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Note: Tables and figures
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Introduction
The issue of health care-seeking
(or medical-care) behaviour is crucible to all society.
All nations rely on its human capital in the creation
and pursuit of growth and/or development. The human
capital is able to accomplish those desired objectives
outlined by the society only on the fundamental premise
that the people are in good health. Health is more than
the absence of diseases and it includes social,
psychological and economic wellbeing. Embedded in good
health is not the least disease, as this is more in
keeping with poor health. While poor and good health
appears to be on the opposite end of a continuum, for
this paper good health denotes the life satisfaction and
general acceptance with the happenings of life. On the
other hand, poor health speaks to the people’s
perception of a low quality of life or life
satisfaction. Hence, this is in keeping with WHO’s
conceptualization of health in the Preamble to its
Constitution in 1946 (WHO, 1948) which stated, health is
not merely the absence of diseases or infirmity but it
is the state of complete physical, social and
psychological wellbeing.
In
spite of a discussion which began in the 1940s, stating
that health was a composite function that includes
biological, social, psychological, environmental and
economic factors (WHO, 1948), Engel (1960,
1977a,1977b,1978, 1980) re-ash this in the late 1950s
and was able to use this in the treatment of mentally
ill-patient. Prior to Engel conceptual model (i.e.
Biopsychosocial model), health was conceptualized,
treated and viewed from a biomedical perspective. This
meant that health-care seeking behaviour was primarily
based on diseases (or disease causing pathogens) and not
based on preventative care. WHO and Engel recognized
this uni-dimensional approach to the view and treatment
of health, and expanded on this conceptual framework.
Despite the contribution of the aforementioned names,
health care-seeking behaviour in Western societies is
still fundamentally driven by negative health (illness,
or poor health) and not in keeping with the broader
framework offered by the World Health Organization.
Health
policy makers in the Caribbean continue to rely on
biomedical approach in the collecting of information
upon which they evaluate the health of the society. This
is evident in how data are collected from the populace
on health. Since 1988, Jamaica has been collecting
statistics on illness from the general populace. The
data were to be used to aid and assess government
policies as well as to guide future programmes. The use
of dysfunctions (or illnesses) to measure health is not
accepting the multi-dimensions to humans; in recognition
that health is more than diseases. It was not until
2007, that the Planning Institute of Jamaica and the
Statistical Institute of Jamaica that are responsible
for the collection of the data, began collecting data on
self-reported health status. Those agents were involved
in the collating of data on dysfunction and health-care
seeking behaviour that were limited to traditional view
of health (i.e. visits to health care institutions and
health care practitioners; bought medication). This
means that all policies were based on the narrow
definition of illness on a construct that has broader
negative view framework about health, which accounts for
Jamaicans (Jamaica Survey of Living Conditions,
1989-2008; Ministry of Health, 2005) and by extension
Caribbean peoples’ willingness to visit doctors (Shaw et
al., 1999).
An
extensive review of health literature revealed that no
study was that examine factors that account for health
care-seeking behaviour of Jamaicans, as well as the
sociodemographic correlates of the health status of
those who sought traditional medical care. The
importance of why people seek medical care is
undoubtedly critical in health policy planning, and it
is within this limitation that this study is timely and
needed. While studies outside of Jamaica have
established different determinants of health-care
seeking behaviour (Grover et al., 2006; Vu 2008;
Williams et al. 2006; Stekelenburg 2005), this cannot be
assumed to apply within the Jamaicans context as the
culture, socio-demographic and economic characteristics
are different and as such calls for an examination of
this phenomenon. Hence, the objectives of this study
were to examine self-rated health status and health
care-seeking behaviour of Jamaicans; and to ascertain
the socio-economic predictors of health care-seekers as
well as to determine factors that account for good
health status of those who sought health care in order
aid public health policy makers and primary care
physicians.
Method
The current study extracted a sample
of 1,006 respondents based on those who indicated having
sought health care in the 4-week period of the survey.
The sample was drawn from a large nationally
representative cross-sectional descriptive survey of
6,783 Jamaicans (Statistical Institute of Jamaica 2007).
The survey was drawn using stratified random sampling.
This design was a two-stage stratified random sampling
design where there was a Primary Sampling Unit (PSU) and
a selection of dwellings from the primary units. The PSU
is an Enumeration District (ED), which constitutes of a
minimum of 100 dwellings 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 Sample of dwelling was compiled, which in turn
provided the sampling frame for the labour force. One
third of the 2007 Labour Force Survey (i.e. LFS) was
selected for the survey (JSLC 2007 – ie Statistical
Institute of Jamaica 2007). The sample was weighted to
reflect the population of the nation.
