Cad Saude Publica
Cadernos de Saúde Pública
Cad. Saúde Pública
0102-311X
1678-4464
Fundação Oswaldo Cruz
Hemos investigado si es estatus socioeconómico durante toda la vida influye en la
asociación entre raza y presencia de mioma uterino. Se analizaron a 1.475 funcionarias,
con datos provenientes de la cohorte Pró-Saúde (1999-2001) en Río de Janeiro, Brasil. La
posición socioeconómica durante toda la vida se determinó por la educación de los padres
(posición socioeconómica temprana), educación de la participante (posición socioeconómica
principio de la edad adulta) y combinaciones de los mismos (posición socioeconómica
acumulada). Exámenes ginecológicos/mama y el plan de salud se consideran marcadores de
acceso a la salud. La razón de riesgo (hazards ratio, HR) y el intervalo de un 95% de
confianza (IC95%) se calcularon utilizando modelos de riesgos proporcionales. La
comparación entre mujeres blancas, negras y mulatas/mestizas concluyó que tenían un riesgo
más elevado de mioma uterino, en los siguientes porcentajes respectivamente HR: 1,6 IC95%:
1,2-2,1; HR: 1,4 IC95%: 0,8-2,5. Las estimaciones fueron prácticamente idénticas en los
modelos que incluyen diferentes variables de posición socioeconómica para toda la vida.
Este estudio apoya la evidencia de mayor riesgo de mioma uterino entre mujeres de color de
piel más oscuro y también sugiere que la posición socioeconómica para toda la vida no
influye en esta asociación.
Introduction
Uterine leiomyomas, also called fibroid tumors, are the most common benign neoplasm of the
female reproductive system. Their etiology is poorly understood, but sex steroid hormones
are thought to influence their development and growth 1 . Although uterine leiomyomas have almost no association with mortality, they are
related to a significant number of gynecological and obstetric problems affecting a woman’s
quality of life during her reproductive years 2 . As a result, uterine leiomyomas are the most common indication for hysterectomy
2
,
3
,
4 .
In the United States, uterine leiomyomas occur two to nine times more often in black than
in white women of all ages, and are associated with more serious symptoms in blacks, who are
diagnosed at younger ages and have higher hysterectomy rates than whites 5
,
6
,
7
,
8
,
9
,
10
,
11 . The underlying mechanisms of this color/race inequality remain unknown.
Established tumor risk factors, for example those tied to reproductive health (e.g. parity,
age at first pregnancy, history of infertility, age at menarche, and contraceptive use),
seem to explain only a small fraction of the race/color inequalities 5
,
6
,
8 . Alternative hypotheses, not yet explored in depth, point to an increase in
polymorphisms and impaired regulation of hormonal receptors involved in the development of
uterine leiomyomas 12
,
13 , as well as vitamin D deficiency 14
,
15 and psychosocial stress 16
,
17 , as potential high-impact causes of tumors in black women.
The role of socioeconomic position in these racial inequalities has also received little
attention. Given that black women in many countries find themselves disproportionately
disadvantaged in the social hierarchy, it is plausible to attribute these disparities, at
least in part, to socioeconomic inequalities over the life course. Moreover, uterine
leiomyomas is a slow-growing tumor that is diagnosed most often in women between 40 and 50
years of age, but can begin to develop a decade earlier 1 . For this reason, socioeconomic position markers from childhood and the beginning
of adult life – time periods that most likely precede the onset of tumors – could help to
clarify the color/race inequalities in uterine leiomyomas.
Empirical exploration of theoretical models from life course epidemiology could help us
better understand these relationships 18
,
19
,
20
,
21 . According to life course models, health outcomes depend not only on exposure to
risk factors, but also on individual lifespan and duration of exposure to those factors.
Three such models have been developed: (1) a “critical period” or “sensitivity” model, (2) a
social mobility model, and (3) a risk accumulation model. Under the first, socioeconomic
position in early life influences health outcomes regardless of socioeconomic position in
adulthood or other mediating factors. In the second, the focus is on socioeconomic position
trajectories and associated health effects over the lifetimes of individuals. In the third,
the gradual accumulation of exposures throughout life is what influences adult health 18
,
19
,
20
,
21 .
It can be hypothesized that socioeconomic adversity throughout life could be a mediator of
the relationship between color/race on the one hand, and influences on uterine leiomyomas on
the other. Socioeconomic disadvantage could influence patterns of health behaviors related
to uterine leiomyomas, sources of psychosocial stress, and more directly the deregulation of
ovarian hormones. This influence could occur at specific times of life, such as the
beginning of adulthood (critical period and/or sensitivity model), or it could be lifelong
(social mobility model), causing the accumulation of different exposures among women of
different racial groups (risk accumulation model).
