Vol.1, No.4, 332-341 (2009)
Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
Self-evaluated health of married people in Jamaica
Paul A. Bourne
Department of Community Health and Psychiatry, Faculty of Medical Sciences, The University of the West Indies, Mona, Kingston 7,
Jamaica; paulbourne1@yahoo.com
Received 2 October 2009; revised 9 November 2009; accepted 10 November 2009.
Background: In the Caribbean in particular Ja-
maica, no study has been done to examine
married respondents in order to understand
reasons for their greater health status. The ob-
jectives of the current study are: 1) examine the
sociodemographic characteristics of married
people in Jamaica; 2) evaluate self-rated health
status of married people in Jamaica; 3) deter-
mine factors that account for good health status
of married people and 4) provide public health
practitioners with empirical studies that can be
used to formulate policies for men in particular
non-married men in Jamaica. Materials and me-
thods: Stratified random sampling technique
was used to select 6,783 respondents. It was a
nationally representative sample. Logistic re-
gression analysis was used to ascertain the
correlates of health status. Results: The mean
age for women in marriage in Jamaica was 6
years lower than that of men. The correlates of
good health status (including moderate health)
of respondents in descending order were self-
reported illness (OR = 0.12, 95%CI = 0.01- 0.17);
age (OR = 0.94, 95%CI = 0.93-0.96); income (OR
= 1.32, 95%CI = 1.05-1.66) and sex of respon-
dents (Or = 1.14-2.32)χ2(df = 4) = 383.2, P <
0.05. The four variables accounted for 44.4% of
the explanatory power of the model; with
self-reported illness accounting for 32.5% of the
explanatory power. Conclusion: Marriage pro-
vides greater access to more socioeconomic
resources for its participants as well as increase
men’s unwillingness to visit medical care prac-
Keywords: Marriage; Sexes; Health Status;
Sociodemographic Correlates; Jamaica
Globally, empirical studies have shown a statistical as-
sociation between marital status and self-reported health
status. Studies found that married people have a better
self-reported health status (or self-reported health, sub-
jective wellbeing) [1-9] and/or lower mortality than non-
married people. This is no different in Jamaica, as stud-
ies have found that married Jamaicans have a better
health status than non-married Jamaicans [10,11]. Al-
though generally findings on health status in Jamaica
indicated the aforementioned, a study by Bourne &
McGrowder [12], using 15,260 rural residents, found no
statistical difference between the good health status of
married and non-married respondents. In spite of Bourne
& McGrowder’s work, the preponderance of empirical
evidence generally indicated that married people have
better health status and experience lower rates of mortal-
ity than non-married people; and so Bourne & Mc-
Growder’s study does not reduce the reality of a differ-
ence in other geographic regions in Jamaica. Within the
context of the health literature, the odds ratio of good
health status for married people is greater than that for
non-married people, and this is ascribed to different
socio-economic and lifestyle issues.
The socio-economic and lifestyle issues include the
following: greater health care-seeking behaviour [13];
social support [2-4]; better lifestyle choices [3]; better
and proper eating habits [6,7]; higher economic wellbe-
ing, more so for women [14], and that they are happier
[15,16] and more contented [17] than non-married peo-
ple. Seemingly, greater health status is associated with
marriage, or is it that those with greater health status are
more likely to get married than those who are unhealth-
ier? A study by Elwert & Christakis [18] unearthed that
the hazard ratio of mortality upon bereavement for a
spouse was 1.17 for men, indicating that men upon the
death of their spouses are 17% more likely to die them-
selves. Embedded in this finding is the benefit of mar-
riage for men, which is corroborated in research con-
ducted by Havens [19], which found that women live
longer after the death of their spouse than men [20,21].
Another research found that the odds ratio of health
status for married men in Jamaica was greater than for
non-married men up to 75 years, while for the non-mar-
P. A. Bourne / HEALTH 1 (2009) 332-341
SciRes Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
ried women up to 75 years the odds ratio was greater
than that for married women. The converse was the case
post 75 years, with the odds of good health status for
women being significantly more than for men [22]. In
Jamaica for 2007, life expectancy at birth for men was
69 years and 74 years for women [23], indicating that
over the life span of the average Jamaican man, marriage
will provide him with greater health status than if he
were not married. Embedded in that finding is the fact
that mortality is greater for men than women, which
means that many men will be hospitalized before death.
