The statistic shows the total population of the United Arab Emirates (UAE) from 2020 to 2030. In 2023, approximately 10.68 million inhabitants lived in the UAE. Population of the United Arab Emirates The United Arab Emirates (UAE) have undergone extreme demographic changes over the past decade. With the increasing developments, tourism and global recognition of cities in the UAE like Abu Dhabi and Dubai, it is to no surprise that the total population has grown by about 6 million people over the past decade. However, the majority of the total population of the UAE are expatriates. Any expatriate having lived in the UAE for a minimum of 20 years can apply for a citizenship, consequently, the growing total population is mainly due to the growing number of expatriates who become citizens and the high number of immigrants which gives the UAE the world’s highest net migration rate. This becomes evident when looking at the fertility rate, the average rate of children born per fertile woman in a year in the UAE, which has been steadily declining over the last decade. Life expectancy, however, has been increasing steadily over the same time span. It is interesting to note that, despite this increase, total population of the UAE consists mainly of people between the ages of 15 to 64, another fact pointing towards expatriates and immigrants contributing to the increasing numbers.

The death rate in the United Arab Emirates decreased to 0.93 deaths per 1,000 inhabitants compared to the previous year. The death rate thereby reached its lowest value in recent years. The crude death rate is the annual number of deaths in a given population, expressed per 1,000 people. When looked at in unison with the crude birth rate, the rate of natural increase can be determined.Find more statistics on other topics about the United Arab Emirates with key insights such as total life expectancy at birth, total fertility rate, and number of tuberculosis infections .

The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

The total fertility rate in the United Arab Emirates increased by 0.1 children per woman (+8.7 percent) compared to the previous year. In total, the fertility rate amounted to 1.2 children per woman in 2023. This increase was preceded by a declining fertility rate.Total fertility rates refer to the average number of children that a woman of childbearing age (generally considered 15 to 44 years) can expect to have throughout her reproductive years. Unlike birth rates, which are based on the actual number of live births in a given population, fertility rates are hypothetical (similar to life expectancy), as they assume that current patterns in age-specific fertility will remain constant throughout a woman's reproductive years.Find more statistics on other topics about the United Arab Emirates with key insights such as crude birth rate, number of tuberculosis infections , and total life expectancy at birth.

United Arab Emirates (UAE) Vegetable and Fruit Market size was valued at USD 427.33 Million in 2024 and is expected to reach USD 612.38 Million by 2032, growing at a CAGR of 4.60% from 2026-2032.

United Arab Emirates (UAE) Vegetable and Fruit Market Drivers

High Dependence on Imports: Due to the UAE's arid climate, limited arable land, and water scarcity, the country heavily relies on imports to meet its demand for fresh fruits and vegetables. This makes it a significant market for global exporters.

Strong Purchasing Power and High Disposable Income: The UAE has a high per capita income, leading to strong consumer spending on food, including high-quality and diverse fruits and vegetables. This allows for the importation of a wide variety of produce from around the world.

Food Security Initiatives: The UAE government prioritizes food security and has launched the National Food Security Strategy 2051. This strategy aims to enhance local food production through modern technologies, diversify import sources, and establish international partnerships. While focused on increasing domestic output, it also ensures a stable supply through imports.

Increasing Health Consciousness: A growing segment of the UAE population is becoming more health-conscious, leading to increased demand for fresh, organic, and nutritious food products, including fruits and vegetables.

Diverse Expatriate Population: The UAE has a large and diverse expatriate population with varied culinary preferences, driving demand for a wide range of fruits and vegetables to cater to different cultural and dietary needs.

Growth of the Tourism and Hospitality Sector: The thriving tourism and hospitality industries create a significant demand for consistent supplies of high-quality fruits and vegetables for hotels, restaurants, and catering services.

The ethnic composition of the population of a country contributes to the uniqueness of each national DNA sequencing project and, ideally, individual reference genomes are required to reduce the confounding nature of ethnic bias. This work represents a representative Whole Genome Sequencing effort of an understudied population. Specifically, high coverage consensus sequences from 120 whole genomes and 33 whole exomes were used to construct the first ever population specific major allele reference genome for the United Arab Emirates (UAE). When this was applied and compared to the archetype hg19 reference, assembly of local Emirati genomes was reduced by ∼19% (i.e., some 1 million fewer calls). In compiling the United Arab Emirates Reference Genome (UAERG), sets of annotated 23,038,090 short (novel: 1,790,171) and 137,713 structural (novel: 8,462) variants; their allele frequencies (AFs) and distribution across the genome were identified. Population-specific genetic characteristics including loss-of-function variants, admixture, and ancestral haplogroup distribution were identified and reported here. We also detect a strong correlation between FST and admixture components in the UAE. This baseline study was conceived to establish a high-quality reference genome and a genetic variations resource to enable the development of regional population specific initiatives and thus inform the application of population studies and precision medicine in the UAE.

