THE 2022 UPDATE OF THE HEALTH EQUITY AND FINANCIAL PROTECTION INDICATORS DATABASE: AN OVERVIEW DISCUSSION PAPER DECEMBER 2022 Sven Neelsen Patrick Eozenou Marc Smitz Ruobing Wang / THE 2022 UPDATE OF THE HEALTH EQUITY AND FINANCIAL PROTECTION INDICATORS DATABASE: AN OVERVIEW Sven Neelsen Patrick Eozenou Marc Smitz Ruobing Wang December 2022 Health, Nutrition, and Population (HNP) Discussion Paper This series is produced by the Health, Nutrition, and Population Global Practice of the World Bank. The papers in this series aim to provide a vehicle for publishing preliminary results on HNP topics to encourage discussion and debate. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the World Bank, to its affiliated organizations, or to members of its Board of Executive Directors or to the countries they represent. 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Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street, NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. © 2022 The International Bank for Reconstruction and Development / The World Bank 1818 H Street, NW, Washington, DC 20433 All rights reserved. ii Health, Nutrition, and Population (HNP) Discussion Paper The 2022 Update of the Health Equity and Financial Protection Indicators Database: An Overview Sven Neelsen,a* Patrick Eozenou,a Marc Smitz,a Ruobing Wangb a Health, Nutrition, and Population Global Practice, The World Bank, Washington, DC, United States b Data Whale LLC, Houston, TX, United States Abstract: This paper outlines changes that have been made for the third version of the World Bank’s Health Equity and Financial Protection Indicators (HEFPI) database launched in 2022. Across all indicators, subpopulation breakdowns by urban and rural place of residence and subnational region were added. On the financial protection side, the number of indicators further expanded to 31, reflecting a broadening of the definition of medical impoverishment from being limited to those pushed below the poverty line by medical spending to also include those already under the poverty line who incur any medical spending—that is, those “further impoverished” by medical spending. The additional financial protection indicators also include indicators that show the intersection of catastrophic and impoverishing health spending, that is, identify the populations exposed to both types of financial hardship simultaneously. The health equity side of the database now includes 19,820 country-level data points from 1,318 surveys across 35 service coverage and 38 health outcome indicators. An upgraded data visualization portal was launched alongside the new dataset. Keywords: Health equity, out-of-pocket health expenditures, financial protection, sustainable development goals, universal health coverage Disclaimer: The findings, interpretations, and conclusions expressed in the paper are entirely those of the authors, and do not represent the views of the World Bank, its Executive Directors, or the countries they represent. Correspondence Details: Sven Neelsen, 1818 H Street, NW, Washington, DC, United States, +1-202-597-8006; sneelsen@worldbank.org. iii Table of Contents ACKNOWLEDGMENTS .............................................................................................. VI PART I – INTRODUCTION ........................................................................................... 7 PART II – NEW INDICATORS AND DATA POINTS................................................ 9 NEW DIMENSIONS OF INEQUALITY AND CHANGES IN COMPUTATION OF THE CONCENTRATION INDEX ................................................................................................... 9 CHANGES TO THE FINANCIAL PROTECTION SIDE OF THE DATABASE ................................ 10 HEALTH EQUITY INDICATORS ........................................................................................ 13 PART III – NEW VISUALIZATIONS IN THE HEFPI PORTAL ........................... 18 PART IV – CONCLUSION ........................................................................................... 20 ACCESSING AND CITING THE DATABASE.......................................................... 21 ACCESSING THE DATABASE ............................................................................................ 21 CITING THE DATABASE ................................................................................................... 21 REFERENCES................................................................................................................ 22 APPENDIX ...................................................................................................................... 23 iv ACKNOWLEDGMENTS We gratefully acknowledge funding from the government of Japan through the World Bank Group–administered Policy and Human Resources Development Fund (PHRD). We are grateful to Aline Weng, Haozheyi Guan, Xian Zhang, Sifan Liu, Yuqi Liao, Yixin Luo, Zetianyu Wang, Ke Zeng, Ning Jiang, Zhuohang Li, Jianing Wu, and Yining Sun, who assisted in the processing of the household survey microdata. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors, and do not necessarily represent the views of the World Bank, its Executive Directors, or the governments of the countries they represent. The authors are grateful to the World Bank for publishing this report as an HNP Discussion Paper. vi PART I – INTRODUCTION Since its first launch in 2018, the Health Equity and Financial Protection Indicators (HEFPI) database and portal provide the public with country-level data on the delivery of health service interventions and health outcomes that together form the “health equity“ side of the database, and on “financial protection in health” (Wagstaff et al. 2018). Moreover, to enable users to explore within-country inequities, the dataset also breaks indicators down by subpopulations, for instance by different quintiles of a country’s wealth distribution, and it includes a summary measure of inequality known as the concentration index (Wagstaff et al. 1991, Kakwani et al. 1997, Erreygers 2009). The data are computed from an extensive and continuously expanding number of nationally representative household surveys that have been conducted by, or in partnership with, national governments, such as the Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS), the Living Standards Measurement Study (LSMS), and a large number of national household budget surveys. A first update of the database in 2019 increased the number of financial protection indicators in the original database from 5 to 14 and added over 500 new datapoints across the then 18 health service coverage and 28 health outcome indicators (Wagstaff et al. 2019). Moreover, some 300 originally included datapoints were dropped in this second 2019 version of the database as a result of extensive quality checks. This paper outlines changes that have been made for the third version of the HEFPI database launched in August 2022. Section 2 describes newly added subpopulation breakdowns by urban and rural place of residence and subnational region. Section 3 describes changes on the financial protection side, where the number of indicators further expanded from 14 to 31, reflecting a broadening of the definition of medical impoverishment from being limited to those pushed below the poverty line by medical spending to also include those already under the poverty line who incur any medical spending—that is, those “further impoverished” by medical spending. The additional financial protection indicators also include indicators that show the intersection of catastrophic and impoverishing health spending, that is, identify the populations exposed to both types of financial hardship simultaneously. Section 4 discusses changes on the health equity side of the database, including the addition of 19 service coverage and 10 health outcome indicators, 10,939 new datapoints across 578 new surveys, and additional quality checks. Section 5 briefly introduces the 2022 HEFPI data visualization portal launched alongside the new dataset, and Section 6 concludes the paper. An important limitation of the 2022 version of the HEFPI database is that despite the addition of datapoints from a large number of newly available household surveys, it, with few exceptions, does not include data from after the onset of the COVID-19 pandemic. More recent data are not available for two reasons. First, after data collection, most household surveys take one to three years of processing before micro-data become publicly available. Second, most countries and international household survey programs stopped their fieldwork during 2020 in light of public health mitigation measures and safety concerns. 