To our knowledge, no studies have undertaken such an approach. Brazil possesses distinct
characteristics for the conduct of such studies, as it has the largest black population
outside of Africa, and marked socioeconomic and cultural diversity. In addition, unlike the
United States, where origin and ancestry determine race, racial classification in Brazil is
based on phenotypic characteristics, mainly skin color. As a result, racial identification
tends to be more complex and fluid in the Brazilian context, resulting in the use of
distinct terms to identify the skin color/race of the population 22 . Until now, information about uterine leiomyomas has been based on studies that
analyzed the variable of race in a dichotomous way (white/non-white); Brazil’s distinct
perspective on matters of skin color/race could increase our understanding of the
relationship between race and uterine leiomyomas.
This article presents the results of a study of color/race inequality in the self-reported
history of uterine leiomyomas among Brazilian women participating in the longitudinal
Pró-Saúde Study. Its principal objective was to investigate whether socioeconomic position –
during childhood, at the beginning of adult life, and throughout the life course – mediates
the association between skin color/race and a self-reported medical diagnosis of uterine
leiomyomas.
Methods
Study population and data collection
The Pró-Saúde Study is a longitudinal study of civil servants at university campi located
in the State of Rio de Janeiro, Brazil. Its principal focus is the investigation of social
determinants of health and health behaviors 23 .
The analyses in this article were conducted using cross-sectional data from participants
enrolled at baseline. Eligible within the Pró-Saúde Study were 2,466 female workers, of
whom 1,819 participated in both phases of the baseline study in 1999 and 2001 (73.8% of
those eligible). Participants were excluded if they did not provide information about
occurrence of uterine leiomyomas, age at diagnosis, or age at hysterectomy (n = 96); if
they had a diagnosis of uterine leiomyomas or a hysterectomy before the age of 20 (n = 4);
or if they did not provide information about one of the exposure variables (n = 235). In
total, 1,475 participants were included in the current analyses.
Multi-dimensional questionnaires were administered by trained field workers and filled
out by participants. Pilot studies, validation of scales, and reliability tests were
carried out to assess the quality of information 23 .
Variables
• Uterine leiomyoma
Ascertainment of uterine leiomyomas was based on the question, “ Has a doctor
ever informed you that you had a uterine leiomyomas, a benign tumor in the
uterus? ”. The test-retest reliability of this information was evaluated over a
two-week period among 98 individuals who were ineligible for the Pró-Saúde Study, but who
were employees of the same university. Reliability was high (kappa = 0.94, or 95%CI:
0.86-1.00). Participants also provided information about their age at uterine leiomyomas
diagnosis, whether that diagnosis was confirmed by a diagnostic ultrasound or
histopathology report, and whether a hysterectomy was performed as a result.
• Skin color/race
Information about the participants’ skin color/race was based on an open-ended question,
“ In your opinion, what is your skin color or race? ”. Forty-one distinct
terms were registered by participants to self-identify participants’ skin color/race 24 . Those terms were categorized into skin color/race: white, brown (e.g., “parda”,
“morena”, “mulata”, “mestiça”, “cabocla”), black (e.g. “negra”, “preta Africana”,
“escura”), and yellow. For the analyses in this article, yellow was excluded due to the
small number of participants who reported being in this category (n = 8, 0.5%). More
information can be found in Maio et al. 24 .
• Markers of life course socioeconomic position
For information on childhood socioeconomic position, maternal and paternal educational
levels were evaluated separately (less than primary education, primary education,
secondary education or more). For socioeconomic position in early adult life, each
participant’s educational level was classified as primary education or less, secondary
education, college or more. Cumulative socioeconomic position measures were also explored,
considering separately (1) the father’s and participant’s education, and (2) the mother’s
and participant’s education, by assigning a score of 0 to 2 for childhood socioeconomic
position and for socioeconomic position in early adult life, with a score of 2
representing the highest level of disadvantage. Specifically, the scores were assigned as
follows: childhood socioeconomic position (less than primary education = 2, primary
education = 1, secondary education or more = 0); socioeconomic position in early adult
life (primary education or less = 2, secondary education = 1, college or more = 0). The
scores for each socioeconomic position variable were then added together to create a
cumulative socioeconomic position score, ranging from 0 (most privileged) to 4 (most
disadvantaged). The polichoric coefficient correlation between the ordinal variables of
education used to compose the scores was 0.426 (participant and father) and 0.465
(participant and mother), showing no redundancy between variables. Previous studies on
life course socioeconomic position and health outcomes have established similar scales
25
,
26 . Scores were categorized as “high” (0-1), “medium” (2), and “low” (3-4), for
inclusion in categorical multivariate models.
Co-variates
• Markers of access to health care services
Pap smears and breast clinical exams (never done, done more than three years ago, or done
within the past three years), as well as private health insurance status (yes, no), were
analyzed.
Statistical analysis
Although the data were collected cross-sectionally, follow-ups were reconstructed from
information reported by the participants.
Follow-up periods were defined as the time between 20 years of age and the age at data
collection (1999) for the non-cases, and the age at uterine leimyomas diagnosis for the
cases. Based on the natural history of uterine leimyomas development, women who were over
the age of 50 at diagnosis were censored.
For bivariate analyses of color/race and uterine leimyomas, the Kaplan-Meier method was
used; significance was determined by the log-rank and Peto tests 27 . Cox proportional risk models were used to estimate the multivariable-adjusted
hazard ratios (HR) with 95% confidence intervals (95%CI).
