 1.02) .555 .99 (.95 – 1.02) .449
Age 1.05 (.97 – 1.15) .216 .98 (.89 – 1.07) .623 1.01 (.92 – 1.11) .872
Years of school .98 (.94 – 1.02) .348 .99 (.95 – 1.03) .626 .99 (.95 – 1.03) .509
Time in the US (years) 1.02 (.95 – 1.09) .579 .97 (.90 – 1.05) .460 .97 (.90 – 1.05) .450
Time on the corners (years) 1.01 (.84 – 1.21) .938 .90 (.73 – 1.12 .340 .89 (.72 – 1.11) .305
Number of children support
Marital status (referent) (referent) (referent)
Single 1.47 (.72 – 3.02)
Married/Living with partner .95 (.37 – 2.46) .289 .42 (.20 – .89) 024ac .46 (.21 – 1.00) .051
Separated/Divorced/Widowed
Country of origin .912 1.09 (.48 – 2.50) .839 .98 (.41 – 2.32) .954
United States
Mexico (referent) .090 (referent) .891 (referent) .894
Central America .26 (.05 – 1.24) .459 1.12 (.23 – 5.32) .850 .89 (.17 – 4.67) .567
Other Latin American Country .55 (.11 – 2.69) .116 .86 (.17 – 4.32) .337 .60 (.11 – 3.40) .126
Spoken language .20 (.03 – 1.49) .34 (.04 – 3.06) .16 (.02 – 1.67)
Primary language Spanish or other non-English language
English equally with or better than Spanish (referent) (referent) (referent)
.54 (.19 – 1.55)
Employment .256 1.07 (.42 – 2.75) .889 1.00 (.38 – 2.66) .993
Most frequent job in last year
Other (referent) (referent) (referent)
Construction
Corner Size 2.02 (1.04 – 3.94) .039ac 1.59 (.81 – 3.12) .182 1.43 (.72 – 2.87) .310
Small
Medium (referent) (referent) (referent)
Large .67 (.33 – 1.35)
1.31 (.60 – 2.86) .260 1.18 (.57 – 2.43) .660 1.17 (.55 – 2.48) .682
Deportation stress 1.16 (1.00 – 1.35)
Mental health .506 .71 (.30 – 1.70) .444 .80 (.32 – 2.00) .636
Depression .055 1.06 (.90 – 1.25) .477 1.00 (.84 – 1.19) .997
Social isolation
Alcohol use Not included Not included 1.13 (1.05 – 1.22) .002bc
Experienced wage theft Not included Not included 1.11 (.90 – 1.37) .338
No Not included Not included .87 (.65 – 1.16) .341
Yes
Outcome of interest (referent) (referent)
1.97 (1.01 – 3.86) .048ac 1.78 (.89 – 3.56) .101
a.P<.05, two-tailed.
b. P<.01, two-tailed.
c. Unstandardized coefficient.
Nagelkerke R2 Predictors of wage theft = .14; Nagelkerke R2 wage theft as a predictor of injury = .14; Nagelkerke R2 wage theft as a predictor of injury controlling for
mental health = .06
350 Ethnicity & Disease, Volume 31, Supplement 1, 2021
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
Table 3. Adjusted linear regression results for association of wage theft with each mental health indicator (dependent
variable)
A. Depression B. Social Isolation C. Frequency of Alcohol Use
B (95% CI) P B (95% CI) P B (95% CI) P
Sociodemographics -.004 (-.053 – .045) .884 .02 (-.002– .04) .073 -.02 (-.03 – -.002) .026ad
Age -.20 (-.33 – -.07) .003bd -.01 (-.06 – .04) .776 .01 (-.03 – .05) .582
Years of school .01 (-.05 – .07) .668 .003 (-.019 – .024) .813 .975
Time in the US , years -.02 (-.12 – .09) .742 .03 (-.01 – .07) .131 < .001 (-.016 – .016) .366
Time on the corners (years) .20 (-.10 – .49) .190 .04 (-.07 – .15) .494 .01 (-.02 – .04) .670
Number of children support .02 (-.07 – .10)
Marital status
Single (referent) (referent) (referent)
Married/living with partner -.10 (-.41 – .21)
Separated/divorced/widowed -.51 (-1.61 – .60) .368 -.52 (-.93 – .11) .013ad .23 (-.16 – .62) .523
Country of origin .247
United States 1.37 (-.01 – 2.76) .052 -.08 (-.59 – .44) .765
Mexico
Central America (referent) (referent) (referent)
Other Latin American country -.32 (-1.02 – .38)
Spoken language .43 (-.2.16 – 3.01) .745 .14 (-.83 – 1.12) .774 -.75 (-1.48 – -.03) .365
Primary language Spanish -.81 (-1.67 – .05) .041ad
or other non-English language .43 (-2.24 – 3.10) .752 .37 (-.64 – 1.37) .475 .064
English equally with
or better than Spanish 2.60 (-.54 – 5.73) .105 1.02 (-.16 – 2.20 .091
Employment (referent) (referent) (referent)
Most frequent job in last year -.21 (-.62 – .21)
Other .56 (-.95 – 2.06) .467 -.21 (-.77 – .35) .463 .330
Construction (referent) (referent) (referent)
Corner size -.02 (-.29 – .25)
.55 (-.43 – 1.52) .269 -.16 (-.52 – .21) .398 .819
Small
Medium (referent) .638 (referent) (referent) .268
Large .27 (-.85 – 1.39) .944 -.17 (-.58 – .25) .427 .17 (-.13 – .48) < .001cd
Deportation stress .05 (-1.24 – 1.33) .022ad .08 (-.39 – .56) .732 .67 (.31 – 1.02)
Experienced wage theft .28 (.19 – .37) <.001cd < .001 (-.068 – .067) .993
No .29 (.04 - .53)
Yes
(referent) (referent) (referent) .518
.62 (-.45 – 1.69) .257 .04 (-.36 – .44) .851 -.10 (-.40 – .20)
a. P<.05, two-tailed.
b. P<.01, two-tailed.
c. P<.001, two-tailed.
d. Unstandardized coefficient.
Adjusted R2 Depression = .05; Adjusted R2 Social Isolation = .14; Adjusted R2 Alcohol Use = .06.
but you did, anyway; or you had were paid what was promised/agreed promised/agreed upon. Experience
to receive medical attention from a upon?” Responses ranged from 1 = of wage theft was then dichoto-
doctor or a clinic.”34 The occurrence strongly disagree to 4 = strongly mized as no (strongly agreed or
of any serious past-year injury or ill- agree. Responses for the wage theft agreed with the statement) or yes
ness was dichotomized as no or yes. item were reverse scored so that (disagreed or strongly disagreed with
Wage theft was measured by a higher scores indicated greater dis- the statement). Participants could
single item, “In your last full day agreement with the statement that refuse to answer any question or
as a day laborer, would you say you the participant was paid what was state they did not know the answer.
Ethnicity & Disease, Volume 31, Supplement 1, 2021 351
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
To reduce the survey burden on tic regression, controlling for the reported construction as the job
participants in the original study, sociodemographic, employment, they most frequently performed in
we adopted a planned missing strat- and deportation stress variables. the last year. The average partici-
egy.35 One of three different versions Third, to determine the associa- pant supported two children finan-
of the survey containing selected tion of wage theft with each men- cially. The average deportation stress
subsets of items were randomly ad- tal health variable, separate linear score was 4.9 (SD = 2.0; N = 331)
ministered to participants. For de- regression analyses were conducted in a 1-8 scale. Although results sug-
pression, isolation, and wage theft with depression, isolation, and al- gest concern, this item was not in-
items, values for planned missing cohol use as the dependent vari- tended to be used as a clinical tool.
items were imputed using the Mon- able. Each separate outcome was
te Carlo method in SPSS. Original regressed on wage theft while con- Regression Results
responses of refused or do not know trolling for sociodemographic, em-
were not changed and were treated ployment, and deportation stress Regression results described
as missing. Although imputed data variables. In the final logistic regres- in this section, as depicted in Fig-
values do not represent the values sion model, to assess the association ure 1, are organized according
that would have been recorded had between wage theft and injury, con- to regression type. Logistic re-
items been administered to all partic- trolling for the mental health vari- gressions are reported in Table 2
ipants, planned missingness is a ma- ables, serious past-year injury was and linear regressions in Table 3.
ture strategy that functioned as in- regressed on wage theft and each of
tended during our data collection.35 the other study variables. For each Wage Theft
analysis, independent variables were Eighty-one of 331 (24.5%)
Data Analysis entered simultaneously. Dummy participants reported wage theft
variables were created for categorical at their last job, and as shown in
In the first part of data analy- variables. Analyses were conducted Table 2, column A, it was more
sis, frequencies were computed with SPSS, v. 26. A significance likely to be reported by partici-
for categorical variables. Ranges, level of P<.05, two-tailed, was used. pants mostly employed in con-
means, and standard deviations struction during the previous year
were computed for continuous R esults (P=.039). Participants experienc-
items. Some demographic vari- ing higher deportation stress were
ables were recoded to facilitate in- Descriptive Statistics marginally more likely to report
terpretation of results. Recoded wage theft (P=.055). Nagelker-
variables are presented in Table 1. As shown in Table 1, partici- ke’ s R2 for the model was .14.
Following the initial descrip- pants, on average, were in their mid-
tive analysis, we conducted regres- 40s and had completed almost eight Depression
sion analyses to assess the primary years of education, they had been The mean depression score was
study questions presented above in the US nearly 13 years and had 13.7 (SD = 4.0; N=331) out of a
and represented in Figure 1. First, a been looking for work at the corners possible range of 7.0 – 28.0. As
logistic regression analysis was con- for nearly four years. Most LDLs shown in Table 3, column A, more
ducted to determine the correlates were born in Mexico or Central years of schooling were associated
of wage theft. Thus, wage theft was America. One-half of participants with a decrease in depression scores
regressed on the sociodemographic, (52.3%) reported being married or (P=.003). Compared with those
employment (including corner size), living with a partner. The majority who were married, those who were
and deportation stress variables. (88.2%) indicated that their pri- formerly married had marginally
Second, to assess the association of mary spoken language was Spanish. higher depression scores (P=.052).
wage theft with injury, injury was Two-thirds of participants (67.7%) Higher scores were also associ-
regressed on wage theft in a logis- ated with more deportation stress
352 Ethnicity & Disease, Volume 31, Supplement 1, 2021
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
(P=.022). Two-fifths (38.8%) of models, as this transformation did not Discussion
participants had at or above the cut- improve the explanation of variance.)
off score (15.0 for our scoring range) In summary, although we pre- Latino day laborers are particu-
cited by Levine31 as indicative of el- dicted that wage theft would be larly vulnerable to wage theft due
evated depressive symptoms. The associated with indicators of men- to individual and structural factors
adjusted R2 for this model was .05. tal health after controlling for so- that make them vulnerable to ex-
ciodemographic, employment, and ploitation by unscrupulous employ-
Social Isolation deportation stress variables, we ers. Their undocumented status is
The mean isolation score was 5.4 found that wage theft was not a sig- used as justification for devaluing
(SD = 1.6; N=331) out of a possible nificant correlate of mental health. their worth and denying them due
range of 2.0 – 8.0. As with the de- payment and basic rights reserved
portation stress item, our isolation Work-Related Injury for legal citizens. Wage theft among
scale was not intended as a clini- Sixty-seven participants (20.2%) LDLs is possible because of histori-
cal measure. As shown in Table 3, reported a total of 88 past-year in-
column B, isolation was inversely jury or illness incidents (range = The most striking aspect
associated with being married or 1 to 4; mean = 1.3; SD = .7). All of our LDLs’ profile is
living with a partner compared but three incidents involved physi- their experience of wage
with never being married (P=.013) cal injuries to the upper body and theft in their last job
and positively associated with de- the extremities, as described else- (25%) and report of
portation stress (P<.001). The ad- where.30 Table 2, column B results serious work-related injury
justed R2 for this model was .14. indicate that those who experienced in the last year (20%),
wage theft were more likely to re- which confirms previously
Alcohol Use port a work-related injury (P=.048). reported high rates of
Of 329 participants, 138 LDLs Compared with those never mar- injury for day laborers.30
(41.9%) reported no past-year alco- ried, those who were married or liv-
hol use, but 32.2% drank 2-4 times ing with a partner were less likely to cally racist labor laws and contem-
a month or more often. As shown report an injury (P=.024). Nagelker- porary anti-immigration rhetoric
in Table 3, column C, frequency of ke’ s R2 for the model was .11. that allow for discriminatory labor
alcohol use in the past year was in- practices to persist.4,14-16 It is within
versely associated with age (P=.026) Work-Related Injury Controlling this political, social, and legal envi-
and with being from Central America for Mental Health ronment that wage theft continues
compared with being from the Unit- As shown in Table 2, column C, to thrive, as employers exploit indi-
ed States (P=.041). It was marginally past-week depression was a signifi- viduals whom they regard as vulner-
inversely associated with being from cant correlate of serious work-relat-
“Other Latin American country” as ed injury in the past year (P=.002)
compared with being born in the and being married or living with a
United States (P=.064). It was also partner compared with being single
associated with looking for work was marginally protective against
in a large corner, compared with a serious injury (P=.051). After con-
small one (P<.001). The adjusted R2 trolling for sociodemographic, em-
for alcohol use was .06. (Due to the ployment, deportation stress, and
skewed distribution of the alcohol use mental health variables, wage theft
variable, we initially transformed it to was no longer significantly associ-
correct for non-normality, but kept ated with injury (P=.101). Nagelker-
the original variable in the regression ke’ s R2 for this model was .16.
