Skip to main content

Mapping of national population-based surveys for better reporting of health-related indicators in the Eastern Mediterranean Region

Abstract

Background

Population-based surveys are the main data source to generate health-related indicators required to monitor progress toward national, regional and global goals effectively. Although the Eastern Mediterranean Region of World Health Organization (WHO) member states conduct many population-based surveys, they are not led regularly and fail to provide relevant indicators appropriately. Therefore, this study aims two-fold: to map out population-based surveys to be conducted data for the health-related indicators in the Region and propose a timetable for conducting national population-based surveys in the Region.

Methods

The study was conducted in six phases: 1) Selecting survey-based indicators; 2) Extracting and comparing relevant survey modules; 3) Identifying sources of data for the indicators; 4) Assessing countries' status in reporting on core health indicators; 5) Review and confirmation of the results by the experts.

Results

Population-based surveys are the sources of data for 44 (65%) out of 68 regional core health indicators and two (18%) out of 11 health-related Sustainable Development Goals (SDG) 3 indicators. The Health Examination Survey (HES) could cover 65% of the survey-based indicators. A total of 91% of survey-based indicators are obtained by a combination of HES, Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS) and Global School-based Student Health Survey (GSHS).

Conclusion

In order to effectively report health-related indicators, HES, DHS/MICS and GSHS are considered essential in national survey timetables. Each country needs to devise and implement a plan for population-based surveys by considering factors such as national health priorities, financial and human capacities, and previous experiences.

Peer Review reports

Background

Reliable and timely information is essential for monitoring progress toward national, regional and international health-related goals and developing and evaluating health-related policies, including identifying national health priorities, needs and effective resource allocation [1,2,3,4,5,6]. In order to support the Member States in effectively monitoring the health situation, the WHO Regional Office for Eastern Mediterranean worked with the Member States of the Region since 2012 to develop a framework for health information systems (HIS) and 68 health core indicators [7]. These core indicators focus on three components: health determinants and risks, health status, morbidity and cause-specific mortality, and health system response. The HIS framework was endorsed during the 61st session of the WHO Regional Committee for the Eastern Mediterranean in 2014. Since then, WHO reports annually on the core indicators and verifies data with the Member States. The HIS framework also covers indicators for monitoring the progress toward Universal Health Coverage (UHC) and health-related Sustainable Development Goals (SDG) [5, 8]. Data to generate the regional core health indicators come from two main sources: registration systems (i.e. surveillance and administrative data) and institution-based or population-based surveys [9].

The Eastern Mediterranean Region (EMR) is a heterogeneous region not only in geopolitical and social context, ethnicity and languages spoken but also in socioeconomic and health profiles. For example there is more than 24 years difference in life expectancies between Somalia (56.5 years) and Kuwait (81.0 years) [10]. Financial resources allocated to the health systems also vary broadly across countries, with the lowest and highest recorded values for per capita current health expenditure (CHE) of 50 USD in Afghanistan and 1817 USD in the United Arab Emirates in 2018 [10].

Moreover, conflicts and terrorism have caused massive humanitarian crises in the Region and disrupted health systems' structures and functions, mostly affecting Afghanistan, Iraq, Libya, Palestine, Somalia, Syria, and Yemen [11, 12].

As a result, there are huge differences between health systems' performances and capacities among the countries. While some countries have well-established health systems and can mobilize national financial and technical resources to strengthen their HIS, others rely only on international funds and technical support [13, 14]. Countries of the Region can be categorized into three groups according to World Bank country classifications by income level [15]. Group 1, or high-income countries, consists of countries where socioeconomic development has progressed considerably over the past decades. These countries are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates. Group 2, or upper-middle and lower-middle income countries, consists of Egypt, the Islamic Republic of Iran, Iraq, Jordan, Lebanon, Libya, Morocco, occupied Palestinian territory, the Syrian Arab Republic, and Tunisia. Although these countries have developed infrastructure for HIS in recent years, they might face resource constraints. Group 3 or low-income countries, including Afghanistan, Djibouti, Pakistan, Somalia, Sudan and Yemen, face major constraints in improving their health information systems due to limited resources, political instability, and other complex development challenges.