Initially, two models were adjusted considering the following variables: skin color/race
and age (model 1) and skin color/race, age, and variables assessing access to health care,
including Pap smear, breast clinical exam, and private health insurance status (model 2).
Five additional models were adjusted, with socioeconomic position variables included
separately, in order to evaluate the possible influence of socioeconomic position on the
association between race and uterine leimyomas. Results from each model were compared to
those of model 2. Schoenfeld residuals were used to test the proportional odds
assumption.
Sensitivity analyses were conducted to evaluate the possibility of misclassification due
to a self-reported outcome. First, to reduce the possibility of false positives, three
subsets of cases were excluded from these analyses: (a) cases of uterine leimyomas with no
ultrasound or histopathology diagnostic confirmation; (b) cases that were asymptomatic at
diagnosis; and (c) cases that did not require hysterectomy (in this case we used age at
hysterectomy instead of age at diagnosis to delimit the period of follow-up). Second, to
reduce the possibility of false negatives, participants younger than 30 were excluded from
the sensitivity analyses.
Data entry and consistency checks were carried out using Epi Info (Centers for Disease
Control and Prevention, Atlanta, USA), and the statistical analyses were executed with the
program R, version 2.6.2 (The R Foundation for Statistical Computing, Vienna, Austria;
http://www.r-project.org). The study was approved by the Ethics Research Committee at the
State University of Rio de Janeiro.
Results
Over half of the women (54.7%) reported their skin color/race as white. Brown and black
skin colors/races were reported by 22.7% and 22.6%, respectively. Participants’ ages ranged
from 22 to 67 years (average, 40 years). Average ages were 38.9 for white women, 40.7 for
brown women, and 41.8 for black women.
Table 1 shows the distribution of variables under
study according to participants’ skin color/race. Black women as a group had the worst
socioeconomic position profile and the lowest proportion with private health insurance. The
proportions of socioeconomic position variables and private health insurance for brown women
were between those of blacks and those of whites. All three groups had high proportions of
participants who had a Pap smear or a breast exam by a gynecologist in the previous three
years, with whites having slightly higher proportions of that history than black and brown
women (though the difference was not statistically significant) ( Table 1 ).
Table 1
Distribution of study variables according to participants’ skin color/race.
Pró-Saúde Study, Rio de Janeiro, Brazil (1999-2001).
White
Brown
Black
p-value *
n (%)
n (%)
n (%)
Age (mean, SE)
38.9 (8.1)
40.7 (8.0)
41,8 (8.1)
< 0.001 **
Childhood socioeconomic position (paternal educational attainment)
Secondary education or more
323 (40.1)
94 (28.1)
53 (15.9)
< 0.001
Primary education
205 (25.4)
82 (24.5)
87 (26.1)
Less than primary education
278 (34.5)
159 (47.5)
193 (58.0)
Childhood socioeconomic position (maternal educational attainment)
Secondary education or more
262 (32.5)
52 (15.5)
24 (7.2)
< 0.001
Primary education
215 (26.7)
87 (26.0)
82 (24.6)
Less than primary education
329 (40.8)
196 (58.5)
227 (68.2)
Early adult life socioeconomic position (participant educational
attainment)
College or more
502 (62.3)
121 (36.1)
101 (30.3)
< 0.001
Secondary education
236 (29.3)
140 (41.8)
143 (42.9)
Primary education or less
68 (8.4)
74 (22.1)
89 (26.7)
Cumulative socioeconomic position (paternal and participant educational
attainment)
High
439 (54.5)
112 (33.4)
74 (22.2)
< 0.001
Medium
204 (25.3)
91 (27.2)
99 (29.7)
Low
163 (20.2)
132 (39.4)
160 (48.0)
Cumulative socioeconomic position (maternal and participant educational
attainment)
High
388 (48.1)
93 (27.8)
54 (16.2)
< 0.001
Medium
240 (29.8)
86 (25.7)
103 (30.9)
Low
178 (22.1)
156 (46.6)
176 (52.9)
Private health insurance
Yes
599 (74.3)
201 (60.0)
150 (45.0)
< 0.001
No
207 (25.7)
134 (40.0)
183 (55.0)
Pap smear
Within the past 3 years
727 (90.2)
295 (88.1)
288 (86.5)
0.167
Never/More than 3 years ago
79 (9.8)
40 (11.9)
45 (13.5)
Breast clinical exams
Within the past 3 years
727 (90.2)
294 (87.8)
288 (86.5)
0.154
Never/More than 3 years ago
79 (9.8)
41 (12.2)
45 (13.5)
SE: standard error.
* p-value derived from Pearson’s chi-squared test for categorical variables;
** p-value derived from ANOVA test.
Table 2 shows the distribution of study variables
according to frequency of uterine leiomyomas. Tumors were more frequent among black women
and among those with the worst socioeconomic conditions (lowest levels of education,
parental education and lifelong socioeconomic position). Uterine leiomyomas were also more
common among women who reported undergoing a breast clinical exam and a Pap smear in the
previous three years ( Table 2 ).