1 Survey work resumed in many countries in 2021, often with increased use of phone surveys and revised protocols for face-to-face interviews, but due to the 1 A survey of National Statistical Offices conducted in May 2020 revealed that 96 percent had stopped data collection; https://blogs.worldbank.org/opendata/phones-rescue-household-survey-implementation-under-covid-and-beyond. 7 aforementioned data processing lag, most of the micro-data from the 2021 surveys will not be available until later. However, despite the lack of COVID-19-era data, the HEFPI dataset remains highly relevant as a baseline for the pandemic’s impacts on health equity and financial protection, as well as its tracking and how health systems and population health have rebounded. 8 PART II – NEW INDICATORS AND DATA POINTS NEW DIMENSIONS OF INEQUALITY AND CHANGES IN COMPUTATION OF THE CONCENTRATION INDEX Previous versions of the HEFPI database included indicators disaggregated by wealth quintiles as one dimension of possible within-country inequality in financial protection, health care service use, and health. The 2022 version adds two additional dimensions of inequality by making indicators available for (1) urban and rural place of residence; and (2) by first administrative-level subnational regions according to the 2015 release of the Global Administrative Unit Layers (GAUL) coding system developed by the Food and Agriculture Organization (FAO) of the United Nations, or by survey-specific subnational regions. Both new inequality dimensions are available for all service coverage and health outcome data points from MICS and DHS surveys as well as for 91 financial protection surveys. Figure 1: Schematic Representation of Financial Protection in Health Source: World Health Organization and World Bank (2021) Note: Catastrophic and impoverishing out-of-pocket health spending are metrics used to identify in which cases out-of-pocket health payments are a source of financial hardship. Catastrophic out-of-pocket metrics include SDG 3.8.2, capacity to pay approaches, etc. Impoverishing out-of-pocket metrics include indicators to identify both people impoverished and further impoverished by out-of-pocket health spending, using various poverty lines (e.g., the global extreme poverty line, a relative poverty line). 9 CHANGES TO THE FINANCIAL PROTECTION SIDE OF THE DATABASE Conceptual background Full financial protection in health is defined as the absence of three potentially overlapping groups of people in a population: (1) those who forgo needed health care for financial reasons; (2) those who use health care when in need but incur out-of-pocket (OOP) health payments that exceed a share of their household budget, which threatens consumption of other essential goods and services like food and education; and (3) those who use health care when in need but are impoverished by the required OOP health payments. The latter two groups of people are considered to be experiencing financial hardship through OOP medical payments (Figure 1). While the new HEFPI database includes 31 indicators of financial hardship, it does not, for data availability reasons, include indicators of forgone care for financial reasons. The HEFPI service coverage indicators may therefore serve as a rough approximation, acknowledging, however, that the forgoing of care captured by low service coverage rates may be for other than financial reasons, for example, poor geographic accessibility of health care providers or cultural and social stigmas. New and retired indicators of financial hardship The 2022 database introduces 22 new financial protection indicators. Five indicators of financial protection that formed part of previous HEFPI databases are no longer included, specifically the population share falling under the $21.70 poverty line due to OOP health expenditure, and the change in the poverty gaps for four poverty lines—$1.90, $3.20, $5.50, and $21.70 per person per day. The population share falling under the $21.70 poverty line is dropped for simplicity, as we decided to rely only on a relative poverty line definition for high-income countries instead of using the higher absolute poverty line definition of $21.70. The four “change in poverty gap indicators” are replaced by alternative measures of the “poverty deepening” impact of OOP health spending— namely the population shares pushed further below different poverty lines by OOP health spending. These new indicators show the share of people in a population who live in households whose total per capita consumption, including any OOP health payments, lies below a specific poverty line and who incur any OOP health payments. Because these households are already poor before OOP health payments are considered, any OOP health payments for them represented financial hardship. 2 The 2022 HEFPI database includes a total of five further pushed into poverty indicators: Three for different absolute poverty lines ($1.90, $3.20, $5.50), one for the relative poverty line of 60 percent of median per capita consumption in a country, and one for the societal poverty line that equals $1.90 per person per day for countries where the 50 percent of per capita median consumption poverty line is below $1.90, and 50 percent of per capita median consumption otherwise. 2 The further pushed into poverty indicators were also newly included in the Global Monitoring Report on Financial Protection in Health 2021 (https://openknowledge.worldbank.org/handle/10986/36723) and the Tracking Universal Health Coverage—2021 Global Monitoring Report (https://openknowledge.worldbank.org/handle/10986/36724). 10 Figure 2: Medical Impoverishment Illustrated with Three Households Using the $1.90 Extreme Poverty Line Source: Own visualization. Note: The total share of medically impoverished people in a country is the sum of the shares of people living in households pushed and further pushed below the poverty line by OOP health spending. For the measurement of the overall poverty impact of OOP health spending, the new indicators are complementary to the pushed into poverty by OOP health payment indicators that were already included in previous versions of the HEFPI dataset. These later indicators represent the share of people who live in households whose total per capita consumption, including OOP health payments, lies above the poverty line but whose per capita consumption net of OOP health payments is below the poverty line (Figure 2). As overall measures of medical impoverishment, the 2022 version of the HEFPI database therefore also now includes indicators for each of the five aforementioned poverty lines, which represent the combined shares of populations pushed or further pushed into poverty by OOP health spending. Finally, the new HEFPI database includes a total of 16 indicators that represent the population shares that incur both catastrophic and impoverishing OOP health payments in a given year—specifically the population shares with catastrophic spending at the 10 and 25 percent thresholds, which are pushed below, further pushed below, and pushed or further pushed below the $1.90 and $3.20 absolute poverty lines and the 60 percent median consumption relative poverty line. This information about the intersection of catastrophic and impoverishing payments forms an important input for policy making, as it enables a more in-depth view on where in the income distribution of a society problematic OOP health payments are incurred. Table 1 lists the short names, descriptions, and number of country-level data points for all financial protection indicators in the 2022 HEFPI database. 