This
study used JSLC (2007) which was conducted by the
Statistical Institute of Jamaica (STATIN) and the
Planning Institute of Jamaica (PIOJ) between May and
August 2007. The researchers chose this survey based on
the fact that it is the latest survey on the national
population and that it has data on self-rated health
status of Jamaicans. A self-administered questionnaire
was used to collect the data which were stored and
analyzed using SPSS for Windows 16.0 (SPSS Inc; Chicago,
IL, USA). The questionnaire was modelled from the World
Bank’s Living Standards Measurement Study (LSMS)
household survey. There are some modifications to the
LSMS, as JSLC is more focused on policy impacts. The
questionnaire covered areas such as socio-demographic,
economic and health variables. The non-response rate for
the survey was 26.2%.
Descriptive statistics, such as mean, standard deviation
(SD), frequency and percentage were used to analyze the
socio-demographic characteristics of the sample.
Chi-square was used to examine the association between
non-metric variables, and an Analysis of Variance
(ANOVA) was used to test the relationships between
metric and non-dichotomous categorical variables.
Logistic regression examined the relationship between
the dependent variable and some predisposed independent
(explanatory) variables, because the dependent variable
was a binary one (self-reported health status: 1 if
reported good health status and 0 if poor health).
The
results were presented using unstandardized
B-coefficients, Wald statistics, Odds ratio and
confidence interval (95% CI). The predictive power of
the model was tested using the Omnibus Test of Model and
Hosmer and Lemeshow (2000) to examine goodness of fit of
the model. The correlation matrix was examined in order
to ascertain if autocorrelation (or multicollinearity)
existed between variables. Based on Cohen and Holliday
(1982), correlation can be low (weak) - from 0 to 0.39;
moderate – 0.4-0.69, and strong – 0.7-1.0. This was
used to exclude (or allow) a variable in the model. Wald
statistics were used to determine the magnitude (or
contribution) of each statistically significant variable
in comparison with the others, and the Odds Ratio (OR)
for the interpreting of each significant variable.
Multivariate regression framework (Asnani, 2008; Bourne,
2008a, 2008b) was utilized to assess the
relative importance of various demographic,
socio-economic characteristics, physical environment and
psychological characteristics of the health status of
Jamaicans as well as health care-seeking behaviour.
Econometric analyses were also employed by other
scholars in other societies (Grossman, 1972; Hambleton
et al., 2005; Smith & Kington, 1997). This approach
allowed for the analysis of a number of variables
simultaneously. Secondly, the dependent variable is a
binary dichotomous one and this statistic technique has
been utilized in the past to do similar studies. Having
identified the determinants of health status from
previous studies, using logistic regression techniques,
final models were built for women in general as well as
for each of the geographical sub-regions (rural, peri-urban
and urban areas), using only those predictors that
independently predict the outcome. A p-value of 0.05
was used to test the significance level.
Model
The use of multivariate analysis in
the study of health and subjective wellbeing (i.e.
self-reported health or happiness) is well established
(Grossman, 1972; Smith & Kington, 1997; Di Tella et al.,
1998; Blanchflower & Oswald, 2004) equally in Jamaica
and Barbados (Bourne, 2008a, 2008b; Bourne & McGrowder,
2009; Hutchinson et al., 2005). The current study will
employ multivariate analyses in the study of health and
health care-seeking behaviour of Jamaicans. The use of
this approach is better than bivariate analyses as many
variables can be tested simultaneously for their impact
(if any) on a dependent variable.
Scholars like Grossman (1972), Smith & Kingston (1997),
Hambleton et al. (2005), Kashdan (2004), Yi & Vaupel
(2002), the World Health Organization pilot work a
100-question quality of life survey (WHOQOL) (Orley,
1995) and Diener (1984, 2000) have both used and argued
that self-reported health status can be used to evaluate
health status instead of objective health status
measurement. Other scholars, on the other hand, employed
self-reported health conditions to operationalize health
of individual (Bourne & McGrowder, 2009). Embedded in
the works of those researchers is the similarity of
self-reported health status and self-reported
dysfunction in assessing health.
