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. 1999 Oct 30;319(7218):1162–1165. doi: 10.1136/bmj.319.7218.1162

Economic transition and changing relation between income inequality and mortality in Taiwan: regression analysis

Tung-liang Chiang 1
PMCID: PMC28264  PMID: 10541504

Abstract

Objective

To examine the changing relation between income inequality and mortality through different stages of economic development in Taiwan.

Design

Regression analysis of mortality on income inequality for three index years: 1976, 1985, and 1995.

Setting

21 counties and cities in Taiwan.

Main outcome measures

All age mortality and age specific mortality in children under age 5.

Results

When median household disposable income was controlled for, the association between income inequality and mortality became stronger in 1995 than in 1976. Especially, the association between income inequality and mortality in children aged under 5, with adjustment for differences in median household disposable income, changed from non-significant in 1976 to highly significant in 1995. In 1995, the level of household income after adjustment for income distribution no longer had a bearing on mortality in children under 5.

Conclusion

The health of the population is affected more by relative income than by absolute income after a country has changed from a developing to a developed economy.

Key messages

  • Income distribution may be more important than the level of income in determining population health in developed countries but has not been examined in a country through different stages of economic development

  • Along with economic development, gross national product per capita in Taiwan has increased rapidly from less than US$200 (£72) in 1953 to US$1132 (£627) in 1976 and to US$12 396 (£7853) in 1995

  • In Taiwan the association between income distribution and mortality was stronger in 1995 than in 1976, contrary to the association between absolute income and mortality, which was stronger in 1976 than in 1995

  • The effect of income distribution on age specific mortality rate in children under 5 became highly significant whereas the effect of absolute income became non-significant in 1995

Introduction

Does relative income become more important than absolute income in determining population health after a country has changed from a developing to a developed economy? By comparing countries that are members of the Organisation for Economic Cooperation and Development, Wilkinson showed that: (a) a strong relation exists between life expectancy and income distribution, whereas its relation with gross national product per capita is weak; and (b) a decrease in the prevalence of relative poverty is significantly related to a rapid improvement in life expectancy.1,2 Kaplan et al3 and Kennedy et al4 reported independently that in the United States the relation between income distribution and mortality remained highly significant even after controlling for absolute income. Nevertheless, most of the studies on population health and relative income versus absolute income are cross sectional studies that were done in post-industrialised countries where the epidemiological transition is complete. I aimed to examine the changing relation between income inequality and mortality through different stages of economic development in Taiwan, using data at county and city level.

Taiwan, with a population of 21.3 million in 1995, is a newly industrialised country; its achievement in economic development has been frequently termed an “economic miracle” (table 1). In the early 1950s, Taiwan was a poor country with a gross national product per capita of no more than US$200 (£72 valued at 1950s prices).5 Since 1953 a series of economic development plans has been effectively implemented, and Taiwan's economy has shifted from agricultural to industrial and from import oriented to export oriented.6 As a result, gross national product per capita has increased rapidly to US$1132 (£627 valued at 1976 prices) in 1976 and to US$12 396 (£7853 valued at 1995 prices) in 1995.5

Table 1.

Basic socioeconomic and health indicators in Taiwan, 1953-955 7 8 9

Variable 1953 1976 1985 1995
Socioeconomic indicators
Population (million) 8.3 16.5 19.3 21.3
Population aged ⩾65 (%) 2.5 3.6 5.1 7.6
Gross national product per capita (US$) 196* 1132 3297 12 396
Gini coefficient 0.56 0.28 0.29 0.32
Ratio of highest fifth's income to lowest fifth's 20.46 4.18 4.50 5.34
Health indicators
Crude death rate (per 1000) 9.4 4.7 4.8 5.6
Under 5s mortality (per 1000) 21.1 3.9 2.1 1.9
Life expectancy (years):
 Male 58.2 68.7 70.8 71.9
 Female 61.4 73.6 75.8 77.8
*

1952. 

Number of deaths in group aged 0-4 per 1000 population in same age group. 