Many national population-based and institution-based surveys have already conducted by the Region’s countries (Table 1) but the health-related indicators that can be obtained from the surveys were not reported. An assessment conducted by Alwan et al. in 2016 of the countries' capacity to report on core indicators in the Region showed that due to lack of a national comprehensive plan, the population-based surveys failed to appropriately provide relevant indicators [9].

Table 1 National population-based and institution-based surveys conducted by the Eastern Mediterranean Region countries and the year of conducting the last survey

Therefore, the aim of this study is to identify health indicators that can be effectively obtained from population-based surveys and provide guidance on the surveys needed to generate data for these indicators.

Methods

Study design

Previous experiences in the Region especially the experiences of Iran in designing and implementing the health observatory and survey timetable [16, 17] was used as a guide to design this study.

The study was designed as a multistage research process in an exploratory approach to identify the survey-based core health indicators for monitoring the health situation and health system performance in the region, as well as health-related Sustainable Development Goals (SDGs) and their preferred sources. We tried to develop and propose a methodology that can be applicable for other indicators and in other Regions and countries.

Data sources

Primary data sources

The "framework for health information systems and core indicators for monitoring health situation and health system performance" and the SDGs were used as primary data sources.

Questionnaires and survey websites

Data from questionnaires and websites of eight surveys were collected to identify survey modules and previously conducted surveys in each regional country.

WHO reports

The WHO 2016 annual report on regional core health indicators and the WHO regional health observatory were used as additional sources of data.

Data analysis and synthesis

Survey-based indicators obtained from the primary data sources and survey modules obtained from questionnaires and survey websites were used as sources of data. Each indicator that could be obtained from population-based surveys was identified along with the appropriate module and the corresponding survey (s). Indicators that were not reported in the 2016 WHO report were identified for each country.

Dialogue

Expert opinions were obtained and reviewed during a consultative meeting. A timetable for conducting population-based surveys was proposed and finalized based on their recommendations.

The study was conducted in five phases:

  1. 1)

    Selecting the survey-based indicators: In order to define the scope of the project, the Regional “framework for health information systems and core indicators for monitoring health situation and health system performance” report [7] and health-related Sustainable Development Goals (SDG) 3 [5] were reviewed by the research team and all their indicators were extracted.

  2. 2)

    A list of 79 indicators containing 68 regional core health indicators and 11 SDG 3 indicators that were not in the regional core indicators list were prepared. Then for each indicator, the preferred source of data was specified. The regional core health indicators and SDG 3 indicators were then categorized into two groups based on their preferred sources of data. 1) indicators that can be obtained from population-based surveys; and 2) indicators that cannot be obtained from population-based surveys, which means that they either can be obtained from administrative data such as death registries or institution-based surveys such as Service Availability and Readiness Assessment (SARA).

  3. 3)

    Extracting and comparing the survey modules: In order to identify the surveys that can provide data for the selected indicators and the overlaps between the surveys, relevant modules from main health-related population-based surveys were extracted and compared using the surveys questionnaires as the sources of data. The following eight surveys were assessed: 1) Tunisian Health Examination Survey (HES); 2) Multiple Indicator Cluster Survey (MICS); 3) Demographic and Health Survey (DHS); 4) STEPwise approach to Surveillance (STEPS) survey; 5) Household Expenditure Survey; 6) Global Adult Tobacco Survey (GATS); 7) Global Youth Tobacco Survey (GYTS); and 8) Global School-Based Student Health Survey (GSHS) [18,19,20,21,22,23,24]. In addition, we explored the websites for these surveys in order to identify the surveys that were previously conducted in each Regional country and therefore, the countries that have experiences with them (Table 1).

  4. 4)

    Identifying the sources for the indicators: Using data gathered in the previous phases, for each indicator that can be obtained from population-based surveys, the appropriate module and the corresponding survey(s) were identified.

  5. 5)

    Assessing countries status in reporting on core indicators: By reviewing the WHO 2016 annual report on regional core health indicators and data obtained from the WHO regional health observatory, the missing core indicators in the 2016 report for each country were identified.

  6. 6)

    Review of results by experts: The results were presented to and reviewed by the experts during a consultative meeting in Cairo, Egypt, 11–12 December 2017. During the meeting, the findings were presented to the participants and then their opinions were taken in focused group discussions. Based on their opinions a time table for conducting population-based survey was proposed and finalized. The participants were academics with related expertise as well as the members from appropriate bodies in the ministries of health from regional countries. The meeting was moderated by the department of Information, Evidence and Research, WHO Regional Office.