One study found that for an elderly couple, on the hos-
pitalization of one, mortality rates increased for the other,
and that this was even greater for men than for women
The literature has provided a partial understanding of
the explanation for the better health status and/or low-
ered mortality ratios of married over non-married people.
While answering some issues, a number of other issues
are still unresolved from the literature. These unresolved
issues include 1) whether married people are healthier
because those who are likely to become married are
healthier, 2) whether men benefit more from marriage
than women, 3) whether marriage is the explanation for
better self-rated health (subjective wellbeing) and 4)
whether there are some protective effects of marriage.
With the literature providing some understanding of the
disparity in the general health status of married over
non-married people, this still does not reduce the unre-
solved issues, and can we use a wholesale sociological
explanation provided by the developed nations with dif-
ferent socialization, customs, practices, sociopolitical
milieu and economic base, or even similar developing
nations experiences, for an understanding of married
people in Jamaica? Concurrently, can we use the general
literature to formulate policies for an understanding of
married people in Jamaica? One of the questions that
was previously asked has been addressed in a longitudi-
nal study that found that happier singles were more
willing to get married [25], suggesting that marriage
attracts singles who have greater subjective wellbeing,
and this accounts for some degree of greater odds ratios
of married people being healthier than unmarried people.
A study among married and non-married men found that
mortality was greater for the latter than for the former
[26]; and this was also the case among women [27].
An understanding of other societies’ experiences un-
doubtedly aids in fashioning a framework for an under-
standing of what takes places in Jamaica. However, it
cannot be relied upon as the sole explanation for hap-
penings in Jamaica. One of the goals of public health
policy formulation is its reliance on empirical research,
in guiding decisions on how to operate because there is
an understanding of the issue at hand. All societies,
while being governed by some fundamental similarities,
have dissimilarities which must be understood in order
to prescribe appropriate measures to address those con-
cerns embedded within the particular society. An exten-
sive research of the literature found no study that has
sought to examine the rationale behind the fact that mar-
ried people record greater health status, in particular the
men, as an approach to understanding how non-married
men’s health status can be improved, and how general
health status can be increased in Jamaica. Therefore
public health policies have been structured around the
literature and studies in other geopolitical zones; al-
though those societies have different cultural practices,
customs and jurisprudence from that found in Jamaica. It
is within this limitation that the current study emerged,
to provide an explanation for what constitute the health
status of married Jamaicans, in order to guide policy
formulation and framework in this society. The objec-
tives of the current study are 1) to examine the sociode-
mographic characteristics of married people in Jamaica,
2) to evaluate self-rated health status of married people
in Jamaica, 3) to determine the factors that account for
the good health status of married people and 4) to pro-
vide public health practitioners with empirical studies
that can be used to formulate policies for men in par-
ticular non-married men in Jamaica.
Secondary cross-sectional survey data were collected
jointly by the Planning Institute of Jamaica (PIOJ) and
the Statistical Institute of Jamaica (STATIN) between
May and August 2007. The survey is called the Jamaica
Survey of Living Conditions (JSLC), and it was primar-
ily collected by the aforementioned institutions as policy
assessments for programmes and policies instituted by
the government of the country. The JSLC began in 1988,
and it has been an annual survey since then. It is stan-
dard practice that the JSLC’s sample be a proportion (i.e.
one third) of the Labour Force Survey (LFC).
The last JSLC was conducted in 2007 with the sample
being 6,783 respondents. Of the sample of respondents,
15.7% (n = 1,056 respondents) were used for this study.
The only criterion for selection was being married.
Stratified random sampling was used to randomly select
a nationally representative sample for the survey. The
design was a two-stage stratified random sample with a
Primary Sampling Unit (PSU) and a selection of dwell-
ings from the primary units. The PSU is an Enumeration
District (ED), which constitutes a minimum of 100 resi-
dences in rural areas and 150 in urban areas. An ED is an
independent geographic unit that shares a common
boundary. This means that the country was grouped into
strata of equal size based on dwellings (EDs). Based on
the PSUs, a listing of all the dwellings was made, and
this became the sampling frame from which a Master
P. A. Bourne / HEALTH 1 (2009) 332-341
SciRes Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
Sample of dwellings was compiled, which in turn pro-
vided the sampling frame for the labour force. A total of
620 households were interviewed from urban areas; 439
from semi-urban areas and 935 from rural areas, which
constituted 6,783 respondents. One third of the Labour
Force Survey (i.e. LFS) was selected for the JSLC. The
sample was weighted to reflect the population of the
nation. The non-response rate for the survey was 27.7%.