The
current study will examine whether self-rated health
status and self-reported dysfunctions are correlated
variables (Equation [1]) as well as to model general
self-reported illness (Equation [2]), health
care-seeking behaviour of Jamaicans (Equation [3]) and
to evaluate the predictors of self-rated health status
of Jamaicans (Equation [4]).
It=
f (Ht)
[1]
where It
is self-reported dysfunction (illness) is a
function of current self-rated health status, Ht.
It=f
(Ai, Gi,HHi, ARi,
Ht, lnLIi, lnC, lnDi,
EDi, MRi, Si, HIi,
lnY, εi) [2]
where It
(i.e. self-reported illness in current time t) is a
function of age of respondents, Ai ; sex of
individual i, Gi; household head of
individual i, HHi; area of residence, ARi;
current self-reported health status of individual i, Ht;
logged length of illness, LIi; logged
consumption per person per household member, lnC; logged
duration of time that individual I was unable to carry
out normal activities, lnDi; Education level
of individual i, EDi; marital status of
person i, MRi; social class of person i, Si;
health insurance coverage of person i, HIi;
logged income, lnY; and an error term (i.e. residual
error).
Mt=f(Ai,
Gi,HHi, ARi, Ht,
lnLIi, lnC, lnDi, EDi,
MRi, Si, HIi, εi)
[3]
where Mt
is the health care-seeking behaviour in current time t,
is a function of age of respondents, and the other
variables were previously stated.
Ht =f (Ai, Gi,HHi,
ARi, Mt, lnLIi, lnC,
lnDi, EDi, MRi, Si,
HIi, It, Jt, εi)
[4]
where Ht
is self-rated health status of time period t (i.e.
current); It is self-reported illness in
current time period t; Jt is self-reported
injured suffered in the last 4 weeks, and the other
variables were previously stated.
Measure
Self-rated health status: “How is
your health in general?” And the options were very good;
good; fair; poor and very poor. For this study the
construct was categorized into 3 groups – (i) good; (ii)
fair, and (iii) poor. A binary variable was later
created from this variable (1=good and fair
0=otherwise).
Self-reported illness (or self-reported dysfunction):
The question was asked: “Is this a diagnosed recurring
illness?” The answering options are: Yes, Cold; Yes,
Diarrhoea; Yes, Asthma; Yes, Diabetes; Yes,
Hypertension; Yes, Arthritis; Yes, Other; and No. A
binary variable was later created from this construct
(1=yes, 0=otherwise) in order to use in the logistic
regression.
Income:
Total expenditure was used to operationalize income.
Social
class: This variable was measured based on the income
quintiles: The upper classes were those in the wealthy
quintiles (quintiles 4 and 5); middle class was quintile
3 and poor those in lower quintiles (quintiles 1 and 2).
Health
care-seeking behavior: This is a dichotomous variable
which came from the question “Has a doctor, nurse,
pharmacist, midwife, healer or any other health
practitioner been visited?” with the option (yes or
no).
Age is
a continuous variable in years.
Age
group is classified into 7 groups: children (ages less
than 15 years); young adults (ages 15 to 30 years);
other adults (ages 31 to 59 years); young-old (or young
elderly, ages 60 to 74 years); old-old (or old elderly,
ages 75 to 84 years); and oldest-old (or oldest elderly,
ages 85 years and older).
Results
The sample was 1,006 respondents
(40.5% men and 59.5% women), with a mean age of 41.8
years (SD=27.6 years). Forty-four percent of the sample
reported at least good health, 20% at least poor health
and 36% indicated fair self-rated health status.
However, 97% of the respondents claimed that they have
had some dysfunctions; 6% reported being injured due to
accidents, and only 11% indicated that their illness was
not diagnosed by a health practitioner. Of those who
indicated being diagnosed with a recurring ailment, 5.6%
had arthritis, 20.5% hypertension, 12.4% diabetes
mellitus, 9.5% asthma and 14.9% cold. Of those who
reported an injury in the last 4 weeks, 19.2% indicated
that it was owing to motor vehicle, 46.2% domestic
accident and 11.5% mentioned industrial accident (Table
1). Forty-five percent dwelled in urban areas or other
towns and 55% in rural areas. Majority of the sample
indicated that they have had no formal education (71%)
compared to 1.2% tertiary, 15.1% basic or elementary
education, 8.7% primary or preparatory schooling and
4.0% secondary level schooling. Substantially, more
Jamaicans do not have health insurance coverage (75.3%);
11.5% private health insurance; 7.6% NI Gold and 5.7%
other public health insurance coverage. Two thirds of
the sample sought health care and a little over one-half
of the respondents were heads of households (Table 1).
