Journal of Public Health - Juniper Publishers
Abstract
The salience of income and education on health may
differ in resource-deficit environments. This study explored this
relationship and its measurement in rural Vietnam. Participants were 343
women with education level of 5.1 grades and household incomes equaling
$170/ month. Women were interviewed by trained indigenous women health
advocates. Results indicated that the perception of income level is a
better predictor of health than actual income. Education is not a
significant predictor of health. Measures of perception of income were
more important predictors than actual income. Actual disease burden was
more effective than a brief, general measure of health.
Keywords:
International; Health Perception and Income and Education; Vietnam;
Indigenous Health Advocates; Developing World Income and Health
Introduction
Conducting research and designing interventions in
the developing world pushes our methodologies and knowledge to its
limits. Researchers make assumptions and create hypotheses based on the
current literature, most of which has been conducted in the developed
countries. When applying them to the developing world, these assumptions
are often in advertently exported without being tested. One such
assumption is the relationship between income, education, and health. In
developed countries, this relationship is substantial [1]. The pathway
between education and income to improved health is intertwined because
both are highly correlated. The pathways, however, in a resource deficit
environment, such as in the developing world, are more convoluted. The
relationship between the two and its impact on health in the aggregate
is supported but is not on individual levels in developing countries
[2]. The purpose of this study was to explore this relationship and ways
of measuring it. Measures with a history of use in a developing country
typically emerge from studies conducted on majority populations in
major cities. In Vietnam, only somewhat educated indigenous people speak
the national language. Indigenous people unfamiliar with answering
multiple choice or Likert scales, call into question the use of complex
scales when simple questions may be sufficient. Therefore, medical and
public health studies frequently use one question self-report
statements. A few studies have used pictorial assessments to produce
more valid research among indigenous people.
Income, Education and Health
In the developed world income has been a strong
predictor of physical [3,4] and mental health [5] in developed country
diseases such as cardiovascular disease [6], cancer [7], and diabetes
[8]. In the developing world, parasitic and infectious diseases are
responsible for the highest disease burden [9]. Only one study
investigated conditions leading to helminths and parasites resulting in
an association with environmental conditions and sanitation which result
from poverty but not income or education directly [10]. There is little
information on how income and education interact with the conditions
that lead to parasitic disease or incidence of parasites in developing
countries. Education and income are measures of status in the developed
world. But in countries that do not operate as meritocracies, education
and income are less important in determining status than heritage. In
some developing countries, income levels are adjusted by the government
so that income does not reflect the position or the education required
to function in that position. An underground system of favors and
services enhance income. In a resource-deficit environment, only a few
may have access to health essentials. Under these conditions, neither
objective nor subjective perceived income nor education may be
predictive of health status. To the degree that income and education
matter, designers of interventions that target parasitic disease rates
must understand how these factors are associated with health.
The pathway from education or income to disease burden due
to parasites is complex. Parasitic disease contributes to financial
hardship through malnutrition due to low-protein, iron and
vitamins in individual’s diet, along with inadequate health care,
and poorer living conditions [11] and both income and education
have an interactive effect of these conditions with childhood
vaccines [12]. In the developed society, the empirical evidence
suggests that education has a significant impact on health via
mediating factors such as economic, social, interpersonal, health
knowledge and behavior mediators [13]. These mediating factors
equip individuals with the ability to access health care, engage in
activities that promote wellbeing, and possess psychological and
coping resources such as social support, stress management,
and proper nutrition, in the developed world [14]. The benefit
of education for women shows up when moving from primary
to secondary education levels and for men when moving from
secondary to post-secondary education levels. Among people in
the developing world, where the norm is limited to only primary
education, education may not hold any predictive power. Two
studies in India and Kenya demonstrated that deworming
children, while leading to better school attendance did not result
in higher test scores [15]. Yet, height (presumably due to better
health and nutrition) was positively correlated with education
among adults in several South American countries [16]. And two
other studies found no effects for education and health, one of
which used the same methods as the Indian study [17]. Many
people never go beyond 5th grade in rural Vietnam. If the point
at which education begins to influence health practices occurs
at higher levels, the advantage would not be seen. Those who do
attain secondary or tertiary education levels seldom return to
their villages due to lack of employment. While both education
levels and income levels may vary somewhat even under these
conditions, they may not vary together. In an investigation
using mathematical modeling, Akguch (2010) demonstrated
that different levels of education were associated with varying
levels of income growth depending on the development levels
of countries. In the least developed countries, growth in tertiary
education seemed to benefit less than growth in primary
education levels in the aggregate with more benefit derived
from improving the quality. These studies suggest that there is
no straightforward correlation between education and income
across countries.
