1 Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, Korea
2 Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
Correspondence: Young-Ho Khang, Department of Preventive Medicine, University of Ulsan College of Medicine, 3881 Pungnap-2Dong Songpa-Gu, Seoul, 138736 Korea. E-mail: youngk{at}amc.seoul.kr
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Abstract |
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Methods Using Korea's 1995 Census and 19952000 Death Certificate data, age-, sex-, and education-specific mortality rates were measured, after which education-specific rate ratios, and relative indices of inequality were calculated.
Results Graded educational differentials in mortality were observed among both sexes with higher mortality rates related to lower educational attainment in most causes of death. However, positive associations were identified between education levels and mortality rates with respect to ischaemic heart disease among older males and breast cancer among older females. The magnitude of educational inequality in mortality was not constant across causes and in some cases differed by sex.
Conclusions The changing relation between educational attainment and mortality rates from ischaemic heart disease and breast cancer likely reflects changes in the social distribution of risk factors that emerged in the process of Korea's rapid economic development. Studies on specific exposures over the life course influencing the occurrence of and survival after specific diseases would help provide a more complete understanding of patterns and trends in socioeconomic mortality differentials in Korea.
Accepted 22 May 2003
Investigations into socioeconomic inequalities in mortality have been common in Great Britain,1,2 the US,3,4 and several European countries.5,6 With the exception of two recent reports,7,8 studies on socioeconomic mortality inequalities generally remain undeveloped in Korea and other parts of Asia. For example, death rates stratified by education and occupation have not been reported by the government, although the information required to calculate those rates is available in Korean Census and Death Certificate data. This paucity of studies may be attributed in part to the ideological climate. Public discussion of the existence of health and other inequalities has been difficult because South Korea's regimes have viewed such discussion as an attack upon their political legitimacy.
Korea has experienced dramatic socioeconomic change during the past half century. Following Japanese colonial occupation and World War II (19101945), the country was further devastated by the Korean War (19501953). After 1962, however, a series of economic development plans were implemented and Korea's rapid economic progress, often termed an economic miracle,9 transformed the country from an agricultural to an industrialized society. With a growth rate approaching 10% a year, the gross national income per capita reached about USD 10 000 in 2000,10 placing Korea 24th in the OECD member countries, ahead of Mexico and Hungary.11 This represents a 100-fold increase in GDP per head in less than 40 years.12 In 1960, life expectancy was 51.1 years for males and 53.7 years for females. In the year 2000 it was 71.0 for males and 78.6 for females; a dramatic improvement.11 Thus, Korea exemplifies an industrialized country whose economic development and health improvement have been achieved in an extremely short period. Accordingly, various birth cohorts may have experienced rather different socioeconomic conditions over their lifetimes (e.g. in childhood). If past socioeconomic circumstances had an effect on present health and health inequalities, such a cohort effect might be evident with cohort age. For instance, Koreans with childhood experiences of war (e.g. those who were born between 1931 and 1950) may show different patterns of health and health inequalities from those whose childhood experiences were of rapid economic development (e.g. Koreans born 19511960). Although socioeconomic health inequalities between different age groups (birth cohorts) might simply reflect age of death differences in educational inequality rather than true cohort differences in the life course exposure, examining age-specific socioeconomic differences may suggest clues to processes that could affect different age groups and potentially different cohorts. This is the first Korean study to examine age- and cause-specific socioeconomic mortality differentials in a sample that includes both men and women representative of the Korean population.
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Methods |
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By law, all deaths of Koreans must be reported to the National Statistical Office within a month after their occurrence. Death during hospitalization or within 48 hours after discharge can be certified by the physician who examined the decedent. In other cases a death certificate is issued by two local community figures. The proportion of deaths certified by physicians was about 7090% among decedents aged 3564. For deaths not certified by physicians, any vague or missing item on the death certificate is clarified by the National Statistical Office via telephone. Levels of education categorized as No Education, Elementary, Middle, High, and College were determined by the highest level of education completed. The rate of failure to report the decedent's educational attainment on the death certificate was low (0.3% for males and 0.4% for females) among decedents aged 3564 from November 1995 to December 2000. Death Certificate data are available to the public.
Analyses
Using causes of death coded in death certificates per the International Classification of Disease, 10th Revision (ICD-10), the 10 most common causes of death were identified for each sex. Age-, sex-, and education-specific mortality rates were calculated for these causes. Education-specific relative risks (RR) were computed using Poisson regression analyses with the data of sex-, 1-year age-, cause-, and education-specific numbers of population and death. With age calculated using 1 November 1995 as the reference date in the Census, age in Death Certificate data was determined by the same method using date of birth information rather than decedent age at the time of death. The results (i.e. mortality rates and RR) using date of birth information will be similar to those by mortality follow-up in cohort studies, provided that (1) Census and Death Certificate data cover all Koreans residing in Korea, (2) emigration and immigration numbers are relatively small compared with total population, and (3) misclassification bias for educational level is slight. Since the Census information at the Korean Statistical Information System13 does not further categorize age-specific educational levels among the 60+ population, the 1995 Census 2% sample data provided by the National Statistical Office was used to estimate sex- and education-specific numbers for the group aged 5564.