11 Table 1: Financial Protection in Health Indicators in the 2022 HEFPI Database # of data # of data Variable name Description points in points in v2019 v2022 OOP health spending amount and budget share oop_cap_yr_ppp Mean household per capita OOP health spending ($ 2011 PPP) 646 634 sh_hexp_1 Mean share of household consumption or income used on OOP health spending (%) 646 634 Catastrophic OOP health spending cata_tot_10 Proportion of population spending more than 10% of household consumption or 646 634 income on OOP health care expenditure (%) cata_tot_25 Proportion of population spending more than 25% of household consumption or 646 612 income on OOP health care expenditure (%) Impoverishing OOP health spending Pushed into poverty by OOP health spending imp_np190 Proportion of population pushed below the $1.90 ($ 2011 PPP) poverty line by OOP 646 593 health care expenditure (%) imp_np320 Proportion of population pushed below the $3.20 ($ 2011 PPP) poverty line by OOP 646 593 health care expenditure (%) imp_np550 Proportion of population pushed below the $5.50 ($ 2011 PPP) poverty line by OOP 646 558 health care expenditure (%) imp_nprelPL60 Proportion of population pushed below the 60% median consumption poverty line by 646 593 OOP health care expenditure (%) imp_npSPL Proportion of population pushed by OOP health care expenditure below the societal 646 593 poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) Further pushed into poverty by OOP health spending imp_p190_pop Proportion of population pushed further below the $1.90 ($ 2011 PPP) poverty line by New 593 OOP health care expenditure (%) imp_p320_pop Proportion of population pushed further below the $3.20 ($ 2011 PPP) poverty line by New 593 OOP health care expenditure (%) imp_p550_pop Proportion of population pushed further below the $5.50 ($ 2011 PPP) poverty line by New 558 OOP health care expenditure (%) imp_prelPL60_pop Proportion of population pushed further below the 60% median consumption poverty New 593 line by OOP health care expenditure (%) imp_pSPL_pop Proportion of population pushed further by OOP health care expenditure below the New 593 societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) Pushed or further pushed into poverty by OOP health spending imp_npp190_pop Proportion of population pushed or pushed further below the $1.90 ($ 2011 PPP) New 593 poverty line by OOP health care expenditure (%) imp_npp320_pop Proportion of population pushed or pushed further below the $3.20 ($ 2011 PPP) New 593 poverty line by OOP health care expenditure (%) imp_npp550_pop Proportion of population pushed or pushed further below the $5.50 ($ 2011 PPP) New 593 poverty line by OOP health care expenditure (%) imp_npprelPL60_pop Proportion of population pushed or pushed further below the 60% median New 593 consumption poverty line by OOP health care expenditure (%) imp_nppSPL_pop Proportion of population pushed or pushed further by OOP health care expenditure New 593 below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) Overlap between catastrophic and impoverishing health spending comb_cata_tot_10_imp_np190 Proportion of population spending more than 10% of household consumption or New 558 _pop income on OOP health care expenditure and pushed below the $1.90 ($ 2011 PPP) poverty line by OOP health care expenditure (%) comb_cata_tot_10_imp_np320 Proportion of population spending more than 10% of household consumption or New 558 _pop income on OOP health care expenditure and pushed below the $3.20 ($ 2011 PPP) poverty line by OOP health care expenditure (%) comb_cata_tot_10_imp_nprelP Proportion of population spending more than 10% of household consumption or New 558 L60_pop income on OOP health care expenditure and pushed below the 60% median consumption poverty line by OOP health care expenditure (%) comb_cata_tot_25_imp_np190 Proportion of population spending more than 25% of household consumption or New 558 _pop income on OOP health care expenditure and pushed below the $1.90 ($ 2011 PPP) poverty line by OOP health care expenditure (%) comb_cata_tot_25_imp_np320 Proportion of population spending more than 25% of household consumption or New 558 _pop income on OOP health care expenditure and pushed below the $3.20 ($ 2011 PPP) poverty line by OOP health care expenditure (%) 12 # of data # of data Variable name Description points in points in v2019 v2022 comb_cata_tot_25_imp_nprelP Proportion of population spending more than 25% of household consumption or New 558 L60_pop income on OOP health care expenditure and pushed below the 60% median consumption poverty line by OOP health care expenditure (%) comb_cata_tot_10_imp_p190_ Proportion of population spending more than 10% of household consumption or New 558 pop income on OOP health care expenditure and pushed further below the $1.90 ($ 2011 PPP) poverty line by OOP health care expenditure (%) comb_cata_tot_10_imp_p320_ Proportion of population spending more than 10% of household consumption or New 558 pop income on OOP health care expenditure and pushed further below the $3.20 ($ 2011 PPP) poverty line by OOP health care expenditure (%) comb_cata_tot_10_imp_prelPL Proportion of population spending more than 10% of household consumption or New 558 60_pop income on OOP health care expenditure and pushed further below the 60% median consumption poverty line by OOP health care expenditure (%) comb_cata_tot_25_imp_p190_ Proportion of population spending more than 25% of household consumption or New 558 pop income on OOP health care expenditure and pushed further below the $1.90 ($ 2011 PPP) poverty line by OOP health care expenditure (%) comb_cata_tot_25_imp_p320_ Proportion of population spending more than 25% of household consumption or New 558 pop income on OOP health care expenditure and pushed further below the $3.20 ($ 2011 PPP) poverty line by OOP health care expenditure (%) comb_cata_tot_25_imp_nprelP Proportion of population spending more than 25% of household consumption or New 558 L60_pop income on OOP health care expenditure and pushed further below the 60% median consumption poverty line by OOP health care expenditure (%) Source: 2019 and 2022 HEFPI databases. Notes: v2019 and v2022 indicate the 2019 and 2022 versions of the HEFPI database. PPP = Purchasing Power Parity. New and retired data points and surveys In total, the 2022 HEFPI dataset includes 18,035 country-level data points across the 31 financial protection indicators—8,991 more than the database’s 2019 version. The data points come from 634 surveys (previously 646). For 93 of these surveys, data points are available at the level of subnational regions, and for 626 surveys, at the level of rural and urban subpopulations. 