Measuring Income, Education and Health
Measuring income: Studies typically measure income
categorically. Such measures may be subject to image
management bias [18]. In countries in which image is a high
value, such a method is likely to be inaccurate. The inaccuracies
can be prevented through asking for an actual amount within
the time space that people naturally consider, such as a presenttime
orientation. In this study, actual income was measured
by asking the amount earned by the entire household in one
month. Individuals’ personal beliefs about their social status are
reliably and strongly related to their overall health. Two studies
demonstrated that subjective SES was a better predictor of
health in Britain [19] and in the US [20], all developing countries.
In developing countries, hosting societies that value image,
perception may be more important and may actually provide
more variance in measurement than actual income. Nancy Adler
et al. [21] developed a pictorial way of measuring subjective
comparative social status that does not require language. The
picture is a ladder, a concept understood in all societies, and
asks the responder to mark the rung on which her family stands
relative to her community.
Measuring Education: In rural Vietnam, the majority of
participants have less than 5th grade or a small percentage
reaching 12 years, with no evidence of anything in between. The
reason is twofold: for a student to continue in school, he/ she
must pass a test and the family must have the income to send
the child to another village to attend. Few current adults have
had this advantage. Therefore, education should be measured in
years of education, not levels. Measuring general health in selfreport
studies. Developing world studies emerge from public
health and typically use specific straightforward questions, often
one or two questions asking the respondent to rate their or their
family’s health on a Likert scale. While broadly accepted, the
measure is likely to be inaccurate due to optimism bias, image
protection efforts and other unconscious processes influencing
memory. Yet, if general health can be adequately measured using
one sentence, it could lead to more studies being conducted in
challenging environments.
Methodology
This study took place in remote areas of Central Vietnam
and was part of a larger study testing an intervention. This study
tested the following hypotheses: Perceived income levels will
be significantly different than actual income level. A checklist of
actual disease experience (FHQ) will be significantly different
than perceived self-report measure of family health. Education
and income will correlate and predict health status? Is actual or
perceived income more predictive of health status? The study
was approved by an ethical review board and the Vietnamese
government. Informed consent was obtained.
Participants
Three hundred and forty-three women were recruited
through the local Women’s Union. Ages ranged from 20-67, x =
38 (sd =10.2) in two villages. Ninety-four percent were married
and living with their spouses. The majority of the husbands
and wives worked at the same vocation. Sixty-six percent were
farmers, 9% fishers, 3.9% were solely homemakers, and the rest
were tradespeople, such as bricklayers and laborers. They had
5.5 years (sd = 3.1) of school on average and household income
was x = $137 (sd = $70) / month for families of 4.3 people. These
women had x = 2.8 (sd = 1.3) children per family, and their
childrens’ average age was 9.8 (sd = 5.1).
Measures
All questionnaires were translated and back-translated into
Vietnamese by a certified translator. The questionnaires were all
answered using a trained health advocate in interviews.
Income: Income was measured in two ways, first, as an
actual amount with the question asked, “How much money does
your entire family earn in a month?” The second assessment
of income was perceived comparative financial status within
the community using Nancy Adler’s 10 question subjective SES
ladder which has been shown to be effective when assessing
individuals’ self-report of social status [22]. Respondents were
asked, “Imagine that the rungs of this ladder represents your
community with the top rung being those who have the most
and the bottom rung being those who have the least. Put an X
where you place your family financially.”
Measuring Health: One question asking, “How do you rate
your health overall?” The five point Likert scale was answered
using 1 = poor to 5 = excellent. A second measure, the Family
Health Questionnaire was also included. The FHQ, developed by
the World Health Organization, measures 22 specific conditions
ranging from menstrual cramps to heart disease. Four diseases
were added because of their prevalence in the area in which
data were gathered, malaria, dengue fever, typhoid, and cholera.
