ArticlesReductions in child mortality levels and inequalities in Thailand: analysis of two censuses
Introduction
Over the past five decades there have been substantial improvements in the health of Thai children, with reductions in the under-five mortality rate (U5MR) from above 160 per thousand in the 1950s and 60s to below 40 per thousand by 1990.1, 2 A further 24% reduction from 1990 to 20002 puts Thailand well on track to achieve the Millennium Development Goal (MDG) of a two-thirds reduction in U5MR between 1990 and 2015.3 This is in stark contrast to many other countries, particularly those in sub-Saharan Africa and southern Asia where varied progress towards this target has led to much doubt as to whether the goal can be achieved.4, 5, 6
As the MDGs focus on average levels, one unanswered question is whether the success in reducing the average U5MR has been accompanied by a reduction in the disparity in child health between subgroups of the Thai population. This notion is in line with global calls for routine monitoring of equity in health outcomes.7, 8, 9 Many other countries provide examples of increasing life expectancy and decreasing child mortality while inequalities between the rich and the poor remain10 or worsen.11 Although Thailand has experienced substantial economic growth over the past two decades (with some interruption due to the 1997 economic crisis), income inequality persists at a relatively high level.12 A critical question is how this has affected the distribution of child mortality. Although Thailand might be, on average, set to meet the MDGs for child health, relatively deprived segments of the population might be lagging behind.
We aimed to measure changes in child mortality inequalities by household-level socioeconomic strata of the Thai population using data from the 1990 and 2000 population censuses obtained from the National Statistics Office, Thailand.
Section snippets
Population data
The 1990 and 2000 Thai population censuses were full enumerations of the Thai population. For both censuses, a random 20% sample of households completed a more detailed questionnaire on household characteristics and the analysis conducted here was limited to this sample (table 1).
The data from the Thai census have been used in other studies;2, 13 completeness is very high and quality is regarded to be good.14 The housing and population censuses can be linked through the use of several
Results
Economic status at the provincial level was highly correlated with gross provincial product; Spearman's rank correlation coefficient was 0·87 (p<0·0001) in 1990 and 0·78 (p<0·0001) in 2000. Mean economic status in Thailand increased from 1990 to 2000 and was accompanied by a narrowing of the distribution at the household level (coefficient of variation 0·40 in 1990 to 0·29 in 2000), as shown in figure 1.
Average U5MR was 27·4 (95% CI 26·8 to 28·0) per 1000 livebirths in the 1990 census and 18·7
Discussion
Between 1990 and 2000, in addition to successfully reducing the average level of under-five mortality by about 30%, Thailand approximately halved inequality between the poorest and the richest populations. This remarkable reduction in child-mortality inequality across economic strata is shown by all three measures used in this analysis—the rate ratio, the absolute difference, and the concentration index. The 55% reduction in the excess child-mortality risk between the poorest and richest
References (48)
How much would poor people gain from faster progress towards the Millennium Development Goals for health?
Lancet
(2005)Determinants of child mortality in LDCs: empirical findings from demographic and health surveys
Health Policy
(2003)- et al.
Assessing the effect of the 2001–06 Mexican health reform: an interim report card
Lancet
(2006) - et al.
Health impacts of rapid economic changes in Thailand
Soc Sci Med
(2000) - et al.
Is universal coverage a solution for disparities in health care? Findings from three low-income provinces of Thailand
Health Policy
(2005) - et al.
Inequities among the very poor: health care for children in rural southern Tanzania
Lancet
(2003) - et al.
The decline in child mortality: a reappraisal
Bull World Health Organ
(2000) - et al.
Epidemiologic transition interrupted: a reassessment of mortality trends in Thailand, 1980–2000
Int J Epidemiol
(2006) - United Nations General Assembly. United Nations Millenium Declaration,...
- et al.
Time to reassess strategies for improving health in developing countries
BMJ
(2005)
Health and the millennium development goals
The Millennium Development Goals report 2005
How does progress towards the child mortality millennium development goal affect inequalities between the poorest and least poor? Analysis of Demographic and Health Survey data
BMJ
Knowledge into action for child survival
Lancet
Inequality in Asia: a synthesis of recent research on the levels, trends, effects and determinants of inequality in its different dimensions
Analysis of geographical heterogeneity in live-birth ratio in Thailand
J Epidemiol Biostat
Estimating permanent income using indicator variables
Socioeconomic inequality in infant mortality in Iran and across its provinces
Bull World Health Organ
Health impacts of macroeconomic crises and policies: determinants of variation in childhood malnutrition trends in Cameroon
Int J Epidemiol
Gross provincial product, 2004 edn
Manual X: indirect techniques for demographic estimation
Regional model life tables and stable populations, 2nd edn
Cited by (54)
Socioeconomic related inequality in depression among young and middle-adult women in Indonesia's major cities
2015, Journal of Affective DisordersAre tuition-free primary education policies associated with lower infant and neonatal mortality in low- and middle-income countries?
2014, Social Science and MedicineSocial inequality in infant mortality: What explains variation across low and middle income countries?
2014, Social Science and MedicineCitation Excerpt :This implies that economic development may be associated with reductions in absolute differences in infant mortality between socioeconomic groups. For example, Vapattanawong et al., (2007) showed that a period of economic growth in Thailand between 1990 and 2000 was accompanied by reductions in both relative and absolute differences in under-five mortality between socioeconomic groups. The opposite associations that we observed between GDP per capita and relative and absolute concentration indices for infant mortality across countries is consistent with overall economic improvement preventing more infant deaths from occurring among lower SES households (in absolute terms) but widening relative differences in infant mortality across socioeconomic groups.