2.1. Data Collection
The JSLC is a modification of the World Bank’s Living
Standards Measurement Study (LSMS) household survey
[22]. The instrument was a questionnaire. Face-to-face
interviews over the aforementioned period were used to
collect the data. A structure questionnaire was used, and
interviewers were trained and subsequently deployed to
collect the data. The questions covered demographic cha-
racteristics, household consumption, health, education,
housing, social welfare and related programmes, and in-
ventory of durable goods. In 2007, a question on health
status was included in the normal health conditions:
length of illness, health insurance coverage, health care-
seeking behaviour, medical expenditure, typology of
health care utilization and immunization coverage of
2.2. Statistical Analysis
Data were stored, retrieved and analyzed using SPSS-PC
for Windows version 16.0. Descriptive statistics were
used to provide background information on the sample.
Chi-square analyses were used to examine the associa-
tion between non-metric variables for area of residence
and gender of respondents. Analysis of variance and
t-test were also used to examine bivariate association.
Logistic regression analyses examined the relationship
between good health status and some socio-demographic,
economic and biological variables. Forward stepwise
logistic regression was used to build the model of good
self-reported health status for the current study.
The correlation matrix was examined in order to as-
certain if autocorrelation and/or multicollinearity existed
between variables. Based on Cohen and Holliday [28]
correlation can be low (weak)—from 0 to 0.39, moder-
ate—0.4-0.69, and strong—0.7-1.0. This was used to
exclude (or allow) a variable in the model. Any correla-
tion that had at least moderate was excluded from the
model in order to reduce multicollinearity and/or auto-
correlation between or among the independent variables
[29-35]. Another approach in addressing and/or reducing
autocorrelation is that all variables identified from the
literature review were included in the model, with the
exception of those in which the percentage of missing
cases was in excess of 30%. Odds Ratios (OR) were
used for the interpretation of each significant variable.
2.3. Model
Many factors are correlated with health status, and so the
best statistical technique is multivariate analysis [36-38]
and not bivariate technique. In keeping with the
multi-nature of health status, the current study will use
multivariate analysis which is captured in Equation 1
Ht=f(Ai, Gi, HHi, ARi, lnY, EDi, MRi, Si, MCt, SRIi, εi)
where Ht (i.e. self-rated good current health status in
time t) is a function of age of respondents Ai; sex of in-
dividual i, Gi; household head of individual i, HHi; area
of residence, ARi; logged income, lnC; Education level
of individual i, EDi; marital status of person i, MRi; so-
cial class of person i, Si; summation of medical expen-
diture of individual i in time period t, MCt; self-reported
illness, SRIi, and an error term (i.e. residual error).
2.4. Measures
An explanation of some of the variables in the model is
provided here. Self-reported illness status is a dummy
variable, where 1 = reporting an ailment or dysfunction
or illness in the last 4 weeks, which was the survey pe-
riod; 0 = if there were no self-reported ailments, injuries
or illnesses. While self-reported ill-health is not an ideal
indicator of actual health conditions because people may
underreport, it is still an accurate proxy of ill-health and
mortality [39,40]. Health status is a binary measure
where 1 = moderate to excellent health; 0 = otherwise,
which is determined from “Generally, how do you feel
about your health”? Answers to this question are on a
Likert scale ranging from excellent to poor. Studies have
shown that self-rated health status can be dichotomized
into good and poor health [39,41]; but Bourne [22] and
Finnas et al. [41] noted that there are issues surrounding
this approach. Bourne [22] opined that the dichotomiza-
tion of health status for females is acceptable; however
there are some challenges when this is done for males.
Both Bourne and Finnas et al. found that the inclusion of
moderate health status in poor self-reported health status
is not best; and this explains the rationale for the inclu-
sion of moderate health into good health status for this
study. Medical care-seeking behaviour was taken from
the question “Has a health care practitioner, healer, or
pharmacist been visited in the last 4 weeks?” with there
being two options—Yes or No. Medical care-seeking
behaviour therefore was coded as a binary measure
where 1 = Yes and 0 = Otherwise.