Table 2
Distribution of study variables according to frequency of uterine leiomyoma.
Pró-Saúde Study, Rio de Janeiro, Brazil (1999-2001).
Uterine leiomyoma
p-value *
n
(%)
Skin color/race
White
146
18.1
< 0.001
Brown
74
22.1
Black
107
32.1
Childhood socioeconomic position (paternal educational attainment)
Secondary education or more
86
18.3
0.032
Primary education
84
22.5
Less than primary education
157
24.9
Childhood socioeconomic position (maternal educational attainment)
Secondary education or more
62
18.3
0.033
Primary education
78
20.3
Less than primary education
187
24.9
Early adult life socioeconomic position (participant educational
attainment)
College or more
152
21.0
< 0.001
Secondary education
100
19.3
Primary education or less
75
32.5
Cumulative socioeconomic position (paternal and participant educational
attainment)
High
123
19.7
0.022
Medium
83
21.1
Low
121
26.6
Cumulative socioeconomic position (maternal and participant educational
attainment)
High
103
19.3
0.025
Medium
91
21.2
Low
133
26.1
Private health insurance
Yes
209
22.0
0.870
No
118
22.5
Pap smear
Within the past 3 years
301
23.0
0.049
Never/More than 3 years ago
26
15.9
Breast clinical exams
Within the past 3 years
305
23.3
0.005
Never/More than 3 years ago
22
13.3
* p-value derived from Pearson’s chi-squared test for categorical variables.
Figure 1 shows the cumulative risk curves for
incidence of self-reported diagnosis of uterine leiomyomas according to skin color/race.
Overall, the lowest incidence of uterine leiomyomas occurred among white women, followed by
brown women and black women. However, at finer calibrations the pattern is not as clear.
Between approximately 20 to 25 follow-up years, white women have a lower cumulative
incidence than brown women. But the cumulative incidence at the end of the follow-up is the
same in whites and browns ( Figure 1 ).
Figure 1
Cumulative risk curves (Kaplan-Meier) and p-values from log-rank and Peto tests
for medical diagnosis of self-reported uterine leiomyoma according to skin color/race.
Pró-Saúde Study, Rio de Janeiro, Brazil (1999-2001).
Table 3 shows hazard ratios for uterine leiomyomas
according to skin color/race for seven models adjusted for age, socioeconomic position, and
variables related to access to health care services. It also shows the same associations
after exclusion (sensitivity analyses) of asymptomatic cases of diagnosed uterine leiomyomas
(which were: 10.4% for whites, 15.4% for browns and 22.9% for blacks – not shown in table),
as well as cases that did not require hysterectomy (4.9% for whites, 7.8% for browns and
17.3% for blacks – not shown in table). Compared with white women, black women had a greater
risk of developing uterine leiomyomas, independently of the variables entered in the
different models. Differences between white and brown women were not statistically
significant. Regardless of the socioeconomic position variables adjusted for, the HR
comparing blacks and whites was 1.7 and statistically significant. These hazard ratios were
further away from 1.0 following exclusion of cases of asymptomatic self-reported diagnosed
uterine leiomyomas and cases that did not require hysterectomy.
Table 3
Hazard ratios (HR) expressing the relationship of skin color/race to medical
diagnosis of self-reported uterine leiomyoma, adjusted for lifecourse socio-economic
position variables, and access to and use of health care services *. Pró-Saúde Study,
Rio de Janeiro, Brazil (1999-2001).
Model
Medical diagnosis of uterine leiomyoma
Sensitivity analysis
Exclusion of asymptomatic cases
Exclusion of cases with no hysterectomy
HR (95%CI) [n = 1,475]
HR (95%CI) [n = 1,328]
HR (95%CI) [n = 1,245]
Model 1 (age)
White
1.0
1.0
1.0
Brown
1.1 (0.9-1.5)
1.4 (1.0-2.1)
1.4 (0.8-2.5)
Black
1.6 (1.2-2.1)
2.0 (1.4-2.8)
2.6 (1.7-4.0)
Model 2 (age and access to health care) **
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.5 (1.0-2.1)
1.6 (0.9-2.7)
Black
1.7 (1.3-2.2)
2.0 (1.4-2.8)
2.8 (1.7-4.4)
Model 3 (Model 2 + paternal educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.6 (0.9-2.7)
Black
1.7 (1.3-2.2)
2.0 (1.4-2.8)
2.7 (1.7-4.3)
Model 4 (Model 2 + maternal educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.5 (0.8-2.5)
Black
1.7 (1.3-2.3)
2.0 (1.4-2.8)
2.5 (1.5-3.9)
Model 5 (Model 2 + participant educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.6 (0.9-2.8)
Black
1.7 (1.3-2.3)
2.0 (1.4-2.8)
2.8 (1.8-4.5)
Model 6 (Model 2 + cumulative socioeconomic position – paternal and participant
educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.6 (0.9-2.7)
Black
1.7 (1.3-2.2)
1.9 (1.3-2.7)
2.7 (1.7-4.3)
Model 7 (Model 2 + cumulative socioeconomic position – maternal and participant
educational attainment]
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.0)
1.5 (0.9-2.6)
Black
1.7 (1.3-2.2)
1.9 (1.3-2.7)
2.6 (1.6-4.1)
* Follow-up periods were defined as the time between 20 years of age and the age at
data collection (1999) for the non-cases, and the age at diagnosis for the
cases;
** Variables for health care access: Pap smear, clinical breast exam, and private
health insurance status.
