Evaluating the health of nations: a Libyan perspective

Researchers leave no doubt regarding the importance of a health system, since health is considered to be a fundamental contributor to the welfare of every country (1). As the evaluation and ranking of countries are based on their health status, it is therefore a crucial issue. Despite numerous attempts, health systems are a difficult issue to measure. The vast majority of researchers use mortality rates as an indicator of the country's health status (2). However, this approach assumes that health is a one-dimensional concept, which is not precisely true (3, 4).

To create a synthesised health status indicator, more variables are incorporated into the analysis by using the statistical I²-distance method (5, 6). The I²-distance method was proposed by Ivanovic (5) and Jeremic and Radojicic (6). They devised this method in order to rank countries according to their level of socio-economic development.

For a selected set of variables X^T=(X₁, X₂, …, X_k) chosen to characterise the entities, the I²-distance between two entities e_r=(x_1r, x_2r, …, x_kr) and e_s=(x_1s, x_2s, …, x_ks) is defined as

$$D^2(r,s)=\sum _{i=1}^k\frac{d_i^2\left(r,s\right)}{{\sigma }_i^2}\prod _{j=1}^{i-1}\left(1-r_{ji.12\dots j-1}^2\right),$$

where $d_i^2(r,s)$ is the square distance between the values of variable X_i for e_r and e_s (e.g. discriminate effect),

$$d_i(r,s)=x_{\mathrm{ir}}-x_{\mathrm{is}},i\in (1,\dots ,k),$$

σ_i the standard deviation of X_i, and r_{ji. 12…j–1} is a partial coefficient of the correlation between X_i and X_j(j<i).

Each of the Eastern Mediterranean Region (EMR) countries’ health status is quantified by use of the I²-distance ranking method. The selection of the indicators was chosen in order to reflect the health of individuals and state of health services (4). Data from the Statistical Information System of the World Health Organisation and the WHO Eastern Mediterranean Region Office was used (3, 7).

Indicators of the health of individuals

• Total life expectancy at birth (years)

• Neonatal mortality rate (per 1,000 live births)

• Infant mortality rate (per 1,000 live births)

• Under five mortality rate (per 1,000 live births)

• Maternal mortality rate (per 1,000 live births)

Indicators of health services

• Population with access to local health services, total (%)

• The number of nurses per 10,000 people

• The number of physicians per 10,000 people

• The number of pharmacists per 10,000 people

• One year olds immunised with measles vaccine (%)

• One year olds immunised with DTP3 (%)

• One year olds immunised with HBV3 (%)

• One year olds immunised with BCG (%)

• One year olds immunised with OPV3 (%)

• Total expenditure on health (per capita) average US$

• Government expenditure on health (per capita) average US$

• Total expenditure on health of percentage of GDP

Qatar tops the list of EMR ‘healthiest countries’, and Libya is in 5th position (Table 1). On the other hand, Afghanistan and Yemen are at the bottom of the list. To fully understand the rankings, it was essential to find which of the input variables is the most important for measuring the health status of countries (7). We used Pearson correlation test and correlation coefficient of each variable, with the I²-distance value presented in Table 2.

Table 1.

The results of the I²-distance method, I-distance values and rank

Country	I2-distance	Rank
Qatar	50.420	1
The United Arab Emirates	30.923	2
Jordan	28.337	3
Kuwait	27.993	4
Libya	27.253	5
Egypt	26.993	6
Oman	26.168	7
Bahrain	24.775	8
Palestine	24.529	9
Saudi Arabia	23.952	10
Lebanon	23.064	11
Tunisia	22.571	12
Syria	21.377	13
Iran	19.108	14
Morocco	16.922	15
Sudan	14.674	16
Djibouti	10.382	17
Pakistan	8.733	18
Iraq	7.068	19
Afghanistan	4.260	20
Yemen	3.291	21

Table 2.

The correlation between the I²-distance and input variables

	r
The number of nurses	0.891**
Under five mortality rate	0.819**
Infant mortality rate	0.811**
Total life expectancy at birth	0.797**
Neonatal mortality rate	0.794**
Total expenditure on health	0.779**
Government expenditure on health	0.762**
One year olds immunised with OPV3	0.705**
One year olds immunised with measles vaccine	0.663**
One year olds immunised with DTP3	0.654**
The number of physicians	0.615**
One year olds immunised with BCG	0.601**
The number of pharmacists	0.578**
The number of dentists	0.534*
Population with access to local health services	0.441*
Maternal mortality rate	0.335
One year old immunised with HBV3	0.130
Total expenditure on health of percentage of GDP	0.05

^**p <.01.

^*p <.05.

The most significant variable for determining the health status of a country is its number of nurses. Various papers have already elaborated upon the number of nurses as being a key factor for a country's health (8). This is precisely one of the key reasons why Qatar was able to take the first rank as it has the largest number of nurses (73.8 per 10,000 people). Following Qatar is Libya with the second largest number of nurses (54 per 10,000 people). Thus, it is crucial for Libya to maintain such a high number of medical staff.

The mortality rate for children under five is the second most significant variable. Libya has a much higher mortality rate than the two ‘healthiest’ countries, Qatar and the United Arab Emirates. We must point out that mortality rates for children are three of the top five most significant health indicators. Thus, child health service is essential and it must be improved (9).

Conclusion

The health system performance of EMR countries by applying the statistical I²-distance method has clearly shown a great disparity. In addition, the I²-distance method has provided information as to which input variables are crucial for determining a country's health system performance. Libya is in a good position to improve the key health indicators elaborated in this paper.