3.1. Demographic Characteristics of
Sample and Bivariate Analyses
The sample was 1,056 respondents: 49.4% males and
P. A. Bourne / HEALTH 1 (2009) 332-341
SciRes Copyright © 2009 http://www.scirp.org/journal/HEALTH/Openly accessible at
Table 1. Demographic characteristics of sample, n=1,056.
Characteristic N Percent
Male 522 49.4
Female 534 50.6
Area of residence
Urban 236 30.9
Semi-urban 217 20.5
Rural 513 48.6
Self-reported illness
Yes 259 24.6
No 795 75.4
Social class
Poorest 20% 153 14.5
Poor 181 17.1
Middle 185 17.5
Wealthy 238 22.5
Wealthiest 20% 299 28.3
Medical care-seeking behaviour
Yes 173 65.3
No 92 34.7
Health insurance coverage
Public 239 22.8
Private 57 5.4
Other 61 5.8
None 691 65.9
Self-rated health status
Very good 301 28.7
Good 440 42.0
Moderate (or fair) 221 21.1
Poor 72 6.9
Very poor 14 1.3
Age Median (Range) 48.0 years (79 years)
Length of illness Median (Range) 7 days (0 )
50.6% females. Of the sample, 24.6% reported an illness;
48.6% dwelled in rural areas; 34.1% had health insur-
ance coverage; 65.3% visited health care practitioners
(including healers) in the last 4 weeks; 70.7% indicated
at least good self-rated health status, and the median age
of marriage was 48.0 years (Range = 79 years); while
the median length of illness was 7 days (Range = 0 day)
(Table 1). Of those who reported an illness, 72.4% indi-
cated that the ailment was diagnosed by a medical practi-
tioner. The illnesses were colds (6.8%); diarrhoea (0.8%);
asthma (3.8%); diabetes mellitus (18.2%); hypertension
(34.5%); arthritis (9.1%); and 19.3% indicated an un-
specified illness.
A significant statistical difference was found between
the sexes and age of respondents. The mean age of males
was 53.7 years (SD = 15.3 years) compared to 48.0 years
(SD = 14.5 years) for females—t statistic = 6.32, P <
0.001. A statistical correlation was found between self-
reported illness and sex of respondents—χ2(df = 1) = 8.21,
P = 0.003. Twenty-one percent of males reported an ill-
ness compared to 28% of females. Concurrently, no sig-
nificant statistical correlation existed between self- re-
ported diagnosed illness and sex of respondents—χ2(df =
7) = 7.70, P = 0.36. Similarly none was found between
medical care-seeking behaviour and sex of respondents
χ2(df = 1) = 0.02, P = 0.50. 64.9% of males visited
ahealth care practitioner (including healer) in the last 4
Table 2. Self-reported illness by sex controlled for by area of
Area of
illness Male Female
Yes 19.4 23.1 69
No 80.6 76.9 256
Total 165 160 325
Yes 20.0 20.7 44
No 80.0 79.3 172
Total 105 111 216
Yes 21.9 34.7 146
No 78.1 65.3 367
Total 251 262 513
weeks compared to 65.6% of females. A cross tabulation
between self-rated health status and sex revealed no sig-
nificant statistical association—χ2(df = 4) = 3.33, P =
A moderate relationship was found between self-rated
health status and age controlled for sex of respondents,
correlation coefficient = 0.48; P < 0.05. Furthermore, the
mean age of respondents who indicated very good health
status was 43.4 years (SD = 11.2 years); 48.8 years (14.1
years) for those who recorded good health status; 59.0
years (SD = 14.7 years) moderate health status; 65.8
years (SD = 13.5 years), poor health status; and 65.8
years (SD = 10.6 years) for those with very poor health
status—F statistic [4, 1043] = 75.1, P < 0.001. Concur-
rently, a cross-tabulation between self-reported illness
and sex of respondents controlled by area of residents
revealed that the significant statistical difference was
found between rural males and females—χ2(df = 1) =
10.3, P = 0.001: 34.7% of rural females reported an ill-
ness compared to 21.9% of rural males (Table 2).