One
half of the sample had annual incomes of US $5,936.77
(US $1.00 = Ja. $80.47) and 50th percentile of health
expenditure was US $9.94. Forty-seven percent of the
respondents were never married (includes common-law),
35.8% were married with 3.0% divorced, 1.8% separated
and 12.0 widowed. The median length of an illness was 7
days and a median of 2 days were calculated as the
length of time in which an individual was ill (Table 1).
Some 54.8% of the sample resided in rural areas, 18.6%
in other towns and 26.6% in urban areas.
Of the
sample, 63.8% responded to the visits to public health
care facilities and 64.1% on visits to private health
care facilities. Of those who responded to each, 49%
attended public health care facilities compared to 57.3%
to private health care facilities.
Thirty-eight percent of the sample were classified as
poor, 21.0% were in the middle class and 41% as wealthy.
Furthermore, 19% were below the poverty line and 21%
were in the wealthiest category. Approximately one-half
of the rural residents were poor compared to 27% in
other towns and 17% in urban areas (χ2 (4)
=132.664, p < 0.001, n=1002). A cross tabulation between
self-rated health status and social standing revealed no
statistical correlation between the two variables (χ2
(8) =14.139, p=0.078, n=1002) (Table 2).
An
examination of health expenditure, injured in the last 4
weeks, and self-reported dysfunction by area of
residence revealed no statistical association (0.088,
0.841, 0.848 respectfully) (Table 3). However there were
statistical relationships between self-rated health
status (p < 0.001), purchase of medication (p=0.020) and
health insurance coverage (p<0.001) by area of
residence. More women (98.3%) than men (94.8%) reported
illness (χ2 (1) =9.885, p = 0.002, n=1001).
Based
on Table 3, rural respondents reported the highest poor
self-rated health status (22.8%) compared to those in
other towns (10.2%) and urban dwellers (10.8%).
Similarly, rural residents reported a lower coverage of
health insurance than those in other towns or urban
areas.
An examination
of head of household by health care-seeking behaviour
revealed no statistical correlation (χ2
(1) =2.010, p=0.088) (Table 4). Furthermore, those who
sought health care had a greater mean consumption per
capita (US $2,168.09 ± US $1,852.36) compared to those
who did not seek health care (US $1,847.39 ± US
$1,625.14) [ t= -2.834, p=0.005].
A cross
tabulation between health care-seeking behaviour and sex
of respondents revealed no statistical correlation
between the two variables (χ2 (1) =3.182,
p=0.074) (Table 5). Table 5 showed that 68% of women
sought health care compared to 62% of men.
On
examination, no statistical correlation existed between
health care seeking behaviour and self-reported illness
of sample (χ2 (1) =2.052, p=0.105). When this
cross tabulation was controlled for sex, there was no
difference between men (χ2 (1) = 1.876, ρ
value = 0.171, n= 406) and women
χ2
(1) = 0.712, ρ value = 0.399, n= 596) (Table 6).
Based
on Figure 1, there was no statistical difference between
self-reported health status of men and women (χ2
(2) =5.618, p=0.060) (Figure 1). Figure 2 showed that
55.8% of the respondents who indicated that they did not
seek health care self-reported good health compared to
37.6% of those who said “yes” they visited a traditional
medical care facility or practitioner. Twenty-four
percent of those who sought medical care reported poor
health compared to 13% who mentioned “no” to seeking
health care in the past 4-weeks; whereas more people who
sought medical care indicated fair health status than
those who reported poor health status (χ2 (2)
=33.298, p < 0.001).
All the
old-old and the oldest-old reported an illness compared
to 97% of young-old, 90.7% of young adults and children
(98.1%) (Figure 3).
A
statistical relation was found between self-reported
illness and age cohort of respondents (χ2
(35) = 453.697, p < 0.001, n=992). The association was a
moderately strong one (contingency coefficient =
0.560). Figure 4 showed that 37% of children had cold,
20% asthma, 21% unspecified compared to 13% of young
adults who had cold, 15% asthma and 40% unspecified and
this change after 31 years. The three leading causes of
morbidity for other aged-adults were unspecified (28%),
hypertension (25%) and diabetes mellitus (15%).