The results of other sensitivity analyses (selective exclusion of participants younger than
30 years of age and those whose diagnosis of uterine leiomyoma was not confirmed by
ultrasound or a histopathology report) were virtually identical to the overall analyses (not
shown in table). Schoenfeld residuals demonstrate that all analyzed variables displayed
constant risk differences over time.
Discussion
To the authors’ knowledge, this is the first epidemiological study evaluating the role of
life course socioeconomic position in the association between uterine leiomyomas and black
or brown skin color/race. Black women had a statistically significant higher likelihood of
reporting a diagnosis of uterine leiomyomas than their white counterparts; brown women’s
risks fell between those of blacks and whites. Differences between white and brown women,
however, were not statistically significant.
These results are consistent with previous studies in the United States, in which black
women were found to have a higher risk of uterine leiomyoma than white women. Marshall et
al. 6 found a relative risk of uterine leiomyomas of 3.3 (95%CI: 2.7-3.9) and of
hysterectomy due to uterine leiomyomas of 1.9 (95%CI: 1.2-2.8) among black compared to white
women, following adjustments for variables such as age, body mass index (BMI), time elapsed
since last pregnancy, history of infertility, alcohol consumption, tobacco use, physical and
leisure activity, age at menarche, age at first pregnancy, contraceptive use, and marital
status 6 . Faerstein et al. 5 reported that, compared with white women, black women had more than nine times the
odds of uterine leiomyomas (OR = 9.4; 95%CI: 5.7-15.7) after adjustment for age at menarche,
use of oral contraceptives, tobacco use, BMI, hypertension, diabetes mellitus, and history
of pelvic inflammatory disease. Baird et al. 8 found a uterine leiomyomas odds ratio for blacks versus whites of 2.7 (95%CI:
2.3-3.2) after adjustment for BMI and parity.
While previous studies have analyzed skin color/race as a dichotomous variable
(white/non-white or white/black), we used three categories. In contrast with the United
States, for example, racial/ethnic classification in Brazil is based on phenotypic
characteristics, such as skin color, which allows for a variety of categories. Currently,
there are three ways of categorizing race in Brazil that are worth emphasizing: (1) that of
the Brazilian census, which distinguishes among five discrete categories of skin color –
white, brown, black, Asian (“yellow”), and Native Brazilian (“indigenous”), the fifth of
which considers ancestry and ethnicity differently from the other four; (2) that of popular
discourse, which uses a diverse nomenclature 24 ; and (3) that of black political activists, who defend the use of the category
“negro” or “of African descent” rather than “brown” and “black”. The objective of the latter
classification system is to reestablish the identification of ancestry, and consequently of
collective identity, among African descendants in Brazil 22 . Results from this study, however, point to differences between brown and black
women, which reinforce the need to consider these distinct racial categories in health
research in societies like Brazil’s. On the one hand, the lack of statistical differences
between white and brown women might indicate the presence of similar risk factors for these
groups; on the other hand, the same lack of statistical difference may show that women with
similar phenotypes placed themselves in distinct color/racial groups, a finding which would
confirm the notion of the fluidity of the color/race construct in Brazilian society 28
,
29 .
Another finding of this study was the strengthening of the racial gradients when cases of
asymptomatic uterine leiomyomas, and those that did not require hysterectomy, were excluded.
These results, the product of sensitivity analyses, may indicate a greater risk of more
clinically severe tumors in black women. Alternative possible explanations include increased
medical surveillance among blacks, or perhaps racial discrimination among health
professionals in deciding or administering treatment 30 . For example, in some studies nonwhite women overall had lower rates of Pap smears
and of anesthesia use in vaginal delivery, and a higher risk of surgical sterilization,
independently of other socio-demographic characteristics 31
,
32
,
33 .
In this study, despite the inverse association between socioeconomic position and uterine
leiomyomas, as well as between socioeconomic position and black color/racial identification,
several adjustments for socioeconomic position markers did not change the associations,
suggesting that socioeconomic position is not a mediator of the relationship between
color/race and uterine leiomyomas. Few studies address associations between socioeconomic
position and uterine leiomyomas, which makes it difficult to compare this study’s results
with the epidemiological literature. Most etiological studies analyze proximal factors in
the uterine leiomyomas causal chain, in general associated with hormonal deregulation, but
do not address social determinants. Thus, variables such as education have been analyzed
34
,
35
,
36
,
37
,
38 as potential confounders, but have not been the central focus of analysis. Still,
some studies observed no association 8
,
39
,
40
,
41 between education and uterine leiomyomas, while one found a direct association 42 . Two studies have addressed the association between tumors and low levels of
parental education, food insecurity, and low income in childhood, and found direct
associations only among whites 43
,
44 .
