In the health index 2023, Singapore ranked first with a score of ****, followed by Japan and South Korea. Afghanistan had a health index score of **** that year. The health index measures the extent to which people are healthy and have access to the necessary services to maintain good health, including health outcomes, health systems, illness and risk factors, and mortality rates.

The current healthcare spending in Southeast Asia was forecast to continuously increase between 2024 and 2029 by in total 98.6 billion U.S. dollars (+52.88 percent). After the fifteenth consecutive increasing year, the spending is estimated to reach 285 billion U.S. dollars and therefore a new peak in 2029. Notably, the current healthcare spending of was continuously increasing over the past years.According to Worldbank health spending includes expenditures with regards to healthcare services and goods. The spending refers to current spending of both governments and consumers.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending in countries like Central Asia and Southern Asia.

Schedule Health Index for Highway Programs Market Outlook

According to our latest research, the global Schedule Health Index for Highway Programs market size in 2024 reached USD 1.42 billion, driven by the growing emphasis on project efficiency and risk mitigation in large-scale infrastructure development. The market is experiencing a robust compound annual growth rate (CAGR) of 10.3% and is forecasted to reach USD 3.38 billion by 2033. This growth is primarily propelled by the increasing adoption of advanced analytics and digital tools in highway construction and management, as well as stringent regulatory requirements for project transparency and accountability.

The primary growth factor for the Schedule Health Index for Highway Programs market is the escalating demand for improved project delivery outcomes in the global highway construction sector. Governments and private sector stakeholders are increasingly recognizing the value of schedule health indices (SHI) in proactively identifying schedule risks, monitoring project milestones, and ensuring timely completion of complex highway infrastructure projects. The integration of SHI solutions enables project managers to gain real-time insights into schedule performance, detect potential delays, and implement corrective actions early in the project lifecycle. This proactive approach is particularly critical in megaprojects where delays can result in substantial financial losses and public inconvenience. Moreover, the rising complexity of highway programs, with multiple contractors and interdependent tasks, necessitates robust schedule management tools, further fueling market expansion.

Another significant driver is the rapid advancement in digital technologies such as artificial intelligence, machine learning, and cloud computing, which are being increasingly incorporated into SHI solutions. These technologies enhance the accuracy and predictive capabilities of schedule health assessments, allowing for more nuanced risk evaluation and performance analytics. The adoption of cloud-based platforms, in particular, facilitates seamless collaboration among geographically dispersed project teams and stakeholders, streamlining data sharing and decision-making processes. Additionally, the growing trend towards smart infrastructure and digital twins in highway management is creating new opportunities for SHI providers to offer integrated solutions that combine schedule analytics with asset management and predictive maintenance features.

The market is also benefiting from stringent regulatory frameworks and compliance mandates that require greater transparency and accountability in public infrastructure projects. Regulatory bodies and funding agencies are increasingly mandating the use of schedule health indices as part of project monitoring and reporting protocols. This trend is especially pronounced in regions with significant public investment in highway infrastructure, such as North America, Europe, and parts of Asia Pacific. The need to demonstrate compliance with project timelines, budget constraints, and quality standards is compelling both government agencies and private contractors to adopt SHI solutions as a standard practice in project management. Furthermore, the emphasis on sustainability and lifecycle management in infrastructure projects is driving the integration of SHI with environmental and social impact assessments, expanding the scope and utility of these tools.

From a regional perspective, North America currently dominates the Schedule Health Index for Highway Programs market, accounting for over 38% of the global market share in 2024. This stronghold is attributed to the region's advanced highway infrastructure, high digital adoption rates, and stringent project governance standards. Europe follows closely, with significant investments in cross-border transport corridors and a strong focus on compliance and performance analytics. The Asia Pacific region is witnessing the fastest growth, with a projected CAGR of 12.1% through 2033, driven by massive infrastructure development initiatives in China, India, and Southeast Asia. Latin America and the Middle East & Africa are gradually emerging as promising markets, supported by increasing government spending on transportation infrastructure and the modernization of project management practices.