To take into account the different population distributions of the exposure with age group, a summary effect measurethe relative index of inequality (RII) was computed.2,6,1416 This measure regresses the midpoint of the cumulative proportion of the population in different educational groups on mortality. The parameter estimate from this regression is then divided by the average mortality resulting in a percentage mortality difference between the highest and lowest educational groups that can then be expressed like a rate ratio, so that a 50% difference is equal to a RII of 1.50.
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Results |
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Tables 1 and 2 show that for both sexes in all age groups, all-cause mortality increased with decreasing education. There were very large absolute and relative educational differences in mortality among younger men aged 3544 (1809 deaths per 100 000 and RII = 20.2, 95% CI: 14.7, 27.9), with relative inequality among educational groups declining with age. For women, absolute and relative educational differences were generally much smaller with the largest also being observed among younger women aged 3544 (567 deaths per 100 000; and RII = 5.5, 95% CI: 4.1, 7.4).
In regard to specific causes of death however, some heterogeneity of strength and direction of educational differences in RII were found. For instance, among males, mortality decreased in a graded fashion as education increased in all age groups for liver disease, cancers, CVA, transport accidents, self-harm, diabetes, and tuberculosis. On the other hand, among the oldest men aged 5564, less education was associated with a lower IHD mortality rate. The opposite pattern was seen in younger men, so that IHD decreased with educational attainment among males aged 3544 and 4554.
For females in all age groups, graded associations between higher education and lower mortality were observed for stomach cancer, CVA, transport accidents, intentional self-harm, and diabetes mellitus. Breast cancer mortality rates showed a positive relationship with education level among females aged 4554 and 5564. However, among females aged 3544, about 20% more elementary school graduates and 40% more of the No Education group died from breast cancer than those who completed higher education. In contrast to males, among females aged 5564 there was no relationship between education level and IHD mortality. Similarly, among this older group of women aged 5564 there was no association between education and liver cancer, lung cancer, and liver disease mortality. It is also noteworthy that educational inequality in mortality was uniformly greater among younger age groups.
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Discussion |
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Since this study was not based on record linkage, where information from the death certificate could be linked to information from the census (thus eliminating numerator/denominator bias), it is possible that artefacts may explain some of the observed educational mortality gradients. Because the relative size of education levels has changed dramatically over time in Korea, with the lowest levels of education becoming much less common, educational mortality differentials might be exaggerated when a broader age range (e.g. 3564) was used. An older population would show a greater probability of dying among the less educated, whereas the younger population would contribute to a low probability of dying among the more educated. To reduce the possibility of this type of induced artefact, 10-year age groups were used.
Emigration and immigration may also contribute to overstatement of educational mortality differences. Citizens who emigrated from Korea from November 1995 to December 2000 were likely to be more educated, thus increasing the denominator of the more educated. Their deaths, however, would not contribute to the numerator of the more educated because they would not be reported to the National Statistical Office of Korea. Only 61 351 people (0.15% of the Korean population) emigrated during 19962000.17 In addition, foreigners residing in Korea were included in the Census, and were likely to raise the denominator of the more educated. However, foreigners aged 35+ numbered only 14 247, accounting for 0.08% of the same-aged Korean population.13 Therefore artefacts from these causes appear slight.
In contrast to emigrants and foreigners, students studying and workers living abroad might produce diluted educational mortality differentials. Because their deaths during the 5.2-year study period might be reported to the National Statistical Office, they could raise the numerator of the more educated. To reduce such a possibility, this study did not include groups aged less than 35 who were more likely to go abroad to study or work.
The role of artefacts in the explanation of our results does not appear to be very plausible given the heterogeneity in the direction of differentials, the highest rate being found sometimes in low education level (e.g. stomach cancer) and sometimes in high education level (e.g. breast cancer). Previous studies have found that education levels tend to be over-reported rather than underreported.18,19 Hence, education levels of the Census might be more inflated than those of Death Certificate data, thus exaggerating educational mortality differentials. However, this seems unlikely because the 1995 Census questionnaire required more detailed information on education than called for by death certificate questionnaires. Sorlie and Johnson found a tendency for the decedent's education to be reported at a higher level on the death certificate than in a household survey.20 The reliability of responses provided by the Korean Census and Death Certificate data requires further investigation.
The contribution of natural/social selection to the generation of socioeconomic health inequalities has been disputed.2125 Health selection is unlikely as a method of explaining the observed educational mortality differentials because educational attainment is less subject to negative adult health selection.26 Causal interpretations for health inequalities according to educational attainment can be interpreted via various mechanisms, including early-life conditions,16,26,27 acquisition of health promoting/damaging behaviours,2831 development of time preferences favourable to health maintenance,32 optimization of health care usage,30,31 and development of positive psychosocial attributes.30,32 However, education can have specific meanings in specific contexts and thus peculiar effects on a society such as Korea, in which socioeconomic advances have occurred at a remarkably rapid pace. The general consensus is that education played an instrumental role in Korea's miraculous industrialization and economic growth.3335 The economy has become primarily dependent on the accelerated growth in labour-intensive, high skill export industries which demand a well-educated workforce. For the same reason, higher education in Korea thus guarantees higher material and social well-being. Thus, education has been the first priority for all parents, who subsequently are willing to sacrifice great amounts of money and time for their children's education. Under such circumstances, educational levels can represent the best way to advance one's socioeconomic position.