This statistic illustrates the distribution of adult population in the United Arab Emirates in 2019 by wealth range group. That year, approximately **** percent of adults in the United Arab Emirates had wealth of 10,000 to 100,000 U.S. dollars.

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Education Market in United Arab Emirates Size 2024-2028

The UAE education market size is forecast to increase by USD 5.41 billion at a CAGR of 9.46% between 2023 and 2028.

United Arab Emirates Education Market is experiencing significant growth, driven by increasing student enrollments and rising awareness of early education. The number of students in the UAE's educational institutions has seen a steady rise, with over 1.2 million students enrolled in various schools and universities in 2020. This trend is expected to continue, fueled by the government's investment in edtech infrastructure and initiatives to promote access to quality education. The future of education lies in digital transformation, with e-learning platforms, STEM education, and coding education gaining popularity.However, this growth comes with challenges. The cost of education in the UAE has been increasing, making it a significant barrier for many families.
The tuition fees in private schools have risen by an average of 5% annually over the past five years. This trend is expected to continue, putting pressure on families and institutions alike. Additionally, there is a need for more affordable education options to cater to the growing student population and address the affordability issue. Companies seeking to capitalize on market opportunities in the UAE's Education Market should focus on providing affordable and quality education solutions while navigating the increasing competition and education costs.

What will be the Size of the United Arab Emirates Education Market during the forecast period?

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The United Arab Emirates Education Market continues to evolve, with digital textbooks and student assessment playing increasingly significant roles. Student engagement and success are at the forefront of educational initiatives, driving the adoption of virtual classrooms and online learning. Educational technology, including language learning platforms and online assessment tools, facilitates personalized learning experiences. Public schools undergo education reform, integrating digital learning resources and curriculum development. Artificial intelligence and cloud computing are transforming educational research, enabling data analytics and teacher training.
Innovation in education is evident in the adoption of educational software, educational data, and learning analytics. Vocational training, adaptive learning, and mobile learning cater to various skill development needs. Higher education institutions embrace digital transformation, with learning management systems and blended learning strategies. Early childhood education and adult education also undergo digital transformation, with interactive learning experiences and distance education gaining traction. Investment in education remains a priority, with a focus on accessibility and inclusivity. Augmented reality and virtual reality technologies offer immersive learning experiences, enhancing the overall educational landscape.

How is this United Arab Emirates Education Industry segmented?

The United Arab Emirates education industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

End-user

  K-12
  Higher education
  Vocational education


Ownership

  Private education
  Public education


Type

  Traditional Education
  Online Learning
  Blended Learning


Curriculum

  International
  Local
  Specialized Programs


Geography

By End-user Insights

The k-12 segment is estimated to witness significant growth during the forecast period.

The UAE K-12 Education Market is characterized by a diverse landscape of international and local private and public schools. Fueled by the country's thriving economy, a large expatriate population, and the increasing demand for English-medium, high-quality education among both local Emiratis and expatriates, this segment of the education market is experiencing continuous growth. Furthermore, the UAE government's commitment to ensuring unlimited enrollment of local children in international schools is expected to further bolster the expansion of the K-12 education sector. Innovative educational approaches, such as digital textbooks, student assessment, and personalized learning, are increasingly gaining popularity in UAE classrooms.

Educational technology, including virtual classrooms, online learning, and e-learning platforms, is transforming the learning experience for students. Artificial intelligence, machine learning, and data analytics are being integrated into curriculum development to enhance student skill development and learning outcomes. The UAE's education reform initiatives, focusing on teacher training, stem education, and coding education, are designed to prepa