The economic development of Taiwan has been identified not only with rapid growth but also with improved income distribution.7 Like most developing countries Taiwan had a large income gap in the early years of economic transition. The ratio of income share of the richest 20% to that of the poorest 20% in Taiwan reached 20.5 in 1953, but it decreased substantially to 4.2 in 1976 and then slightly increased to 5.3 in 1995.5 Similarly, the Gini coefficient—a commonly used measure of the degree of income inequality, ranging from zero to a maximum of one—for Taiwan has decreased from 0.56 in 1953 to 0.28 in 1976 and gradually increased to 0.32 in 1995.5

Besides being an “economic miracle” Taiwan has also achieved a “health miracle” (table 1). Since the 1950s, mortality has declined remarkably among all age groups in Taiwan. Improvement is especially significant in age specific mortality in children under age 5, which has decreased from 21.1 per 1000 population in 1953 to 1.9 per 1000 in 1995. Accordingly, life expectancy at birth in Taiwan has increased for males and females respectively from 58.2 years and 61.4 years in 1953 to 71.9 years and 77.8 years in 1995.8

With the decline in death rates Taiwan has experienced an epidemiological transition. In the early 1950s most of the leading causes of death in Taiwan were infectious diseases including gastroenteritis, pneumonia, tuberculosis, nephritis, bronchitis, and malaria. These began to give way to non-infectious diseases as the leading cause of death, and by the 1990s non-infectious diseases such as cancer, stroke, heart disease, hypertensive diseases, and diabetes mellitus have become dominant health problems in Taiwan.8

Methods

Source of data

I collected data for three index years: 1976, 1985, and 1995. Data on income were obtained from the family income and expenditure survey, conducted by the directorate-general of budget, accounting, and statistics, Republic of China. The family income and expenditure survey, which aimed to address the general conditions of livelihood and to present the status of family income and expenditure in Taiwan, was conducted mainly through personal interview. In order to check the validity of results from the interview a small number of households were asked to keep accounts. The survey covered the civilian non-institutionalised population of Taiwan, with about 15 000 registered households selected through a two stage stratified random sampling in a calendar year. The information collected included family composition, housing conditions, family income and expenditure, fixed assets, mutual saving funds, and miscellaneous items. The earliest available electronic data file on the family income and expenditure survey was for 1976.

Data on mortality were obtained from the Taiwan-Fukien Demographic Fact Book,9 which is published annually by the ministry of the interior. Two mortality measures were used in the analysis: mortality in all ages, and age specific mortality in children under 5 years. Mortality in children under 5, which refers to the number of deaths in the group aged 0-4 per 1000 population in the same age group, was presumed to be more sensitive to economic change than all age mortality. Further, the population of Taiwan has been ageing since the 1970s, and to compare crude death rates over the study period might be misleading because mortality depends strongly on age. Thus a direct method of age standardisation was introduced,10 and the all age mortality in any study year was adjusted to allow for discrepancies in the age structure of population by using the 1976 world population as the standard.

Measure of absolute and relative income

In the analysis absolute income was defined as median household disposable income after payment of taxes and receipt of benefits. Relative income was defined as the proportion of household disposable income received by households whose disposable income was below a specified centile on the distribution of household disposable income. For example, the relative income for the 50th centile in Taiwan in 1995 was 28.2% because the less well off 50% households received 28.2% of disposable income. Using data from the family income and expenditure survey I calculated relative income for the 20th, 50th, 70th, and 90th centiles for all 21 counties and cities and for Taiwan as a whole.

Statistical analysis

To determine the association between absolute and relative income and measures of mortality I calculated Pearson correlation coefficients. Ordinary least squares multiple regression was further used to discover whether median household disposable income or the share of household disposable income received by the less well off 50% had more influence on mortality. For the regression analysis I presented squared multiple correlation coefficients as well as partial regression coefficients. The squared multiple correlation coefficient or R2 was interpreted as the proportion of the variance of the measure of mortality which was “explained” by the model comprising two predictors: median household disposable income and the share of household disposable income received by the less well off 50%.11 Because R2 must increase as further variables are introduced into a regression, I further presented adjusted R2 to take into account the chance contribution of each variable included.10 The partial regression coefficient or β was the amount by which the measure of mortality changed on the average when median household disposable income or the share of household disposable income received by the less well off 50% changed by one unit and the other remained constant.

Results

Association between mortality and income measures

Table 2 shows Pearson correlation coefficients for the association between mortality and absolute income as well as income distribution. Although the association between all age mortality and median household disposable income remained highly significant (P<0.001) across the three index years (Pearson correlation coefficient −0.66 to −0.71), the association between mortality in children under 5 and median household disposable income tended to weaken from 1976 to 1995 (r=−0.79; P<0.001 v r=−0.50; P<0.05). The relation, however, between mortality and income distribution tended to strengthen over the study period, and the relation patterns were broadly consistent across the four measures of income distribution. In 1995 the share of household disposable income received by the less well off 20%, 50%, 70%, and 90% were all strongly correlated with all age mortality (Pearson correlation coefficient −0.57 to −0.64); the association with mortality in children under 5 was even stronger (−0.64 to −0.75). To the contrary, the association between mortality and income distribution was very weak in 1976, especially for all age mortality (−0.08 to −0.22). Only the association between mortality in children under 5 and the share of household disposable income received by the less well off 20% and 50% was statistically significant in 1976 (P<0.05).