Component Analysis

The

The data about women's literacy and children's mortality rate across 11 countries in Southeast Asia from 1991 to 2020

This dataset presents the number of neonatal deaths per 1,000 live births, using data from the UNICEF Data Warehouse. Neonatal mortality refers to the death of a baby within the first 28 days of life and is a critical indicator of newborn health and health system performance. Monitoring this rate supports efforts to improve the quality of care around birth and during the early postnatal period, and to reduce preventable newborn deaths through timely, skilled interventions.Data Source:UNICEF Data Warehouse: https://data.unicef.org/resources/data_explorer/unicef_f/?ag=UNICEF&df=GLOBAL_DATAFLOW&ver=1.0&dq=.CME_MRM0.&startPeriod=1990&endPeriod=2024Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hubthe following codes are also possible values:not reported does not apply don’t knowThis is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.

This data explain the process of screening and analysis for the systematic review entitled Personal recovery on people with psychosis in Southeast Asia: A systematic review and narrative synthesis

The current health expenditure as a share of the GDP in Southeast Asia was forecast to continuously increase between 2024 and 2029 by in total *** percentage points. After the seventh consecutive increasing year, the share is estimated to reach **** percent and therefore a new peak in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Central Asia and Western Asia.

Asset Health Index for Substation Equipment Market Outlook

According to our latest research, the Global Asset Health Index for Substation Equipment market size was valued at $2.4 billion in 2024 and is projected to reach $6.9 billion by 2033, expanding at a robust CAGR of 12.5% during the forecast period 2025–2033. The primary driver of this substantial growth is the accelerating adoption of digitalization and advanced analytics in power infrastructure, enabling utilities and industries to proactively manage substation equipment health, reduce downtime, and optimize maintenance costs. As the energy sector undergoes a paradigm shift towards smart grids and increased integration of renewable resources, the need for real-time asset health monitoring and predictive maintenance solutions is becoming ever more critical, further propelling the market’s expansion on a global scale.

Regional Outlook

North America currently holds the largest share of the Asset Health Index for Substation Equipment market, accounting for approximately 38% of the global revenue in 2024. This dominance is attributed to the region’s mature power infrastructure, high penetration of advanced grid technologies, and robust regulatory frameworks promoting grid modernization. The United States, in particular, has been at the forefront, driven by extensive investments in smart grid initiatives and a strong focus on reliability and resilience of electrical networks. The presence of major technology providers, coupled with frequent upgrades and replacements of aging substation equipment, has further accelerated the adoption of asset health index solutions. Additionally, supportive governmental policies and incentives for digital transformation in utilities have created a conducive environment for sustained market growth in North America.

The Asia Pacific region is projected to be the fastest-growing market, with an impressive CAGR of 15.1% during 2025–2033. This rapid expansion is fueled by significant infrastructure investments, urbanization, and the ongoing electrification of rural areas, especially in China, India, and Southeast Asian countries. Governments in the region are prioritizing grid stability, reliability, and efficiency, leading to increased deployment of advanced monitoring and predictive maintenance systems in substations. Furthermore, the proliferation of renewable energy projects and the integration of distributed energy resources are compelling utilities to adopt sophisticated asset management solutions. Strategic partnerships between global technology vendors and local utilities, along with favorable policy reforms, are further accelerating the adoption of asset health index solutions across the Asia Pacific.

In emerging economies across Latin America, the Middle East, and Africa, the adoption of Asset Health Index for Substation Equipment is steadily gaining momentum, albeit at a comparatively slower pace. These regions face unique challenges such as budget constraints, limited technical expertise, and the presence of legacy infrastructure, which can hinder the rapid deployment of advanced asset health solutions. However, growing awareness about the benefits of predictive maintenance, coupled with international funding and development programs, is driving gradual adoption. Localized demand for reliable power supply, especially in industrial and commercial sectors, is prompting utilities to explore cost-effective digital solutions. Policy initiatives aimed at improving grid reliability and reducing operational losses are expected to further stimulate market growth in these regions over the forecast period.

Report Scope

The current healthcare spending per capita in Southern Asia was forecast to continuously increase between 2024 and 2029 by in total 34.9 U.S. dollars (+44.57 percent). After the eleventh consecutive increasing year, the spending is estimated to reach 113.24 U.S. dollars and therefore a new peak in 2029. Depicted here is the average per capita spending, in a given country or region, with regards to healthcare. The spending refers to the average current spending of both governments and consumers per inhabitant.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current healthcare spending per capita in countries like Central Asia and Southeast Asia.