Ethnicity & Disease, Volume 31, Supplement 1, 2021 353
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
able, and benefit from the lack of not related to wage theft, as reported wage theft is a frequent and stress-
protection afforded to these workers. in previous qualitative research.18,19 ful event experienced by LDLs
The most striking aspect of our Limitations of the wage theft mea- and should be explored further.
LDLs’ profile is their experience of sure are discussed in the next section.
wage theft in their last job (25%) Conclusion
and report of serious work-related Limitations
injury in the last year (20%), which The wage theft experienced by
confirms previously reported high There are several limitations to LDLs perpetuates factors rooted in
rates of injury for day laborers.30 the interpretation of our findings structural racism. Nearly a quar-
Being married (compared with be- that should be considered. First, as ter of the LDLs in our sample re-
ing single) was marginally protec- it is often the case with other regres- ported experiencing wage theft
tive of injury replicating previous sion analyses, the study items were on their last job and more than a
findings that have been attributed measured according to different time fifth reported serious work-related
to family obligations but may need frames (eg, wage theft on the last job injury in the past year. These ex-
further exploration. 30 Notably, our performed vs past-year injury). This periences are indicative of a risk
results indicate that wage theft is lack of correspondence may have environment rooted in structural
associated with injury. Although limited our ability to detect hypoth- racism, where LDLs are forced to
this association has limitations esized relationships (eg, wage theft endure exploitive conditions not
to be discussed in the next sec- and injury, wage theft and mental acceptable to most Americans.
tion, this study represents one of health indicators). Second, our sig- Contrary to what we predicted,
the first instances where these two nificant findings only predict results wage theft was not significantly as-
work-related conditions have been in the statistical sense and are not sociated with mental health and was
found to be significantly associated. indicative of true causality. Third, not associated with injury in the final
Regression results depicted in additional measures (eg, anxiety) model. However, the greater vulner-
Tables 2 and 3 have several implica- that could have accounted for the ability to physical health indicated
tions for understanding wage theft unexplained variance in regression by injury incidents partially sup-
among LDLs. First, the association results or could have intervened in ported our basic premise that wage
of wage theft with work in the con- the proposed relationships (eg, wage theft may act as a stressor that stems
struction sector (Table 2, column A) theft and injury, wage theft and from conditions reflecting structural
confirms previous studies indicating mental health indicators) were not racism, making workers vulnerable
that labor law violations are com- included in the parent study. Fourth, to poorer health. Future studies may
mon in this sector.1,8 This finding is our measure of wage theft in the last need to explore the mechanisms me-
particularly notable because Latinos job performed as a day laborer, re- diating the influence of wage theft on
(including LDLs) make up about stricted reports to a single event and health and other outcomes, as the liv-
27% of the construction workers this restriction may have attenuated ing and working conditions of day la-
in the United States.23 Second, sev- its variability, explaining the lack of borers may interact in complex ways
eral socio-demographic factors were association with the mental health that may be better represented by
associated with depression, social indicators. Finally, our measure of models that capture this complexity.
isolation, and frequency of alcohol construction work did not specify
use, confirming patterns previously the type of job and may have arti- Acknowledgements
reported for LDLs (eg, higher de- ficially inflated the association with We want to thank the Latino day
pression scores among previously wage theft, as two-thirds (67.7%) of laborers and other members of our Com-
married men, less frequent drinking participants reported construction munity Advisory Board for their valuable
among foreign-born Latinos)17-20 as their most frequent job in the last advice throughout the study. This work
but mental health indicators were year. In spite of these limitations, was supported by the National Institute
this exploratory study suggests that of Minority Health and Health Dispari-
354 Ethnicity & Disease, Volume 31, Supplement 1, 2021
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Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
ties (Grant No. 5R24MD007975-02) and Los Angeles: UCLA Institute for Research on in Mexican/Latino migrant day laborers. J
the National Cancer Institute through a Labor and Employment; 2009. Immigr Health. 2005;7(4):269-281. https://
predoctoral fellowship to Lynn Ibekwe, 8. Fussell E. The deportation threat dynamic doi.org/10.1007/s10903-005-5124-0
MPH (T32CA057712: Cancer Prevention and victimization of Latino migrants: PMID:19813293
and Control Research Training and Career Wage theft and robbery. Sociol Quar- 21. Walter N, Bourgois P, Margarita Loinaz
Development Program) at the University terly. 2011;52(4):593-615. https://doi. H, Schillinger D. Social context of work
of Texas Health Science Center at Houston org/10.1111/j.1533-8525.2011.01221.x injury among undocumented day la-
School of Public Health. The content of 9. Lee S. Policing wage theft in the day labor borers in San Francisco. J Gen Intern
this paper is solely the responsibility of the market. UC Irvine L Rev. 2014;4(2):655. Med. 2002;17(3):221-229. https://doi.
authors and does not necessarily represent 10. Sanidad C. Stories from Immigrant Workers org/10.1046/j.1525-1497.2002.10501.x
the official views of the National Institute in the Valley of the Sun: Status, Wage Theft, PMID:11929509
for Minority Health and Health Disparities Recourse, and Resilience. Tempe, AZ: Arizona 22. Torres R, Heyman R, Munoz S, et al.
or the National Cancer Institute. State University; 2011. Building Austin, building justice: immi-
Conflict of Interest 11. Gee GC, Ford CL. Structural racism and grant construction workers, precarious labor
No conflicts of interest to report. health inequities: old issues, new directions. regimes and social citizenship. Geoforum.
DuBois Rev. 2011;8(1):115-132. https:// 2013;45:145-155. https://doi.org/10.1016/j.
Author Contributions doi.org/10.1017/S1742058X11000130 geoforum.2012.10.012
Research concept and design: Fernán- PMID:25632292 23. Bureau of Labor Statistics, U.S. Department
dez-Esquer, Ibekwe, Guerrero-Luera, King, 12. Powell JA. Structural racism: building upon of Labor. Hispanics and Latinos in industries
Durand; Acquisition of data: Fernández- the insights of John Calmore. North Carol and occupations. The Economics Daily 2015.
Esquer, Atkinson; Data analysis and Law Rev. 2008;86:791-816. Last accessed January 16, 2020 from https://
interpretation: Fernández-Esquer, Ibekwe, 13. Williams DR, Lawrence JA, Davis BA. www.bls.gov/opub/ted/2015/hispanics-and-
Guerrero-Luera, King, Durand, Atkinson; Racism and health: evidence and needed latinos-in-industries-and-occupations.htm..
Manuscript draft: Fernández-Esquer, Ibe- research. Annu Rev Publ Health. 2019;40(1). 24. Martínez AD, Piedramartel A, Agnew J.
kwe, Guerrero-Luera, King, Durand, Atkin- https://doi.org/10.1146/annurev-publ- Going beyond the injury: regulatory condi-
son; Statistical expertise: Durand, Atkinson; health-040218-043750 tions contributing to latina/o immigrants’
Acquisition of funding: Fernández-Esquer; 14. Ruan N. Facilitating Wage theft: How courts occupational psychosocial Stressors. Front
Administrative: Ibekwe, Guerrero-Luera, use procedural rules to undermine substan- Public Health. 2015;3(240):240. https://
King; Supervision: Fernández-Esquer tive rights of low-wage workers. Vanderbilt doi.org/10.3389/fpubh.2015.00240
Law Rev. 2010;63(3):725. PMID:26539426
References 15. Coleman LG. Disrupting the discrimina- 25. Crotty SM. Locating day-labor employ-
1. Bobo K. Wage Theft in America: Why Millions tion narrative: an argument for wage and ment: toward a geographic understanding
hour laws’ inclusion in antisubordination of day-labor hiring site locations in the San
of Working Americans Are Not Getting Paid— advocacy. Stanford J Civ Rights Civ Lib. Diego metropolitan area. Urban Geogr.
And What We Can Do About It. New York: 2018;14(1):49-87. 2015;36(7):993-1017. https://doi.org/10.10
The New Press; 2011. 16. Solomon D, Maxwell C, Castro A. System- 80/02723638.2015.1049481
2. Cooper D, Kroeger T. Employers steal billions atic Inequality and Economic Opportunity. 26. Menzel NN, Gutierrez AP. Latino worker
from workers’ paychecks each year. Washing- Center for American Progress; 2019. Last perceptions of construction risks. Am J Ind
ton, D.C.: Economic Policy Institute; 2017. accessed January 5, 2020 from https:// Med. 2010;53(2):179-187. https://doi.
3. Fernández-Esquer ME, Agoff MC, Leal IM. www.americanprogress.org/issues/race/ org/10.1002/ajim.20735 PMID:19670290
Living Sin Papeles: Undocumented Latino reports/2019/08/07/472910/systematic- 27. Seixas NS, Blecker H, Camp J, Neitzel R.
workers negotiating life in “illegality.” Hisp inequality-economic-opportunity/ Occupational health and safety experience
J Behav Sci. 2017;39(1):3-18. https://doi. 17. Mora DC, Grzywacz JG, Anderson AM, et of day laborers in Seattle, WA. Am J Ind
org/10.1177/0739986316679645 al. Social isolation among Latino work- Med. 2008;51(6):399-406. https://doi.
4. Quesada J, Hart LK, Bourgois P. Structural ers in rural North Carolina: exposure org/10.1002/ajim.20577 PMID:18330894
vulnerability and health: Latino migrant and health implications. J Immigr Minor 28. Organista KC, Arreola SG, Neilands TB.
laborers in the United States. Med Anthropol. Health. 2014;16(5):822-830. https:// Depression and risk for problem drinking
2011;30(4):339-362. https://doi.org/10.1080/ doi.org/10.1007/s10903-013-9784-x in latino migrant day laborers. Subst Use
01459740.2011.576725 PMID:21777121 PMID:23417706 Misuse. 2017;52(10):1320-1327. https://
5. Valenzuela A, Theodore N, Melendez E, 18. Negi NJ; Nalini Junko Negi. Identifying doi.org/10.1080/10826084.2016.1276599
Gonzalez AL. On the Corner: Day Labor in the psychosocial stressors of well-being and PMID:28346082
United States. Los Angeles, CA: UCLA Center factors related to substance use among 29. Ibarra-Mejia G, Maynez-Guaderrama AI,
for the Study of Urban Poverty; 2006. Latino day laborers. J Immigr Minor Vargas-Salgado MM, Gomez-Bull KG. Pre-
6. Siqueira CE, Gaydos M, Monforton C, et al. Health. 2011;13(4):748-755. https:// dictive Cultural Dimensions of Occupational
Effects of social, economic, and labor policies doi.org/10.1007/s10903-010-9413-x Risk Perception and Behavior in Migrant
on occupational health disparities. Am J PMID:21107694 Mexican Construction Workers. El Paso, TX:
Ind Med. 2014;57(5):557-572. https://doi. 19. Negi NJ. Battling discrimination and social University of Texas at El Paso; 2019.
org/10.1002/ajim.22186 PMID:23606055 isolation: psychological distress among 30. Fernández-Esquer ME, Aguerre CF, Ojeda
7. Bernhardt A, Milkman R, Theodore N, et al. Latino day laborers. Am J Community M, et al. Documenting and understand-
Broken Laws, Unprotected Workers: Violations Psychol. 2013;51(1-2):164-174. https:// ing workplace injuries among Latino
of Employment and Laws in America’s Cities. doi.org/10.1007/s10464-012-9548-0 day laborers. J Health Care Poor Under-
PMID:22864958 served. 2020;31(2):791-809. https://doi.