However, some methodological aspects of our study may have influenced these findings.
Although information about the education marker for socioeconomic position covered more than
one time period in participants’ life course, this marker most likely does not fully capture
the complexity of social stratification and resulting lifelong, socially patterned exposures
and behaviors 45
,
46
,
47 . In addition, this marker may not be equivalent across color/race groups, again for
complex social, economic and political reasons 46
,
47 . In the United States, for example, there are great differences in the quality of
education enjoyed by whites and blacks; moreover, the incomes of individuals of similar
educational level were higher among whites than among blacks and Hispanics 45
,
48
,
49 . Nonetheless, education is a widely utilized measure of an individual’s location in
the social hierarchy. Higher levels of education provide better opportunities for jobs and
higher wages, which lead to better nutrition, housing, and access to health services. Higher
educational attainment also strengthens cognitive resources that influence health-related
decisions and behaviors 46
,
50
,
51 . Parental education level, in turn, is a widely used indicator of childhood
socioeconomic position, and is a powerful clue to the environment in which the child grows,
learns, and adopts behaviors that may influence his or her future life 50 .
If life course socioeconomic position does not mediate the uterine leiomyomas-color/race
association, alternative hypotheses must be discussed even though they were not objects of
empirical exploration in this study. Sources of psychosocial stress throughout a woman’s
life (which may or may not be influenced by life course socioeconomic position) may be a
link in the causal chain. For example, a study of black women in the U. S. showed that
increased exposure to racial discrimination may be associated with uterine leiomyomas via
allostatic load 52 . In addition, recent studies have demonstrated that physical and sexual abuse
during childhood or adolescence may be associated, in a graded pattern, with higher uterine
leiomyomas risk, and that parental emotional support may buffer the impact of that abuse.
These studies have found that severe stress in early life is associated with deregulation of
the hypothalamic-pituitary-adrenal (HPA) stress pathway, and may affect ovarian hormone
synthesis and uterine leiomyomas growth. This autonomic stress response may persist into
adulthood 53
,
54 .
Other biological mechanisms may also be involved. Women with darker skin color tend to have
lower levels of circulating vitamin D, which may be a risk factor for the development of
uterine leiomyomas 14
,
15
,
55 . In addition, cytogenetic studies have found similarities between the structural
organization of uterine leiomyomas and that of keloids – overgrowths of scar tissue that
increase the production of extracellular matrix proteins during the scarring process 56 – also associated with elevated melanin levels 57 and vitamin D deficiency 58 . The investigation of such biological mechanisms, possibly resulting from
phenotypic features, would not mean an endorsement of genetic inheritance as the basis for
racial classifications. The wide variability of humans’ external physical characteristics,
commonly used to describe racial groups, seems to reflect changes and adjustments, over the
millennia, to variations of climate and other environmental factors, as well as historical
and social conditions 22
,
59
,
60
,
61 .
Two methodological choices by the authors should be mentioned. First, we prioritized the
study of distal variables in the causal chain. We therefore chose not to include in the
analysis proximal or intermediate variables (known risk factors) such as those related to
lifestyle and reproductive health. We believed that to include such variables, while
tempting as a route of investigation, would complicate the relationships among color/race,
socioeconomic position and uterine leiomyomas, and might reduce or even eliminate the main
association of interest, hindering the understanding of these very relationships.
Our other choice was to use Cox models in multivariate analyses. This decision was made
because the study had collected data on participant age at uterine leiomyomas diagnosis.
Therefore, a “follow-up” period could be estimated, and our analyses could then be used as
alternatives to cross-sectional analysis, which necessarily disregards the distribution of
time that each participant contributed to the study.
Among our study’s limitations is the use of self-reported information regarding tumor
diagnosis. Because many uterine leiomyomas cases are asymptomatic, diagnosis depends on
access to and utilization of health care services. When participants did not have access to
a diagnosis, they may report their illness inaccurately, and the resulting associations may
be underestimated. We implemented two specific strategies to reduce the likelihood of these
biases. The first, albeit indirect, was to assess the reliability of the question about
diagnosis of uterine leiomyomas. That reliability proved to be excellent. Second, analyses
were conducted following the selective exclusion of cases lacking a confirmatory diagnosis
of uterine leiomyomas by way of ultrasound or histopathology report, as well as cases in
women under 30 years of age. Our estimates remained unchanged in each of these
situations.
Other biases potentially associated with cross-sectional studies may have influenced our
results. First, certain hypothesized risk factors for uterine leiomyomas, such as those
related to atherogenesis 57 , may also be associated with color/race. As such, an increase in premature
mortality among black and brown women could dilute the associations among the women who
survived. The population under study, however, can be considered to be young (average age 40
years), which makes this explanation less likely. Second, although Pap smears and breast
exams were used as markers of access to health care services, a residual bias may exist in
which the exams performed on white women were of higher quality, even though they had the
same frequency; this may also have diluted the strength of the associations we observe.