Table 2.

Pearson correlation coefficients for relation between age adjusted mortality in all ages and mortality in children under 5, and median household disposable income and the share of disposable income received by households below specified centile in Taiwan, 1976, 1985, and 995

Variable All age mortality
Mortality in under 5s
1976 1985 1995 1976 1985 1995
Median household disposable income −0.69*** −0.66*** −0.71*** −0.79*** −0.61** −0.50*
Share of household disposable income received by less well off:
 20% −0.17 −0.31 −0.57** −0.47* −0.54* −0.64**
 50% −0.22 −0.29 −0.62** −0.47* −0.49* −0.73***
 70% −0.14 −0.22 −0.64** −0.38 −0.48* −0.75***
 90% −0.08 −0.20 −0.58** −0.38 −0.34 −0.68***
*

P<0.05; ** P<0.01; *** P<0.001. 

Relative importance of level of income v income distribution

Results from the ordinary multiple regression analysis of mortality on median household disposable income and the share of household income received by the less well off 50% show the relative importance of absolute income versus relative income in determining mortality (table 3). Overall, the proportion of the variance of mortality accounted for by the two absolute and relative income measures in any of the six multiple regression models was significantly high (at least P<0.01). The value of R2 ranged from 46% to 58% for all age mortality and from 38% to 63% for mortality in children under 5. The adjusted R2 tended to have a value slightly lower than that of R2 across different measures of mortality and different study years.

Table 3.

Multiple regression analysis of age adjusted mortality in all ages and mortality in children under 5 on median household disposable income and share of household disposable income received by less well off 50% in Taiwan, 1976, 1985, and 1995 (standard errors in parentheses)

Variable All age mortality
Mortality in under 5s
1976 1985 1995 1976 1985 1995
Median household disposable income (NT$10 000) −45.43*** (10.97) −18.43** (5.18) −3.43** (1.15) −0.58*** (0.13) −0.07* (0.03) −0.05 (0.06)
Share of household disposable income received by less well off 50% 1015.27 (952.85) 1264.04 (1193.57) −1467.34 (750.79) −4.86 (11.30) −4.41 (7.65) −13.23** (3.83)
R2 0.51 0.46 0.58 0.63 0.38 0.55
Adjusted R2 0.46 0.40 0.54 0.59 0.32 0.50
F value 9.45 7.77 12.74 15.40 4.74 10.88
P value 0.0016 0.0037 0.0004 0.0001 0.0118 0.0008
*

P<0.05; **P<0.01; ***P<0.001. 

Table 3 clearly indicates that, with median household disposable income constant, the association between mortality and the share of household disposable income received by the less well off 50% had become increasingly strong over the study period. On all age mortality, the effect of the share of household disposable income received by the less well off 50% with the adjustment of median household disposable income had changed from positive and non-significant in 1976 (β=1015; P=0.301) to negative and barely significant in 1995 (β=−1467; P=0.064). On mortality in children under 5, which was presumed to be more sensitive to economic change, the effect of the share of household disposable income received by the less well off 50% with the adjustment of median household disposable income had even shifted from non-significant in 1976 (β=−4.86; P=0.672) to highly significant in 1995 (β=−13.23; P=0.003). It is worth noting that in 1995 median household disposable income no longer had a bearing on mortality in children under 5 after the share of household disposable income received by the less well off 50% was controlled for (P=0.373).

Discussion

During the past two decades Taiwan has undergone critical stages of economic transition and become a newly industrialised country. This study shows that, contrary to the weak relation of income inequality to mortality in 1976, counties and cities with more equal income distribution in 1995 were more likely, with the adjustment of median household disposable income, to have a lower mortality (table 3). Especially, in 1995 the effect of income distribution on mortality in children aged under 5 became highly significant and the effect of median household disposable income became non-significant. Therefore, the Taiwan case examined here supports Wilkinson's proposition that relative income is more important than absolute income in determining population health in developed countries.12

In attempting, however, to generalise from this study it should be noted that Taiwan's success in economic development is unique. Firstly, Taiwan has achieved economic transition in a very short period. Secondly, it has succeeded in combining a rapid growth of national economy with improved income distribution, which is different from the experience of Western industrialised countries.13 Thirdly, county and city income inequality has been significantly associated with the level of economic development as measured by median household disposable income (Pearson correlation coefficient 0.51 to 0.66). These and other factors such as drastic political reform in Taiwan since the 1980s might have conditioned the changing relation of income inequality to mortality.