CYP2D6 belongs to the cytochrome P450 superfamily of enzymes and plays an important role in the metabolism of 20–25% of clinically used drugs including antidepressants. It displays inter-individual and inter-ethnic variability in activity ranging from complete absence to excessive activity which causes adverse drug reactions and toxicity or therapy failure even at normal drug doses. This variability is due to genetic polymorphisms which form poor, intermediate, extensive or ultrarapid metaboliser phenotypes. This study aimed to determine CYP2D6 alleles and their frequencies in the United Arab Emirates (UAE) local population. CYP2D6 alleles and genotypes were determined by direct DNA sequencing in 151 Emiratis with the majority being psychiatric patients on antidepressants. Several new alleles have been identified and in total we identified seventeen alleles and 49 genotypes. CYP2D6*1 (wild type) and CYP2D6*2 alleles (extensive metaboliser phenotype) were found with frequencies of 39.1% and 12.2%, respectively. CYP2D6*41 (intermediate metaboliser) occurred in 15.2%. Homozygous CYP2D6*4 allele (poor metaboliser) was found with a frequency of 2% while homozygous and heterozygous CYP2D6*4 occurred with a frequency of 9%. CYP2D6*2xn, caused by gene duplication (ultrarapid metaboliser) had a frequency of 4.3%. CYP2D6 gene duplication/multiduplication occurred in 16% but only 11.2% who carried more than 2 active functional alleles were considered ultrarapid metabolisers. CYP2D6 gene deletion in one copy occurred in 7.5% of the study group. In conclusion, CYP2D6 gene locus is heterogeneous in the UAE national population and no significant differences have been identified between the psychiatric patients and controls.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Whole genome sequences (WGS) of four nationals of the United Arab Emirates (UAE) at an average coverage of 33X have been completed and described. The selection of suitable subpopulation representatives was informed by a preceding comprehensive population structure analysis. Representatives were chosen based on their central location within the subpopulation on a principal component analysis (PCA) and the degree to which they were admixed. Novel genomic variations among the different subgroups of the UAE population are reported here. Specifically, the WGS analysis identified 4,161,067–4,798,806 variants in the four individual samples, where approximately 80% were single nucleotide polymorphisms (SNPs) and 20% were insertions or deletions (indels). An average of 2.75% was found to be novel variants according to dbSNP (build 151). This is the first report of structural variants (SV) from WGS data from UAE nationals. There were 15,677–20,339 called SVs, of which around 13.5% were novel. The four samples shared 1,399,178 variants, each with distinct variants as follows: 1,085,524 (for the individual denoted as UAE S011), 1,228,559 (UAE S012), 791,072 (UAE S013), and 906,818 (UAE S014). These results show a previously unappreciated population diversity in the region. The synergy of WGS and genotype array data was demonstrated through variant annotation of the former using 2.3 million allele frequencies for the local population derived from the latter technology platform. This novel approach of combining breadth and depth of array and WGS technologies has guided the choice of population genetic representatives and provides complementary, regionalized allele frequency annotation to new genomes comprising millions of loci.

The Red Meat Market in United Arab Emirates size was valued at USD 789.11 Million in 2023 and is projected to reach USD 860.64 Million by 2032, exhibiting a CAGR of 4.20 % during the forecasts periods. The red meat market in the United Arab Emirates (UAE) covers the production, import, distribution and consumption of red meat, including beef, lamb, mutton and goat. This market is an integral part of the food industry in the UAE and is driven by a growing population, growing wealth and a diverse expatriate community with different eating habits. Due to limited local production, the UAE relies heavily on imports to meet demand for red meat. The main suppliers are Australia, India, Brazil and the United States, which bring high quality meat products to the market. The UAE government supports the industry with strict quality standards and certifications to ensure food safety and halal compliance. In recent years, there has been a significant shift towards high-quality and organic meat products, reflecting the trend towards healthier and more sustainable consumption patterns. In addition, the market benefits from a strong distribution network that includes supermarkets, hypermarkets, specialty meat shops and a growing online shopping sector. This comprehensive framework supports the UAE's position as a key player in the regional red meat market. Recent developments include: February 2023: Saudi-based Tanmiah Food Company and US-based Tyson Foods Inc. renewed their partnership signed previously in 2022. The partnership was signed in order to recognize the potential growth opportunities across Saudi Arabia and the broader Middle East.July 2022: Tanmiah Food Company and Tyson Foods entered a strategic partnership to expand meat production capacity. The investment is expected to enable Tanmiah Food Company to access the high demand for protein in the Middle East and other international markets.December 2021: Tanmiah Food Company’s wholly owned subsidiary Gulf Brand Fast Food Co. signed a master franchise and development agreement with Popeyes, an international quick service restaurant chain, to diversify across the value chain by offering high-quality food options, including Popeyes Chicken Sandwich made from fresh and locally sourced fresh chicken.. Key drivers for this market are: Escalating Demand for Processed Poultry Products, Favorable Government Initiatives to Boost Production. Potential restraints include: Rising Vegan Trend among Young Consumers, Deeper Penetration of Red Meat Across Saudi Arabia. Notable trends are: OTHER KEY INDUSTRY TRENDS COVERED IN THE REPORT.