A cross-tabulation between self-reported illness and
area of residence revealed a significant statistical rela-
tionship—χ2(df = 2) = 8.20, P = 0.017: 28.5% of rural
respondents reported an illness compared to 21.2% of
urban and 20.4% of semi-urban respondents. Similarly a
significant statistical association existed between
self-reported diagnosed illness and area of resi-
dence—χ2(df = 14) = 24.93, P = 0.035. Hypertension
was greatest among rural respondents (40.9%) as well as
asthma (4.7%); unspecified ailments were greatest
among urban residents (28.6%) as well as diabetes mel-
litus (21.4%), and colds were greatest among semi-urban
respondents (17.8%) (Table 3).
A significant statistical correlation existed between
self-rated health status and area of residence—χ2(df = 8) =
24.8, P< 0.001. Rural respondents recorded the greatest
very poor health status (2.2%) compared to semi-urban
(0.0%) and urban dwellers (0.9%). With respect to poor
P. A. Bourne / HEALTH 1 (2009) 332-341
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Table 3. Self-reported illness by area of residence.
Area of residence
Urban Semi-urban Rural Total
% % % %
Self-reported diagnosed illness
Cold 2.9 17.8 5.4 6.8
Diarrhoea 0.0 0.0 1.3 0.8
Asthma 2.9 2.2 4.7 3.8
Diabetes mellitus 21.4 15.6 17.4 18.2
Hypertension 21.4 33.3 40.9 34.5
Arthritis 11.4 8.9 8.1 9.1
Unspecified 28.6 15.6 16.1 19.3
Non-diagnosed 11.4 6.7 6.0 7.6
Total 70 45 149 264
Table 4. Self-reported health status by area of residence.
Area of residence
Urban Semi-urban Rural Total
% % % %
Self-rated health status
Very good 31.6 31.3 25.8 28.7
Good 42.1 46.7 39.9 42.0
Moderate 21.7 17.3 22.3 21.1
Poor 3.7 4.7 9.8 6.9
Very poor 0.9 0.0 2.2 1.3
Total 323 214 511 1,048
Table 5. Self-rated health status by social class (in %).
Social class
Poorest 20% Poor Middle Wealthy Wealthiest20% Total
Self-reported health status
% % % % % %
Very good 20.5 17.7 26.2 34.9 36.3 28.7
Good 42.4 42.5 43.7 39.9 42.0 42.0
Fair 23.2 28.7 22.4 18.1 16.9 21.1
Poor 12.6 8.3 7.7 5.0 4.1 6.9
Very poor 1.3 2.8 0.0 2.1 0.7 1.3
Total 151 181 183 238 295 1048
Table 6. Self-rated health status by self-reported illness.
Self-reported illness
Yes No
% % %
Self-rated health status
Very good 4.3 36.8 28.8
Good 24.8 47.5 41.9
Moderate 45.0 13.3 21.1
Poor 21.7 2.0 6.9
Very poor 4.3 0.4 1.3
Total 258 788 1,046
P. A. Bourne / HEALTH 1 (2009) 332-341
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Table 7. Self-rated health status by self-reported diagnosed illness (in %).
Self-reported diagnosed illness
Cold Diarrhoea Asthma Diabetes Hypertension Arthritis Unspecified No Total
health status
% % % % % % % % %
Very good 22.2 0.0 0.0 2.1 3.3 0.0 3.9 10.0 4.6
Good 44.4 0.0 22.2 20.8 17.6 33.3 29.4 40.0 25.5
Moderate 33.3 50.0 33.3 50.0 47.3 41.7 43.1 35.0 44.1
Poor 0.0 0.0 33.3 20.8 27.5 25.0 21.6 10.0 21.7
Very poor 0.0 50.0 11.1 6.3 4.4 0.0 2.0 5.0 4.2
Total 18 2 9 48 91 24 51 20 263
Table 8. Logistic regression: Correlates of good self-rated health status of married
people in Jamaica.