Results

Identifying indicators

The review of indicators showed that 44 (65%) out of 68 Regional core health indicators and two (18%) out of 11 SDG 3 indicators not covered in the regional core health indicators list, can be obtained from population-based surveys (Table 2). The indicator "Percentage of individuals who slept under an insecticide threatened bednet the previous night" is only applicable to countries with high risk of local transmission of malaria and is provided by the technical unit in the WHO Regional Office, so it was not included in Table 2. Although data to generate mortality indicators can be obtained from DHS or MICS, it is important to emphasize that the preferred source of data for mortality rates such as neonatal, infant, under-five and maternal mortality is death registry information and surveys are considered as the alternate source [25].

Table 2 Survey-based regional core health and SDG 3 indicators by survey modules and the survey(s) that contains the module

Mapping surveys

As seen in Table 2, these 46 survey-based indicators then were sub-categorized according to the survey modules they can be obtained from and the survey(s) that contains the module(s). The HES could generate data to cover most indicators including all the indicators that can be obtained from STEPS, Household Expenditure Survey and GATS. Thirty (65%) out of 46 indicators can be covered by HES whereas 24 (52%) out of 46 indicators can be covered by DHS/MICS which has 16 overlaps with HES. Six (13%) out of 46 indicators can be covered by STEPS; but all can also be obtained from HES. Four (9%) indicators can be covered by GSHS. Another four (9%) indicators can be covered by Household Expenditure Survey; and all these indicators can also be covered by HES. Two (4%) indicators can be covered by surveys targeting high risk populations for HIV/AIDS. Another two (4%) indicators can be covered by Mental Health Survey although one of them could somehow be covered by HES; and another indicator (Hepatitis B incidence per 100,000 population) requires a serology survey for Hepatitis B.

Furthermore, the review of the 2016 annual report on regional core health indicators for each country is summarized in Fig. 1. Results show that there are relatively more indicators reported that use data from routine HIS than survey-based indicators. Finally, during the expert consultative meeting, the following key issues were discussed in separate working groups: 1) review and validated the main findings about the last surveys that were conducted in the countries (Table 1), and the indicators and their sources (Table 2), and 2) recommended a list of the population-based surveys for better reporting of core health indicators and SDG3 indicators, as well as the ideal inter-survey period.

Fig. 1
figure 1

Percentage of regional core health indicators reported by member states for the 2016 report based on the sources of the indicators

During the expert consultative meeting, the following key issues were discussed in separate working groups: 1) review and validated the main findings about the last surveys that was conducted in the countries (Table 1), and the indicators and their sources (Table 2), 2) recommended list of the population-based surveys for better reporting of core health indicators and SDG3 indicators, as well as the ideal inter-survey period.

Discussion

Our study showed that 44 (65%) out of 68 of the regional core health indicators are obtainable using the data from population-based surveys and the rest need to be gathered by the registration data and routine system. It must be noted that the line between these two groups of indicators is somehow blurry and some indicators can be generated using data from both routine and population-based survey sources. For these indicators, the routine system may be preferred over surveys [26, 27]. However, since many countries lack a robust HIS to gather timely and accurate registration data [28], surveys are usually the default sources of data.

Our findings showed that Health Examination Survey (HES) could cover 65% of the survey-based indicators, and could cover all the indicators that can be obtained from STEPS, Household Expenditure Survey and GATS. Therefore, it is recommended that HES be considered as the main survey in national survey timetables. Further analysis showed that 42 (91%) out of 46 survey-based indicators could be covered by a combination of three surveys (HES, DHS/MICS, and GSHS).

The four indicators that are not covered by these three surveys are as follow:

  • 1 & 2. "Estimated number of new HIV infections" and "Percentage of key populations at higher risk (people who inject drugs, sex workers, men who have sex with men) who have received an HIV test in the past 12 months and know their results": In order to obtain these indicators, a survey of high-risk populations is required. Although both indicators could be covered by a single survey.

  • 3. "Coverage of services for severe mental health disorders": Although the HES questionnaire contains questions about major depression, the denominator for this indicator requires mental health surveys in order to obtain the prevalence of severe mental health disorders.

  • 4. "Hepatitis B incidence per 100,000 population" requires a serology test, which can be added to the HES laboratory test module.