20. Organista KC, Kubo A. Pilot survey of HIV org/10.1353/hpu.2020.0061
risk and contextual problems and issues 31. Levine SZ. Evaluating the seven-item
Ethnicity & Disease, Volume 31, Supplement 1, 2021 355
Created for free by https://foxyutils.com
Wage Theft, Mental Health, and Injury - Fernández-Esquer et al
Center for Epidemiologic Studies depres-
sion scale short-form: a longitudinal U.S.
community study. Soc Psychiatry Psychiatr
Epidemiol. 2013;48(9):1519-1526. https://
doi.org/10.1007/s00127-012-0650-2
PMID:23299927
32. Steel KC, Fernandez-Esquer ME, Atkinson
JS, Taylor WC. Exploring relationships
among social integration, social isola-
tion, self-rated health, and demograph-
ics among Latino day laborers. Ethn
Health. 2018;23(4):425-441. https://doi.
org/10.1080/13557858.2017.1280130
PMID:28100070
33. Thomsen C, McClain J, Rosenman K, Davis
L; Centers for Disease Control and Preven-
tion (CDC). Indicators for occupational
health surveillance. MMWR Recomm Rep.
2007;56(RR-1):1-7. PMID:17230144
34. Bureau of Labor Statistics, U.S. Department
of Labor. Clarification of preexisting condi-
tions and reportable incidents. 2010; Last ac-
cessed January 5, 2021 from www.osha.gov/
pls/oshaweb/owadisp.show_document?p_
table=STANDARDS&p_id=9638.
35. Enders CK. Applied Missing Data Analysis.
New York: Guilford Press; 2010.
356 Ethnicity & Disease, Volume 31, Supplement 1, 2021
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Stress, Allostatic Load, and Health of
Mexican Immigrants n
Robert Kaestner, University of Illinois and NBER
Jay A. Pearson, University of Michigan
Danya Keene, University of Michigan
Arline T. Geronimus, University of Michigan
Objective. To assess whether the cumulative impact of exposure to repeated or
chronic stressors, as measured by allostatic load, contributes to the ‘‘unhealthy
assimilation’’ effects often observed for immigrants with time in the United
States. Methods. We analyzed data from the National Health and Nutrition Exam-
ination Survey, 1988–1994, to estimate multivariate logistic regression models of the
odds of having a high allostatic load score among Mexican immigrants, stratified by
adult age group, according to length of residence in United States, controlling for
demographic, socioeconomic, and health input covariates. Results. Estimates indicate
that 45–60-year-old Mexican immigrants have lower allostatic load scores upon
arrival than U.S.-born Mexican Americans, non-Hispanic whites, and non-
Hispanic blacks, and that this health advantage is attenuated with duration of
residence in the United States. Conclusions. The findings of our analysis are con-
sistent with the hypothesis that repeated or chronic physiological adaptation to
stressors is one contributor to the ‘‘unhealthy assimilation’’ effect observed for
Mexican immigrants.
A broad array of evidence suggests that immigrants are often healthier
when they arrive in the United States than comparable native-born persons,
but that their health advantage declines with time in the United States
(Antecol and Bedard, 2006; Cho et al., 2006; Dey and Lucas, 2006; Goel
et al., 2004; Harker, 2001; Jasso et al., 2004; Kandula, Kersey, and Lurie,
2004; Landale, Oropesa, and Gorman, 2000; Lara et al., 2005; Singh and
Hiatt, 2006; Singh and Siapush, 2002; Stephen et al., 1994). The conven-
tional explanation of this immigrant health trajectory is that immigrants are
nDirect correspondence to Robert Kaestner, Institute of Government and Public Affairs,
University of Illinois, 815 W. Van Buren St., Ste. 525, Chicago, IL 606007 hkaestner@
uic.edui. Jay A. Pearson, Population Studies Center, Institute for Social Research, University
of Michigan, will provide all data and coding information for those wishing to replicate
the study. We thank Felicia LeClere, John Bound, and three anonymous reviewers for
comments on earlier drafts. We are also grateful to the National Institute on Aging (Grant 5
T32 AG000221) for funding part of the study. Finally, Arline Geronimus acknowledges the
support of the Center for Advanced Study in the Behavioral Sciences of Stanford University.
SOCIAL SCIENCE QUARTERLY, Volume 90, Number 5, December 2009
r 2009 by the Southwestern Social Science Association
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1090 Social Science Quarterly
positively selected on health, which explains their health advantage on ar-
rival, and that deterioration in health with time in the United States rep-
resents an unhealthy effect of assimilation. Previous research has identified
several possible explanations of the ‘‘unhealthy assimilation’’ effect: a wors-
ening diet and declining physical activity (Antecol and Bedard, 2006; Goel
et al., 2004); adoption or intensification of other unhealthy behaviors such
as smoking and drinking (Blake et al., 2001; Johnson, VanGeest, and Cho,
2002; Lopez-Gonzalez, Aravena, and Hummer, 2005; Markides, Coreil,
and Ray, 1987; Marks, Garcia, and Solis, 1990; Singh and Siapush, 2002);
and increased stress as a result of discrimination and the process of accul-
turation (Arau´jo and Borrell, 2006; Escobar, Nervi, and Gara, 2000; Finch
and Vega, 2003; Finch, Kolody, and Vega, 2000; Gee, Kobayashi, and Prus,
2006; Kessler, Mickelson, and Williams, 1999; Paradies, 2006; Thomas,
1995; Vega and Rumbaut, 1991; Vega et al., 2004).
In this article, we take a novel approach to exploring the question of
whether stress contributes to the worse health observed among Mexican
immigrants with time in the United States. Typically, investigators inter-
ested in the role of stress have assessed the relationship between health and
variables thought to be correlated with stress such as indicators of accul-
turation (e.g., language and social support) and perceived discrimination.
We take a fundamentally different approach by examining how allostatic
load scores differ by nativity and by time in the United States among
Mexican immigrants. Conceptually, allostatic load refers to the cumulative
wear and tear on important body systems induced by repeated physiological
adaptation to stressors (McEwen, 1998). No previous study has used the
construct of allostatic load to assess the role that stress may play in the health
of immigrants with time in the United States.
Mexican Immigrant Health Trajectories
There are surprisingly few studies of how health changes with time since
immigration for Mexican immigrants. Although there are a larger number of
studies of the health trajectories of all foreign-born persons, and some of
Hispanic immigrants, Mexican immigrants differ from other immigrants,
including other Hispanics, in their modes of acculturation, socioeconomic
incorporation, pattern of geographic dispersion, and health-related country
of origin characteristics, such as quality of medical care and health behav-
ioral norms. As a result, health trajectories of Mexican immigrants may
differ from those of other Hispanics.
Cho et al. (2006) and Singh and Miller (2004) analyzed data from the
National Health Interview Survey (NHIS) from the early 1990s to study
changes in health with time since immigration among Mexican immigrants.
Cho et al. (2006) found that the reported health (self-reported health, ac-
tivity limitations, and number of days in bed due to illness) of Mexican
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Stress, Allostatic Load, and Health of Mexican Immigrants 1091
immigrants declined with duration in the United States after adjusting for
demographic and socioeconomic characteristics. Singh and Miller (2004)
reported results similar to Cho et al. (2006). Vega et al. (2004) studied
Mexican Americans in Fresno, California and found that Mexican immi-
grants had lower prevalence of psychiatric disorders, overall, and that time in
the United States was associated with increased prevalence of psychiatric
disorders, particularly among those who entered the United States when
young. Palloni and Arias (2004) examined linked NHIS-NDI (National
Death Index) data and concluded that the Mexican mortality advantage did
not decline with time in the United States, and that there was evidence of a
‘‘salmon-bias’’—the return migration of Mexican immigrants in poor
health, unemployed, or near death.
Few studies have investigated potential causes of changes in health with
time since immigration among Mexican immigrants. A prominent expla-
nation of the ‘‘unhealthy assimilation’’ effect is stress resulting from dis-
crimination and the process of acculturation. A major premise of stress
theory is that environmental demands that exceed one’s ability to cope with
result in physiological and behavioral changes that place an individual at risk
for illness (Cohen, Kessler, and Gordon, 1997; Cohen and Wills, 1985). For
Mexican immigrants, the process of assimilation may involve both increased
exposure to environmental stressors and coping responses that are detri-
mental to health (Finch and Vega, 2003). Acculturation, or the process of
adopting and adjusting to a new culture, may be stressful, as immigrants are
uprooted, their social networks disrupted, and they may find it difficult to
become socially, economically, or culturally incorporated into their new
society (Rogler, 1994). Stress from acculturation may also lead immigrants
to adopt coping mechanisms such as substance use and changes in diet that
adversely affect health, although these behavior changes may also reflect
assimilation into the ways of the new host society, rather than being in-
dicative of stress, per se. Acculturation among immigrants may also lead to
increased contact with the dominant society and a resultant increased ex-
posure to stressful social encounters (Finch and Vega, 2003).
Studies that focus on stress-related explanations of the ‘‘unhealthy assim-
ilation’’ effect often study the relationship between indicators of accultur-
ation and health. Burnam et al. (1987) used data on residents of Los Angeles
from the Epidemiologic Catchment Area (ECA) to study the relationship
between acculturation and prevalence of psychiatric disorders. They found
Mexican immigrants to have lower prevalence of psychiatric disorders than
U.S.-born persons, and that, among Mexican Americans (immigrants and
U.S.-born, together), a high degree of acculturation, as measured by a 26-
item scale, was associated with a higher prevalence of psychiatric disorders
such as depression and alcohol dependence. However, most of the effect of
acculturation was accounted for by nativity. Within nativity, acculturation
had no significant association with psychiatric disorders. Kaplan and Marks
(1990) used a sample of Mexican Americans from the Hispanic Health and
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1092 Social Science Quarterly
Nutrition Examination Survey (HHANES) and found that greater accul-
turation, as measured by an eight-item scale of language and ethnic identity,
was associated with higher rates of depression, although results differed by
gender and age, and this study did not adjust for nativity. Vega et al. (2004)
studied Mexican Americans in Fresno, California and found that Mexican
immigrants had lower prevalence of psychiatric disorders and that time in
United States was associated with increased prevalence of psychiatric dis-
orders, particularly among those who entered the United States when young.
Acculturation, which was measured by a person’s language capability, was
not a significant predictor of illness. Finally, Ortega et al. (2000) reported
that among Mexican Americans drawn from the National Comorbidity
Survey, those who were more acculturated reported greater incidence of
psychiatric disorders.
Similar studies of the effects of acculturation have been conducted using
self-reported measures of physical health. Shetterly et al. (1996) found that
acculturation was associated with better self-rated health among Hispanics in
Colorado. In contrast, Finch and Vega (2003) found that some aspects of
acculturation, in this case legal status stress, were associated with lower levels
of self-reported general health among Mexican Americans in Fresno. A
similar finding using the same data and sample was reported by Finch et al.
(2001), although in this case, job market stress and not legal status stress was
the only measure of acculturation that was significantly related to worse
health.
Previous researchers have sought to measure the mental and physical
health consequences of discrimination-induced stress among Mexican im-
migrants. In a series of papers, Finch and colleagues (Finch and Vega, 2003;
Finch, Kolody, and Vega, 2000; Finch et al., 2001) examined the relation-
ship between perceived discrimination and depression, poor health, and
number of chronic conditions among Mexican Americans in Fresno. Gen-
erally, but not consistently, they found that greater levels of perceived dis-
crimination were associated with worse mental and physical health. Salgado
and Snyder (1987) also found that, among Mexican Americans from Los
Angeles, California, greater perceived discrimination was associated with
depression.
This brief review of the literature reveals that while stress is often cited as
an explanation of the ‘‘unhealthy assimilation’’ effect, there is relatively little
evidence on this issue. Most of what is known comes from studies that
examined how indicators of acculturation and perceived discrimination
affect Mexican health. Moreover, there is considerable inconsistency in the
findings from these studies.
Acculturation and time in the United States are naturally linked and some
studies measure acculturation by time in the United States, shedding little
light on the extent to which negative assimilation effects may be stress-
mediated. In addition, the effects of stressors related to discrimination or
acculturation may change or accumulate with time in the United States,
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Stress, Allostatic Load, and Health of Mexican Immigrants 1093
although no study has explicitly incorporated this possibility into the anal-
ysis. In this article, we add to the literature assessing whether stress is a
contributing factor to the decline in Mexican immigrant health with time in
United States by examining the relationship between allostatic load and time
in the United States. No previous study has used allostatic load, a construct
specifically developed to reflect the health consequences of prolonged or
cumulative stress, to assess whether the ‘‘unhealthy assimilation’’ effect may
be related to stress.