Hypertension was significantly more for those older than
60 years, with rate being the highest for the
oldest-elderly (Figure 4). Based on Figure 4, 31% of
young elderly reported hypertension compared to 44% of
old-old and 47% of oldest-old whereas for diabetes
mellitus, the most number of cases were reported by
young-old (26%), then old-old (17%), oldest-old (17%)
and other aged-adults (15%).
The
cross tabulation between visits to public health care
facilities and area of residents revealed a statistical
correlation (χ2 (2) = 18.332, p < 0.001,
n=641) as well as a relationship between private health
care facilities and area of residents (χ2 (2)
= 22.147, p < 0.001, n=644). Based on Figure 5, most of
the rural residents attended public health care
facilities (56.9%) while most of the other town
residents visited private health care facilities.
An
examination of visits to health care facilities and
social class revealed a statistical correlation: public
(χ2 (2) = 35.874, p < 0.001, n=641) and
private (χ2 (2) = 37.025, p < 0.001, n=644).
The poor were more likely to attend public health care
facilities (63.3%) compared to the middle class (52.5%)
and the wealthy (36.6%), indicating that the rich were
substantially probable to visit private health agencies
(68.8%) compared to the poor (41.7%) and those in the
middle class (57.9%) (Figure 6).
Results: Multivariate Analyses
Using logistic regression analyses,
self-rated health status was found to be a significant
statistical predictor of self-reported dysfunction
(Table 7): good self-rated health status with reference
to poor self-rated health status (OR=0.271, 95%CI=0.081,
0.915).
The
model had statistically significant predictive power
(Model χ2=12.183, p=0.002; Hosmer and
Lemeshow goodness of fit χ2=0.000, P = 1.00)
and correctly classified 96.9% of the sample (correctly
classified 100% of those who indicated self-reported
dysfunctions and 0% of those who do not have
dysfunctions. The logistic regression model can be
expressed as: Log (probability of self-reported
dysfunction/probability of not having dysfunction =
4.195 – 1.304 (1=Good Self-rated Health Status,
0=otherwise). Furthermore, the odds of reporting a
dysfunction for those who indicated good health status
was 82.9%which is less likely than the odds of
reporting a dysfunction for those with poor health
status (Table 7).
Predictors of Self-reported
dysfunction
From the sample, three factors were
found to be predictors of self-reported illness: logged
consumption (OR=0.088,
95%CI= 0.008, 0.961); social
class of the individual (upper class – OR=76.024,
95%CI=1.846, 3130.54); and age of respondents (OR=1.095,
95%CI=1.024, 1.171) (Table 8).
Table 8
revealed that self-reported dysfunction model had a
significant predictive power (Model χ2=27.515,
p=0.001; Hosmer and Lemeshow goodness of fit χ2=1.450,
P = 0.93), and correctly classified 99.7% of the sample
(correctly classified 95.8% of those who indicated
self-reported dysfunctions and 0% of those who do not
have dysfunctions.
The
findings revealed that when the demographic variables
were included with self-rated healthy status, the latter
was no longer significant (Table 8).
Predictors of Health Care-Seeking
Behaviour
Based on Table 9, from the logistic
regression, 5 variables are statistically significant
predictors: Age of respondents (OR=1.031, 95%CI=1.014,
1.049); Area of residence (Other towns with reference to
rural area – OR=0.5, 95%CI=0.278, 0.902); logged
consumption (OR=3.605, 95%CI=1.814, 7.167); marital
status (married – OR=0.468, 95%CI=0.260, 0.843;
divorced, separated or widowed – OR=0.383, 0.163, 0.903)
and social class (Upper class – OR=0.319, 95%CI=0.106,
0.958).
Health
Care-Seeking Behaviour Model had statistically
significant predictive power (Model χ2=49.628,
p=0.001; Hosmer and Lemeshow goodness of fit χ2=13.900,
P = 0.84), and correctly classified 77.8% of the sample
(correctly classified 97.8% of those who sought health
care and 13.3% of those who did not seek health care
(Table 9). The logistic regression model can be
expressed as: Log (probability of seeking health
care/probability of not seeking health care = -14.059 +
0.031 (Age in years) – 0.692 (1=Other Town, 0=Rural
area) + 1.282(logged consumption) – [0.759(1=if married,
0=single) + 0.959(1=if divorced, 0=single)] -1.144(1=if
upper class, 0=otherwise) (Table 9).
