Geographic distribution of need and access to health care in rural population: an ecological study in Iran
© Kiadaliri et al; licensee BioMed Central Ltd. 2011
Received: 3 June 2011
Accepted: 22 September 2011
Published: 22 September 2011
Equity in access to and utilization of health services is a common goal of policy-makers in most countries. The current study aimed to evaluate the distribution of need and access to health care services among Iran's rural population between 2006 and 2009.
Census data on population's characteristics in each province were obtained from the Statistical Centre of Iran and National Organization for civil registration. Data about the Rural Health Houses (RHHs) were obtained from the Ministry of Health. The Health Houses-to-rural population ratio (RHP), crude birth rate (CBR) and crude mortality rate (CMR) in rural population were calculated in order to compare their distribution among the provinces. Lorenz curves of RHHs, CMR and CBR were plotted and their decile ratio, Gini Index and Index of Dissimilarity were calculated. Moreover, Spearman rank-order correlation was used to examine the relation between RHHs and CMR and CBR.
There were substantial differences in RHHs, CMR and CBR across the provinces. CMR and CBR experienced changes toward more equal distributions between 2006 and 2009, while inverse trend was seen for RHHs. Excluding three provinces with markedly changes in data between 2006 and 2009 as outliers, did not change observed trends. Moreover; there was a significant positive relationship between CMR and RHP in 2009 and a significant negative association between CBR and RHP in 2006 and 2009. When three provinces with outliers were excluded, these significant associations were disappeared.
Results showed that there were significant variations in the distribution of RHHs, CMR and CBR across the country. Moreover, the distribution of RHHs did not reflect the needs for health care in terms of CMR and CBR in the study period.
KeywordsEquality Gini Index Index of Dissimilarity Rural Health Houses Iran
Following Alma-Ata declaration on the key role of primary health care (PHC) in achieving health for all and decreasing inequality in health , the Iranian government attempted to develop an extensive network of PHC facilities, especially in rural areas. PHC in Iran's rural areas are mainly provided through the rural health houses (RHHs). RHHs, which are considered as the main component of progressive expansion of PHC coverage, are aimed at reducing the urban-rural gap in Iran's health care delivery system . Following a series of pilot projects in early of 1970s, RHHs were introduced in 1981 .
During past decades, the number of rural health houses has continuously increased in the country. However, it is not just the quantity of health care resources which affect health status of people, but how they are distributed is also important. Inequitable distribution of health services is a major barrier for improving health service delivery for health systems around the world . There is indeed a positive linkage between availability of health care resources and health status of population . For this reason, the distribution of health care is considered as one of the social determinants of health .
In a sense, the geographic distribution of health facilities is considered as a major health policy issue in many countries, both developed and developing. It is believed that the utilization of, and access to, healthcare among individuals should not be affected by the geographical region in which they reside .
Although studies in Iran have examined the effectiveness of rural health houses in improvement of the population's health status  and decreasing the disparities between rural and urban areas , little attention has been paid to the distribution of RHHs within rural areas in the country.
The current study examines availability of RHHs in Iran using inequality measures. This study specifically focuses on the following research questions: How were RHHs, crude mortality rate (CMR) and crude birth rate (CBR) distributed between different provinces in years 2006 and 2009? How has changed the inequality measures between 2006 and 2009? Did the distribution of RHHs reflect CMR and CBR in the rural population of the provinces?
Material and methods
Some main health indicators in Iran
Crude birth rate (per 1000 people)
Crude mortality rate (per 1000 people)
Population with access to improved sanitation (%)
Total expenditure on health of % of GDP
Out-of-pocket expenditure as % of total health expenditure
Physicians per 10,000 population
primary health care units and centres per 10,000 population
Population with access to local health services, total (%)
Total life expectancy at birth (years)
Infant mortality rate (per 1000 live births)
Under five mortality rate (per 1000 live births)
Maternal mortality ratio (per 10000 live births)
Data sources and variables
The census and estimated data on the distribution and characteristics of population at province level were obtained from the Statistical Centre of Iran . The data about the number of total births and mortalities were also obtained from National Organization for Civil Registration . The data on the number of RHHs in the provinces were gathered from the Statistics Centre of Ministry of Health and Medical Education (MOHME). The centre collects data about health facilities and other health indicators from the Medical Universities in the provinces.
In the current study, the number of RHHs per 1000 rural people (RHP) was used as the indicator for availability of health care resources for the rural population in each province. Moreover, two variables including CMR (number of deaths per 1000 rural people) and CBR (number of births per 1000 rural people) were selected to show the community's health needs. CMR have been used in the literature as an estimate of community health need [14–16]. In addition, CBR was used as another community health need indicator in this study since health services for newborns and infants are one of the main components of the services provided by RHH.
To see how the distribution of access and need to health care services has changed over time, the data for years 2006 and 2009 (as latest available data) were gathered. Moreover, this enables us to control for potential measurement bias in the data as each year can used as a control for other year.
Lorenz Curve and Gini index
G: Gini Index
Yi: cumulative share of RHH in the ith province
Xi: cumulative share of population (ranked by RHP) in the ith province
k: total number of provinces
To calculate the decile ratio, the provinces were ranked by RHP. The top 10% from the top ratio is then divided by the 10% of the bottom.