Explanatory variables OR Std. Error 95% CI R2
Self-reported illness 0.12 0.18 0.01-0.17 0.325
Age 0.94 0.01 0.93-0.96 0.102
Log income 1.32 0.12 1.05-1.66 0.010
Sex (male) 1.63 0.18 1.14-2.32 0.007
Chi square = 383.2
LR = 873.9
health status rural dwellers recorded the greatest per-
centage (9.8) and semi-urban (4.7%) and urban respon-
dents (3.7%) (Table 4). Conversely, rural respondents
recorded the lowest very good health status (25.8%)
compared to other residents.
A statistical association existed between self-reported
health status and social class—χ2(df = 16) = 49.5, P <
0.001. The wealthiest 20% of respondents recorded the
highest very good self-reported health status (36.3%)
compared to the wealthy (34.9%); middle class (26.2%);
poor (17.7%) and the poorest 20% (20.5%) (Table 5).
Conversely, the middle class recorded the least very poor
health status compared to the other social classes. How-
ever, as the social class increased from poorest 20% to
wealthiest 20%, the poor health status of the individual
declined (Table 5).
There is significant correlation between self-reported
health status and self-reported illness—χ2(df = 4) = 318.6,
P < 0.001. A moderately strong association was found
between the two mentioned variables, coefficient corre-
lation = 0.48 (Table 6). Based on Table 6, 4.3% of those
who indicated having an illness recorded very good
health status compared to 36.8% of those who did not
indicate an ailment. Of those who indicated having an
illness in the last 4 weeks, 26% recorded at least poor
health status compared to 2.4% of those who had not
indicated an ailment.
A statistical correlation existed between self-rated
health status and self-reported diagnosed illness—χ2(df =
28) = 47.9, P=0.011. The association between the two
variables is a moderate one, correlation coefficient =
0.39. Respondents who indicated chronic illness (i.e.
diabetes mellitus, hypertension and arthritis) were more
likely to record moderate health status. Of those with
chronic illnesses, 231.9% of hypertensive respondents
indicated at least poor health status compared to 27.1%
of the diabetics, and 25% of the arthritic respondents.
Forty-four percent of asthmatic respondents indicated
that their health status was at least poor health status
(Table 7). Less than 5% of respondents who indicated a
chronic illness recorded very good self-reported health
status. Furthermore, when self-rated health status and
self-reported illness were controlled by sex and age of
respondents, the correlation coefficient increased to 0.43,
P < 0.001. And when self-rated health status and
self-reported illnesses were controlled by sex, age and
social class of respondents, the correlation coefficient
increased even further to 0.44, P < 0.001.
3.2. Multivariate Analysis
The correlates of good health status (including moderate
health) of respondents in descending order were self-
reported illness (OR = 0.12, 95%CI = 0.01-0.17); age
(OR = 0.94, 95%CI = 0.93-0.96); income (OR = 1.32,
95%CI = 1.05-1.66) and sex of respondents (Or = 1.14-
2.32)—χ2(df = 4) = 383.2, P < 0.05. The four variables
accounted for 44.4% of the explanatory power of the
model, with self-reported illness accounting for 32.5%
of the explanatory power. Marital status, education, so-
cial class, area of residence and other variables that were
identified as significant in relation to self-reported health
status using bivariate analysis, dissipated when they
were included among other variables in a general collec-
tion of variables (Table 9).
P. A. Bourne / HEALTH 1 (2009) 332-341
SciRes Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
The current study found that the mean age for married
people in Jamaica was 50 years. On disaggregating the
data it was revealed that the mean age for married fe-
males was 6 years less than that for their male counter-
parts (54 years). This finding adds some explanation to
the disparity in life expectancy of the sexes in Jamaica,
as females are expected to live 6 years longer than males
[23,42] and with females who are married 6 years earlier
than males; this indicates that the advantage of good
health status in married couples does not dissipate the
life expectancy gap between the sexes. In wanting to
understand why married people have better health status,
we found that 51% of married Jamaicans were at least
wealthy which more than for the unmarried populace is.
Embedded in this finding is the access to financial re-
sources which are not available to unmarried Jamaicans,
and this accounts for greater health insurance coverage
(34%) compared to the populace (21%); less time spent
in illness (7 days compared to 10 days for the popula-
tion), and they seek more preventative measures, which
accounts for the lower time spent receiving medical care.