Predictors of Self-rated Health
Status
Health status of those who seek
health care can be predicted by 3 factors. These are
logged duration of the individuals to carry out their
normal activities (OR=0.594, 95%CI=0.413, 0.855); age of
respondents (OR=0.967, 95%CI=0.949, 0.986) and area of
residence (urban area – OR=2.415, 1.195, 4.881; other
towns – OR=2.514, 1.162, 5.442).
The
Health Status Model was a statistically predictive one
(Model χ2=59.824, p=0.001; Hosmer and
Lemeshow goodness of fit χ2=4.324, P =
0.827), and correctly classified 77.2% the sample
(correctly classified 34.5% of those who reported good
health status and 93.0% of those who do not (Table 10).
The logistic regression model can be expressed as: Log
(probability of self-reported good health
status/probability of not reporting good health = 1.219
– 0.520 (logged duration unable to work) +
[0.882(1=Urban area, 0=otherwise) + 0.922(1=other town,
0=otherwise)] – 0.033(Age) (Table 10).
Discussion
Two thirds of the sample mentioned
that they sought medical care in the last 4-week, while
marginally more individuals who indicated having sought
health care, reported fair health status than those who
claimed good health status. Interestingly, 9 out of 10
respondents reported an illness with 89 out of every 100
opined that their illness was diagnosed by a health care
practitioner. Rural residents were 2.4 times more likely
to report poor health status than other town dwellers;
whereas urban residents were one-half less likely to
evaluate their health as poor. A critical finding of
this study is that 51 out of every 100 rural residents
were poor, while the ratio was 27 out of 100 in other
towns and 17 out of 100 in urban areas. In spite of the
high report of illness and that 5 out of 19 respondents
had diagnosed chronic recurring illness (i.e. diabetes
mellitus, arthritis, asthma, and hypertension); only 6
out of 10 respondents purchased the prescribed
medication. The study revealed that good health status
was negatively correlated with self-reported
dysfunctions. However, when the socio-demographic
variables were introduced within the model, health
status dissipated as a factor of self-reported
dysfunctions. Of the socio-demographic variables chosen
to be tested in the self-reported dysfunction model,
consumption, social class and age of respondents were
found to be determinants. Whereas, this is so for the
abovementioned variables the determinants of health
care-seeking behaviour of Jamaicans were age, area of
residents, consumption, marital status, and social
class; with duration of time unable to work, area of
residents and age of respondents.
Many
theories (or models) have been developed to explain
health care-seeking behaviour of people and these are
widely used by Caribbean public health policy makers in
planning health demands and needs of societies. The
disadvantages in using those theories (Health Belief
Model; Theory of Reasoned Actions; Theory of Planned
Behaviour; Transtheoretical Model and Stages of Change;
Precaution Adoption Process Model) are that they were
not developed from data collected from the populace.
These theories are atypical to Caribbean or in
particular Jamaica. They are germane the context that
the culture is different along with other indigenous
characteristics. The use of health care-seeking models
which are not biased to the culture means that we mis-prescribed
solutions which are for the targeted population.
According to Glanz et al. (2002), while it is reasonable
to assume that a theory such as Health Belief Model is
applicable to different cultures, it also is important
to realize that constructs may have to be adapted to
make them more relevant to the target culture. Those
modifications may be applicable with some
generalizability to developing nations, but this does
not suggests its comprehensive understanding of
Caribbean peoples or Jamaicans.
Although the Health Belief Model did not emerge from
data in Jamaica or the wider Caribbean, it has some
merits which we examine in this study. This conceptual
model is a framework for health behaviour. The Health
Belief Model (HBM) was developed in the 1950s by some
social psychologists in the United States Public Health
Service. It was designed to account for the failure of
people to become involve in preventative and detection
disease programmes (Hochbaum, 1958; Rosenstock, 1960);
and then it evolved to peoples’s response to symptoms
(Kirscht, 1974) with a later expansion that entails
individuals’ behaviour in response diagnosed
dysfunctions (Becker, 1974). Hence, embedded in the HBM
are preventative actions, illness behaviour, and
sick-role behaviour, suggesting that dysfunction is the
primary focus of this model. This work does not concur
with the HBM as it was found that health status was not
correlated with health care-seeking behaviour of
Jamaicans. However, marital status, area of residence
and social class (i.e. upper class with reference to
poor) were found to be negative determinants of health
care-seeking behaviour while age and consumption were
positive determinants.