Analytical Framework
To measure the health consequences of stress, we use allostatic load score,
a composite biomeasure that builds on the tradition of using biomeasures as
indicators of the physiologic consequences of social inequities. Blood-pres-
sure reactivity, cytokine production, waist-to-hip ratio, cortisol levels, sym-
pathetic nerve activity, and glycated hemoglobin levels have been found to
be related to socioeconomic status, occupation, birth outcome, and envi-
ronmental risk (Seeman et al., 2001; Uchino, Cacioppo, and Kiecolt-Glaser,
1996; Roy, Steptoe, and Kirschbaum, 1998; Steptoe et al., 2002; Cohen,
Doyle, and Skoner, 1999; Marmot et al., 1998; Daniel et al., 1999; Sch-
norpfeil et al., 2003; Weinstein et al., 2003; Wadhwa et al., 2001; Stancil
et al., 2000; Maes et al., 1998; Evans, 2003; Geronimus et al., 2007).
McEwen and colleagues (McEwen, 1998; McEwen and Seeman, 1999)
developed the more global concept of allostatic load, or the cumulative wear
and tear on the body’s systems owing to repeated adaptation to stressors.
Stress and the coping required in stressful circumstances induce a phys-
iological response, introducing a complex cascade of stress hormones into
the body that, ideally, is shut down when the challenge to homeostasis
recedes (McEwen, 1998). The body’s ability to respond to acute stress
is protective in certain threatening situations (e.g., the ‘‘fight or flight’’
response), yet, when allostatic systems are not completely deactivated, the
body experiences overexposure to stress hormones causing health to dete-
riorate. Allostatic systems can be activated by stressors that are psychosocial
(e.g., perceived unfair treatment), environmental (e.g., toxic exposures or
ambient stressors in residential areas or workplaces), or by disregulation
of diurnal rhythms (i.e., disruption of the sleep/wake cycle). Long periods
of overexposure result in ‘‘allostatic load,’’ which can cause wear and tear on
the cardiovascular, metabolic, and immune systems and, thereby, contribute
to the development of chronic conditions such as hypertension, obesity, and
diabetes (McEwen, 1998; McEwen and Seeman, 1999; Seeman et al.,
1997a, 1997b). The biomeasures comprising the allostatic load score were
chosen to reflect such wear.
Both the cumulative nature of, and population differences in, allostatic
load are borne out in empirical studies that indicate increases in allostatic
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1094 Social Science Quarterly
load scores across the lifecourse (Crimmins et al., 2003; Geronimus et al.,
2006). Not only does allostatic load increase absolutely with age within
groups, but group differences become more pronounced at older ages. For
example, while black-white differences in allostatic load are small in the late
teens and early 20s, they widen significantly with increasing age (Geronimus
et al., 2006). This age pattern is consistent with early health deterioration, or
‘‘weathering,’’ among more disadvantaged groups, as insults to their health
accumulate across the lifecourse (Geronimus, 1992). If Mexican immigrants
are disproportionately exposed to physiological challenges in their residential
and work environments, or through persistent high-effort coping with the
demands of acculturation or with experiences of discrimination, then greater
durations of stay in the United States may have adverse health impacts. That
is, if stress, per se, contributes to the worse health observed in immigrants
with longer stays in the United States compared to recently arrived immi-
grants, one would expect to see evidence of higher allostatic load with time
in the United States.
By focusing on allostatic load, we look directly at a constellation of bi-
ological outcomes that are impacted by the physiological response to chronic
stress exposure, rather than measure respondents’ subjective assessment of
stressors. These biological outcomes are often objectively measured in the
data we analyze based on clinical examination, anthropometric measure-
ment, and laboratory analysis. Although data limitations do not allow us to
identify the specific sources of stress among immigrants, this approach
contributes evidence on whether there are differences in stress-mediated
health outcomes, whatever the source. We hypothesize that stress exposure
contributes to the worse health of Mexican immigrants with time in the
United States, and that those whose residence in the United States is of
longer duration will have higher allostatic load than those who arrived in the
United States recently.
We note that some unhealthy behaviors, such as cigarette smoking or poor
diet, can themselves contribute to biological outcomes that are associated
with increased allostatic load. If Mexican immigrants are more prone to
adopt unhealthy behaviors as they reside in the United States for longer
periods, this might damage important body systems in ways that intensify
allostatic load. Whether to view increased adoption of unhealthy behaviors
as confounding the association between stress and allostatic load or as one
mechanism by which stress contributes to allostatic load is theoretically am-
biguous. In our empirical models, we consider the possibility that increased
adoption of unhealthy behaviors is a potential confounder of any association
between stress and allostatic load among immigrants with longer-term stays
in the United States compared to others. To the extent that adoption
of these behaviors is more accurately construed as responsive to stressors, this
is a conservative approach to studying whether stress contributes to the
worse health of Mexican immigrants residing in the United States for longer
periods.
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Stress, Allostatic Load, and Health of Mexican Immigrants 1095
Empirical Model
To consider the question of whether stress contributes to the general
decline in Mexican immigrant health with time in the United States, we
assess whether the health consequences of stress, as measured by allostatic
load, differ by time in the United States among immigrants in a regression
framework controlling for potential confounders. Specifically, for Mexican
immigrants of a specific age, we specify the following regression model:
XK
ALL LOADit ¼ a þ lkTIME USitk þ g1HBit þ g2HIit þ g3DVit
k¼1
þ Xit G þ dt þ eijt : ð1Þ
In Equation (1), the allostatic load (ALL_LOAD) of immigrant i in year t
is a function of: time in the United States (TIME_US), which is measured
by k dummy variables indicating different lengths of stay in the United
States; health behaviors such as tobacco use (HB); and health inputs such as
doctor visits (DV ) and health insurance (HI), which is a proxy for use of
other health-care services. Equation (1) also includes additional controls for
person characteristics such as gender, marital status, education, and controls
for year effects.1
Note that Equation (1) is specified for persons of a specific age. In the
analysis, we use two age groups because of limited sample size: 30 to 44 year-
olds and 45 to 60 year-olds. The age restriction is imposed to account
explicitly for the possibility that the relationship between time in the United
States and allostatic load may differ by age of arrival. Being in the United
States for 20 years may have different implications for persons age 35 years
than for persons age 55 years.2 As specified in Equation (1), immigrants are
grouped into narrower age groups and thus age at arrival will be less of a
confounding influence for estimates of the effect of time in the United States.
We also conduct two sets of secondary analyses. As a bridge to the earlier
literature on the unhealthy assimilation effect, we repeat our analyses of
Mexican immigrants using self-reported health as the outcome. In this way,
we note whether we can, in effect, replicate in NHANES data the findings of
others who used the NHIS. Finally, to address whether stress and its health
consequences can explain the erosion with time in the United States of any
health advantage on arrival (or ‘‘healthy immigrant’’ effect), we estimate
regressions of allostatic load including U.S.-born persons in the analysis. We
1Sample size limitations prevent separate analyses by gender. Preliminary analyses indi-
cated that separate analyses by gender, or even allowing the effect of time in United States to
differ by gender, did not have sufficient statistical power to yield informative estimates. This
is a limitation of the study.
2There may be cohort effects (year of arrival effects), but these effects cannot be identified.
Year of arrival is a linear combination of year, age, and time in United States, all of which are
included in Equation (1).
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1096 Social Science Quarterly
use three groups of U.S. born as referents: Mexicans, non-Hispanic whites,
and non-Hispanic blacks. U.S.-born Mexicans are an appealing group to use
as a reference group because of their common heritage, although they, too,
may face discrimination or acculturative stress, as many are second gener-
ation. Using non-Hispanic whites and non-Hispanic blacks as referent
groups allows us to contextualize the experience of Mexican Americans
within the broader context of racial stratification in the United States. In all
analyses, we apply sampling weights and statistical procedures to account for
the complex sample design.
Data
Data for the analysis come from the National Health and Nutrition
Examination Survey, 1988–1994 (NHANES III). The NHANES surveys,
conducted by the National Center for Health Statistics (NCHS), used
stratified, multistage probability samples to provide national estimates of
health and nutritional status for the civilian, noninstitutionalized population
of the United States. An important strength of using NHANES data com-
pared to other surveys is that many health outcomes are measured objec-
tively and diagnoses of chronic disease, such as hypertension or diabetes, are
not conditioned on health-service access or utilization. We use data from the
NHANES III because, unlike more recent waves of NHANES data, they
provide information on nativity and time in the United States. The sample
selected for analysis includes Mexican Americans, both U.S. and foreign
born, and non-Hispanic U.S.-born white and black persons between the
ages of 30 and 60. The number of foreign-born Mexican immigrants aged
30 to 60 in the NHANES III is approximately 700, with approximately
500, or 70 percent, being between the ages of 30 and 44.
Dependent Variables
To measure allostatic load, we employ the algorithm used by Geronimus
et al. (2006), who adapted Seeman et al.’s (1997b) model for use with
NHANES, which does not collect data on primary mediators, and for use in
samples of broad age range compared to the primarily elderly samples in
which allostatic load algorithms were initially developed. Allostatic load is
measured by 10 biomeasures: systolic and diastolic blood pressures, body
mass index (BMI), glycated hemoglobin, albumin, creatinine clearance, tri-
glycerides, C-reactive protein, homocysteine, and total cholesterol. For each
biomeasure, we determine the high-risk threshold empirically based on the
distribution of that biomeasure in our sample. Following a standard ap-
proach, participants with a biomeasure reading beyond the threshold (de-
fined as o25th percentile for creatinine clearance and albumin and 475th
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Stress, Allostatic Load, and Health of Mexican Immigrants 1097
percentile for all others) receive a point for that biomeasure (Seeman et al.,
1997b, 2001; Crimmins et al., 2003). The points are then summed to
obtain the allostatic load score, with a maximum score of 10. In the
NHANES sample, high-risk thresholds are: albumin (4.2 g/dl); BMI (30.9);
C-reactive protein (0.41 mg/dl); creatinine clearance (66 mg/dl); diastolic
blood pressure (80 mmHg); glycated hemoglobin (5.4 percent); homocy-
steine (9 umol/l); systolic blood pressure (127 mmHg); total cholesterol
(225); and triglycerides (168 mg/dl). We include those on medication for
diabetes, hypertension, or high cholesterol in the determination of high-risk
status when assigning points for glycated hemoglobin, blood pressure, or total
cholesterol.3
Following Geronimus et al. (2006), and for ease of interpretation, we
construct the dependent variable by dichotomizing allostatic load scores
according to a high-score threshold. We estimate models using two different
thresholds (3 or 4) to assess whether estimates are sensitive to the cutoff
choice. We defined a high score as above either 3 or 4 based on previous
literature suggesting that differences between groups in subsequent mor-
bidity and mortality are seen when allostatic load scores reach 3 or 4 (Ge-
ronimus et al., 2006; Seeman et al., 1997b). We note these thresholds are
close to our sample means, suggesting that having a high score may be
conceived as being above the mean.
Self-rated health is conceptualized as an individual’s specific assessment of
his or her overall health status at the time of data collection. Self-rated health
is an ordered categorical variable coded in descending order with response
categories 1 5 excellent, 2 5 very good, 3 5 good, 4 5 fair, and 5 5 poor.
Following a standard approach, we constructed a dichotomous measure of
poor self-rated health equal to 1 if the respondent indicated that his or her
health was fair or poor and 0 otherwise.4
Explanatory Variables
Our key explanatory variable is time in the United States. We measure
this variable by a set of dummy variables indicating that the person has been
in the United States 10 or fewer years, 11 to 20 years, or 21 or more years.
Ideally, we would use finer categories of time in the United States, but
limited sample sizes prevent us from doing so. We did experiment with
slightly finer divisions for the younger age cohort, which is larger. Results
3We assume that those taking medication (and, thus, previously diagnosed with a chronic
disease) have already experienced systemic deterioration.
4We also constructed a measure of good health, which is equal to 1 if the person reported
his or her health to be excellent or good. Results using this measure were qualitatively the
same, but of opposite sign, as those reported in the text pertaining to poor health. Results are
available from the authors upon request.
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1098 Social Science Quarterly
were qualitatively similar to those reported in the text (results available from
the authors upon request).