Comparatively 16 out of every 100 Jamaicans reported
an illness in 2007 and this was 25 out of every 100 for
married people, which indicates two things: 1) their
willingness to recognize that they are experiencing
ill-health, and 2) the identification of this group’s will-
ingness to first accept illness means that they address
this more than unmarried people before severity comes
into focus, which accounts for the lowered number of
days recorded for them in illness.
In a study conducted by Hambleton et al. [36], on eld-
erly Barbadians, it was found that self-reported current
illness accounted for 87.7% of the variability in
self-rated health status, and in this research we found it
accounted for 73%. Embedded in these findings is the
strong importance of illness on self-rated health status.
Concurrently, in this paper, we found that a married re-
spondent who indicated an illness was 0.12 times less
likely to report moderate-to-excellent health status. In
addition, the current study found that the mean age of
married persons who reported very good self-rated
health status was 43 years and the mean age increased as
the self-reported health status declined to very poor
health: the mean age for those with very poor health
status was 66 years and 59 years for those with moderate
Married people are wealthier, older, with more finan-
cial resources at their disposal, and they have 1) more
choices; 2) more maturity; 3) more social support; and
these cushion the effect of economic hardship which is
likely to be experienced by unmarried and single people.
Income plays a critical role in determining the health
status of people [43] and married people have more of it
than unmarried people, which puts them in the advan-
tage category of the health status scale. Marmot [43]
opined that poverty translated into poor health from the
choice of nutrition, milieu and the choice of freedom,
and this helps in the explanation of the advantage that
income plays in aiding improvements in health status.
The current study concurs with Marmot and other stud-
ies in that income is correlated with good health status;
but disagrees that the correlation is a strong one. The
current work showed that income only accounted for 1%
of 44.4% explanatory power of good health status of
married Jamaicans. Although income opens access to
better physical milieu, choice of medical care, education,
freedom, general choices and entertainment options, it
cannot buy health and it plays a secondary role in im-
proving one’s moderate-to-excellent health status.
The next variable that is correlated with moderate and
beyond health status is age of respondents. The age of
respondents accounted for 10.2% of the variability in
health status in this study. The current study found a
correlation between poor health status and age of re-
spondents, and with 50% of the sample being 48 years;
25% being 39 years and 75% being 62 years and below,
the better health status is carried across the age cohorts
even into older ages for married Jamaicans. Thirty-five
percent of the sample recorded having diabetes mellitus
compared to 12% of the population; 34.5% had hyper-
tension compared to 22.4% of the population and 9.1%
had arthritis compared to 8.8% of the population; yet
still 71% indicated at least good health and 92% at least
moderate health status. This means that preventative care
is high among married respondents. It is this preventa-
tive mechanism which separates and accounts for some
of the health disparity between married and unmarried
people. Within the context of the health conditions
among married people, preventative lifestyle practice is
one of the measures that aid in the health inequality be-
tween this cohort and unmarried people, but it also is the
A study of 1,147 Jamaicans revealed that there was no
significant difference between the health statuses of the
sexes [11]. However, in the current study, married males
were 1.32 times more likely to report moder-
ate-to-excellent health status compared to married fe-
males. This begs the question, why life expectancy be-
tween the sexes has increased to 6 years since 2004?
Since 1988, females have been reporting more illnesses
than males, yet still they outlive males on an average by
6 years; it means therefore that marriage increases the
current health status of males. The findings of this study
revealed that 21 out of every 100 married men reported
an illness compared to 28 out of every 100 married
women and with the context that the latter group is out-
living the former, it can be extrapolated from this study
that men are either under-reporting their ill-health or that
P. A. Bourne / HEALTH 1 (2009) 332-341
SciRes Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
women are more impaired by ill-health than men. A
study by Herzog [44] found that elderly women are more
impaired by their health problems than men, and that
men are more likely to die from them, which goes to the
crux of their under-reporting their illness and so they are
unable to receive adequate care before severity sets in.
Underscoring the under-reporting of ill-health of men,
Schoen et al. found [45] that men in general tend to be
more stressed and less healthy than females, and further
argued that men can use denial, distraction, alcoholism
and other social strategies to conceal their illness or dis-
abilities. It should be noted here that there was no sig-
nificant statistical difference between medical care
seeking behaviour of married men (65%) and women
(66%), which indicated that men benefit from marriage
which is accounted for in their choice to visit health care
practitioners (including healers): in 2007, 63% of the
male population visited a health care practitioner com-
pared to 68% of their female counterparts. Marriage
therefore benefits the health status of males.