Live Tank Breaker Health Indexing Market Outlook

According to our latest research, the Global Live Tank Breaker Health Indexing market size was valued at $1.45 billion in 2024 and is projected to reach $3.62 billion by 2033, expanding at a robust CAGR of 10.7% during the forecast period of 2025 to 2033. The primary driver of this market’s growth is the increasing emphasis on grid reliability and preventive maintenance strategies by utilities and industrial operators worldwide. As the global energy infrastructure ages and the demand for uninterrupted power supply intensifies, asset managers and grid operators are turning to advanced health indexing solutions to monitor, assess, and optimize the operational performance of live tank circuit breakers. These solutions help prevent costly outages, improve safety, and extend asset lifespans, making them indispensable in modern power management ecosystems.

Regional Outlook

North America currently commands the largest share of the global Live Tank Breaker Health Indexing market, accounting for approximately 34% of total revenue in 2024. This dominance is attributed to the region’s mature utility infrastructure, strong regulatory frameworks, and early adoption of advanced grid monitoring technologies. The United States, in particular, has been at the forefront, driven by significant investments in smart grid modernization, digital substations, and asset management solutions. The presence of leading technology vendors, high awareness of asset health monitoring benefits, and stringent reliability standards have further solidified North America’s leadership in this sector. Moreover, government incentives and mandates for predictive maintenance and grid resilience have encouraged utilities and large industrial players to deploy comprehensive health indexing platforms for their live tank breakers.

Asia Pacific is projected to be the fastest-growing region, with a staggering CAGR of 13.4% from 2025 to 2033. The rapid expansion of power generation and transmission networks, especially in China, India, and Southeast Asia, is a significant growth catalyst. Governments in these regions are heavily investing in grid infrastructure upgrades and smart monitoring systems to accommodate rising electricity demand and renewable energy integration. The proliferation of new substations and the replacement of aging equipment are driving the adoption of live tank breaker health indexing solutions. Additionally, increasing awareness of operational efficiency, asset reliability, and the need to minimize unplanned outages are pushing utilities and industries to embrace these advanced diagnostic tools. Strategic partnerships with global technology providers and local system integrators are accelerating deployment rates across Asia Pacific.

Emerging economies in Latin America, the Middle East, and Africa are experiencing gradual but steady adoption of live tank breaker health indexing, albeit at a lower base. Market growth in these regions is influenced by infrastructure modernization initiatives and the need to bridge reliability gaps in power delivery. However, challenges such as limited technical expertise, budget constraints, and fragmented regulatory environments have somewhat slowed the pace of adoption. Localized demand is being shaped by urbanization, industrialization, and the increasing incidence of power outages. Governments and utilities are beginning to recognize the long-term value of asset health monitoring, but widespread implementation is often hampered by procurement hurdles and the need for tailored solutions that address specific grid conditions and operational realities.

Report Scope

List of selected 27 health-related SDG indicators.

This dataset reports the number of midwives per 10,000 population, based on data from the WHO National Health Workforce Accounts (NHWA) platform. It provides a standardised measure of workforce density, reflecting the availability of midwifery services in relation to population size. This indicator is essential for assessing health system capacity, identifying gaps in coverage, and informing policies aimed at equitable access to skilled midwifery care worldwide.Number of midwives (Midwifery Professionals + Midwifery Associate Professionals + Nurse-midwife professionals + Nurse-midwife associate professionals) per 10,000 population. Note: Data doesn't include nurse-midwives.Data Source: WHO national health workforce reporting systems: https://apps.who.int/nhwaportal/Data Dictionary:The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hubthe following codes are also possible values:not reported does not apply don’t knowThis is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.

India Foreign Tourist Arrivals: Medical Visa: South East Asia: Philippines data was reported at 1,384.000 Unit in 2014. India Foreign Tourist Arrivals: Medical Visa: South East Asia: Philippines data is updated yearly, averaging 1,384.000 Unit from Dec 2014 (Median) to 2014, with 1 observations. India Foreign Tourist Arrivals: Medical Visa: South East Asia: Philippines data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB029: Foreign Tourist Arrivals: by Visa Type: Medical Visa.