One of the popular surveys in the regional countries is DHS/MICS [29, 30]. Since there are many overlaps between HES and DHS/MICS, conducting both of these surveys in a country is not ideal. One of the most appropriate solutions would be to add relevant modules from DHS/MICS to HES. The following indicators can be generated using data from DHS/MICS as they are not covered by HES:

  1. 1.

    Children under-5 with diarrhea receiving oral rehydration therapy: a question to collect this information can be added to HES individual questionnaire.

  2. 2.

    Exclusive breastfeeding rate 0–5 months of age: relevant questions can be added to the HES individual questionnaire.

  3. 3.

    Maternal mortality ratio: the denominator is already covered by HES, but the question to collect data for the numerator can be added to the questionnaire.

  4. 4.

    Anthropometry in children under 5 (to obtain stunting, wasting, overweighting, and obesity indicators): since adult anthropometry is already part of the HES module, if under-5 anthropometry could be added to the survey, indicators can also be obtained.

These recommendations can be considered when planning to update HES modules.

Although conducting a single omnibus survey such as HES instead of multiple single-purpose surveys has many benefits, such as saving resources and enabling countries to conduct multiple thematic analyses using different variables, there are some issues of concern: 1) Since it takes more time to complete an omnibus survey questionnaire, this might lead to errors and low response rates [31, 32]; 2) Larger surveys require much better planning and logistics before and during the surveys [33]; 3) the donors might not be interested in sponsoring an omnibus survey. To address these challenges, the following solutions are suggested: 1) using a multistage data gathering approach and collecting data over a period of at least two days; 2) WHO could work closely with countries to provide needed technical support to effectively implement an omnibus survey; 3) If the national survey plan or timetable is developed by consultation with development partners and other national stakeholders, then it can be used to the advocate the donors to fund the survey. It must be noted that a well-functioning national HIS is one of the main prerequisites for conducting surveys [34, 35].

Based on the data obtained in the study especially the experts’ opinions, a suggested timetable was proposed for conducting national population-based surveys for the countries in the Region. Three principles were considered when designing the timetable: 1) Since most indicators can be covered by HES, it was selected as the hub of the timetable; 2) According to metadata, most indicators especially those that are generated using data from population-based surveys have to be updated every 3–5 years, therefore, it was recommended that the same survey be conducted every five years; and 3) Considering the difficulties in securing the financial and resources to conduct surveys mentioned during group discussions, only one national population-based survey to be conducted in each year. The finalized timetable is presented in Table 3. The timetable contains both the surveys and the intervals between them. We tried to keep the minimum surveys in the timetable that can generate nearly all required indicators.

Table 3 Presentation of the suggested 10-year timetable for conducting national population-based surveys and the intervals between them to obtain the core indicators in priority order

This survey timetable can be implemented in the country in the form of a national charter, which could contain the following: 1) the main steward(s) for conducting each population-based survey in the country; 2) the estimated amount of budget, budget source(s) and how to secure the budget for each survey; 3) the plan for enhancing the secretariat(s) capacity to reliably report on the core health and SDG 3 indicators as well as the public availability survey data. Since many surveys have already been conducted in the countries but the results were not reported to the WHO [9], and 4) as several surveys that are conducted in the Region are not easily accessible or lack clear conditions for access, the charter must also contain a data sharing policy to enhance public access of the data. Further, implementing population-based surveys in the Region at regular intervals can support the validation of some countries' estimates, such as for the global burden of disease when data are calculated and validated across neighboring countries [14, 25, 36].

The high-income countries in the Region that generally have a good electronic HIS, and if needed, they can secure funds to conduct the surveys and implement their own timetable for the surveys. While middle-income countries might need technical and financial support from WHO and other development partners to implement the survey timetable. The low-income countries in the Region mostly lack a robust HIS and may rely on international funds to conduct population-based surveys. This might limit their ability to implement their own timetable, thereby making it crucial to work closely with the WHO in designing and implementing their timetable. However, our findings showed that there were no major differences between high-income and middle and low-income countries in reporting on the core health indicators (Fig. 1).

Also it must be note that as the Region is experiencing some of the worst humanitarian crises [37,38,39,40], these crises, along with the political instability and insecurity have affected the coordination, planning and implementation of major data collection activities in the countries.