Index of Dissimilarity
pip: ith province's population share
pih: ith province's health variable share
In the current study, the geographic unit of analysis is 30 provinces in Iran. RHP for each province was calculated as the number of RHHs per 1000 rural people. This ratio was used to rank the provinces in drawing the Lorenz curve and calculating the Gini index and decile ratio for access indicator. In case of need indicators, the CBR and CMR were used to rank the provinces.
Inequality measures (including Lorenz curve, Gini, decile ration and dissimilarity index) were used to assess the level of inequality in the distribution of RHHs, CMR and CBR across the provinces.
The spearman rank-order correlation coefficients between RHP, CMR and CBR were calculated to examine if there is any linear relationship between distribution of RHHs and community health needs. Correlation measures have been used in some other studies to evaluate the linear relationship between two variables in examining the inequality in health [19, 22].
To find the potential outliers in data, the box plots of percentage changes in CBR and CMR between 2006 and 2009 were used. The results are reported for total sample and non-outlier sample where outliers were removed from total sample. Moreover, in order to explore changes in CMR and CBR over study period; the median was used due to these outliers in the data.
Population a, RHP b, CMR c and CBR d in provinces of Iran, 2006 and 2009
Sistan & Baluchestan
The median of CMR increased 0.7% from 5.78 in 2006 to 5.82 in 2009. Tehran had the lowest CMR in both 2006 and 2009. Hormozgan and South Khorasan were the provinces with the highest CMR in 2006 and 2009, respectively. There were 16.5- and 8-fold differences between provinces with the highest and the lowest CMR in 2006 and 2009, respectively. 20 out of 30 provinces experienced an increase in CMR between 2006 and 2009.
The median of CBR increased 0.4% over the study period. Tehran had the lowest CBR in both 2006 and 2009. The highest CBR was seen in Sistan & Baluchestan in the same period. There were 3.6- and 3.3-fold differences between the provinces with the highest and the lowest CBR in 2006 and 2009, respectively. 23 out of 30 provinces experienced an increase in CBR between 2006 and 2009.
As provinces of Hormozgan, Semnan and South Khorasan had the outlier values on variables, we reported the total sample results and results after excluding these provinces separately. As there were no significant changes in general results and interpretation, the results of total sample will be discussed in following sections.
Inequality indicators of the distribution of RHHs, Deaths and Births in rural area of Iran
Index of Dissimilarity
Index of Dissimilarity
Outliers excluding sample b
Correlation between RHP, CMR and CBR in Iran in 2006 and 2009
- 0.15 (0.42) d
- 0.34 (0.06)
- 0.41 (0.03)
Outliers excluding sample e
- 0.06 (0.77)
- 0.24 (0.24)
- 0.31 (0.11)
The current study assessed access to and need for health services in rural areas of Iran for the years 2006 and 2009. The study showed that the distribution of RHHs is not based on need in terms of CMR and CBR across the provinces in Iran. Moreover, the results indicated significant regional variations in both access and need indicators across the country. To achieve an equal distribution of RHHs across the country, about one out of 10 RHHs should be re-allocated from the relatively over-served provinces to the relatively under-served ones.
The results showed that RHHs are not distributed based on CMR and CBR in the provinces. One possible explanation for these results is maybe that policy makers consider some other indicators than those used in this study (CMR and CBR) for the distribution of RHHs across the country (for example; having a minimum number of RHHs for each province or socio-economic situation of the provinces).
Although, access to RHHs (measured by RHP) improved between 2006 and 2009, the needs for health services (measured by CMR and CBR) increased at the same time. In terms of inequality measures, there were changes in need indicators toward more equal distributions, while inverse trend was seen for the access indicator.
The degree of inequality in the distribution of RHH and the CBR were rather stable during the study period, while it significantly changed for CMR in total sample. However, when we excluded the outliers, then no significant changes in inequality indicators were observed. Generally, there was no strong association between the distribution of RHH and CMR and CBR in rural areas of Iran.
Previous studies mostly evaluated the rural-urban differences in distribution of health care resources and outcomes, not differences within the rural areas . Among the few studies within rural areas, Theodorakis et al  reported an uneven distribution of primary care physicians in remote areas of Greece and Albania. Another study in the USA in 2005 indicated unequal distribution of physician among rural areas .
The results of this study however should be interpreted in light of some limitations. Firstly, the data are gathered from census data which are subject to incompleteness and measurement errors and these may bias the results. For example, undercounting, misreporting and delayed registration are some well known problems of census and mortality data in Iran . These possibly explain the outliners in our data. Secondly, the data used in the study are aggregated data at the province level. It implies that the variation within the provinces could be higher than the variation between the provinces. Hence, these results are not necessarily applicable to smaller geographic units such as counties or cities. Thirdly, need variables used in this study were crude measures and sex and age differences in these measures were not taken into account due to the lack of data. Fourthly, our results are limited to geographical comparisons; without knowing who actually use the services provided by RHHs, one cannot know their distribution according to other dimensions of the population, such as income, education and etc.
This study showed that the distribution of RHHs does not reflect the needs for health care in terms of CMR and CBR. There were significant variations in the distribution of RHHs, CMR and CBR across the country. While the inequality in access increased during the study period, the inequality in need for health care decreased at the same time in the rural areas. It is suggested that the results of this study be considered in making decisions on rural health care services by policy-makers in Iran.
It is acknowledged that the current study was supported by the School of Management and Medical Informatics, Tehran University of Medical Sciences.
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