The scale has three columns next to each disease in which a
participant checks whether they were bothered “not at all (0)”,
“a little (1)” or “a lot (2)” by that ailment during the last month.
Education was a straightforward question rather than asking
about levels of schooling in order to obtain a figure that can be
compared [23]. The question was, “How many years did you go
to school?”
Results
Using a one-sample t-test, findings indicated that there was
a significant difference between perceived income levels and
actual income (t =25, df=168, p <.000. There was a dramatic
and significant difference between using brief question and
FHQ to measure health (t = 11.13, df = 343, p < .000). A series
of correlations were performed on measures of income coupled
with measures of health. Actual income was modestly and
negatively correlated with health measured by FHQ (r = -0.215,
p <.006) and perceived income was also negatively significantly
correlated with health measured by FHQ (r = -0.223, p <.004).
Both actual and perceived income levels were entered into
a stepwise regression resulting in perceived income as the
stronger predictor of health as measured by the FHQ (F (df =158)
= 8.9, p <.003). Perceived income level within the communities
is more relevant in health research than actual income levels in
rural Vietnam. Not surprisingly, when the same analyses were
conducted using the one question rating scale, results were not
significant, thus indicating that in measuring health, the actual
disease-specific health information is a better practice than nonspecific
general sense of health, while in measuring income levels,
the relative measure is more important than actual measures of
income [25,26]. There were no significant correlations between
education and health regardless of how health was measured,
either perceived or actual disease conditions. Additionally,
education and income were both significantly correlated but
these correlations are more modest than one would see in
developed world research, with perceived financial status (r =
.249, p < .000) more highly correlated with number of years in
school than actual income levels (r = .20, p < .002).
Discussion
The practice of using one question to measure health
in developing world research is relied upon because of the
difficulties involved in translating measures and validating the
constructs measured. However, this study suggests that there
is danger in such a practice. This study demonstrates that the
reliance on short-cut measures may be inaccurate and lead to
faulty research. Furthermore, the measures that were most
effective in this study were those that transcended language.
The perceived income measure was pictorial. The findings in this
study corresponds with prior research findings indicating that
the higher individuals rated themselves in the social hierarchy,
the better health they had (Adler & Epel, 2000) as well. The
best health measure was a list of illness conditions with the
participant simply checking if they were bothered by that
condition this month, none, a little, or a lot. In a communal society, it is possible that the perceived
standing would be held more important than actual income,
especially since even those with higher income levels do not have
appreciably different lives than others in the same village. It is
also possible that education did not make a difference in health
because we measured it by asking number of years in school and
not by attendance within those years. In rural Vietnam, planting
and harvesting supercedes regular school attendance. Parasitic
disease rates are very high and interfere with attendance and
children stay home to care for younger siblings while parents
till the fields. Thus, education may matter more than is revealed
in this study. Future research should include attendance and
quality as well. Additionally, the resulting lack of significance
could be due to the fact that most of the people did not go beyond
primary school years and the difference in impact may not be
realized until many more years of school are achieved. In rural developing country areas, education is does not appear to be a
factor due to low variance.
While education and income are strong correlates of health
in developed countries, this link is questionable in developing
world conditions. This study found a correlation between
perceived and actual income with health, with perceived income
being more relevant but did not find a significant association
between education and health. Therefore, perception of
income levels should be addressed in developing and testing
interventions.
Limitations
As in many studies conducted in areas where indigenous
languages and constructs blend with the national language, the
way questions are asked impose a challenge. Testing populations
that are unfamiliar with testing in general pose a problem that
has not been studied. Future studies should focus on how
indigenous populations comprehend various ways of asking
questions in research. Another limitation is that this study did
not use an objective measure of health such as testing for actual
parasites. Education measure did not elicit information on
school attendance where truancy is a common part of life.
Implications and Conclusion
When measuring income, perceived income appears to be
either more understood or more predictive than actual income.
Studies should not rely on one or two sentence general questions
when asking about health. It appears that a very specific measure
is required. In this study, the list of actual conditions and amount
of discomfort was predictive. The findings of this study suggest
that best practices in research include: use of pictorial relative
measures with income, specific years in school and attendance
for education, and specific disease conditions for general health.
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