Conversely, if the exams were of higher quality among black women than white women, our
results could be overestimated.
In summary, the observation of a higher occurrence of uterine leiomyomas in women with
darker skin color in a Brazilian sample is consistent with findings from U.S. studies. The
results also suggest that life course socioeconomic position does not mediate this
association, a possibility that had not been explored in previous studies.
Much remains to be understood about the ways in which social exposures are related to
biological mechanisms that affect the development of outcomes like uterine leiomyomas.
Future epidemiologic studies should be longitudinal in nature, and should include additional
markers of socioeconomic position. The color/race inequalities found in our study suggest
that further research should evaluate both biological and environmental exposures, such as
the role of vitamin D deficiency and sources of psychosocial stress, including experiences
of racial discrimination among black women, as potential explanatory factors for the
color/race-uterine leiomyomas relationship.
To Capes (proccess n. 23038009349/201) for the financial support.
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Autoría
Karine de Limas Irio Boclin
Instituto de Medicina Social, Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brasil.Universidade do Estado do Rio de JaneiroBrasilRio de Janeiro, BrasilInstituto de Medicina Social, Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brasil.
Eduardo Faerstein
Instituto de Medicina Social, Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brasil.Universidade do Estado do Rio de JaneiroBrasilRio de Janeiro, BrasilInstituto de Medicina Social, Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brasil.
Moyses Szklo
Bloomberg School of Public Health, John Hopkins
University, Baltimore, USA.John Hopkins UniversityUSABaltimore, USABloomberg School of Public Health, John Hopkins
University, Baltimore, USA.
Correspondence : K. L. I. Boclin. Instituto de Medicina Social, Universidade
do Estado do Rio de Janeiro. Rua Sousa Lima 257, apto. 902, Rio de Janeiro, RJ 22081-010,
Brasil. karine.boclin@gmail.com
Contributors
All authors collaborated to the conception, analyses and writing of this review article
and approved the final version.
SCIMAGO INSTITUTIONS RANKINGS
Instituto de Medicina Social, Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brasil.Universidade do Estado do Rio de JaneiroBrasilRio de Janeiro, BrasilInstituto de Medicina Social, Universidade do Estado do
Rio de Janeiro, Rio de Janeiro, Brasil.
Bloomberg School of Public Health, John Hopkins
University, Baltimore, USA.John Hopkins UniversityUSABaltimore, USABloomberg School of Public Health, John Hopkins
University, Baltimore, USA.
Figure 1
Cumulative risk curves (Kaplan-Meier) and p-values from log-rank and Peto tests
for medical diagnosis of self-reported uterine leiomyoma according to skin color/race.
Pró-Saúde Study, Rio de Janeiro, Brazil (1999-2001).
Table 3
Hazard ratios (HR) expressing the relationship of skin color/race to medical
diagnosis of self-reported uterine leiomyoma, adjusted for lifecourse socio-economic
position variables, and access to and use of health care services *. Pró-Saúde Study,
Rio de Janeiro, Brazil (1999-2001).
imageFigure 1
Cumulative risk curves (Kaplan-Meier) and p-values from log-rank and Peto tests
for medical diagnosis of self-reported uterine leiomyoma according to skin color/race.
Pró-Saúde Study, Rio de Janeiro, Brazil (1999-2001).
open_in_new
table_chartTable 1
Distribution of study variables according to participants’ skin color/race.
Pró-Saúde Study, Rio de Janeiro, Brazil (1999-2001).
White
Brown
Black
p-value *
n (%)
n (%)
n (%)
Age (mean, SE)
38.9 (8.1)
40.7 (8.0)
41,8 (8.1)
< 0.001 **
Childhood socioeconomic position (paternal educational attainment)
Secondary education or more
323 (40.1)
94 (28.1)
53 (15.9)
< 0.001
Primary education
205 (25.4)
82 (24.5)
87 (26.1)
Less than primary education
278 (34.5)
159 (47.5)
193 (58.0)
Childhood socioeconomic position (maternal educational attainment)
Secondary education or more
262 (32.5)
52 (15.5)
24 (7.2)
< 0.001
Primary education
215 (26.7)
87 (26.0)
82 (24.6)
Less than primary education
329 (40.8)
196 (58.5)
227 (68.2)
Early adult life socioeconomic position (participant educational
attainment)
College or more
502 (62.3)
121 (36.1)
101 (30.3)
< 0.001
Secondary education
236 (29.3)
140 (41.8)
143 (42.9)
Primary education or less
68 (8.4)
74 (22.1)
89 (26.7)
Cumulative socioeconomic position (paternal and participant educational
attainment)
High
439 (54.5)
112 (33.4)
74 (22.2)
< 0.001
Medium
204 (25.3)
91 (27.2)
99 (29.7)
Low
163 (20.2)
132 (39.4)
160 (48.0)
Cumulative socioeconomic position (maternal and participant educational
attainment)
High
388 (48.1)
93 (27.8)
54 (16.2)
< 0.001
Medium
240 (29.8)
86 (25.7)
103 (30.9)
Low
178 (22.1)
156 (46.6)
176 (52.9)
Private health insurance
Yes
599 (74.3)
201 (60.0)
150 (45.0)
< 0.001
No
207 (25.7)
134 (40.0)
183 (55.0)
Pap smear
Within the past 3 years
727 (90.2)
295 (88.1)
288 (86.5)
0.167
Never/More than 3 years ago
79 (9.8)
40 (11.9)
45 (13.5)
Breast clinical exams
Within the past 3 years
727 (90.2)
294 (87.8)
288 (86.5)
0.154
Never/More than 3 years ago
79 (9.8)
41 (12.2)
45 (13.5)
table_chartTable 2
Distribution of study variables according to frequency of uterine leiomyoma.