Regression models included demographic, socioeconomic, and health in-
put covariates. Demographic variables included age, gender, and marital
status. Age was coded as a set of dummy variables with response categories
30–34, 35–39, 40–44, 45–49, 50–54, and 55–60. Gender is a dichotomous
variable equal to 1 for male and 0 for female. Marital status is measured by a
dichotomous indicator of married (married spouse in household, married
spouse not in household, living as married) and not married (widowed,
divorced, separated, and never married). Rural/urban status is equal to 1 if a
person lived in a place that is not located within an urbanized area as defined
by the U.S. Census Bureau and that has less than 2,500 inhabitants. Re-
spondents not qualifying as rural were classified as urban. Socioeconomic
variables included education and income. Education was measured by a
set of dummy variables indicating the following: 0–8 years, 9–11 years
(some high school), 12 years (high school graduate), some college, and
college graduate. Poverty income ratio is a continuous income-to-needs
variable measuring the ratio of household income to the poverty threshold,
which is adjusted for family size and composition.
Two measures of health inputs were included in the regression analyses.
Health insurance is a dichotomous variable coded yes or no. Number of
doctor visits in the past year was coded as an ordered categorical variable in
ascending order with response categories none, 1, 2, 3–5, 6–11, and 12 or
more. In addition, we included measures of health behaviors: smoking,
physical activity, and fruit and vegetable consumption. Smoking status is a
dichotomous variable coded yes or no. The amount of physical activity the
respondent regularly engages in is an ordered categorical variable with re-
sponse categories low, medium, and high. Fruit and vegetable intake is a
continuous variable reflecting the total servings consumed per day.
Results
Table 1 presents sample means of allostatic load by nativity, ethnicity, and
time in the United States. Note that the mean allostatic load score is ap-
proximately 3 for those ages 30 to 44 and 4.5 for those ages 45 to 60,
approximately at our high-score cutoffs. Table 1 reveals that U.S.-born
Mexicans and foreign-born Mexicans have significantly higher mean allo-
static loads than U.S.-born non-Hispanic whites. Among foreign-born
Mexicans, mean allostatic load and the proportion of persons with a high
allostatic load score tend to increase with time in the United States, par-
ticularly among the older cohort. Among those 45 to 60, foreign-born
Mexicans who have lived in the United States for 10 or fewer years have the
lowest allostatic load score and the smallest proportion of persons with a
high allostatic load. In contrast, foreign-born Mexicans who have lived in
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Stress, Allostatic Load, and Health of Mexican Immigrants 1099
TABLE 1
Allostatic Load Score by Nativity, Ethnicity, and Time in the United States
Mean Score Proportion with Proportion with
Allostatic Load Score of 31 Score of 41
Age 30 to 44 2.50 0.43 0.26
U.S.-born white
3.23 n n 0.61 n n 0.39 n n
(N 5 1,314)
U.S.-born black 3.15 n n 0.58 n n 0.41 n n
(N 5 1,244) 2.92 n n 0.55 n n 0.34 n n
U.S.-born Mexican
2.83 0.52 0.32
(N 5 569) 2.91 0.55 0.34
Foreign-born Mexican 3.10 0.63 n n 0.38
(N 5 575) 4.14 0.76 0.58
In U.S. 0 to 10 years
In U.S. 11 to 20 years 4.75 n n 0.87 n n 0.71 n n
In U.S. 21 or more
4.62 n n 0.84 n n 0.71 n n
years
Age 45 to 60 4.46 n n 0.80 0.67 n n
U.S.-born white
3.96 0.72 0.50
(N 5 1,188) 4.22 0.81 n n 0.61
U.S.-born blacks 4.56 n n 0.80 n n 0.77 n n
(N 5 655)
U.S.-born Mexican
(N 5 355)
Foreign-born Mexican
(N 5 261)
In U.S. 0 to 10 years
In U.S. 11 to 20 years
In U.S. 21 or more
years
n nIndicates estimate is statistically different at the 0.05 level from the corresponding estimate
for U.S.-born white.
the United States for 21 or more years have the highest allostatic load score
and the greatest proportion of persons with a high allostatic load. Non-
Hispanic blacks have the highest allostatic load scores of any group.
To assess whether time in the United States has an independent asso-
ciation with allostatic load among foreign-born Mexicans, we estimated a
regression model similar to Equation (1). The estimates, which are reported
as odds ratios from a logistic regression, are presented in Table 2. The
dependent variable is a dichotomous variable indicating whether a person
had an allostatic load of 3 or more, or 4 or more. Separate analyses were
conducted for two age groups: 30 to 44 and 45 to 60. For each group, we
estimate two specifications to assess how sensitive estimates of the effect of
time in the United States are to the addition of measured characteristics that
may be confounding influences: a model that includes a basic set of cov-
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TABLE 2
Associations (Odds Ratios) Between Time in the United States and Allostatic Load Among Foreign-Born Mexicans
Age 30–44 Age 45–60
Score of 31 Score of 31 Score of 41 Score of 31 Score of 31 Score of 41
In U.S. 11 to 20 years 1.05 1.08 1.15 2.39 n n 2.19 n 1.43
(po0.42) (po0.37) (po0.28) (po0.05) (po0.08) (po0.50)
In U.S. 21 or more years 3.85 n n n 5.53 n n n 4.60 n n n
1.29 1.18 1.19 (po0.01) (po0.01) (po0.01)
Extended covariates (po0.24) (po0.33) (po0.32)
Observations No Yes Yes
No Yes Yes
200 200 200
522 510 510
nOR is statistically significant po0.10; n nOR is statistically significant po0.05; n n nOR is statistically significant po0.01. Social Science Quarterly
NOTES: Reference category is persons in the United States 10 or fewer years. Score of 31 refers to when allostatic load is measured as a dichotomous variable
indicating a value of 3 or more. Score of 41 refers to when allostatic load is measured as a dichotomous variable indicating a value of 4 or more. Basic
covariate set includes age dummy variables, sex dummy variables, education dummy variables, marital status dummy variables, poverty indicator, rural/urban
residence indicator, and wave of study. Extended covariate set includes these additional variables: smoking indicator, fruit and vegetable consumption, health
insurance, doctor visits, and level of physical activity.
Stress, Allostatic Load, and Health of Mexican Immigrants 1101
ariates and another that includes an extended set of covariates, including
health behaviors and health-care inputs (see notes to the tables for list of
variables).
For the sample of younger persons (30 to 44), there is little evidence to
suggest that time in the United States is associated with an increased prob-
ability of having a high allostatic load score. This is true whether a high
allostatic load score is defined as 3 or more or 4 or more. For example, those
who have been in the United States for between 11 and 20 years have
virtually the same probability of having a high allostatic load score as newer
arrivals (0 to 10 years) who are the reference group (OR 5 1.08 or 1.15 in
models with the extended covariate set). Estimated odds ratios for those in
the United States for 21 or more years are of similar magnitude (OR 5 1.18,
or 1.19 for the extended covariate set), but neither estimate is significantly
different from 1.00.
Among Mexican immigrants who are older (ages 45–60), the probability
of having high allostatic load increases markedly with time in the United
States. For this older age group, the odds of having an allostatic load score of
at least 3 more than double for those who have been in the United States for
11 to 20 years compared to those who arrived in the United States in the
past 10 years (2.39 or 2.19 in models with the basic or extended covariate
set, respectively). The same group has a 43 percent (OR 5 1.43) higher
probability of having an allostatic load score of at least 4 than more recent
arrivals. Among older immigrants who have been in the United States for 21
or more years, the odds of having a high allostatic load score are approx-
imately four (OR 5 3.85) to five-and-one-half times (OR 5 5.53) higher
than those who have been in the United States for 10 or fewer years.
In sum, estimates in Table 2 for immigrants who are 45–60 years old are
consistent with the view that stress and its health consequences may accu-
mulate or increase with time in the United States and be a partial expla-
nation of the ‘‘unhealthy assimilation’’ effect. Moreover, there is no evidence
that health behaviors or medical care confound this association as the odds
ratios remain stable, or increase, once the extended set of covariates are
controlled.
Table 3 presents estimates of odds ratios from a logistic regression de-
signed to assess whether there are differences in allostatic load by nativity,
and whether any such differences vary with time in the United States of the
foreign born. We use three different reference groups: U.S.-born Mexicans,
U.S.-born non-Hispanic whites, and U.S.-born non-Hispanic blacks. Using
U.S.-born Mexicans and U.S.-born non-Hispanic blacks as comparison
groups may understate the role of stress on immigrant health because these
groups may be affected by discrimination and U.S.-born Mexicans may face
acculturation issues associated with being second (or third) generation im-
migrants. In fact, as Table 1 documents, the mean allostatic load of U.S.-
born Mexicans and non-Hispanic blacks is significantly higher than that of
U.S.-born non-Hispanic whites. For these analyses, we report only estimates
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TABLE 3
Associations (Odds Ratios) Between Nativity and Time in the United States and Allostatic Load Among Foreign-Born Mexicans and
U.S.-Born (Mexicans, Non-Hispanic Whites, Non-Hispanic Blacks)
Age 30–44 Age 45–60
Reference Group U.S.-Born U.S.-Born U.S.-Born U.S.-Born U.S.-Born U.S.-Born
Mexicans Whites Blacks Mexicans Whites Blacks
In U.S. 0 to 10 years 0.71 n 1.56 n 0.52 n n n 0.38 n n 0.42 n 0.13 n n n Social Science Quarterly
(po0.09) (po0.08) (po0.01) (po0.05) (po0.09) (po0.01)
In U.S. 11 to 20 years 1.45 n 0.50 n n n 0.90 1.16 0.43 n n
0.71 n (po0.08) (po0.01) (po0.42) (po0.38) (po0.03)
In U.S. 21 or more years (po0.06) 1.70 n n 0.60 n 0.96 2.08 n n 0.61
(po0.05) (po0.07) (po0.46) (po0.05) (po0.12)
Extended covariate set 0.86
N (po0.32) Yes Yes Yes Yes Yes
Yes 1,760 1,646 509 1,290 771
1,034
nOR is statistically significant po0.10; n nOR is statistically significant po0.05; n n nOR is statistically significant po0.01.
NOTES: Reference category is listed in column heading. Allostatic load is measured as a dichotomous variable indicating a value of 3 or more. Basic covariate
set includes age dummy variables, sex dummy variables, education dummy variables, marital status dummy variables, poverty indicator, rural/urban residence
indicator, and wave of study. Extended covariate set includes these additional variables: smoking indicator, fruit and vegetable consumption, health insurance,
doctor visits, and level of physical activity.
Stress, Allostatic Load, and Health of Mexican Immigrants 1103
obtained using a measure of high allostatic load defined as 3 or more;
estimates obtained from models using the alternative cutoff of 4 or more are
qualitatively the same (results available upon request).
Estimates indicate that in the younger cohort, foreign-born Mexicans tend
to have a lower likelihood of having high allostatic load (value of 3/4 or
more) than U.S.-born Mexicans and non-Hispanic blacks, but a greater
likelihood of having a higher allostatic load score than U.S.-born non-
Hispanic whites. The former result is consistent with a healthy migrant effect.
Most estimates are statistically significant. Estimates indicate that foreign-
born Mexicans are 14 percent (OR 5 0.86) to 29 percent (OR 5 0.71) less
likely to have a relatively high allostatic load than U.S.-born Mexicans, and
are 40 percent (OR 5 0.60) to 48 percent (OR 5 0.52) more likely to have a
high allostatic load score than U.S.-born non-Hispanic whites. However,
regardless of the reference group, estimates do not indicate a statistically
significant relationship between time in the United States and allostatic
load. Consistent with evidence in Table 2, the estimates in Table 3 provide
little evidence of an unhealthy assimilation effect for the younger cohort of
Mexican immigrants.
Among older cohorts, there is evidence consistent with a pronounced
healthy migrant effect. Foreign-born Mexicans who are recent arrivals (0 to
10 years) have a significantly lower probability of having a high allostatic
load score than the three other demographic groups. Odds ratios of the
association between being foreign born and allostatic load for this group
(i.e., newer arrivals) are 0.13, 0.38, and 0.42, depending on the reference
group, and are statistically significant. A much different story emerges for
older, foreign-born Mexicans who have been in the United States longer.
Among this older cohort, foreign-born Mexicans who have been in the
United States between 11 and 20 years have about the same probability of
having a high allostatic load score as U.S.-born Mexicans and U.S.-born
non-Hispanic whites, and their advantage vis-a`-vis U.S.-born blacks has
diminished markedly. For those foreign-born Mexicans who have been in
the United States the longest, their odds of having a high allostatic load
score are double (OR 5 2.08) that of U.S.-born whites, about the same as
U.S.-born Mexicans, and approximately 40 percent (OR 5 0.61) lower than
non-Hispanic blacks.