The
current study revealed that consumption was the most
significant predictor of health care-seeking behaviour
of Jamaicans followed by age of respondents. It was
found that those who are able to spend more on consumer
expenditure are 4 times more likely to seek medical
care, which concurred with Brow et al (2008). Biological
ageing means a greater likelihood for people to seek
health care and this concurs with other studies (Bourne,
McGrowder & Nevins, in print; Bourne 2009; Brown et al
2008; Erber 2005; Brannon & Fiest 2004; Costa 2002;
Buzina 1999; CAJANUS 1999; Anthony 1999) as the reasons
are linked to increased biological conditions. According
to Morrison (2000), there is a shift from infectious
communicable diseases to chronic non-communicable
diseases as a rationale for the longevity of the
Anglophone Caribbean populace. This research concurs
with Morrison. The findings on in this study revealed
that as people age, the typology of diseases change from
cold, diarrhoea and asthma to diabetes mellitus,
hypertension and arthritis. The probability of the first
three illnesses resulting in mortality is lower than the
latter three morbidities.
In
Jamaica, statistics showed that among the 10 leading
cause of mortality for males 5 years and older were
external causes, cerebrovascular diseases, diabetes
mellitus, ischaemic heart diseases, malignant neoplasm
and hypertension, while for females 5 years and older
the diseases were diabetes mellitus, cerebrovascular
diseases, hypertension, ischaemic heart disease,
external cause and heart diseases (Statistical Institute
of Jamaica, 2008). On the other hand, the leading
mortality among males and females under 5 years were
disorders relating to gestation and fetal growth,
respiratory distress, other respiratory conditions,
other congenital malformations, and perinatal
conditions. Hence, the study concurs with the
statistics and Morrison’s claim that the typology of
diseases shift with the ageing of an individual. In
addition another study found that the sixth leading
causing of mortality for elderly in Barbados, Trinidad
and Tobago, St. Lucia, Montserrat, Guyana, Dominica,
Barbados and Bahamas were fundamentally the same. They
were respiratory infections, cerebrovascular diseases,
hypertension, diabetes, malignant neoplasm, and diabetes
mellitus, which reinforced the primary finding that 39
out of every 100 Jamaican reported being diagnosed with
diabetes mellitus, hypertension and arthritis and the
unspecified group was 23 out of 100 respondents. Among
the diseases in the unspecified category would be
malignant neoplasm. In 2007, statistics indicated that
8.5% of the Jamaica’s population was less than 5 years;
9.7% was 5 to 9 years; 10.3% was 10 to 14 years, meaning
that 28.6% of the population was children. With
approximately 71% of Jamaica’s population ages 15 years
and older, this explains the high probability of chronic
diseases accounting for more deaths than communicable
and illnesses affecting children.
The
current findings indicate that health status is not
determined by health care-seeking behaviour,
self-reported illness or length of illness. This speaks
volume about the culture of unwillingness to visit
traditional medical practitioners, and adds more
information to the discussion, of illness and mortality.
Jamaicans are unlikely to visit health care
practitioners owing to their perspective of illness,
severity of illness and the likely of the dysfunction to
cause mortality. When illness is equated to mortality,
the probability of seeking medical care will be high. A
part of the reason for this health care-seeking
behaviour is embedded in the culture as illness is
viewed as weakness. Another explanation for this low
probability is Jamaicans involvement of non-traditional
medical care behaviours. To address ill-health,
Jamaicans visit spiritual advisers (i.e. unknown as
obeah men). These individuals perform the similar
functions like the traditional health practitioners
except surgeries. The data used for this study excluded
non-traditional medical healers, and so underestimate
the coverage of medical care-seeking behaviour of
sample.
There
is a finding which appears paradoxical as people who
resided in urban areas do not exhibit greater or lower
health care-seeking behaviour than those who dwelled in
rural areas. Rural residents were more likely to seek
medical care than other town dwellers while more
consumption was positively correlated with seeking more
health care. Interestingly, the wealthy spent more on
consumption than the poor, yet the poor sought more
medical care-seeking behaviour than upper class
Jamaicans. Although rural residents were more likely to
be poorer than other Jamaicans and that they were more
likely to spend less than urban and other town dwellers.