Furthermore, given that rapid economic growth would bring about rapid growth of health-related knowledge and healthcare technology, education might well assure the cognitive ability to adopt health-promoting lifestyles and practices quickly. In Korea, rapidly declining fertility rates may also contribute to educational mortality differentials. Educated women might participate more in the national family planning campaign promoting smaller families, which started with governmental economic development plans and has proven to be very successful.36 Higher per child expenditures for education could be converted to a consequent increase in the quantity and quality of schooling and thus generate intergenerational (from mothers to children) educational inequalities.
Based on the results of RII, relative levels of all-cause mortality inequalities were smaller in females than in males. In other countries, women's socioeconomic all-cause mortality differences have appeared to be smaller than those of men.37,38 The idea that gender differences in socioeconomic health inequalities depended on the measure of the inequality used has also been investigated.37,39 In Korea, different socioeconomic measures capturing other dimensions of social inequality among women may produce similar or even greater social mortality gradients than those in men.
Compared with a previous study in six European countries,40 educational mortality differences according to the broad causes of death showed similar patterns in Korea. Compared with all causes mortality inequalities measured by RII, relatively small mortality inequalities in neoplasms and greater mortality inequality in other causes were found among males, while female mortality inequalities in circulatory diseases were greater than in all causes. In contrast to the previous study,40 however, negative relationships between education levels and mortality rates from external causes of death persisted in this study.
In this study IHD presented a cross-over pattern of educational mortality differences according to age in males, such that higher education was associated with lower IHD risk among the youngest men and women. This pattern reduced with age and then reversed so that among those aged 5564 higher IHD mortality was associated with higher education. This pattern was less clear among women although there was some evidence from the RII that a similar situation occurred among the oldest women. A previous study found no relation between income and mortality from coronary heart disease among Korean male civil servants aged 3064,7 but this could have resulted from collapsing age groups. Kunst et al. observed no or even a positive association between social class and IHD mortality in males in several southern European countries where IHD mortality is traditionally low.41 Meanwhile, studies in the UK42 and the US43 reported that the relation between socioeconomic position and coronary heart disease mortality has changed from positive (increasing mortality with higher social status) to negative among males, but remained negative among females. Davey Smith suggested that these findings were attributable to misclassification of cause of death combined with the early 20th century's prevalent views that IHD is a disease of the affluent classes.44 While this may be true for early 20th century Britain, it may not hold for late 20th century Korea, as it is unlikely to produce that kind of misclassification of IHD exclusively for one age group (5564 in this study). Thus, the observed reversed socioeconomic pattern with age may be real. The fact that socioeconomic gradients for IHD reversed in men by birth cohort but not in women may reflect the timing and gender distribution of the risk factors for IHD as they move through the rapid economic development of Korean society.
Korean male civil servants aged 3064 with higher socioeconomic position showed higher levels of serum cholesterol and obesity, and similar levels of alcohol consumption than those of lower socioeconomic position.7 Because this study found that lung cancer, liver disease, and CVA mortality decreased with educational attainment among all age groups, smoking, alcohol consumption, and hypertension (especially for haemorrhagic stroke) may not contribute to the reversing pattern. Considering that about 60% of females aged 3564 in 1995 did not participate in the labour market,13 the changing relationship among males may reflect changes in job-related risk factors (e.g. sedentary lifestyle), sex differences in social distribution of dietary fat intake, and metabolic responses to dietary fat45 as ways of understanding sex differences in the social distribution of IHD. In addition, given that body mass index and triglyceride levels were dependent on childhood social class while smoking behaviour, alcohol consumption, and hypertension were more strongly associated with current social class,46 a contribution of childhood experience to the reversing pattern in men is worth investigating.
This study found a positive association between education level and breast cancer mortality among females aged 4564, but identified higher breast cancer mortality among females aged 3544 with an educational attainment of elementary school or less. Several reports have suggested that the social distribution of breast cancer in terms of both incidence and survival may be changing, so that the social differences are attenuating or perhaps even reversing.4749
The heterogeneity in relationships between cause of death and socioeconomic position suggests that any single factor (e.g. differences in general susceptibility50,51 or smoking) cannot account for these associations. Studies on specific exposures over the life course which influence the occurrence of and survival after specific diseases would provide better understanding of this heterogeneity. Birth cohort analysis rather than collapsing broad age groups may give more information on socioeconomic health inequalities in a society like Korea with a rapid socioeconomic transition. Since it is uncertain whether the IHD and breast cancer mortality distributions at different socioeconomic stages and younger ages in this study would persist, follow-up studies for different age groups are needed.
KEY MESSAGES
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References |
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