To summarize, for the older cohort of foreign-born Mexicans, there is
strong evidence that is consistent with both a healthy migrant effect and an
unhealthy assimilation effect, as those in the United States for 10 years or
less exhibit less than half the probability of having high allostatic load than
U.S.-born non-Hispanic whites, but this large advantage is eliminated for
those residing in the United States for 11–20 years. Even more striking,
those in the United States for more than 20 years suffer a large disadvantage
as they face twice the odds of high allostatic load as non-Hispanic whites.
In addition to the analyses just presented, we also assessed the relation-
ship between time in the United States and individual components of
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1104 Social Science Quarterly
allostatic load: BMI, systolic and diastolic blood pressure, and cholesterol.
Estimates obtained using these dependent variables are not included be-
cause they confirm the findings presented. Foreign-born Mexicans gen-
erally arrive in the United States healthier—lower blood pressure, lower
BMI, but higher cholesterol—than U.S.-born Mexicans, and the health
advantage deteriorates with time in the United States for older Mexican
immigrants.
In Table 4 we present estimates from regressions where we replace high
allostatic load score with a dichotomous measure of self-reported fair or poor
general health as the outcome. Among the younger cohort, longer durations
in the United States are associated with a lower probability of reporting fair
or poor health, although these results are not statistically significant. When
the extended covariate set is included, a small estimated increase in the odds
of reporting fair or poor health is seen for those in the United States 21 years
or more relative to more recent arrivals, compared to those in the United
States 11–20 years (relative to more recent arrivals), but in both cases the
point estimate fails to reach statistical significance at conventional levels. In
sum, there is little evidence of an unhealthy assimilation effect for the
younger cohort of foreign-born Mexicans.
Among older immigrants, estimates are consistent with a significant un-
healthy assimilation effect. The probability of being in fair or poor health
increases significantly with time in the United States. Those in the United
States for 11–20 years are estimated to be about three times more likely to
report being in fair or poor health than those in the United States 10 or
fewer years, although these estimates are not significant. However, those in
the United States 21 or more years are 875 percent (OR 5 9.75) more likely
to report being in fair or poor health than those in the United States 10 or
TABLE 4
Associations (Odds Ratios) Between Time in the United States and Poor/Fair
Self-Rated Health Among Foreign-Born Mexicans
Age 30–44 Age 45–60
In U.S. 11 to 20 years 0.66 0.43 3.01 2.46
In U.S. 21 or more years 0.60 0.75 9.75 n n n 8.81 n n n
Extended covariate set No Yes No Yes
N 507 495 197 197
n n nOR is statistically significant po0.01.
NOTES: Reference category is persons in the United States 10 or fewer years. Self-rated health is
measured as a dichotomous indicator of poor health, equal to 1 if self-rated health is reported
as fair or poor, otherwise equal to 0. Basic covariate set includes age dummy variables, sex
dummy variables, education dummy variables, marital status dummy variables, poverty indi-
cator, rural/urban residence indicator, and wave of study. Extended covariate set includes these
additional variables: smoking indicator, fruit and vegetable consumption, health insurance,
doctor visits, and level of physical activity.
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Stress, Allostatic Load, and Health of Mexican Immigrants 1105
fewer years in the specification with the basic set of covariates; and 781
percent (OR 5 8.81) more likely to report being in poor health than those
in the United States 10 or fewer years, after controlling for the extended set
of covariates.
Evidence on Selection
An important limitation of our analysis is its cross-sectional nature. Pre-
vious research has provided some evidence that selective migration with
respect to health by Mexican immigrants is most likely to be migration back
to Mexico of the less healthy (Abraido-Lanza et al., 1999; Palloni and Arias,
2004). This ‘‘salmon bias’’ would imply that a cross-sectional study of
changes in health with time in the United States, such as ours, provides a
conservative test of the hypothesis that health deteriorates among Mexican
immigrants with time in the United States.
To provide some evidence on this point, we examined how time in the
United States is correlated with socioeconomic status. We found that con-
ditional on age and gender, time in the United States is positively associated
with educational attainment and negatively associated with poverty. That is,
among the older immigrants (ages 45–60), those who have been in the
United States for 20 years or more are more highly educated and less likely
to be poor than those who have been in the United States for a shorter time.
This is exactly the same group where we find consistent evidence of stress-
mediated health deterioration with time in the United States. Thus, our
findings imply that the immigrants who have the highest probability of
having a high allostatic load score (45–60 year-olds in the United States for
at least 20 years) do so despite having the most advantaged socioeconomic
profiles. Further, while it is possible that 45–60 year-old immigrants in-
creased their educational attainment during their residence in the United
States, it may be more plausible that this association reflects either cohort
effects or the return migration of the least educated and the poorest im-
migrants as, unlike income, educational status is often a relatively stable
feature of adult life. Regardless of the cause, the bias resulting from the
association between socioeconomic profile and time in the United States
would lead us to underestimate the increased probability of having high
allostatic load with time in the United States.
Conclusion
A prominent hypothesis to explain the ‘‘unhealthy assimilation’’ effect
observed for Mexican immigrants is that repeated experience with stressors
linked to discrimination and acculturation adversely affects Mexican immi-
grant health as time in the United States increases. While plausible, this
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1106 Social Science Quarterly
hypothesis has not been extensively studied. Also, it has been examined in an
indirect fashion where measures thought to be correlated with stress are
correlated with health.
In this article, we tested this hypothesis in an arguably more direct way.
Specifically, we used the concept of allostatic load, which was developed to
measure the health consequences of prolonged exposure to stress, to assess
whether the cumulative impact of exposure to repeated or chronic stressors is
a partial explanation of the ‘‘unhealthy assimilation’’ effect often observed
for immigrants. Consistent with a healthy migrant effect, we found evidence
that 45–60 year-old Mexican immigrants are healthier upon arrival than
U.S.-born Mexican Americans or non-Hispanic whites or blacks. Consistent
with a stress-mediated ‘‘unhealthy assimilation’’ effect, we also found that
the health advantage of this group disappeared with time in the United
States. In this age group, those immigrants who resided in the United States
for at least 20 years exhibited twice the probability of having high allostatic
load than U.S.-born non-Hispanic whites and about the same probability as
U.S.-born Mexicans and non-Hispanic blacks. Estimates of the increased
probability of having high allostatic load with time in the United States for
this age group also remained stable in the presence of controls for health
behaviors and indicators of medical-care utilization, suggesting that such
factors are not confounders and that the poorer health of Mexican immi-
grants with longer stays in the United States should not be reduced to the
adoption of unhealthy lifestyles alone.
Data limitations constrained us to use a cross-sectional design, rather than
to follow immigrants longitudinally to observe whether their health changed
with time or whether selective migration might threaten the validity of our
results. However, previous literature and some evidence we presented point
to a ‘‘salmon bias’’ being the most likely form of selection bias. A salmon
bias would serve to dampen evidence of health deterioration with time in the
United States, suggesting that our findings are likely to underestimate the
extent to which health deteriorates with time in the United States.
In contrast, our findings for younger adult immigrants (ages 30–44) do
not offer consistent evidence of either a healthy migrant effect or of a stress-
mediated unhealthy assimilation effect with time in the United States. A
possible explanation for the divergence in findings between the older and
younger cohorts for allostatic load is that our capacity to detect such re-
lationships is likely smaller among this younger age group. Allostatic load is
conceived as a measure of cumulative wear and tear on the body’s systems
that results from chronic and prolonged exposure to stress (McEwen, 1998;
Crimmins et al., 2003; Geronimus et al., 2006). In the current study, the
absence of evidence of an unhealthy assimilation effect among younger
immigrants may be a result of both the cumulative nature of allostatic load
and the age pattern of weathering. At young ages, the effects of unhealthy
assimilation on allostatic load may not yet be observable, or may be too
small to detect with our current sample size. Had we been able to include
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Stress, Allostatic Load, and Health of Mexican Immigrants 1107
primary mediators in our allostatic load algorithm, our ability to pick up
differences at younger ages might have been improved.
A strength of our study is the use of a measure of stress-mediated wear and
tear on the body that is derived from objective clinical exam data and lab
tests performed as part of a national survey, rather than relying only on self-
reported health measures alone, or on variables that are more steps removed
from the stress process. Importantly, our measure of health is not affected by
differential access to healthcare. The findings of our analysis are consistent
with the hypothesis that repeated or chronic physiological adaptation to
stressors is one cause of the ‘‘unhealthy assimilation’’ effect. Our findings
neither rule out other potential contributors, nor provide a quantitative
estimate of how important stress is relative to other potential contributors.
This study also was subject to several limitations. First, we had relatively
small samples that resulted in imprecise estimates in some cases, and a
limited ability to draw firm inferences. Small samples also prevent us from
conducting analyses separately by gender. Second, measurement error in
years since immigration may result in significant bias (Jasso et al., 2004).
However, such measurement error would serve to dilute evidence of health
deterioration with time in the United States. Third, we could not control for
all the potentially confounding influences. We found little evidence of con-
founding by those variables we were able to include, such as smoking, diet,
physical activity, or medical-care utilization. Still, there may be unobserved
factors that are correlated with year of or age at immigrant arrival and past
determinants of health. In light of the limitations of the current study, as
well as those that pertain to the previous literature, we cannot conclude that
the repeated physiologic response to stressors to which Mexican immigrants
may be disproportionately exposed contributes to the apparently worsening
health of Mexican immigrants with time in the United States. However, our
findings, at least for the older age group we studied, are robust and con-
sistent with that hypothesis and, as such, add to a growing body of evidence
in favor of the plausibility of cumulative stress hypotheses to help explain
racial/ethnic and socioeconomic inequalities in health.
REFERENCES
Abraido-Lanza, A. F., B. P. Dohrenwend, D. S. Ng-Mak, and J. B. Turner. 1999. ‘‘The
Latino Mortality Paradox: A Test of the ‘Salmon Bias’ and Healthy Migrant Hypotheses.’’
American Journal of Public Health 89:1543–48.
Antecol, H., and K. Bedard. 2006. ‘‘Unhealthy Assimilation: Do Immigrants Converge to
American Health Status Levels?’’ Demography 43(2):337–60.
Arau´jo, Beverly Y., and Luisa N. Borrell. 2006. ‘‘Understanding the Link Between Dis-
crimination, Mental Health Outcomes, and Life Chances Among Latinos.’’ Hispanic Journal
of Behavioral Sciences 28(2):245–66.
Created for free by https://foxyutils.com
1108 Social Science Quarterly
Blake, S., R. Ledsky, C. Goodenow, and L. O’Donnell. 2001. ‘‘Recency of Immigration,
Substance Use, and Sexual Behavior Among Massachusetts Adolescents.’’ American Journal of
Public Health 91:794–98.
Burnam, A., R. Hough, M. Karno, J. Escobar, and C. Telles. 1987. ‘‘Acculturation and
Lifetime Prevalence of Psychiatric Disorders Among Mexican American in Los Angeles.’’
Journal of Health and Social Behavior 28:89–102.
Cho, Y., W. Frisbie, R. Hummer, and R. Rogers. 2006. ‘‘Nativity, Duration of Residence
and the Health of Hispanic Adults in the United States.’’ International Migration Review
38:184–211.
Cohen, S., W. Doyle, and D. Skoner. 1999. ‘‘Psychological Stress, Cytokine Production, and
Severity of Upper Respiratory Illness.’’ Psychosomatic Medicine 61:175–80.
Cohen, S., R. Kessler, and L. Gordon. 1997. Measuring Stress: A Guide for Health and Social
Scientists. New York: Oxford University Press.
Cohen, S., and T. A. Wills. 1985. ‘‘Stress, Social Support and the Buffering Hypothesis.’’
Psychological Bulletin 98(2):310–57.
Crimmins, E., M. Johnston, M. Hayward, and T. Seeman. 2003. ‘‘Age Differences in Allostatic
Load: An Index of Physiological Dysregulation.’’ Experimental Gerontology 38:731–34.
Daniel, M., K. O-Dea, K. Rowley, R. McDermott, and S. Kelly. 1999. ‘‘Social Environ-
mental Stress in Indigenous Populations: Potential Biopsychosocial Mechanisms.’’ Annals of
the New York Academy of Sciences 896:420–23.
Dey, A., and J. Lucas. 2006. ‘‘Physical and Mental Health Characteristics of U.S. and
Foreign-Born Adults: United States, 1998–2003.’’ Advance Data 369.
Escobar, J., C. Nervi, and M. Gara. 2000. ‘‘Immigration and Mental Health: Mexican
Americans in the United States.’’ Harvard Review of Psychiatry 8:64–72.