Embedded in this finding, is the fact that it is not
higher social class that determines health seeking
behaviour but money. Those in the upper class may have
access to more financial resources, but rural residents
have greater social network which avails them of
extended economic resources. Rural residents have more
children, and the culture within those areas is such
that the wider community is willing to aid each other
for consumption including medical care. Another issue
that is not on the surface of the finding is the fact
that they (i.e. rural residents) were attending more to
medical care than other town dwellers and there is no
evidence of statistical difference in health-seeking
behaviour between rural versus urban residents, owing to
disproportionally more of them in the country than other
dwellers. The wide primary health care coverage which is
inexpensive means that Jamaicans even if they are poor
can access health care. Where the difference will be is
in access to private health care service, and this is
basic fundamentally on one’s ability to afford it and
not on wanting to access the service.
The
inverse correlation between self-reported dysfunction
and consumption, showed a positive association between
health care-seeking behaviour and consumption within the
context that those in the upper class have a greater
degree of reporting illness, means that there is a
cultural bias that explains Jamaicans unwillingness to
seek health care. This study did not initially examine
lifestyle behaviour of Jamaicans, but given that
consumption expenditures are constituted of meal and
non-consumption expenditures, consumption being a
negative predictor of self-reported illness, suggests
that Jamaicans were involved in relatively good
decisions that are lowering illness. The positive
relations between health care-seeking behaviour and
consumption are indicators of preventative lifestyle
practices. This is so, because in 2006, 70% of Jamaicans
who reported ill-health sought medical care (Planning
Institute of Jamaica and Statistical Institute of
Jamaica, 2008) compared to 66% in this study (in 2007),
within the context that inflation increased by 194.7%
over 2006 (in 2007), this means that increased
consumption expenditure does not necessarily mean more
meal consumed or non-consumption as this change is owing
to price increases. With more Jamaicans attended
private health care facilities, inflation would increase
costing of the offered services.
The
current study found that rural residents had the least
self-evaluated health status, and thereby justify more
of them seeking medical care than upper class Jamaicans.
Another explanation for more rural residents attended
health care institution is owing to greater percentage
of them in older ages than in other geographic zones.
Age is a negative determinant of health status and
positively correlated with self-reported dysfunction,
and accounts for more rural residents demanding more
health care than other people in Jamaica.
This
study refined the finding of Grover el’s work (2006).
They found that significantly more urban area dwellers
take self medication compared to rural area residents
(see also, Sudha et al, 2003). In this study, it was
revealed that that more urban dwellers purchased over
the counter medication than rural residents; but that it
was other town dwellers (i.e. semi-urban) that
significantly used self medication than rural area
people. This means that self treatment was more an urban
and/or semi-urban phenomenon than a rural area reality.
On the other hand, rural area residents significantly
purchased more prescribed medication than other town
dwellers, while urban area settlers bought more
prescribed medicine compared to rural and semi-urban
residents. This study went further than Grover et al.
(2006) and Sudha (2003), when it examined those who did
not buy by area of residence. The current work revealed
that significantly more rural area residents did not
purchase medication than residents in other geographic
areas.
Interestingly health care-seeking did not differ
significantly between the sexes, which concur with a
study by Williams et al (2006). One of the explanations
for this non-significance can be accounted for based on
the non-significant disparity in health status and
self-reported dysfunctions of males and females.
Conclusion
Jamaica is comprised of peoples of
different ethnic; socialization; social class;
geographic zones and culturalization, and this accounts
for a difference in belief system and health behaviour.
This disparity must be taken into consideration when
designing public health programmes. Hence, the wholesale
utilization of any health model that is developed
outside of the society or even medication of such a
theory is not necessarily applicable to the nation.
The
current study revealed that health behaviour is a
function of socio-demographic variables. Poverty which
is synonymous to rural areas influences people choice in
visits to health care-seeking facilities. An interesting
consideration of rural residence with those than
residents of other geographic zones is the culture and
its influence on health care-seeking behaviour and other
such decisions. Home remedy and non-traditional healers
(i.e. obeah men) is a substitute product that is used
more by rural dwellers than others, because of the
retention of the African tradition. While urban and
other town residents were exposed to this culture and
socialization, their higher level of education, access
to more information and financial resources account for
re-socialization and new re-adaptation to traditional
medical care utilization. Therefore, when health
literacy and public health programmes are fashioned in
Jamaica or other developing societies, health
care-seeking behaviour model must not only be modified
but must utilize data from those nations to address the
health needs of the geo-political zones and not some
model developed for developed societies with some
modifications. The findings of this study suggests that
health service professionals need to increase awareness
about the benefits of purchasing prescribed medication,
and that this must be more so for rural and urban
residents.
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