Why is greater income equality associated with better health? Psychosocial stress from relative deprivation, disrupted social cohesion, disinvestment in social capital, and under investment in human resources all have been suggested as pathways through which income inequality affects population health,2,14,15 but only a small number of empirical studies to date have attempted to clarify the relation.3,1619 Taiwan, as well as other newly industrialised countries blessed with a rapid economic transition, should provide a good opportunity for further work to understand mechanisms linking income inequality to health.

Conclusion

The health of the population is affected more by income distribution than by the level of income after a country has changed from a developing to a developed economy. Thus, a newly developed country such as Taiwan should pay more attention to the consequences on population health of the gap between the rich and the poor and not merely healthcare reform.20

Acknowledgments

I thank Shu-Chen Liu, Shao-I Lin, and Tsung-Hsueh Lu for their help in data processing.

Footnotes

Funding: None.

Competing interests: None declared.

References

  • 1.Wilkinson RG. Income distribution and life expectancy. BMJ. 1992;304:165–168. doi: 10.1136/bmj.304.6820.165. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Wilkinson RG. Unhealthy societies: the afflictions of inequality. London: Routledge; 1996. [Google Scholar]
  • 3.Kaplan GA, Pamuk E, Lynch JW, Cohen RD, Balfour JL. Inequality in income and mortality in the United States: analysis of mortality and potential pathways. BMJ. 1996;312:999–1003. doi: 10.1136/bmj.312.7037.999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Kennedy BP, Kawachi I, Prothrow-Stith D. Income distribution and mortality: cross sectional ecological study of the Robin Hood index in the United States. BMJ. 1996;312:1004–1007. doi: 10.1136/bmj.312.7037.1004. . [Important correction BMJ 1996;312:1194.] [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Republic of China Council for Economic Planning and Development. Taiwan statistical data book, 1998. Taipei: Council for Economic Planning and Development; 1998. [Google Scholar]
  • 6.Li KT. The evolution of policy behind Taiwan's development success. New Haven: Yale University Press; 1988. [Google Scholar]
  • 7.Kuo SWY, Ranis G, Fei JCH. The Taiwan success story: rapid growth with improved distribution in the Republic of China, 1952-1979. Boulder, CO: Westerview; 1981. [Google Scholar]
  • 8.Republic of China Department of Health. Health and vital statistics, vol I. General health statistics, 1997. Taipei: Department of Health; 1998. [Google Scholar]
  • 9.Republic of China, Ministry of the Interior. Taiwan-Fukien demographic fact book (published annually). Taipei: Ministry of the Interior. (Sources: 1973, 1976, 1985, 1995.)
  • 10.Armitage P, Berry G. Statistical methods in medical research, 3rd ed. Oxford: Blackwell Scientific; 1994. [Google Scholar]
  • 11.Goldstone LA. Understanding medical statistics. London: William Heinemann Medical; 1983. [Google Scholar]
  • 12.Wilkinson RG. Health inequalities: relative or absolute material standards? BMJ. 1997;314:591–595. doi: 10.1136/bmj.314.7080.591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Kuznets S. Economic growth and income inequality. Am Econ Rev. 1955;45:1–28. [Google Scholar]
  • 14.Davey Smith G, Egger M. Commentary: understanding it all—health, meta-theories, and mortality trends. BMJ. 1996;313:1584–1585. doi: 10.1136/bmj.313.7072.1584. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Kaplan GA, Lynch JW. Whither studies on socioeconomic foundations of population health. Am J Public Health. 1997;87:1409–1411. doi: 10.2105/ajph.87.9.1409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kawachi I, Kennedy BP, Lochner K, Prothrow-Stith D. Social capital, income inequality, and mortality. Am J Public Health. 1997;87:1491–1498. doi: 10.2105/ajph.87.9.1491. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Wilkinson RG, Kawachi I, Kennedy BP. Mortality, the social environment, crime and violence. Sociol Health Ill. 1998;20:578–597. [Google Scholar]
  • 18.Daly MC, Duncan GJ, Kaplan, Lynch JW. Macro-to-micro links in the relation between income inequality and mortality. Milbank Q. 1998;76:339. doi: 10.1111/1468-0009.00094. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Wallberg P, McKee M, Shkolnikov V, Chenet L, Leon DA. Economic change, crime, and mortality crisis in Russia: regional analysis. BMJ. 1998;317:312–318. doi: 10.1136/bmj.317.7154.312. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Chiang TL. Taiwan's 1995 health care reform. Health Policy. 1997;39:225–239. doi: 10.1016/s0168-8510(96)00877-9. [DOI] [PubMed] [Google Scholar]

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