The total life expectancy at birth in the United Arab Emirates increased by 2.4 years (+2.98 percent) in 2023. With 82.91 years, the life expectancy at birth thereby reached its highest value in the observed period. These figures refer to the expected lifespan of the average newborn in a given country or region, providing that mortality patterns at the time of birth remain constant thereafter.Find more statistics on other topics about the United Arab Emirates with key insights such as number of tuberculosis infections , crude birth rate, and total fertility rate.

In general, foreign direct investments (FDIs) play a crucial role in driving a country’s economic development, promoting diversification, and enhancing competitiveness. The Gulf Cooperation Council (GCC) countries, which heavily rely on the oil and gas sectors, are particularly vulnerable to fluctuations in commodity prices. However, these countries have recognized the imperative of economic diversification and have increasingly turned to inward FDIs to achieve it. By attracting capital, advanced technology, and expertise from foreign investors, FDIs enable the GCC countries to expand their economic base beyond the oil and gas sectors. This diversification not only creates employment opportunities but also fosters resilient economic growth, ultimately leading to an improvement in the living standards of the local population. This study investigates the macroeconomic and environmental factors that potentially attract foreign direct investment (FDI) inflows into the Gulf Cooperation Council (GCC) countries in the long run. Additionally, the study explores the causal relationship between these factors and FDI inflows. The panel autoregressive distributed lag (ARDL) approach to co-integration is the primary analytical technique used, utilizing long time-series data from six GCC countries, including Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE) during the period 1990–2019. The empirical results indicate that, in the long run, almost all independent variables significantly influence FDI in GCC countries. Variables such as GDP growth (GDPG), inflation (INFL), carbon dioxide emissions (CO2), and urbanization (URB) are found to be highly significant (p≤0.01) in their impact on FDI. Moreover, unemployment (UNEMP) also positively and significantly influences FDI in these countries in the long run. Based on the key findings, strategies aimed at reducing persistently high unemployment rates, maintaining population growth, viewing FDI as a driver for GDP growth, and continuing with infrastructure development and urbanization are expected to attract more FDI inflows into GCC countries in the long run. Additionally, fostering both long-term economic incentives and creating a conducive business infrastructure for investors are vital for attracting inward FDI into any nation, including those in the GCC. This research would benefit various stakeholders, including governments, local businesses, investors, academia, and the local society, by providing valuable knowledge and informing decision-making processes related to economic development, diversification, and investment promotion.

BackgroundFor more than half a century, there has been much research and controversies on how to accurately screen for and diagnose gestational diabetes mellitus (GDM). There is a paucity of updated research among the Emirati population in the United Arab Emirates (UAE). The lack of a uniform GDM diagnostic criteria results in the inability to accurately combine or compare the disease burden worldwide and locally. This study aimed to compare the incidence of GDM in the Emirati population using six diagnostic criteria for GDM.MethodsThe Mutaba’ah study is the largest multi-center mother and child cohort study in the UAE with an 18-year follow-up. We included singleton pregnancies from the Mutaba’ah cohort screened with the oral glucose tolerance test (OGTT) at 24–32 weeks from May 2017 to March 2021. We excluded patients with known diabetes and with newly diagnosed diabetes. GDM cumulative incidence was determined using the six specified criteria. GDM risk factors were compared using chi-square and t-tests. Agreements among the six criteria were assessed using kappa statistics.ResultsA total of 2,546 women were included with a mean age of 30.5 ± 6.0 years. Mean gravidity was 3.5 ± 2.1, and mean body mass index (BMI) at booking was 27.7 ± 5.6 kg/m2. GDM incidence as diagnosed by any of the six criteria collectively was 27.1%. It ranged from 8.4% according to the EASD 1996 criteria to 21.5% according to the NICE 2015 criteria. The two most inclusive criteria were the NICE 2015 and the IADPSG criteria with GDM incidence rates of 21.5% (95% CI: 19.9, 23.1) and 21.3% (95% CI: 19.8, 23.0), respectively. Agreement between the two criteria was moderate (k = 0.66; p < 0.001). The least inclusive was the EASD 1996 criteria [8.4% (95% CI: 7.3, 9.6)]. The locally recommended IADPSG/WHO 2013 criteria had weak to moderate agreement with the other criteria, with Cohen’s kappa coefficient ranging from (k = 0.51; p < 0.001) to (k = 0.71; p < 0.001). Most of the GDM risk factors assessed were significantly higher among those with GDM (p < 0.005) identified by all criteria.ConclusionsThe findings indicate discrepancies among the diagnostic criteria in identifying GDM cases. This emphasizes the need to unify GDM diagnostic criteria in this population to provide accurate and reliable incidence estimates for healthcare planning, especially because the agreement with the recommended criteria was not optimal.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was a multi-stage random probability sample representative of the population residing in the U.A.E. The sample structure was based on the estimated population structure from the UAE Census data of 1995. The estimates for various categories that are excluded from the sample were compiled using information from the UAE census. The categories of workers excluded from the sample and from projected population estimates include: • Domestic helpers, servants, drivers etc., which are principally of Asian ethnic origin. • Building watchmen, usually consisting of Egyptians, Sudanese, as well as some Pakistanis and Indians. • Laborers in camps, or on sites such as construction workers, and service workers in facilities such as public transport, airport cleaning services, hospital cleaning services, etc. They are predominantly men, the majority of whom are of a low literacy level, and mostly unskilled.