Evans, G. 2003. ‘‘A Multimethodological Analysis of Cumulative Risk and Allostatic Load
Among Rural Children.’’ Developmental Psychology 39(5):924–33.
Finch, B., R. Hummer, B. Kolody, and W. Vega. 2001. ‘‘The Role of Discrimination and
Acculturative Stress in Physical Health of Mexican-Origin Adults.’’ Hispanic Journal of Be-
havior Science 23:399–429.
Finch, B., B. Kolody, and W. Vega. 2000. ‘‘Perceived Discrimination and Depression
Among Mexican-Origin Adults in California.’’ Journal of Health and Social Behavior 41:
295–313.
Finch, B., and W. Vega. 2003. ‘‘Acculturation Stress, Social Support, and Self-Rated Health
Among Latinos in California.’’ Journal of Immigrant Health 5:109–15.
Gee, E., K. Kobayashi, and S. Prus. 2006. ‘‘Examining the ‘Healthy Immigrant Effect’ in
Later Life: Findings from the Canadian Community Health Survey.’’ Memo. Social and
Economic Dimensions of an Aging Population.
Geronimus, A. T. 1992. ‘‘The Weathering Hypothesis and the Health of African American
Women and Infants.’’ Ethnicity and Disease 2(3):207–21.
Geronimus, A., J. Bound, D. Keene, and M. Hicken. 2007. ‘‘Black-White Differences in
Age-Trajectories of Hypertension Prevalence Among Adult Women and Men, 1999–2002.’’
Ethnicity and Disease 17(1):40–48.
Geronimus, A., M. Hicken, D. Keene, and J. Bound. 2006. ‘‘‘Weathering’ and Age-Patterns
of Allostatic Load Scores Among Blacks and Whites in the United States.’’ American Journal
of Public Health 96:826–33.
Created for free by https://foxyutils.com
Stress, Allostatic Load, and Health of Mexican Immigrants 1109
Goel, M., E. McCarthy, R. Phillips, and C. Wee. 2004. ‘‘Obesity Among US Immigrant
Subgroup by Duration of Residence.’’ Journal of the American Medical Association 292:
2860–67.
Harker, K. 2001. ‘‘Immigrant Generation, Assimilation, and Adolescent Psychological
Wellbeing.’’ Social Forces 79(3):969–1004.
Jasso, G., D. Massey, M. Rosenzweig, and J. Smith. 2004. ‘‘Immigrant Health—Selectivity
and Acculturation.’’ In Racial and Ethnic Disparities in Health. Washington, DC: National
Academy Press.
Johnson, T., J. VanGeest, and Y. Cho. 2002. ‘‘Migration and Substance Use: Evidence from
the U.S. National Health Interview Survey.’’ Substance Use Misuse 37:941–72.
Kandula, N. R., M. Kersey, and N. Lurie. 2004. ‘‘Assuring the Health of Immigrants: What
the Leading Health Indicators Tell Us.’’ Annual Review of Public Health 25:357–76.
Kaplan, M., and G. Marks. 1990. ‘‘Adverse Effects of Acculturation: Psychological Distress
Among Mexican American Young Adults.’’ Social Science and Medicine 31:1313–19.
Kessler, R., K. Mickelson, and D. Williams. 1999. ‘‘The Prevalence, Distribution and
Mental Health Correlates of Perceived Discrimination in the United States.’’ Journal of
Health and Social Behavior 40:208–30.
Landale, N. S., R. S. Oropesa, and B. K. Gorman. 2000. ‘‘Migration and Infant Death:
Assimilation or Selective Migration Among Puerto Ricans?’’ American Sociological Review
65(6):888–909.
Lara, M., C. Gamboa, M. I. Kahramanian, L. S. Morales, and D. Hayes. 2005. ‘‘Accul-
turation and Latino Health in the United States: A Review of the Literature and its So-
ciopolitical Context.’’ Annual Review of Public Health 26:367–97.
Lopez-Gonzalez, L., V. Aravena, and R. Hummer. 2005. ‘‘Immigrant Acculturation, Gender
and Health Behavior: A Research Note.’’ Social Forces 84:581–93.
Maes, M., C. Son, A. Lin, R. DeJongh, A. Van Gastel, G. Kenis, E. Bosmans, I. De Meester,
I. Benoy, H. Neels, P. Demedts, A. Janca, S. Scharpe, and R. Smith. 1998. ‘‘The Effects of
Psychological Stress on Humans: Increased Production of Pro-Inflammatory Cytokines and a
Th1-Link Response in Stress-Induced Anxiety.’’ Cytokine 10:313–18.
Markides, K., J. Coreil, and L. Ray. 1987. ‘‘Smoking Among Mexican Americans: A Three
Generation Study.’’ American Journal of Public Health 77:708–11.
Marks, G., M. Garcia, and J. Solis. 1990. ‘‘Health Risk Behaviors of Hispanics in the United
States: Findings from NHANES, 1982–1984.’’ American Journal of Public Health
80(Supp.):20–26.
Marmot, M., R. Ruhrer, S. Ettner, N. Marks, L. Bumpass, and C. Ryff. 1998. ‘‘Contribution
of Psychosocial Factors to Socioeconomic Differences in Health.’’ Milbank Quarterly
76(3):403–48.
McEwen, B. 1998. ‘‘Protective and Damaging Effects of Stress Mediators.’’ New England
Journal of Medicine 338(3):171–79.
McEwen, B., and T. Seeman. 1999. ‘‘Protective and Damaging Effects of Mediators of
Stress: Elaborating and Testing the Concepts of Allostasis and Allostatic Load.’’ Annals of the
New York Academy of Sciences 896:30–47.
Ortega, A., R. Rosenheck, M. Alegria, and R. Deshi. 2000. ‘‘Acculturation and the Lifetime
Risk of Psychiatric and Substance Use Disorders Among Hispanics.’’ Journal of Nervous and
Mental Disease 118:728–35.
Created for free by https://foxyutils.com
1110 Social Science Quarterly
Palloni, A., and E. Arias. 2004. ‘‘Paradox Lost: Explaining the Hispanic Adult Mortality
Advantage.’’ Demography 41:385–415.
Paradies, Y. 2006. ‘‘A Systematic Review of Empirical Research on Self-Reported Racism and
Health.’’ International Journal of Epidemiology 35:888–901.
Rogler, L. H. 1994. ‘‘International Migrations: A Framework for Directing Research.’’
American Psychologist 49:701–08.
Roy, M., A. Steptoe, and C. Kirschbaum. 1998. ‘‘Life Events and Social Support as Mod-
erators of Individual Differences in Cardiovascular and Cortisol Reactivity.’’ Journal of Per-
sonality and Social Psychology 75(5):1273–81.
Salgado, D., and N. Snyder. 1987. ‘‘Factors Associated with Acculturative Stress and De-
pressive Symptomatology Among Married Mexican Immigrant Women.’’ Psychology of
Women Quarterly 11:475–88.
Schnorpfeil, P., A. Noll, R. Schulze, U. Ehlert, K. Frey, and J. E. Fischer. 2003. ‘‘Allostatic
Load and Work Conditions.’’ Social Science and Medicine 57:647–56.
Seeman, T., B. McEwen, B. Singer, M. Albert, and J. Rowe. 1997a. ‘‘Increase in Urinary
Cortisol Excretion and Memory Declines: MacArthur Studies of Successful Aging.’’ Journal
of Clinical Endocrinology and Metabolism 82:2458–65.
Seeman, T., B. Singer, J. Rowe, R. Horwitz, and B. McEwen. 1997b. ‘‘Price of Adaptation
—Allostatic Load and its Health Consequences.’’ Archives of Internal Medicine 157:
2259–68.
Seeman, T., B. Singer, C. Wilkinson, and B. McEwen. 2001. ‘‘Gender Differences in Age-
Related Changes in HPA Axis Reactivity.’’ Psychoneuroendocrinology 26:225–40.
Shetterly, S., J. Baxter, L. Mason, and R. Hamman. 1996. ‘‘Self-Rated Health Among
Hispanic vs Non-Hispanic White Adults: The San Luis Valley Health and Aging Study.’’
American Journal of Public Health 86:1798–1801.
Singh, G., and R. A. Hiatt. 2006. ‘‘Trends and Disparities in Socioeconomic and Be-
havioural Characteristics, Life Expectancy, and Cause-Specific Mortality of Native-Born and
Foreign-Born Populations in the United States, 1979–2003.’’ International Journal of
Epidemiology 35(4):903–19.
Singh, G., and Barry A. Miller. 2004. ‘‘Health, Life Expectancy, and Mortality Patterns
Among Immigrant Populations in the United States.’’ Canadian Journal of Public Health
95(3):1–14.
Singh, G., and M. Siapush. 2002. ‘‘Ethnic-Immigrant Differentials in Health Behaviors,
Morbidity, and Cause-Specific Mortality in the United States: An Analysis of Two National
Data Bases.’’ Human Biology 74(1):83–109.
Stancil, T., I. Hertz-Picciotto, M. Schramm, and M. Watt-Morse. 2000. ‘‘Stress and
Pregnancy Among African American Women.’’ Paediatric and Perinatal Epidemiology 14:
127–35.
Stephen, E., K. Foote, G. Hendershot, and C. Schoenborn. 1994. ‘‘Health of the Foreign-
Born Population: United States, 1989–1990.’’ Advance Data 241.
Steptoe, A., P. Feldman, S. Kunz, N. Owen, G. Willemsen, and M. Marmot. 2002. ‘‘Stress
Responsivity and Socioeconomic Status: A Mechanism for Increased Cardiovascular Disease
Risk?’’ European Heart Journal 23:1757–63.
Thomas, T. 1995. ‘‘Acculturative Stress in the Adjustment of Immigrant Families.’’ Journal
of Social Distress and the Homeless 4:131–42.
Created for free by https://foxyutils.com
Stress, Allostatic Load, and Health of Mexican Immigrants 1111
Uchino, B., J. Cacioppo, and J. Kiecolt-Glaser. 1996. ‘‘The Relationship Between Social
Support and Physiological Processes: A Review with an Emphasis on Underlying Mecha-
nisms and Implications for Health.’’ Psychological Bulletin 119(3):488–531.
Vega, W., and R. Rumbaut. 1991. ‘‘Ethnic Minorities and Mental Health.’’ Annual Review of
Sociology 17:351–83.
Vega, W., W. Sirbney, S. Aguilar-Gaxiola, and B. Kolody. 2004. ‘‘12-Month Prevalence of
DSM-III-R Psychiatric Disorders Among Mexican Americans: Nativity, Social Assimilation,
and Age Determinants.’’ Journal of Nervous and Mental Disease 192:532–41.
Wadhwa, P., J. Culhane, V. Rauh, and S. Barve. 2001. ‘‘Stress and Preterm Birth: Neu-
roendocrine, Immune-Inflammatory, and Vascular Mechanisms.’’ Maternal and Child Health
Journal 5:119–25.
Weinstein, M., N. Goldman, A. Hedley, L. Yu-Hsuan, and T. Seeman. 2003. ‘‘Social
Linkages to Biological Markers of Health Among the Elderly.’’ Journal of Biosocial Science
35:433–53.
Created for free by https://foxyutils.com
NIH-PA Author ManuscriptNIH Public Access
NIH-PA Author ManuscriptAuthor Manuscript
NIH-PA Author ManuscriptAAOHN J. Author manuscript; available in PMC 2010 October 26.
Published in final edited form as:
AAOHN J. 2010 May ; 58(5): 185–196. doi:10.3928/08910162-20100428-01.
Stressors Among Latino Day Laborers A Pilot Study Examining
Allostatic Load
A. B. de Castro, PhD, MSN/MPH, RN, Joachim G. Voss, PhD, RN, Ayelet Ruppin, MN, RN,
Carlos F. Dominguez, MPH, and Noah S. Seixas, PhD, MS
Dr. de Castro is Assistant Professor, Dr. Voss is Assistant Professor, and Ms. Ruppin was a master's
student, University of Washington School of Nursing, Seattle, WA. Mr. Dominguez is Research
Coordinator and Dr. Seixas is Professor, University of Washington School of Public Health, Seattle,
WA
Abstract
This pilot study evaluated the feasibility of conducting a research project focused on stressors and
allostatic load (AL) among day laborers. A total of 30 Latino men were recruited from CASA Latina.
a worker center in Seattle. Participants completed an interview and researchers measured six
indicators of AL (body mass index, waist-to-hip ratio, systolic blood pressure, diastolic blood
pressure, C-reactive protein, and cortisol). Percentages and mean scores were calculated for several
self-reported stressors in work, economic, and social contexts and were compared between low and
high AL groups. Overall, participants with high AL reported experiencing more stressors than those
with low AL. Additionally, those with high AL generally reported being less healthy both physically
and mentally. Findings suggest that Latino day laborers experience stressors that place them at risk
for high AL. Also, a study of this nature is possible, but must be conducted with trust and collaboration
between researchers and community partners.