Despite the strong influence of culture on men’s social
behaviour, the current study highlights that men’s un-
willingness to seek medical care can be reversed. In the
general population women outnumber men by 5%; but
while married, no statistical difference was found be-
tween visits to medical care facilities by the sexes. This
suggests that during marriage men will disregard to
some degree the culture for the family, as they see their
health and longevity as an important family success.
Although this study did not examine the psychological
status of men and women during marriage, we can ex-
trapolate that some aspect of this changes for men, and
we see them attending medical care facilities in milieu,
which signals weakness and lowered masculinity. Young
males are socialized to be strong, masculine and brave,
and they are taught to shun the appearance of weakness.
One such case is illness. The male child therefore as a
part of his socialization is supposed to accept that illness
is correlated with weakness, and that he must not be
willing to participate in health care seeking behaviour
unless it is unavoidable. This definition of unavoidable
is embedded into severity, and being unable to rectify the
complaint outside of health care practitioners. This gen-
der role of the sexes is not limited to Jamaica or the
Caribbean, but a study carried out by Ali and de Muynck
[46] on street children in Pakistan found a similar gender
stereotype. A descriptive cross-sectional study carried
out during September and October 2000, of 40
school-aged street children (8-14 years) revealed sever-
ity of illnesses, and only when ill-health threatened fi-
nancial opportunities, males sought medical care. How-
ever, married men will utilize health care facilities more
than other men, and this is one of the ways in which they
are able to have better health status, as they would be
more likely to rectify ailments before severity sets in and
premature death results. Recognition of the illness at that
time is difficult to cure or averted.
Another aspect is the psychological component. It can
be deduced from the current findings that marriage pro-
vides positive psychological benefits to both parties that
are embedded in mortality and suicide data. A study by
Kposowa [47] found that divorced and separated people
have a greater rate of suicide than married people; and
that divorced and separated men are 2.4 times more
likely to commit suicide than their female counterparts.
One study found that premature mortality from pneumo-
nia was 7 times higher for divorced men than married
men [48]. Lynch [48] found that divorced or separated
men underwent inpatient or outpatient psychiatric care
10 times more often than married men. In Jamaica, the
suicide rate disparity between the sexes was 9 times
more for men than for women [49]; and while this was
not disaggregated by sex from the literature it can be
extrapolated that marriage provides psychological bene-
fits to men that aid in their better health status, and in-
crease the likelihood of their decision to seek medical
care, unlike their unmarried counterparts. Like men,
marriage provides women with psychological benefits.
A study by Stroup & Pollock [50] found that divorced
women experienced a 30% decline in income compared
to a 10% reduction for their male counterparts. Divorce
therefore sees a financial separation from particular life-
style choices by the women, which also means that the
children as well as the divorced women must now alter
their choices owing to this new reality. The financial
instability which accompanies divorce denotes that
women will be more pressured to carry out some of the
roles that previously were left to their husbands. Hence,
this role, coupled with the financial challenge of the
separation from the man’s resources, demonstrates why
divorced women experience more depressive bouts than
their married counterparts [51]. For women, the benefits
of marriage are more financial, as the literature showed
that women, on separation or divorce, experienced
greater levels of depression [52-54]. Marriage therefore
benefits both sexes. However, like Smith & Waitzman’s
[3], and Lillard & Panis [2], this study concurs that the
health gains from marriage for men were greater than
those for women, and the financial benefits greater for
women than men. The financial gains for women from
marriage were also documented in a study by Prause et
al. [55] which found that married women had higher
economic wellbeing than divorced females, and this in-
dicates the gains that marriage affords them.
Marriage provides greater access to more socioeconomic
resources for its participants, as well as increasing men’s
P. A. Bourne / HEALTH 1 (2009) 332-341
SciRes Copyright © 2009 Openly accessible at http://www.scirp.org/journal/HEALTH/
unwillingness to visit medical care practitioners. Al-
though married people have greater health status, the
benefits are different based on the sex of the individual.
For men the health gains from marriage are greater than
for women; while women benefit more from the finan-
cial access to resources.
The author has no conflict of interest to disclose.
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