As of January 2025, Andalusia was the most populated autonomous community in Spain, with a total amount of approximately 8.6 million inhabitants. Catalonia and Madrid followed closely, with populations amounting to approximately eight million and seven million respectively. The population in Spain has also been analyzed by gender and autonomous community.

Andalusia, with a total number of 8.6 million inhabitants, ranked first on the list of most populous autonomous communities in Spain as of January 1st, 2025. The least populated regions of Spain were the two autonomous cities of Ceuta and Melilla, both with a population of under 90,000 inhabitants that year. The population of Spain has been increasing for many years after experiencing a downward trend between 2012 and 2015, and is projected to grow by nearly half a million by 2027. The population of Spain is dying more than being born Spain has one of the lowest fertility rate in the European Union, with barely 1.29 children per woman. According to the most recent data, more people died in Spain than were being born in 2023, with figures reaching over 434,000 deaths versus 320,000 newborns. Immigration countered this trend One of the key points to balance out this population downtrend in Spain is immigration. Spain’s immigration figures finally started to pick up in 2015 after a downward trend that presumably initiated after the 2008 financial crisis. Nevertheless, Spaniards still migrate is much larger numbers than before the crisis. According to the latest data, nationals aged between 25 and 34 years represented the largest bulk of emigrants.

As of January 2024, the Spanish-born population accounted for more than 42 million out of the national total. Foreign-born residents grew during the analyzed period of time, with over 6.5 million in 2023, while between 2014 and 2018 they amounted to less than five million. The population in Spain has also been analyzed by autonomous community, with Andalusia topping the list of the most populated regions.

In 2023, Asturias, Castilla and León, and Galicia were the Autonomous Communities that reported more than a quarter of their population aged 65 or over. The regions with the lowest reported percentage of elderly people were the Autonomous Communities of Ceuta and Melilla, with **** and **** percent, respectively.

The Islamic necropolis discovered in Tauste (Zaragoza, Spain) is the only evidence that a large Muslim community lived in the area between the 8th and 10th centuries. A multi-isotope approach has been used to investigate the mobility and diet of this medieval Muslim population living in a shifting frontier region. Thirty-one individuals were analyzed to determine δ15N, δ13C, δ18O and 87Sr/86Sr composition. A combination of strontium and oxygen isotope analysis indicated that most individuals were of local origin although three females and two males were non-local. The non-local males would be from a warmer zone whereas two of the females would be from a more mountainous geographical region and the third from a geologically-different area. The extremely high δ15N baseline at Tauste was due to bedrock composition (gypsum and salt). High individual δ15N values were related to the manuring effect and consumption of fish. Adult males were the most privileged members of society in the medieval Muslim world and, as isotope data reflected, consumed more animal proteins than females and young males.

In 2023, at least *** million people in Spain suffered from obesity. Of the total, close to ** percent were concentrated in just two autonomous communities: Catalonia and Madrid. It is worth highlighting the case of Andalusia, which despite being the most populated autonomous region in the country, only accumulates **** percent of the national total of obesity cases.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National.

Analysis unit

Household Individual

Universe

Spanish population, both sexes,18 and more years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 1209.

1) Interviewees were distributed proportionally to population in each of the 17 Autonomous Communities (Regions). 2) Interviews were then distributed, within each region, by size-categories of municipalities population. 3) Municipalities are randomly selected within each region and size category. 4) Census regions are randomly selected within each municipality. 5) Random routes are used within each census section to select building. 6) Stages and/or households are randomly selected within each building. 7) Kish tables are used to select individual within each household. The final number of clusters was 131. Lower age cut-off was set at 18 years.

Remarks about sampling: Substitution was permitted after 3-4 attempts to find at home the selected individual or after a definite refusal. All substitutions are selected within the same census section (which is the smallest census unit). The substitution rate is high, a growing problem for every institute doing face-to-face interviewing at Rs home. However, the demographic profile (even cross-tabs) of each sample is similar in all of our studies and similar to census data. Stratification factors used were: Region (17) and Size of Municipality (7 categories). Proportional distribution of interviews to population 18 years and over in both cases was then used.

Mode of data collection

Face-to-face [f2f]

Research instrument

The English official version WVS questionnaire was used.