7,262 data points that were included in the previous version of the HEFPI database were retired for the 2022 version after additional quality checks. In 2,393 cases, retired points were replaced with updated estimates. Appendix Table A.1 lists all data points where the change from the 2019 to the 2022 version exceeded 5 percentage points for indicators with percentages as the unit of measurement and 15 percent for indicators with other units of measurement. For the nine previously included financial protection indicators, the additional quality checking exercise in fact resulted in a reduction of the number of country-level data points in 2022 compared to the 2019 version of the HEFPI database. However, the 2022 financial protection datapoints are more recent, with a median survey year of 2008 compared to 2007 in the 2019 dataset. HEALTH EQUITY INDICATORS New health equity indicators The 2022 version of the HEFPI database includes a total of 73 indicators on the health equity side, including 35 health service coverage and 38 health outcome indicators. Nineteen health service coverage and 10 health outcome indicators were newly added in 13 2022. Appendix Table A.2 shows short names and descriptions, along with the number of data points for all health equity indicators in the 2022 HEFPI database. The 16 new health care utilization indicators include three indicators of health care quality and three indicators of effective coverage. Effective coverage requires that everyone in need of a particular health service receives it in a timely manner and at the quality necessary to obtain the desired effect and potential health gains (Shengelia et al. 2005, Jannati et al. 2018). The concept has been receiving increased attention recently in global health research and policy because of the observation that the large improvements in health care access many low- and middle-income countries (LMICs) have achieved over the past two decades have not always coincided with commensurate gains in health outcomes because health care quality remained lacking (Gabrysch et al. 2019). The interrelation of health care coverage and quality and effective coverage can be visualized in a care cascade like that shown in Figure 3 (Shengelia et al. 2005). Figure 3: Coverage, Quality, Effective Coverage, and the Care Cascade Source: Own visualization. The effective coverage rate (share of the population in need receiving the correct treatment, in formula in Figure 3) is the product of the crude coverage rate (share of the population receiving any treatment, ) and the share of those with crude coverage who receive the correct treatment, or quality care ( . 3 For instance, the effective coverage rate for antenatal care would be obtained by multiplying the share of pregnancies (population in need) with any antenatal care (crude coverage) by the share of pregnancies with any antenatal care where care was delivered according to established 3 More advanced and data-demanding definitions of effective coverage consider coverage effective under the condition that clinical guidelines are not only adhered to but that maximum possible health gains are achieved (e.g., for HIV/AIDS, that patients not only receive antiretroviral drugs but also that that their viral load is suppressed). 14 clinical guidelines. While data constraints limit our ability to generate care quality measures that are fully aligned with, for example, recommendations by the World Health Organization (WHO), the indicators of care quality (conditional on crude coverage) and effective coverage for antenatal care (WHO 2016), delivery (WHO 2018), and postnatal care (WHO 2014) in the 2022 HEFPI database approximate care standards as closely as the available data permit. Specifically, we include the following: • For antenatal care − Crude coverage: Percentage of most recent births in last two years with at least one antenatal care check. − Quality of care/Correct treatment rate among those covered: Of births in last two years with at least one antenatal care check; percentage with at least four antenatal care checks; any checks with skilled provider; and blood pressure, blood sample, and urine sample taken. − Effective coverage: Percentage of most recent births in last two years where women received at least four antenatal care checks; any checks with skilled provider; and blood pressure, blood sample, and urine sample taken. • For birth attendance − Crude coverage: Percentage of most recent births in last two years attended by any skilled health personnel. − Quality of care/Correct treatment rate among those covered: Of births in the last two years attended by any skilled health personnel, percentage that took place in a formal health facility, with both mother and child staying in the facility for 24 hours or more and breastfeeding initiated within one hour of birth. − Effective coverage: Percentage of most recent births in last two years attended by any skilled health personnel, taking place in a formal health facility, with both mother and child staying in the facility for 24 hours or more and breastfeeding initiated within one hour of birth. • For postnatal care − Crude coverage: Percentage of most recent births in last two years where mother or child receive postnatal care in first six weeks. − Quality of care/Correct treatment rate among those covered: Of most recent births in last two years where mother or child received any postnatal care in first six weeks, percentage where mother and child receive postnatal care in first 24 hours from a skilled health worker. − Effective coverage: Percentage of most recent births in last two years where mother and child receive postnatal care in first 24 hours from a skilled health worker. 15 Besides the six new care quality and effective coverage indicators and two new “crude coverage” indicators for antenatal and postnatal care, the 2022 HEFPI database includes nine new indicators of health care coverage, specifically: • Two new family planning indicators, namely the percentage of women aged 15–49 who are married or live in union who do not want to become pregnant and are using modern contraception; and the share of women aged 15–49 who are married or live in union who do not want to become pregnant and are using any contraceptive methods, including traditional ones. Women who do not want to become pregnant, that is, are in need of contraception are identified according to the revised definition of need for family planning by Bradley (2012) as well as by Barros et al. (2015). • The share of births where mothers received antenatal care in the first trimester of the pregnancy. • Two indicators in the domain of delivery care, namely the share of births taking place in a formal health facility, the share of births taking place in a hospital. • The share of children aged 15–23 months who received none of eight essential vaccines at birth. • Three new indicators representing access to formal health care providers for children under five with (1) fever; (2) diarrhea; and (3) fever, diarrhea, or a cough and rapid breathing originating from the chest. In terms of health outcomes, the 2022 version of the HEFPI database introduces a total of 10 new indicators. Six are new anthropometric indicators for children under five, specifically the shares of children with (1) any wasting, (2) severe wasting, (3) severe underweight, (4) severe stunting, (5) both wasting and stunting, and (6) both severe wasting and stunting. Moreover, there are four new indicators of disease prevalence among children under five, namely the percentages of children with (1) cough and rapid breathing from the chest; (2) diarrhea; (3) fever; (4) cough and rapid breathing originating from the chest, diarrhea and/or fever in the two weeks preceding the survey. New and retired data points and surveys In total, the health equity side of the 2022 HEFPI dataset includes 19,820 country-level data points across the 73 health service and health outcome indicators—9,890 more datapoints than the database’s previous 2019 version. The data points come from 1,318 surveys (previously 1,208). For 482 of these surveys, data points are available at the level of subnational regions; for 617 surveys for rural and urban households; and for 915 surveys by income, consumption, or wealth quintile. For 957 data points the database includes concentration indexes and their standard errors. 