Abstract
Child mortality rates (0–4 years) between 1979 and 2010 and poverty were shown to be significantly worse in five of the six English-speaking countries than in the other 15 western nations suggesting that in these countries children are relatively disadvantaged.
Introduction
Health care outcomes, especially children’s, have moral and political dimensions outlined in the UN’s Children’s Rights (UN, 2009), and objectified in the UN Millennium Goals to reduce child poverty and child mortality rates (CMR) for the under-fives (0–4 years) in all nations. As ‘in the final analysis child mortality rates are an indicator of how well a nation meets the needs of its children’ (UNICEF, 2001) so can we judge between countries how well a nation ‘meets the needs of its children’ (Faye et al., 2012; UN, 2009).
CMR are influenced by different socioeconomic policies (House et al., 2009) but especially in regard to poverty, evidenced in many recent studies (e.g. Brosco, 2012; Sengoelge et al., 2013).
In this brief article we examine the cost-effectiveness of reducing CMR for the under-fives (0–4 years) and compare the six English-Speaking Countries (ESC) with the remaining 15 Other Western Nations (OWN). CMR are examined within the context of what the nations spend on health, GDP Health Expenditure (GDPHE) (US Bureau of Statistics, 2012), and a measure of relative poverty, Income Inequality (Wilkinson and Pickett, 2009).
There are two working null hypotheses:
The is no statistical association between CMR, GDPHE and Income Inequality;
There are no significant differences in reduced CMR between the ESC and the OWN.
Methodology
Baseline and index years (1979–1981 vs 2008–2010)
The three baseline years of 1979–1981 were chosen to match the earliest available GDPHE data (US Bureau of Statistics, 2012) with WHO three-year average index years for 2008–2010. Australia, Canada, Ireland, New Zealand, the UK and the USA (ESC) are compared against the Other Western Nations (OWN). Some countries’ CMR data were earlier than 2008–2010, as shown in Table 1. The latest Canadian and Australian rates were for 2002–2004 and 2004–2006 respectively, whose rates are matched for the same years against the two highest countries from the OWN.
Average GDPHE, child mortality rate per million (pm) 1980–2010, percentage of reduction and Income Inequality in ESC and OWN.
Earliest OWN matched against the years for Australia and Canada.
= sign in column 2 indicates joint co-equal ranking.
Cost-effectiveness
The economic input is the total percentage of GDPHE (US Bureau of Statistics, 2012) from which an average for the 1980–2008 period is calculated.
The clinical output is the combined boy and girl under-five CMR per million (pm) (WHO, 2012) from the age-bands of Infant (< 1year) and Young Child (1–4) from which 0–4 CMR are calculated.
It should be noted that not every country’s CMR match the final index years 2008–2010, which should be borne in mind when discussing the results.
Income inequality
There are debates about the definitions of poverty (Laderichi et al., 2003), but western studies are concerned with relative rather than absolute poverty. A recent measure of poverty in ‘Income Inequality’ based upon World Bank data shows the gap between the top and bottom 20% of incomes, highlighting the end-points of poverty, rather than using the older Gina coefficient whose averages blur the extremities (Wilkinson and Picket, 2009).
Cost-effectiveness ratios
The cost-effectiveness ratio is calculated by dividing the reduced CMR over the period by the average GDPHE, indicating the degree of productivity between economic inputs and clinical outputs (Pritchard and Hickish, 2011).
Spearman rank order correlation is used to examine any association between GDPHE, CMR and Income Inequality.
Chi-square tests compare the changes of CMR in each ESC with each OWN over the period.
Results
Economic input
Column 2 in Table 1 presents the countries’ GDPHE, ranked by the highest average GDP spending on health.
The current highest GDPHE is the USA at 16%, then Switzerland 11.5% and France 11.2% to lows of 8.0% in Japan, 8.4% Finland and 8.5% in Norway. The average in OWN was 10.9% compared to a 10.5% average in ESC.
The USA has the highest average GDPHE over the period at 13.2%, followed by France and Germany at 9.6%, to the four lowest of 7.3% in Ireland, Japan, Spain and the UK. Over the period the OWN average was 8.9% compared to 8.7% in the ESC.
Relative poverty
Column 3 in Table 1 shows the relative poverty scale of Income Inequality where four of the ESC occupy the five widest inequalities. Heading the table is the USA whose top 20% of incomes was 8.5 times that of the lowest 20%; followed by Portugal 8 times, the UK 7.2 times, Australia 7.0 times and New Zealand 6.8 times. The remaining ESC were Ireland 8th and Canada 10th out of 21 countries at 6.1 and 5.6 times respectively, both above the OWN average of 5.2 times, with ECS averaging 6.9 times, a ratio of 1:1.33.
The five lowest countries included the Scandinavian countries, all at 4.3 times or less, the lowest was Japan at 3.4 times.
There was no significant correlation between GDPHE and Income Inequalities (rho = −0.0209).