Most important of all, implementing a plan is far more complicated than designing it. The timetable presented here is just a recommendation, and each country should develop its own tailored timetable. This timetable can be developed and adjusted based on the surveys already conducted in a country in order to provide a good trajectory for the course of surveys and indicators to be generated in the future. The experiences of countries in the Region such as Iran, Sudan, and Qatar that have already developed national survey plans, shows that formal endorsement of the plans by the highest executive authority (i.e. the Minister of Health) can ensure commitment to the national plans [16, 41]. National survey timetables and relevant survey modules should also be reviewed and updated in line with changes or updates in the global, regional or national public health priorities and their monitoring indicators.

Conclusions

Given that a vast majority (91%) of survey-based indicators can be obtained through the HES, DHS/MICS, and GSHS, these surveys are essential components of national survey plans for reporting health-related indicators in the EMR. Moreover, modifying survey questionnaires can lead to the collection of additional indicators. It is critical to establish an optimal schedule for conducting population-based surveys and to use it as a framework for national planning.

Limitations

This study mainly focused on population-based surveys that can generate most indicators. However, it must be emphasized that several other factors must be considered when designing and implementing a national survey timetable, such as national development priorities, technical expertise and available resources.

Availability of data and materials

The summary report on the expert consultative meeting held in Cairo, Egypt, 11–12 December 2017 is available from: https://apps.who.int/iris/handle/10665/260371.

The datasets on regional core health indicators reported by countries (Fig. 1) are available from the WHO Regional Health Observatory (https://rho.emro.who.int/). All analytical data and related methods are available from the corresponding author upon request.

Abbreviations

DHS:

Demographic and Health Survey

EMR:

Eastern Mediterranean Region

GATS:

Global Adult Tobacco Survey

GSHS:

Global School-based Student Health Survey

GYTS:

Global Youth Tobacco Survey

HES:

Health Examination Survey

HIS:

Health Information System

MICS:

Multiple Indicator Cluster Survey

SARA:

Service Availability and Readiness Assessment

SDG:

Sustainable Development Goal

STEPS:

STEPwise approach to surveillance

UHC:

Universal Health Coverage

WHO:

World Health Organization

References

  1. AbouZahr C, Boerma T. Health information systems: the foundations of public health. Bull World Health Organ. 2005;83(8):578–83.

    PubMed  PubMed Central  Google Scholar 

  2. Hunink MM, Weinstein MC, Wittenberg E, Drummond MF, Pliskin JS, Wong JB, et al. Decision making in health and medicine: integrating evidence and values. Cambridge: University Press; 2014.

    Book  Google Scholar 

  3. Hogan DR, Stevens GA, Hosseinpoor AR, Boerma TJTLGH. Monitoring universal health coverage within the Sustainable Development Goals: development and baseline data for an index of essential health services. Lancet Glob Health. 2018;6(2):e152–68.

    Article  PubMed  Google Scholar 

  4. Fullman N, Lozano R. Towards a meaningful measure of universal health coverage for the next billion. Lancet Glob Health. 2018;6(2):e122–3.

    Article  PubMed  Google Scholar 

  5. Organization WH. World health statistics 2019: monitoring health for the SDGs, sustainable development goals. 2019.

    Google Scholar 

  6. Tilahun B, Teklu A, Mancuso A, Endehabtu BF, Gashu KD, Mekonnen ZA, et al. Using health data for decision-making at each level of the health system to achieve universal health coverage in Ethiopia: the case of an immunization programme in a low-resource setting. Health Res Policy. 2021;19(2):1–8.

    Google Scholar 

  7. World Health Organization. Eastern Mediterranean Region: Framework for health information systems and core indicators for monitoring health situation and health system performance 2016. World Health Organization. Regional Office for the Eastern Mediterranean; 2016.

  8. Nam UV. Transforming our world: The 2030 agenda for sustainable development. 2015.

    Google Scholar 

  9. Alwan A, Ali M, Aly E, Badr A, Doctor H, Mandil A, et al. Strengthening national health information systems: challenges and response. East Mediterr Health J. 2016;22(11):840.

    Article  Google Scholar 

  10. World Health Organization. Monitoring health and health system performance in the Eastern Mediterranean Region: core indicators and indicators on the health-related Sustainable Development Goals 2019. World Health Organization. Regional Office for the Eastern Mediterranean; 2020.