Indian Journal of Public Health Research And Development CiteScore 2024-2025 - ResearchHelpDesk - Indian Journal of Public Health Research & Development is a double blind peer-reviewed. The frequency is monthly. It deals with all aspects of Public Health including Community Medicine, Clinical Research, Epidemiology, Occupational Health, Public Health, Environmental Hazards, and Public Health Laws and covers all medical specialties concerned with research and development for the masses. The journal strongly encourages reports of research carried out within Indian continent and South East Asia. ISSN No of Indian "Journal of Public Health Research & Development" Print ISSN: 0976-0245 Online ISSN: 0976-5506 and is indexed with Index Copernicus (Poland). It is also brought to notice that the journal is being covered by many international databases. The journal is covered by EBSCO (USA), Embase, EMCare & Scopus database. The journal is now part of DST, CSIR, and UGC consortia. We have pleasure to inform you that our journal is covered for faculty promotion in relation to MCI letter dated 3-9-2015 regarding indexing of journals. This journal qualifies the criteria as it is indexed in EMBASE Scopus till date. (Proof can be submitted on request) This journal was covered by Index Copernicus till 2010. It has been again submitted to Index Copernicus and likely to cover soon.

This data used for study impact of climate change and related factor on mental health in Southeast Asia.

India Foreign Tourist Arrivals: Medical Visa: South East Asia: Singapore data was reported at 452.000 Unit in 2014. India Foreign Tourist Arrivals: Medical Visa: South East Asia: Singapore data is updated yearly, averaging 452.000 Unit from Dec 2014 (Median) to 2014, with 1 observations. India Foreign Tourist Arrivals: Medical Visa: South East Asia: Singapore data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB029: Foreign Tourist Arrivals: by Visa Type: Medical Visa.

India Foreign Tourist Arrivals: Medical Visa: South East Asia: Malaysia data was reported at 262.000 Unit in 2014. India Foreign Tourist Arrivals: Medical Visa: South East Asia: Malaysia data is updated yearly, averaging 262.000 Unit from Dec 2014 (Median) to 2014, with 1 observations. India Foreign Tourist Arrivals: Medical Visa: South East Asia: Malaysia data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under India Premium Database’s Tourism Sector – Table IN.QB029: Foreign Tourist Arrivals: by Visa Type: Medical Visa.

The current health expenditure as a share of the GDP in Southern Asia was forecast to continuously decrease between 2024 and 2029 by in total *** percentage points. According to this forecast, in 2029, the share will have decreased for the ninth consecutive year to **** percent. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Eastern Asia and Southeast Asia.

The Workload Indicators of Staffing Needs (WISN) is a tool used to estimate health workforce requirements for national or sub-national regions and health facilities. We determined the implementation of WISN for six countries in the World Health Organization South-East Asia Region (WHO-SEAR). This research ascertained whether WISN’s recommendations were adopted and operationalised after the initial assessment. This will then help policymakers identify implementation barriers and enablers for the successful implementation of WISN for the improvement of access to health workforce. We used a multi-method approach comprising qualitative, in-depth, semi-structured interviews, literature reviews and document reviews. First, we conducted a desktop review to understand the context of WISN implementation in Bangladesh, Bhutan, India, Indonesia, Nepal and Sri Lanka. Second, we interviewed a key policymaker responsible for the implementation of WISN in Sri Lanka, Bangladesh, Bhutan and India. Interviews were undertaken virtually, in English using Microsoft Teams virtual software and auto transcribed and recorded using Microsoft Teams. Literature reviews were conducted using electronic databases, documents and reports were sourced from the WHO-SEAR office and/or country of interest’s focal persons. Findings from the different methods were synthesized, triangulated and presented using four themes, namely, initial implementation, key findings, primary lessons and directions forward. This study found a high utility of WISN on informing policymakers of the health workforce needs or surplus once the service activity standards were determined. However, all the countries did not have pre-defined service standards and they did not always have the required service data or health information. For WISN to be of utility, countries need to first strengthen their health workforce information systems and digitize workload standards. Furthermore, the government treasury and the employing ministry must be involved at early stages of the planning process to ensure easy phasing in and adaptation of recommendations.