1,049 data points that were included in the previous version of the HEFPI database were retired for the 2022 version as the result of a new round of quality checks. Because of a complete revamp of the coding structure for the 513 DHS and MICS surveys in the database, many values of previously included indicators derived from these surveys changed from the 2019 to the 2022 HEFPI version. However, in the large majority of cases, these changes were small in size. Appendix Table A.1 lists all data points where the change from the 2019 to the 2022 version exceeded 5 percentage points for indicators 16 with percentages as the unit of measurement and 15 percent for indicators with other units of measurement. 17 PART III – NEW VISUALIZATIONS IN THE HEFPI PORTAL Figure 4: Radar Chart in the 2022 HEFPI Portal Source: https://datatopics.worldbank.org/health-equity-and-financial-protection/. An upgraded HEFPI portal is launched alongside the new dataset. Like the previous portal, the upgrade includes maps and bar charts showing country-level indicator means and concentration indexes; country and wealth/consumption quintile-level mean trend line charts; wealth/consumption quintile-level lollipop (dot-plot) charts by indicator and country; and charts visualizing data availability for specific countries and indicators. In addition, to enable users to visually capture the multidimensionality of universal health coverage (UHC), customizable radar charts were added that also allow comparisons across countries (Figure 4). The newly added rural, urban, and subnational region means are visualized using bar charts (Figure 5). 18 Figure 5: Subnational Region Indicator Bar Chart in the 2022 HEFPI Portal – Share of Pregnancies with 4+ Antenatal Care Visits in Zambia, 2018 Source: https://datatopics.worldbank.org/health-equity-and-financial-protection/. 19 PART IV – CONCLUSION The HEFPI database will continue to evolve. New datapoints will continue to be added, through a mix of adding new indicators and additional datapoints to already included indicators. The process of improving the reliability of estimates will also continue, meaning that some existing datapoints may be revised or dropped in future versions. Documentation (like this working paper) will be released to accompany new versions of the HEFPI database. 20 ACCESSING AND CITING THE DATABASE ACCESSING THE DATABASE The 2022 and prior versions of the database can be freely downloaded from the World Bank’s Development Data Hub: https://datacatalog.worldbank.org/int/search/dataset/0038633. The HEFPI portal provides customizable data visualizations: https://datatopics.worldbank.org/health-equity-and-financial-protection/. Example code for the processing of the micro-data of the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) is available in a public GitHub repository: https://github.com/worldbank/HEFPI2022-Programmes. CITING THE DATABASE The reference citation for the data is S. Neelsen, P. Eozenou, M. Smitz, and R. Wang. 2022. “The Health Equity and Financial Protection Indicators Database 2022.” Washington, DC: World Bank. 21 REFERENCES Barros, A. J., et al. (2015). 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Global Monitoring Report on Financial Protection in Health 2021, World Bank. 22 APPENDIX Table A.1: Data Points in the 2022 HEFPI Database That Changed Substantively compared to the 2019 Database Version Indicator Indicator Data point (Country Variable name Description value in value in Year) v2022 v2019 oop_cap_yr_ppp Mean household per capita OOP health Angola 2008 214.07 79.5 spending ($ 2011 PPP) Armenia 2007 139.93 36.18 Armenia 2008 129.46 80.65 Armenia 2009 121.3 67.59 Armenia 2010 187.01 87.88 Australia 2010 288.36 524.7 Bangladesh 2000 79.56 30.29 Bangladesh 2005 74.19 44.89 Bangladesh 2016 163.45 61.11 Bhutan 2003 43.83 34.3 China 2002 68.29 90.65 China 2007 111.59 148.46 Dominican Republic 253.3 184.91 2007 Egypt 2008 120 187.49 India 2000 57.56 48.59 Iraq 2006 53.81 109.19 Jordan 2002 57.38 80.86 Jordan 2008 71.31 97.54 Kenya 2015 52.9 44.24 Latvia 2002 147.85 100.93 Latvia 2003 162.3 110.77 Latvia 2004 207.22 141.44 Latvia 2007 350.08 238.94 Latvia 2008 339.41 231.68 Latvia 2009 304.94 208.14 Latvia 2010 456.16 311.4 Maldives 2004 100.51 79.52 Mexico 2008 174.25 85.61 Malawi 2016 13.3 18.89 Nigeria 2012 22.75 67.86 Sierra Leone 2003 26.92 37.07 Yemen 2005 120.66 160.99 Yemen 2014 103.97 135.76 Zambia 2006 0.01 10.14 Zambia 2010 0 3.18 sh_hexp_1 Mean share of household consumption or - - - income used on OOP health spending (%) cata_tot_10 Proportion of population spending more than Armenia 2009 9.7% 4.4% 10% of household consumption or income on Armenia 2010 17.5% 5.5% OOP health care expenditure (%) Bangladesh 2000 14.8% 4.1% Bangladesh 2005 12.3% 4.5% Bangladesh 2016 25.6 10.3% Nigeria 2012 3.6% 15.1% cata_tot_25 Proportion of population spending more than Bangladesh 2016 9.9% 1.4% 25% of household consumption or income on OOP health care expenditure (%) imp_np190 Proportion of population pushed below the Bangladesh 2016 7.9% 2.6% $1.90 ($ 2011 PPP) poverty line by OOP health care expenditure (%) imp_np320 Proportion of population pushed below the - - - $3.20 ($ 2011 PPP) poverty line by OOP health care expenditure (%) imp_np550 Proportion of population pushed below the - - - $5.50 ($ 2011 PPP) poverty line by OOP health care expenditure (%) imp_nprelPL60 Proportion of population pushed below the 60% Bangladesh 2016 7.9% 2.1% median consumption poverty line by OOP health care expenditure (%) imp_npSPL Proportion of population pushed by OOP health Bangladesh 2016 8.7% 3.7% care expenditure below the societal poverty line, defined as the higher of the $1.90 ($ 2011 PPP) poverty line and a 50% of median consumption poverty line (%) a_bmi Mean BMI of population aged 18 or older - - - 23 Indicator Indicator Data point (Country Variable name Description value in value in Year) v2022 v2019 a_height Mean height in meters of population aged 18 - - - and older a_obese Percentage of population aged 18 or older with - - - BMI above 30 a_overweight Percentage of population aged 18 or older with - - - BMI above 25 m_bmi Mean BMI of male population aged 18 or older - - - m_height Mean height in meters of males aged 18 and - - - older m_obese Percentage of males aged 18 and older with - - - BMI above 30 m_overweight Percentage of male population aged 18 or - - - older with BMI above 25 w_bmi Mean BMI of female population aged 18 or - - - older w_bmi_1549 Mean BMI of female population aged 15-49 - - - (excludes currently pregnant women and women having given birth in the three months preceding the survey) w_height Mean height in meters of females aged 18 and - - - older w_height_1549 Mean height in meters of females aged 15-49 - - - w_obese Percentage of females aged 18 and older with - - - BMI above 30 w_obese_1549 Percentage of females aged 15-49 with BMI Jordan 1997 38.2% 28.8% above 30 (excludes currently pregnant women Turkey 1998 24.3% 19.0% and women having given birth in the three months preceding the survey) w_overweight Percentage of female population aged 18 or - - - older with BMI above 25 w_overweight_1549 Percentage of female population aged 15-49 Colombia 1995 45.7% 39.9% with BMI above 25 (excludes currently Dominican Republic 45.3% 38.6% pregnant women and women having