Clinical outcome
Column 4 in Table 1 lists the countries in order of the highest current CMR to find that the top five positions are occupied by ECS led by the USA at 3334pm, New Zealand 3092pm, Canada 2734pm, the UK 2394pm and Australia 2508pm. Australian and Canadian rates ended in 2002–2004 and 2004–2006 but when matched for the same years against the highest OWN, the Netherlands and Portugal, Australia and Canada were still higher. The ESC exception was Ireland at 1914pm and ranking 14th out of the 21 countries.
The bottom five CMR countries were all OWN: Denmark at 1854pm (also ending in 2004–2006), Norway 1620pm, Finland 1483pm, Japan 1431pm and Sweden 1329pm, whose collective average was 1543pm compared to the top five countries’ average of 2860pm, all ECS, a ratio of 1:1.85.
Over the period average ESC rates fell 56% compared to 71% in the OWN.
It should be noted that every country had substantial reductions in CMR, the smallest decline was in the USA and was the equivalent of a 49% fall; the biggest reductions were in Greece and Portugal, 79% and 82% respectively.
Numbers of deaths
When transposing rates into actual numbers, the average CMR of the two largest OWN, France and Germany, were 1928pm. If the UK had had this CMR then there would have been 874 fewer annual deaths over the period.
With respect to the USA, they would have been 20,665 fewer annual deaths if it had matched France and German rates.
Correlating CMR, GDPHE and relative poverty
There is no significant correlation between CMR and GDPHE (rho = −0.1464, n.s.) but there is a highly signification correlation between Income Inequality and CMR (rho = 0.7929, p < 0.001).
Comparing ESC vs OWN CMR
Despite under-fives mortality falling substantially in every western country the chi-square results in Table 1 show the majority of the ESC doing comparatively less well compared to each OWN.
The USA had significantly lower CMR reductions than any of the OWN. Ireland was the most successful ESC, having greater reductions than eight of the OWN. With the exception of the Netherlands, whose reduced CMR was still less than Australia, Canada, New Zealand and the UK, all had significantly smaller reductions in child mortality than every OWN.
Cost-effectiveness ratios
From the data in Table 1 the cost-effectiveness ratio of each country can be calculated, i.e. the extent of reduced CMR over the period divided by the average % GDPHE of each country. The top five biggest cost-effectiveness ratios were all OWN, led by Portugal 1: 1296pm, Greece 1: 950pm and Spain 1: 625. Ireland at 1: 609 and the UK 1: 534pm were the two most cost-effective ESC, being 5th and 7th respectively, the USA was bottom at 1: 229pm, being the least cost-effective.
Discussion
Limitations
The earlier CMR in some OWN were matched with the highest CMR ESC with the same years 2004–6 but this means the results are indicative rather than definitive, but the positive correlation between relative poverty and CMR reflects many western clinical studies (e.g. Brosco, 2012; Sengoelge et al., 2013).
When interpreting the cost-effectiveness ratios, there is the problem of diminishing returns as countries with initially high CRM can make a greater proportional reduction over the period, whilst the increased fiscal investment may not yield the same level of gain over time (Murphy and Topel, 2003; Pritchard and Hickish, 2011; Vukmir and Howell, 2010). Despite these limitations the study offers a new view of western nations’ ability ‘to meet the needs of its children’ (UNICEF, 2001) and provides a baseline for future study.
Main findings
The first hypothesis is rejected because Income Inequality significantly correlated with CMR but there was no significant correlation between GDPHE and CMR, suggesting poverty has the bigger impact upon child mortality, especially in ESC. Moreover the four countries with the lowest relative poverty had the lowest CRM, whilst four of the top five income inequalities had the highest CMR and were ESC, a finding similar to poverty-related disparities found in education, crime and bio-psychosocial outcomes (Whitworth, 2013; Wilkinson and Pickett, 2009).
Correlation of course is not causal and there may be alternative explanations, for example, there may be genetic factors influencing some countries having lower CMR, though this does not explain the bigger mortality reductions in OWN; but only country-specific research could determine this.
It should be noted that every country had substantial increases in their GDPHE but there is indicative evidence that these increases disproportionately went to older people, especially in the drive to reduce cancer deaths (Pritchard and Hickish, 2011).
There was however relative ‘success’ of two ESC in terms of cost-effectiveness ratios. Ireland and the UK had relatively good cost-effectiveness ratios being 5th and 7th respectively, indicating that their health care systems achieved proportionately more with relatively less.
We conclude that with the exception of Ireland, children in English-speaking countries appear to be relatively disadvantaged because of higher 0–4 year olds mortality and worse income inequality.
The governments of these five ESC should realize that comparatively they are not ‘meeting the needs of their children’. Indeed, if each of the five ESC were ‘parents’, they might well be considered to be relatively ‘neglectful’ and we concur with William Penn’s (1644–1718) statement, that ‘It is a reproach to religion and government to suffer so much poverty and excess’.
Footnotes
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.