This dataset identifies whether midwives hold leadership roles within a country's national or federal Ministry of Health. It reflects the inclusion of midwifery expertise in national health policy and decision-making structures, offering insight into professional recognition, influence, and the integration of midwives in health system governance. Data Source:State of the World"s Midwifery (SoWMy) global and regional reports: https://internationalmidwives.org/resources/state-of-the-worlds-midwifery-2021/The State of the World’s Midwifery (SoWMy) series of reports, led by ICM, UNFPA, and WHO, provides country-level data on the midwifery workforce, including national midwives" associations, education, leadership, and regulation. It highlights gaps and opportunities to strengthen midwife-led care and improve maternal and newborn health outcomes. Data were collected by the International Confederation of Midwives (ICM) in collaboration with Novametrics through a global midwifery regulatory survey.Data Dictionary: The data is collated with the following columns:Column headingContent of this columnPossible valuesRefNumerical counter for each row of data, for ease of identification1+CountryShort name for the country195 countries in total – all 194 WHO member states plus PalestineISO3Three-digit alphabetical codes International Standard ISO 3166-1 assigned by the International Organization for Standardization (ISO). e.g. AFG (Afghanistan)ISO22 letter identifier code for the countrye.g. AF (Afghanistan)ICM_regionICM Region for countryAFR (Africa), AMR (Americas), EMR (Eastern Mediterranean), EUR (Europe), SEAR (South east Asia) or WPR (Western Pacific)CodeUnique project code for each indicator:GGTXXnnnGG=data group e.g. OU for outcomeT = N for novice or E for ExpertXX = identifier number 00 to 30nnn = identifier name eg mmre.g. OUN01sbafor Outcome Novice Indicator 01 skilled birth attendance Short_nameIndicator namee.g. maternal mortality ratioDescriptionText description of the indicator to be used on websitee.g. Maternal mortality ratio (maternal deaths per 100,000 live births)Value_typeDescribes the indicator typeNumeric: decimal numberPercentage: value between 0 & 100Text: value from list of text optionsY/N: yes or noValue_categoryExpect this to be ‘total’ for all indicators for Phase 1, but this could allow future disaggregation, e.g. male/female; urban/ruraltotalYearThe year that the indicator value was reported. For most indicators, we will only report if 2014 or more recente.g. 2020Latest_Value‘LATEST’ if this is the most recent reported value for the indicator since 2014, otherwise ‘No’. Useful for indicators with time trend data.LATEST or NOValueIndicator valuee.g. 99.8. NB Some indicators are calculated to several decimal places. We present the value to the number of decimal places that should be displayed on the Hub.SourceFor Caesarean birth rate [OUN13cbr] ONLY, this column indicates the source of the data, either OECD when reported, or UNICEF otherwise.OECD or UNICEFTargetHow does the latest value compare with Global guidelines / targets?meets targetdoes not meet targetmeets global standarddoes not meet global standardRankGlobal rank for indicator, i.e. the country with the best global score for this indicator will have rank = 1, next = 2, etc. This ranking is only appropriate for a few indicators, others will show ‘na’1-195Rank out ofThe total number of countries who have reported a value for this indicator. Ranking scores will only go as high as this number.Up to 195TrendIf historic data is available, an indication of the change over time. If there is a global target, then the trend is either getting better, static or getting worse. For mmr [OUN04mmr] and nmr [OUN05nmr] the average annual rate of reduction (arr) between 2016 and latest value is used to determine the trend:arr <-1.0 = getting worsearr >=-1.0 AND <=1.0 = staticarr >1.0 = getting betterFor other indicators, the trend is estimated by comparing the average of the last three years with the average ten years ago:decreasing if now < 95% 10 yrs agoincreasing if now > 105% 10 yrs agostatic otherwiseincreasingdecreasing Or, if there is a global target: getting better,static,getting worseNotesClarification comments, when necessary LongitudeFor use with mapping LatitudeFor use with mapping DateDate data uploaded to the Hub the following codes are also possible values: not reported does not apply don’t know This is one of many datasets featured on the Midwives’ Data Hub, a digital platform designed to strengthen midwifery and advocate for better maternal and newborn health services.