given birth 1996 in the three months preceding the survey) Gabon 2000 33.9% 28.9% Jordan 1997 71.0% 62.0% Kazakhstan 1995 46.2% 38.8% Kyrgyz Republic 1997 36.4% 27.9% Nicaragua 1997 50.9% 42.5% Peru 2000 54.1% 46.7% Turkey 1998 57.7% 51.4% Uzbekistan 1996 29.9% 21.8% c_stunted Percentage of children under-5 with a Height- — — — for-Age z-score <-2 standard deviations from the reference median (z-score calculated using WHO 2006 Child Growth Standards) c_underweight Percentage of children under-5 with a Weight- — — — for-Age z-score <-2 standard deviations from the reference median (z-score calculated using WHO 2006 Child Growth Standards) a_hi_bp140_or_on_med Percentage of adult population with high blood Bangladesh 2011 25.7% 90.4% pressure or on treatment for high blood pressure (age range may vary) a_hi_chol_5_190_or_on_meds Percentage of adult population with high — — — cholesterol or on treatment for high cholesterol (age range may vary) a_hiv Percentage of population age 15–49 who had — — — blood tests that are positive for HIV1 or HIV2 a_bp_dial Mean diastolic blood pressure (mmHg) in adult — — — population (age range may vary) a_bp_sys Mean systolic blood pressure (mmHg) in adult — — — population (age range may vary) a_chol_mmol_L Mean cholesterol (mmol/L) in adult population — — — (age range may vary) a_gluc_mm Mean fasting blood glucose (mmol/L) in adult — — — population (age range may vary) a_imp_glyc Percentage of adult population with impaired — — — fasting glycaemia (age range may vary) c_u1mr Deaths of children before their 1st birthday per Nigeria 2016 112.22 69.9 1,000 live births. Sample: children born up to 5 years before the survey for full population mortality estimates, and up to 10 years before the survey for wealth quintile specific mortality estimates 24 Indicator Indicator Data point (Country Variable name Description value in value in Year) v2022 v2019 c_u5mr Deaths of children before their 5th birthday per Nigeria 2016 203.23 120.13 1,000 live births. Sample: children born up to 5 years before the survey for full population mortality estimates, and up to 10 years before the survey for wealth quintile–specific mortality estimates a_bp_meas_1yr Percentage of population over 18 having their — — — blood pressure measured by health professional in the last year a_bp_treat Percentage of adult population being treated Namibia 2013 78.3% 12.8% for high blood pressure (age range may vary) a_chol_meas Percentage of adult population at risk — — — (overweight or obese and older than 20, male and older than 34) having their cholesterol levels measured in the last 5 years a_diab_treat Percentage of adult population being treated — — — for raised blood glucose or diabetes (age range may vary) a_gluc_meas2 Percentage of population aged 40–69 at — — — increased risk of diabetes (overweight, obese) having their blood sugar measured in the last 5 years a_inpatient_1yr Percentage of population age 18 and older — — — using inpatient care in the last 12 months w_mam_2y Percentage of women who received a Nicaragua 2001 65.8% 8.8% mammogram in the last 2 years (preferably age 50–69 but age groups may vary) w_pap_3y Percentage of women who received a pap Colombia 2004 84.7% 78.0% smear in the last 3 years (preferably age 20–69 Dominican Republic 89.6% 70.4% but age groups may vary) 1996 Nicaragua 1997 85.0% 58.8% Peru 1996 37.2% 27.6% Peru 2003 27.4% 33.4% Peru 2011 30.4% 37.0% Peru 2012 31.8% 39.0% Peru 2013 47.7% 59.3% w_condom_conc Percentage of women aged 18–49 who had — - - more than one sexual partner in the last 12 months and used a condom during last intercourse w_CPR Percentage of women aged 15–49 who are Dominican Republic 68.3% 59.2% married or live in union and currently use a 1996 modern method of contraception. Modern India 1992 42.6% 36.3% methods are defined as female sterilization, India 1998 48.4% 42.8% male sterilization, the contraceptive pill, Jordan 1997 43.9% 37.7% intrauterine contraceptive device (IUD), Uzbekistan 1996 57.6% 51.3% injectables, implants, female condom, male condom, diaphragm, contraceptive foam and contraceptive jelly, lactational amenorrhea method (LAM), emergency contraception, country-specific modern methods and other modern contraceptive methods respondent mentioned. w_unmet_fp Percentage of women aged 15–49 who are Central African 24.3% 19.3% married or live in union who do not want to Republic 1994 become pregnant but are not using Cote d’Ivoire 1994 36.3% 30.6% contraception (revised definition by Bradley Cameroon 1998 26.4% 21.0% 2012) Comoros 1996 42.1% 36.0% Gabon 2000 34.2% 27.9% Morocco 1992 28.8% 23.5% Madagascar 1997 33.5% 27.8% Mozambique 1997 30.9% 25.2% Senegal 1997 40.7% 35.1% Uganda 1995 35.5% 30.0% c_anc Percentage of most recent births in last two Burundi 2016 51.8% 45.5% years with at least 4 antenatal care visits Haiti 2016 62.7% 70.5% (women aged 15–49 at the time of the survey) c_sba Percentage of most recent births in last two Burkina Faso 1992 57.2% 41.1% years attended by any skilled health personnel Burkina Faso 1998 48.9% 32.3% (women aged 15–49 at the time of the survey). Burkina Faso 2003 37.2% 55.7% Definition of skilled varies by country and Bangladesh 1996 17.5% 9.0% survey but always includes doctor, nurse, Bangladesh 1999 24.5% 13.4% midwife, and auxiliary midwife). Bangladesh 2007 33.6% 22.7% Brazil 1996 96.0% 90.8% 25 Indicator Indicator Data point (Country Variable name Description value in value in Year) v2022 v2019 Democratic Republic 54.3% 76.8% of Congo 2007 Ethiopia 2011 19.2% 12.4% Ghana 1993 59.6% 43.1% Ghana 1998 68.8% 44.5% Guinea 2005 32.3% 38.0% Guatemala 2014 95.1% 68.7% India 1992 41.9% 35.4% Kenya 1993 53.0% 43.0% Kenya 1998 54.6% 43.8% Morocco 1992 25.0% 33.7% Madagascar 2008 57.9% 43.8% Mali 2001 26.3% 42.6% Malawi 1992 64.2% 53.1% Niger 1998 44.1% 18.0% Niger 2000 36.0% 15.3% Niger 2006 34.2% 19.4% Nepal 2011 43.3% 49.7% Pakistan 1990 34.3% 19.7% Philippines 1993 93.9% 54.0% Philippines 2017 88.6% 81.8% Senegal 1997 58.6% 48.1% Senegal 2010 77.0% 64.5% Senegal 2012 76.3% 49.8% Senegal 2014 81.0% 59.8% Senegal 2015 78.2% 53.9% Senegal 2016 78.6% 58.1% Tanzania 1996 51.5% 45.2% Tanzania 2004 54.6% 47.1% Zimbabwe 1994 82.2% 68.2% Zimbabwe 2005 78.3% 66.4% c_ARItreat Percentage of children under-5 with cough and - - - rapid breathing which originated from the chest in the two weeks preceding the survey who visited a formal health care provider (excluding pharmacies). The definition of formal health care providers varies by country and data source. Variable was called c_treatARI in previous HEFPI version. c_diarrheaORS Percentage of children under-5 with diarrhea in - - - the 2 weeks before the survey who were given oral rehydration salts (ORS). Variable was called c_treatdiarrhea in previous HEFPI version. c_ITN Percentage of children under-5 who slept Ghana 2008 40.9% 29.7% under an insecticide treated bed net (ITN) the Zimbabwe 2005 14.5% 2.9% night before the survey. A bed net is considered treated if it (a) is a long-lasting treated net, (b) a pretreated net that was purchased or soaked in insecticides less than 12 months ago, or (c) a non-pretreated net that was soaked in insecticides less than 12 months ago c_fullimm Percentage of children aged 15–23 months Azerbaijan 2006 47.5% 54.4% who received Bacillus Calmette-Guerin (BCG), Republic of Congo 54.4% 44.5% measles/Measles-Mumps-Rubella (MMR), 3 2011 doses of polio (excluding polio given at birth) Comoros 2000 56.1% 63.7% and 3 doses of diphtheria-pertussis-tetanus Dominican Republic 61.7% 51.0% (DPT)/Pentavalent vaccinations, either verified 2013 by vaccination card or by recall of respondent Georgia 2005 33.8% 39.0% Moldova 2000 86.6% 66.9% Myanmar 2000 80.5% 51.0% Malawi 2000 44.5% 72.9% Nigeria 2016 21.8% 36.5% Tajikistan 2000 73.9% 58.5% Uzbekistan 1996 89.5% 84.0% Vietnam 2013 85.6% 80.1% Zambia 2001 52.4% 74.0% c_measles_vacc Percentage of children aged 15–23 months Azerbaijan 2006 69.2% 77.4% who received measles or MMR vaccination, Burkina Faso 1992 60.0% 65.9% either verified by vaccination card or by recall Myanmar 2000 89.3% 52.7% of respondent Malawi 1992 79.0% 86.9% Malawi 2000 97.2% 86.7% 26 Indicator Indicator Data point (Country Variable name Description value in value in Year) v2022 v2019 Nigeria 2016 42.9% 67.8% Pakistan 1990 52.0% 57.3% Tajikistan 2000 81.0% 73.8% Turkey 1993 77.7% 83.0% Source: 2019 and 2022 HEFPI databases. Note: v2019 and v2022 indicate the 2019 and 2022 versions of the HEFPI database. 