The sampling system design employed in all the Emirates was an advanced sample design method. The survey did not cover any irregular, casual or provisional shacks or shelters. Interviews were conducted with people living only within legal households.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

The size of the United Arab Emirates Drug Delivery Devices Market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 20.00% during the forecast period.The United Arab Emirates drug delivery devices market holds much promise in the context of this high prevalence of chronic diseases and the increasing geriatric population. It grows significantly due to increasing expenditure in the healthcare sector. Innovative drug delivery devices were specifically designed to deliver medicines at the target site itself for enhanced therapeutic efficacy while lowering the side effects caused. Such devices have total control over the release of the drug, which maximizes the dose while maintaining a minimal level of systemic exposure. The UAE is a promising drug delivery device market, particularly with a well-developed healthcare infrastructure and state of the art medical technology in the country. Demand in the country for drug delivery is increasing due to the continuously expanding population and the emerging awareness of health care services. This is furthered through the initiatives of the government pertaining to health care innovation and through foreign investments. The important segments under the umbrella of drug delivery devices in UAE are insulin delivery devices, inhalers, infusion pumps, and transdermal patches. The primary segments for insulin delivery devices mainly comprise pen injectors as well as insulin pumps which are experiencing a tremendous amount of growth because of high disease prevalence among the population due to diabetes. It is also going through a growth phase as individuals increasingly use inhalers during treatment for respiratory conditions that have been on an expansion spurt due to increasingly rising pollution levels within this country. Infusion pumps, which are used for the precise delivery of drugs, have applications in many therapies such as oncology and pain management. Transdermal patches in which drugs are released for longer periods are being increasingly applied as they are easy on the patient and convenient in nature. This, in turn, will push the growth of the market for drug delivery devices as the UAE focuses more on medical advancement. Emerging technologies like wearable drug delivery systems and implantable devices will likely lead to promising futures. Recent developments include: October 2022: Abu Dhabi Medical Devices Company, the Abu Dhabi Ports Group, and Abu Dhabi Polymers Company partnered with PureHealth, for AED 260 million (USD 70.79 million) to manufacture medical equipment, such as medical syringes, administration devices, and blood collection tubes, locally., June 2022: ADQ, an Abu Dhabi investment company, acquired Birgi Mefar Group (BMG) to boost the United Arab Emirates' ability to manufacture sterile injectable products such as vials and pre-filled syringes.. Key drivers for this market are: Rising Prevalence of Chronic Diseases and Growth in the Biologics Market, Increased Understanding of Drug Metabolism and Growing Requirement of Controlled Drug Release and Technological Advancements. Potential restraints include: High Cost of Development, Regulatory Concern and Risk of Needlestick Injuries. Notable trends are: Oral Segment Expects to Register a High CAGR in the United Arab Emirates Drug Delivery Devices Market Over the Forecast Period.

This statistic shows the degree of urbanization in the Mashriq countries in 2024. The Mashriq, also Mashreq, is the region encompassing the eastern part of the Arab World, comprising the countries Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Oman, Palestine, Qatar, Saudi Arabia, Sudan, Syria, United Arab Emirates, and Yemen. Urbanization is defined as the share of urban population in the total population. In 2024, 92.21 percent of the total population of Jordan lived in urban areas.

From 2015 to 2020, the forecasted net migration rate per 1,000 population in the United Arab Emirates (UAE) was 4.2, down from 6.1 between 2010 and 2015. The net number of migrants in the UAE reached 200 thousand from 2015 to 2020.

From 2015 to 2020, the rate of natural increase per thousand population in the United Arab Emirates reached 8.9 percent, down from 9.9 percent between 2010 and 2015. The total population of the UAE was estimated to reach around 9.9 million inhabitants in 2020.