    Google Scholar 

  11. Mokdad AH, Forouzanfar MH, Daoud F, El Bcheraoui C, Moradi-Lakeh M, Khalil I, et al. Health in times of uncertainty in the eastern Mediterranean region, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet Glob Health. 2016;4(10):e704–13.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Al-Mandhari A, Ardalan A, Mataria A, Rifaey T, Hajjeh R. Refugee and Migrant Health Strategy for the Eastern Mediterranean Region. East Mediterr Health J. 2021;27(12):1129–31.

    Article  PubMed  Google Scholar 

  13. Sahay S, Rashidian A, Doctor HV. Challenges and opportunities of using DHIS2 to strengthen health information systems in the Eastern Mediterranean Region: A regional approach. Electron J Info Syst Dev Ctries. 2020;86(1):e12108.

    Google Scholar 

  14. Doctor HV, Mabry R, Kabudula CW, Rashidian A, Hajjeh R, Hussain SJ, et al. Progress on the health-related Sustainable Development Goals in Eastern Mediterranean Region countries: getting back on track in the time of COVID-19. East Mediterr Health J. 2021;27(6):530–4.

    Article  Google Scholar 

  15. New World Bank country classifications by income level: 2022–2023 2022 [Available from: https://blogs.worldbank.org/opendata/new-world-bank-country-classifications-income-level-2022-2023] Accessed 20 July 2022.

  16. Rashidian A, Damari B, Larijani B, Moghadda AV, Alikhani S, Shadpour K, et al. Health observatories in Iran. Iran J Public Health. 2013;42(Supple1):84.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Damari B, Heidari A, Rashidian A, Vosoogh Moghaddam A, Khosravi A, Alikhani S. Designing a health observatory system for the Islamic Republic of Iran. Payesh (Health Monitor). 2020;19(5):499–509.

    Google Scholar 

  18. La SO. Santé Des Tunisiens: Résultats de L’enquête" Tunisian Health Examination Survey-2016. Février: Publication de l’Institut National de la Santé; 2019.

    Google Scholar 

  19. Khan S, Hancioglu A. Multiple indicator cluster surveys: delivering robust data on children and women across the globe. Stud Fam Plann. 2019;50(3):279–86.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Ties Boerma J, Sommerfelt AE. Demographic and health surveys (DHS: contributions and limitations. World Health Stat Q. 1993;4:222–6.

    Google Scholar 

  21. Organization WH, The WHO. STEPwise approach to surveillance. Regional Office for Europe: World Health Organization; 2021.

    Google Scholar 

  22. Abdalmaleki E, Abdi Z, Gohrimehr M, Alvandi R, Riazi Isfahani S, Ahmadnezhad E. Multiple Indicator Clustar Survey and Demographic and Health Survey in the Eastern Mediterranean Region: What Is the Iran’s Situation in Terms of Implementation? Iran J Epidemiol. 2020;16(2):108–21.

    Google Scholar 

  23. Abdalmaleki E, Abdi Z, Isfahani SR, Safarpoor S, Haghdoost B, Sazgarnejad S, et al. Global school-based student health survey: country profiles and survey results in the eastern Mediterranean region countries. BMC Public Health. 2022;22(1):1–11.

    Article  Google Scholar 

  24. Tarasenko Y, Ciobanu A, Fayokun R, Lebedeva E, Commar A, Mauer-Stender K. Electronic cigarette use among adolescents in 17 European study sites: findings from the Global Youth Tobacco Survey. Eur J Pub Health. 2022;32(1):126–32.

    Article  Google Scholar 

  25. Wang H, Naghavi M, Allen C, Barber RM, Bhutta ZA, Carter A, et al. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1459–544.

    Article  Google Scholar 

  26. Lundin R, Mariani I, Peven K, Day LT, Lazzerini M. Quality of routine health facility data used for newborn indicators in low-and middle-income countries: A systematic review. J Global Health. 2022;12:04019.

  27. Shama AT, Roba HS, Abaerei AA, Gebremeskel TG, Baraki N. Assessment of quality of routine health information system data and associated factors among departments in public health facilities of Harari region, Ethiopia. BMC Med Inform Decis Mak. 2021;21(1):1–12.