27 Table A.2: Health Outcome and Service Coverage Indicators in the 2022 HEFPI Database # of # of data data Variable point Description points name s in in v202 v2019 2 Health outcomes Adult and child anthropometrics a_bmi Mean BMI of population aged 18 or older 292 300 a_height Mean height in meters of population aged 18 and older 157 157 a_obese Percentage of population aged 18 or older with BMI above 30 294 304 a_overweight Percentage of population aged 18 or older with BMI above 25 271 280 m_bmi Mean BMI of male population aged 18 or older 294 301 m_height Mean height in meters of males aged 18 and older 157 157 m_obese Percentage of males aged 18 and older with BMI above 30 294 306 m_overweight Percentage of male population aged 18 or older with BMI above 25 275 283 w_bmi Mean BMI of female population aged 18 or older 293 300 w_bmi_1549 Mean BMI of female population aged 15-49 (excludes currently pregnant women and women having given 192 220 birth in the three months preceding the survey) w_height Mean height in meters of females aged 18 and older 156 156 w_height_1549 Mean height in meters of females aged 15–49 192 220 w_obese Percentage of females aged 18 and older with BMI above 30 295 304 w_obese_1549 Percentage of females aged 15–49 with BMI above 30 (excludes currently pregnant women and women 192 220 having given birth in the three months preceding the survey) w_overweight Percentage of female population aged 18 or older with BMI above 25 274 282 w_overweight_ Percentage of female population aged 15–49 with BMI above 25 (excludes currently pregnant women and 192 220 1549 women having given birth in the three months preceding the survey) c_stu_was Percentage of children under-5 with a Height-for-Age and a Weight-for-Height z-score <-2 standard New 441 deviations from the reference medians (z-score calculated using WHO 2006 Child Growth Standards) c_stu_was_se Percentage of children under-5 with a Height-for-Age and a Weight-for-Height z-score <-3 standard New 440 v deviations from the reference medians (z-score calculated using WHO 2006 Child Growth Standards) c_stunted Percentage of children under-5 with a Height-for-Age z-score <-2 standard deviations from the reference 350 430 median (z-score calculated using WHO 2006 Child Growth Standards) c_stunted_sev Percentage of children under-5 with a Height-for-Age z-score <-3 standard deviations from the reference New 408 median (z-score calculated using WHO 2006 Child Growth Standards) c_underweight Percentage of children under-5 with a Weight-for-Age z-score <-2 standard deviations from the reference 351 431 median (z-score calculated using WHO 2006 Child Growth Standards) c_underweight Percentage of children under-5 with a Weight-for-Age z-score <-3 standard deviations from the reference New 409 _sev median (z-score calculated using WHO 2006 Child Growth Standards) c_wasted Percentage of children under-5 with a Weight-for-Height z-score <-2 standard deviations from the New 407 reference median (z-score calculated using WHO 2006 Child Growth Standards) c_wasted_sev Percentage of children under-5 with a Weight-for-Height z-score <-3 standard deviations from the New 407 reference median (z-score calculated using WHO 2006 Child Growth Standards) Adult chronic conditions a_hi_bp140_or Percentage of adult population with high blood pressure or on treatment for high blood pressure (age range 95 115 _on_med may vary) a_hi_chol_5_1 Percentage of adult population with high cholesterol or on treatment for high cholesterol (age range may 32 43 90_or_on_med vary) s a_hiv Percentage of population age 15–49 who had blood tests that are positive for HIV1 or HIV2 54 59 a_bp_dial Mean diastolic blood pressure (mmHg) in adult population (age range may vary) 100 112 a_bp_sys Mean systolic blood pressure (mmHg) in adult population (age range may vary) 100 112 a_chol_mmol_ Mean cholesterol (mmol/L) in adult population (age range may vary) 62 70 L a_gluc_mm Mean fasting blood glucose (mmol/L) in adult population (age range may vary) 51 57 a_imp_glyc Percentage of adult population with impaired fasting glycaemia (age range may vary) 54 61 Childhood infectious disease c_ari Percentage of children under-5 with cough and rapid breathing from the chest in the two weeks preceding New 327 the survey c_diarrhea Percentage of children under-5 with diarrhea in the two weeks preceding the survey New 512 c_fever Percentage of children under-5 with fever in the two weeks preceding the survey New 300 c_illness Diarrhea, respiratory infection, or fever, under-5 New 326 Childhood mortality c_u1mr Deaths of children before their 1st birthday per 1,000 live births. Sample: children born up to 5 years before 267 324 the survey for full population mortality estimates, and up to 10 years before the survey for wealth quintile specific mortality estimates c_u5mr Deaths of children before their 5th birthday per 1,000 live births. Sample: children born up to 5 years before 267 324 the survey for full population mortality estimates, and up to 10 years before the survey for wealth quintile specific mortality estimates Service coverage Adult chronic conditions and inpatient care 28 # of # of data data Variable point Description points name s in in v202 v2019 2 a_bp_meas_1 Percentage of population over 18 having their blood pressure measured by health professional in the last 43 43 yr year a_bp_treat Percentage of adult population being treated for high blood pressure (age range may vary) 63 74 a_chol_meas Percentage of adult population at risk (overweight or obese and older than 20, male and older than 34) 47 47 having their cholesterol levels measured in the last 5 years a_diab_treat Percentage of adult population being treated for raised blood glucose or diabetes (age range may vary) 60 61 a_gluc_meas2 Percentage of population aged 40–69 at increased risk of diabetes (overweight, obese) having their blood 40 40 sugar measured in the last 5 years a_inpatient_1y Percentage of population age 18 and older using inpatient care in the last 12 months 458 457 r w_mam_2y Percentage of women who received a mammogram in the last 2 years (preferably age 50–69 but age 244 244 groups may vary) w_pap_3y Percentage of women who received a pap smear in the last 3 years (preferably age 20-–69 but age groups 296 298 may vary) Family planning w_condom_co Percentage of women aged 18–49 who had more than one sexual partner in the last 12 months and used 110 94 nc a condom during last intercourse w_CPR Percentage of women aged 15–49 who are married or live in union and currently use a modern method of 368 295 contraception. Modern methods are defined as female sterilization, male sterilization, the contraceptive pill, intrauterine contraceptive device (IUD), injectables, implants, female condom, male condom, diaphragm, contraceptive foam and contraceptive jelly, lactational amenorrhea method (LAM), emergency contraception, country-specific modern methods and other modern contraceptive methods respondent mentioned. w_metany_fp Percentage