Occupational health risks for immigrant day laborers have received increasing attention in
recent years (Buchanan, 2004; Cummings & Kreiss, 2008; Pransky et al., 2002; Seixas,
Blecker, Camp, & Neitzel, 2008). Day labor is defined as temporary, informal work
arrangements with employers lasting for short periods, typically one day at a time. Working
on this contingent basis, day laborers are precariously employed and face job insecurity, low
income, limited benefits and protections, and increased social and economic vulnerability
(Benach & Muntaner, 2007; Tompa, Scott-Marshall, Dolinschi, Trevithick, & Bhattacharyya,
2007). Further, day labor is commonly associated with work involving high-risk job activities
(e.g., construction, painting, landscaping, fishing, household moving, home renovation,
warehousing, janitorial and cleaning work, and manufacturing) that can have serious work-
related injury and illness consequences (Pransky et al., 2002; Valenzuela, 1999). These jobs
involve a variety of hazards (e.g., dangerous mechanized tools and equipment, high noise
levels, falls from height, and exposure to chemicals and dust) and often lack appropriate
controls, including the absence of personal protective equipment (PPE). Further, job
opportunities (albeit temporary) for day laborers may fluctuate based on demand and season,
resulting in extended periods of unemployment.
Copyright © American Association of Occupational Health Nurses, Inc.
Address correspondence to A. B. de Castro, PhD, MSN/MPH, RN, University of Washington School of Nursing, Box 357263, Seattle,
WA 98195-7263. [email protected]..
The authors disclose that they have no significant financial interests in any product or class of products discussed directly or indirectly
in this activity.
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de Castro et al. Page 2
NIH-PA Author Manuscript Latino immigrants are a significant portion of the day labor work force and are increasingly
hired for the most hazardous jobs (Baron & Dorsey, 2006; LaVeist, 2005; Ochsner et al.,
NIH-PA Author Manuscript 2008; Seixas et al., 2008; Walter, Bourgois, Margarita Loinaz, & Schillinger, 2002), due in
part to their marginalized social and immigration status. For example, the majority of day
laborers may be undocumented immigrants (Valenzuela & Theodore, 2006) who live in
constant fear of deportation. Lack of documentation can provide supervisors and employers a
means to control, exploit, and intimidate poor workers into accepting abusive circumstances
(Martinez, 2006). As such, these workers are less likely to demand improved working
conditions or to refuse hazardous work. Among immigrants, Latinos have repeatedly been
shown to have an elevated risk of occupational injury and fatality, with injury and fatality rates
nearly twice those of all workers (Loh & Richardson, 2004; Pransky et al., 2002). Injured
immigrant Latino workers report little or no occupational safety and health training and often
do not benefit from workers' compensation or other forms of insurance, an oft-cited challenge
for precariously employed and contingent workers (Azaroff, Levenstein, & Wegman, 2004;
Quinlan & Bohle, 2004; Quinlan & Mayhew, 1999; Welch, Dong, Carre, & Ringen, 2007).
Applying Research to Practice
Day laborers can benefit from services that occupational health nurses provide, including
training about injury prevention, as a way to help prevent more chronic effects of stress.
Occupational health nurses can assume several roles, such as informing research questions,
determining features of study design and protocol, participating in data collection, and
crafting interventions based on research findings, in studies examining the effects of work-
related stressors on health. As advocates for worker health, occupational health nurses can
encourage and facilitate relationships between researchers and community-based
organizations serving marginalized work forces. Using an ecological perspective,
occupational health nurses should consider how factors external to the immediate work
environment spanning the many layers of society impact the health of worker populations.
NIH-PA Author Manuscript Working in contingent, precarious jobs, living as a marginalized population, and having
restricted means to improve social and economic status can be overwhelmingly stressful to
Latino day laborers. For example, consistently working under conditions that pose the threat
of injury or death can be highly stressful. Employment insecurity can also be a major stressor
because of implications related to income shortages and lack of benefits (e.g., health insurance),
which, in turn, lead to difficulties paying for food, housing, and health care services. Further,
chronic unemployment may contribute to social isolation, loss of self-esteem, and unhealthy
behaviors (Bartley, 1994). Walter et al. (2002) depict the sorts of stressful circumstances that
day laborers typically encounter using an ecological perspective. The authors present a set of
layered social contexts (e.g., large-scale social forces, local street corner, workplace, family)
that shape day laborers' lives and their experiences of work injury.
ALLOSTATIC LOAD AND RELEVANCE TO DAY LABOR
Previous research has shown that stressful life and work experiences are harmful to health.
Lazarus and Folkman (1984) characterized the “stressor-stress-strain” model as a process in
which an event or a set of conditions (stressor) can elicit a physiologic response (stress) that
may subsequently lead to a more chronic reaction (strain) should the stressor persist or the
stress response go unrelieved. Environmental stressors and challenges can activate physiologic
responses at multiple levels—from the cellular to the systemic. For example, under dangerous
conditions, adrenalin is released, causing increased heart rate and blood pressure (i.e., “fight
or flight” response). Chronic stress experiences can result in sustained elevations of multiple
stress hormones (e.g., cortisol, epinephrine, norepinephrine) and, subsequently, disruption of
normal functioning of various physiologic systems (e.g., cardiovascular, immune, endocrine,
AAOHN J. Author manuscript; available in PMC 2010 October 26.
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de Castro et al. Page 3
NIH-PA Author Manuscript and nervous systems) (The John D. and Catherine T. McArthur Foundation, Research Network
on Socioeconomic Status and Health, 1999).
NIH-PA Author Manuscript
McEwen (1998) and McEwen and Seeman (1999) developed the concept of allostatic load
NIH-PA Author Manuscript (AL) to characterize the physiologic effects of chronic stress. The idea of allostasis (“stability
through change” or the active process of returning the body to homeostasis), introduced by
Sterling and Eyre (1988), suggests that persistent activation of multiple physiologic responses
returns the body to its “normal” state in reaction to environmental stressors. Over time, this
process results in an accumulation and burden of “allostatic load.” These dysregulations, even
if minor, across multiple physiologic systems collectively have a “wear and tear” effect that
ultimately leads to overall health risk and manifests in clinical conditions (Karlamangla, Singer,
McEwen, Rowe, & Seeman, 2002; McEwen, 1998; Seeman, Singer, Ryff, Dienberg Love, &
Levy-Storms, 2002). As such, measuring markers of AL as a precursor to clinical indicators
of disease provides insight into risk prior to clinical onset.
Conventionally, AL is a composite measure composed of multiple biological indicators.
Seeman et al. (2004), Seeman, McEwen, Rowe, and Singer (2001), and Seeman et al. (2002)
have used 10 biological parameters to measure AL: systolic and diastolic blood pressure (SBP
and DBP), waist-to-hip ratio (WHR), serum high-density lipoproteins (HDL), total cholesterol,
glycosylated hemoglobin (HbA1c), serum dihydroepiandrosterone sulfate (DHEA-S), 12-hour
urinary cortisol excretion, and 12-hour urinary norepinephrine (NE) and epinephrine (EPI)
excretion. An AL score is calculated by summing the number of parameters (SBP, DBP, WHR,
HbA1c, cortisol, NE, and EPI) in which levels were in the highest quartile and the parameters
(HDL and DHEA-S) in the lowest quartile. Other researchers have used a subset of these
measures or have substituted alternative measures, such as body mass index (BMI), C-reactive
protein (CRP), and tumor necrosis factor alpha (TNF-α) (Crimmins, Johnston, Hayward, &
Seeman, 2003; Langelaan, Bakker, Schaufeli, van Rhenen, & van Doornen, 2007; Sabbah,
Watt, Sheiham, & Tsakos, 2008; Schnorpfeil et al, 2003).
Although the majority of previous research on AL has been conducted with general population
samples, a few studies have considered AL in relation to occupational stressors. For example,
Schnorpfeil et al. (2003) reported that self-reported job demand was associated with higher AL
scores among German industrial workers. In a study of school teachers in Germany and
Luxembourg, Bellingrath, Weigl, and Kudielka (2008) observed significantly higher AL scores
among those reporting high effort-reward imbalance at work. And, von Thiele, Lindfors, and
Lundberg (2006) found that work-related fatigue increased the risk for higher AL among
Swedish women working in public health organizations.
No previous research was found that examined the impact of AL in a sample of immigrant
workers with minority status “employed” under unstable, precarious conditions. Given the
circumstances and conditions in which Latino day laborers live and work, it is reasonable to
suspect that they bear significant AL. They work in unsafe, unregulated conditions, are exposed
to uncontrolled occupational hazards, and are not provided safety or PPE. Regarding broader
work organization issues, these workers have no formal workplace structure, but rather
temporary employment situations and job tasks (primarily manual labor) that change on a daily
basis and for which they are paid low wages in cash. In the United States, the demand for
contingent workers, including day laborers, has increased, reducing employer costs and
potentially exploiting workers, particularly those who are undocumented. Workers in urban
areas are more likely to be hired to fill day labor jobs in home repair, construction, food service,
and cleaning services. Further, Latino day laborers may face discrimination, both
interpersonally and institutionally, because of their minority and documentation status. Finally,
it is not uncommon for these workers to have transitory lives, moving between various cities
in search of work, and they are often separated from family or other social support networks.
AAOHN J. Author manuscript; available in PMC 2010 October 26.
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de Castro et al. Page 4
NIH-PA Author Manuscript The combination of work-related, economic, and social stressors encountered by Latino day
laborers can have a profound effect on individual health status and may contribute to disparate
health for Latinos over and above experiencing a work-related injury or illness.
STUDY PURPOSE
This article presents descriptive data from a pilot study assessing the feasibility of conducting
research on work-related, economic, and social stressors experienced by Latino day laborers
and their potential impact on health and AL. Second, the authors report methods and procedures
for navigating the issues related to accessing this difficult-to-reach population as well as
recruiting study participants. Additionally, the authors illustrate how academic institutions and
local community-based organizations can effectively work together to conduct research. The
underlying purpose of this research project was to evaluate the feasibility of conducting a study
involving an interview survey and the collection of biological markers for AL among Latino
day laborers.
NIH-PA Author Manuscript METHODS
Study Participants
This pilot study involved collaboration between researchers at the University of Washington
and CASA Latina, a worker center in downtown Seattle. Although worker centers operate in
different ways, many function as organized systems for hiring day laborers. They provide a
space for more equitable hiring practices, including holding a lottery for distributing jobs and
setting wage scales for various jobs.
NIH-PA Author Manuscript A total of 30 male day laborers of Latino descent participated in this pilot study. Recruitment
and enrollment were integrated into the morning job lottery system at CASA Latina.
Recruitment announcements briefly explaining the research project and procedures were read
in Spanish at the beginning of the job lottery, indicating that participants would be paid $60
cash for 4 hours ($15 per hour is commensurate with the rates for gardening and moving). After
the job lottery, another lottery was held for the opportunity to participate in the study. This was
done to avoid interfering with standard operating procedures and the opportunity to obtain
“real” work for the day, which sometimes leads to more long-term employment. Five day
laborers were selected and enrolled per day. Only one individual refused to participate after
being selected, which occurred after the consent process. Private office space at CASA Latina
was used for the consent process. To obtain informed consent, a research team member read
the consent form in either English or Spanish (as preferred by the study participant) to address
the potential for low literacy. In addition, a CASA Latina staff member served as an impartial
witness to ensure that informed consent was obtained without coercion. Approval to conduct
this study was provided by the Human Subjects Division at the University of Washington.
Data Collection
Study participants were driven from CASA Latina to the University of Washington for data
collection. Spanish-speaking research team members conducted survey interviews and were
available during the collection of biological measures. After data collection was completed,
study participants were driven back to CASA Latina.
Measures
Allostatic Load—For the pilot study, six AL indicators were collected: (1) height and weight
for BMI; (2) waist and hip circumference in centimeters for WHR; (3) SBP; (4) DBP; (5) CRP,
a marker of inflammation, through dried blood spots; and (6) salivary cortisol, a stress hormone.
For SBP and DBP, study participants were seated and two readings were taken and averaged.
AAOHN J. Author manuscript; available in PMC 2010 October 26.
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