    Article  Google Scholar 

  28. World Health Organization. A regional strategy for integrated disease surveillance–overcoming data fragmentation in the Eastern Mediterranean Region. World Health Organization. Regional Office for the Eastern Mediterranean; 2021.

    Google Scholar 

  29. Al-Jawaldeh A, Abul-Fadl A, Farghaly NF. Enacting the Code by effective national laws influence trends in exclusive breastfeeding: An analytical study from the Eastern Mediterranean Region. Indian J Child Health. 2021;8(1):12–9.

    Article  Google Scholar 

  30. Wogderes B, Shibre G, Zegeye B. Inequalities in childhood stunting: evidence from Sudan multiple indicator cluster surveys (2010–2014). BMC Public Health. 2022;22(1):1–14.

    Article  Google Scholar 

  31. Ansah EK, Powell-Jackson T. Can we trust measures of healthcare utilization from household surveys? BMC Public Health. 2013;13(1):853.

    Article  PubMed  PubMed Central  Google Scholar 

  32. De Heer W, De Leeuw E. Trends in household survey nonresponse: A longitudinal and international comparison. Survey nonresponse. 2002;41:41–54.

  33. O’Donnell O, van Doorslaer E, Wagstaff A, Lindelow M. Analyzing health equity using household survey data: A guide to techniques and their implementation. Washington, D.C: The World Bank; 2008.

  34. Sligo J, Gauld R, Roberts V, Villa L. A literature review for large-scale health information system project planning, implementation and evaluation. Int J Med Informatics. 2017;97:86–97.

    Article  Google Scholar 

  35. Sauerborn R. Introduction (What is wrong with current health information systems?) In: Lippeveld T, Sauerborn R, Bodart C. Design and Implementation of Health Information Systems. Geneva: World Health Organization. 2000. p. 3–5.

  36. Weyer K, Dennis Falzon D, Jaramillo E, Zignol M, Mirzayev F, Raviglione M. Drug-resistant tuberculosis: what is the situation, what are the needs to roll it back. AMR control. 2017.

  37. Taleb ZB, Bahelah R, Fouad FM, Coutts A, Wilcox M, Maziak W. Syria: health in a country undergoing tragic transition. Int J Public Health. 2015;60(1):63–72.

    Article  Google Scholar 

  38. Devakumar D, Birch M, Rubenstein LS, Osrin D, Sondorp E, Wells JC. Child health in Syria: recognising the lasting effects of warfare on health. Confl Heal. 2015;9(1):34.

    Article  Google Scholar 

  39. Heisler M, Baker E, McKay D. Attacks on health care in Syria—normalizing violations of medical neutrality? N Engl J Med. 2015;373(26):2489–91.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Burki T. Libya’s health crisis looks set to worsen. Lancet. 2016;387(10026):1363.

    Article  Google Scholar 

  41. Abdi Z, Majdzadeh R, Ahmadnezhad E. Developing a framework for the monitoring and evaluation of the Health Transformation Plan in the Islamic Republic of Iran: lessons learned. Eastern Mediterr Health J. 2019;25(6):394–405.

Download references

Acknowledgements

This study was technically and financially supported by the WHO Regional Office for the Eastern Mediterranean. The authors also would like to thank Dr. Roghayeh Khabiri, Assistant Professor, Tabriz University of Medical Sciences, Iran, for providing valuable input during the study.

Funding

This study was technically and financially supported by the WHO Regional Office for the Eastern Mediterranean.

Author information

Authors and Affiliations

Authors

Contributions

RM and AR designed and supervised the study and helped analyze and interpret the data. SR, HD, EAA, and HMB helped gather and analyze the data. SR conducted the literature review and wrote the original draft of the manuscript. All authors corrected and approved the final manuscript.

Corresponding author

Correspondence to Reza Majdzadeh.

Ethics declarations

Ethics approval and consent to participate

The study protocols were approved by World Health Organization, Regional Office for the Eastern Mediterranean. All experiments were performed in accordance with relevant guidelines and regulations. Informed consent of the participants in the consultative meeting was obtained before the meeting.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Riazi-Isfahani, S., Victor Doctor, H., Aly, E.A. et al. Mapping of national population-based surveys for better reporting of health-related indicators in the Eastern Mediterranean Region. BMC Public Health 23, 563 (2023). https://doi.org/10.1186/s12889-023-15330-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-023-15330-6

Keywords