of women aged 15–49 who are married or live in union who do not want to become pregnant New 267 and are using contraceptive methods, including traditional ones (revised definition by Bradley 2012) w_metmod_fp Percentage of women aged 15–49 who are married or live in union who do not want to become pregnant New 267 and are using modern contraception w_unmet_fp Percentage of women aged 15–49 who are married or live in union who do not want to become pregnant 226 268 but are not using contraception (revised definition by Bradley 2012) Maternal care c_anc Percentage of most recent births in last two years with at least 4 antenatal care visits (women age 15–49 at 355 426 the time of the survey) c_anc_any Percentage of most recent births in last two years with at least one antenatal care check New 457 c_anc_ear Percentage of most recent births in last two years where women received first antenatal care check in first New 348 trimester c_anc_eff Percentage of most recent births in last two years where women received at least four antenatal care New 310 checks, any checks with skilled provider, and blood pressure, blood sample, and urine sample taken c_anc_eff_q Of births in last two years with at least one antenatal care check, percentage with at least four antenatal New 310 care checks, any checks with skilled provider, and blood pressure, blood sample, and urine sample taken c_facdel Percentage of most recent births in last two years which took place in a formal health facility New 428 c_hospdel Percentage of most recent births in last two years which took place in a hospital New 425 c_sba Percentage of most recent births in last two years attended by any skilled health personnel (women age 415 505 15–49 at the time of the survey). Definition of skilled varies by country and survey but always includes doctor, nurse, midwife, and auxiliary midwife). c_sba_eff1 Percentage of most recent births in last two years attended by any skilled health personnel, taking place in New 187 a formal health facility, with both mother and child staying in the facility for 24h or more and breastfeeding initiated within 1 hour of birth. Definition of skilled varies by country and survey but always includes doctor, nurse, midwife, and auxiliary midwife). c_sba_eff1_q Of births in the last two years attended by any skilled health personnel, percentage which took place in a New 187 formal health facility, with both mother and child staying in the facility for 24h or more and breastfeeding initiated within 1 hour of birth. Definition of skilled varies by country and survey but always includes doctor, nurse, midwife, and auxiliary midwife). c_pnc_any Percentage of most recent births in last two years where mother or child receive postnatal care in first six New 193 weeks c_pnc_eff Percentage of most recent births in last two years where mother and child receive postnatal care in first 24 New 188 hours from a skilled health worker c_pnc_eff_q Of most recent births in last two years where mother or child received any postnatal care in first six weeks, New 188 percentage where mother and child receive postnatal care in first 24 hours from a skilled health worker Childhood infectious disease c_ARItreat Percentage of children under-5 with cough and rapid breathing which originated from the chest in the two 339 262 weeks preceding the survey who visited a formal health care provider (excluding pharmacies). The definition of formal health care providers varies by country and data source. Variable was called c_treatARI in previous HEFPI version. c_diarrheaOR Percentage of children under-5 with diarrhea in the 2 weeks before the survey who were given oral 358 451 S rehydration salts (ORS). Variable was called c_treatdiarrhea in previous HEFPI version. c_diarrheatreat Percentage of children under-5 with diarrhea in the two weeks preceding the survey who visited a formal New 339 health care provider (excluding pharmacies). The definition of formal health care providers varies by country and data source. c_fevertreat Percentage of children under-5 with fever in the two weeks preceding the survey who visited a formal New 229 health care provider (excluding pharmacies). The definition of formal health care providers varies by country and data source. 29 # of # of data data Variable point Description points name s in in v202 v2019 2 c_illtreat Percentage of children under-5 with fever, diarrhea, and/or acute respiratory infection in the two weeks New 237 preceding the survey who visited a formal health care provider (excluding pharmacies). The definition of formal health care providers varies by country and data source. c_ITN Percentage of children under-5 who slept under an insecticide treated bed net (ITN) the night before the 118 149 survey. A bed net is considered treated if it (a) is a long-lasting treated net, (b) a pretreated net that was purchased or soaked in insecticides less than 12 months ago, or (c) a non-pretreated net that was soaked in insecticides less than 12 months ago Childhood vaccination c_fullimm Percentage of children aged 15–23 months who received Bacillus Calmette-Guerin (BCG), 381 466 measles/Measles-Mumps-Rubella (MMR), 3 doses of polio (excluding polio given at birth) and 3 doses of diphtheria-pertussis-tetanus (DPT)/Pentavalent vaccinations, either verified by vaccination card or by recall of respondent c_measles_va Percentage of children aged 15–23 months who received measles or MMR vaccination, either verified by 406 499 cc vaccination card or by recall of respondent c_vaczero Percentage of children aged 15–23 months who received none of 8 essential vaccines at birth (Bacillus New 456 Calmette-Guerin (BCG), measles/Measles-Mumps-Rubella (MMR), 3 doses of polio (excluding polio given at birth) and 3 doses of diphtheria-pertussis-tetanus (DPT)/Pentavalent vaccinations, either verified by vaccination card or by recall of respondent) Source: 2022 HEFPI database. Note: v2019 and v2022 indicate the 2019 and 2022 versions of the HEFPI database. 30 This paper outlines changes that have been made for the third version of the World Bank’s Health Equity and Financial Protection Indicators (HEFPI) database launched in 2022. Across all indicators, subpopulation breakdowns by urban and rural place of residence and subnational region were added. On the financial protection side, the number of indicators further expanded to 31, reflecting a broadening of the definition of medical impoverishment from being limited to those pushed below the poverty line by medical spending to also include those already under the poverty line who incur any medical spending—that is, those “further impoverished” by medical spending. The additional financial protection indicators also include indicators that show the intersection of catastrophic and impoverishing health spending, that is, identify the populations exposed to both types of financial hardship simultaneously. The health equity side of the database now includes 19,820 country-level data points from 1,318 surveys across 35 service coverage and 38 health outcome indicators. An upgraded data visualization portal was launched alongside the new dataset ABOUT THIS SERIES: This series is produced by the Health, Nutrition, and Population Global Practice of the World Bank. The papers in this series aim to provide a vehicle for publishing preliminary results on HNP topics to encourage discussion and debate. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the World Bank, to its affiliated organizations or to members of its Board of Executive Directors or the countries they represent. Citation and the use of material presented in this series should take into account this provisional character. 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