Pró-Saúde Study, Rio de Janeiro, Brazil (1999-2001).
Uterine leiomyoma
p-value *
n
(%)
Skin color/race
White
146
18.1
< 0.001
Brown
74
22.1
Black
107
32.1
Childhood socioeconomic position (paternal educational attainment)
Secondary education or more
86
18.3
0.032
Primary education
84
22.5
Less than primary education
157
24.9
Childhood socioeconomic position (maternal educational attainment)
Secondary education or more
62
18.3
0.033
Primary education
78
20.3
Less than primary education
187
24.9
Early adult life socioeconomic position (participant educational
attainment)
College or more
152
21.0
< 0.001
Secondary education
100
19.3
Primary education or less
75
32.5
Cumulative socioeconomic position (paternal and participant educational
attainment)
High
123
19.7
0.022
Medium
83
21.1
Low
121
26.6
Cumulative socioeconomic position (maternal and participant educational
attainment)
High
103
19.3
0.025
Medium
91
21.2
Low
133
26.1
Private health insurance
Yes
209
22.0
0.870
No
118
22.5
Pap smear
Within the past 3 years
301
23.0
0.049
Never/More than 3 years ago
26
15.9
Breast clinical exams
Within the past 3 years
305
23.3
0.005
Never/More than 3 years ago
22
13.3
table_chartTable 3
Hazard ratios (HR) expressing the relationship of skin color/race to medical
diagnosis of self-reported uterine leiomyoma, adjusted for lifecourse socio-economic
position variables, and access to and use of health care services *. Pró-Saúde Study,
Rio de Janeiro, Brazil (1999-2001).
Model
Medical diagnosis of uterine leiomyoma
Sensitivity analysis
Exclusion of asymptomatic cases
Exclusion of cases with no hysterectomy
HR (95%CI) [n = 1,475]
HR (95%CI) [n = 1,328]
HR (95%CI) [n = 1,245]
Model 1 (age)
White
1.0
1.0
1.0
Brown
1.1 (0.9-1.5)
1.4 (1.0-2.1)
1.4 (0.8-2.5)
Black
1.6 (1.2-2.1)
2.0 (1.4-2.8)
2.6 (1.7-4.0)
Model 2 (age and access to health care) **
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.5 (1.0-2.1)
1.6 (0.9-2.7)
Black
1.7 (1.3-2.2)
2.0 (1.4-2.8)
2.8 (1.7-4.4)
Model 3 (Model 2 + paternal educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.6 (0.9-2.7)
Black
1.7 (1.3-2.2)
2.0 (1.4-2.8)
2.7 (1.7-4.3)
Model 4 (Model 2 + maternal educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.5 (0.8-2.5)
Black
1.7 (1.3-2.3)
2.0 (1.4-2.8)
2.5 (1.5-3.9)
Model 5 (Model 2 + participant educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.6 (0.9-2.8)
Black
1.7 (1.3-2.3)
2.0 (1.4-2.8)
2.8 (1.8-4.5)
Model 6 (Model 2 + cumulative socioeconomic position – paternal and participant
educational attainment)
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.1)
1.6 (0.9-2.7)
Black
1.7 (1.3-2.2)
1.9 (1.3-2.7)
2.7 (1.7-4.3)
Model 7 (Model 2 + cumulative socioeconomic position – maternal and participant
educational attainment]
White
1.0
1.0
1.0
Brown
1.2 (0.9-1.6)
1.4 (1.0-2.0)
1.5 (0.9-2.6)
Black
1.7 (1.3-2.2)
1.9 (1.3-2.7)
2.6 (1.6-4.1)
Como citar
Boclin, Karine de Limas Irio, Faerstein, Eduardo y Szklo, Moyses. ¿El nivel socioeconómico influye en las desigualdades raciales en cuanto a la incidencia de miomas uterinos? Evidencia del Estudio Pró-Saúde. Cadernos de Saúde Pública [online]. 2014, v. 30, n. 2 [Accedido 3 Abril 2025], pp. 305-317. Disponible en: <https://doi.org/10.1590/0102-311X00025413>. ISSN 1678-4464. https://doi.org/10.1590/0102-311X00025413.
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RJ -
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