Response rate

There were some limitations in the sample. The substitution rate is high, a growing problem for every institute doing face-to-face interviewing at R´s home. However, the demographic profile (even crosstabs) of each sample is similar in all of our studies and similar to census data. - There were selected respondent too sick/incapacitated to participate: 3 - There were selected respondent away during the survey period: 10 - No contact at selected address: 25 - No contact with selected person: 15 - Proxy refusal (on behalf of selected respondent): 10 - Personal refusal by selected respondent: 15 - Full productivity interview: 1209

Sampling error estimates

Estimated error: 2

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

The Valencian Community was the autonomous community in Spain with the highest number of museums as of mid-2025, totaling ***. This is also the fourth most populated region in the Iberian country, with more than ************ inhabitants as of 2025.

Economically Active Population Survey: Unemployment rates by nationality, sex and Autonomous Community. Quarterly. Autonomous Communities and Cities.

Background: The opioid epidemic has been extensively documented in the United States and Canada, but fewer data are available for Europe.Aim: To describe the trends in opioid use—volume of prescriptions, dosage and number of patients treated—in a Spanish population with more than 4.2 million inhabitants aged 18 years and older.Patients and Methods: Population-based cross-sectional analysis of opioid prescription in adults (≥18 years) from January 1, 2010 to December 31, 2018 in the region of Valencia, Spain. Outcomes were estimated on an annual basis: number of prescriptions, prescription rate per 100 inhabitants, dosage per capita (morphine mg equivalents, MME/c) and volume of patients treated (overall and by drug).Results: Over the study period, 2,107,756 unique patients were prescribed more than 35 million total treatments. The yearly number of treatments doubled, and total MME/c showed almost a threefold increase. Fentanyl MME/c more than tripled, accounting for 34.4% of the total MME/c in 2018. Oxycodone MME/c showed a 10-fold increase, while tapentadol, launched in 2011, showed the highest growth rates. The annual number of patients receiving at least one opioid prescription more than doubled, from 335,379 in 2010 to 722,838 in 2018.Conclusions: Even if proportions still seem far from epidemic, urgent research is warranted on the observed patterns of use, their appropriateness and their association with health and safety outcomes, especially for high-use and high-strength drugs.

The distribution of the population at risk of poverty in Spain reveals a disparity between the Northern and Southern regions. The poverty rate of all Northern regions is below the national average of **** percent. In contrast, Andalusia, Extremadura, and the autonomous cities of Melilla and Ceuta had the highest percentage of population, exceeding ** percent, at risk of poverty.

Spain ES: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data was reported at 3.200 % in 2015. This records an increase from the previous number of 2.900 % for 2014. Spain ES: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data is updated yearly, averaging 2.200 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 3.200 % in 2015 and a record low of 1.500 % in 2007. Spain ES: Poverty Headcount Ratio at $5.50 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Spain – Table ES.World Bank: Poverty. Poverty headcount ratio at $5.50 a day is the percentage of the population living on less than $5.50 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Spain ES: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 1.500 % in 2015. This stayed constant from the previous number of 1.500 % for 2014. Spain ES: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 1.200 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 1.700 % in 2013 and a record low of 0.700 % in 2007. Spain ES: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Spain – Table ES.World Bank: Poverty. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

In 2023, the geographical distribution of the population at risk of poverty in Spain shows a north-south divide. The autonomous cities of Melilla and Ceuta, together with the Andalusia, topped the list with more than ** percent of their population at risk of poverty or social exclusion. On the other hand, less than ** percent of the population of the Basque Country and Navarre were at risk.

As of January 2024, roughly 24.8 million women lived in Spain, thus outnumbering men by about 980,000. A report on expected population of EU member states forecasts the number of Spanish inhabitants growing to 49.9 million by 2050, which would make the Mediterranean nation the fourth most populated country in the EU, after Germany, France and Italy. Data relating to the population of Spain by gender and autonomous community shows the most populous region was Andalusia, with 4.4 million females and 4.2 million males, followed by the communities of Catalonia and Madrid. Moroccans made up the largest share of foreign nationals living in Spain, closely followed by Romanian nationals.

As of the first of January 2024, roughly *** million residents in Spain came from Africa, and more than half of them were male. There were approximately *** percent more female residents original from South America than males from the same region.

Andalusia was the Spanish autonomous community with the highest number of holiday rentals as of November 2024, with more than ****** in total. Andalusia is also the most populated region in the Iberian country.

In 2024, Catalonia was the most visited region by international tourists in Spain. This Spanish autonomous community ranked first thanks to the almost ** million people visiting from abroad, roughly **** million more than the visitors welcomed in the insular communities.

In July 2025, the number of women living in Spain was approximately 25.1 million, with the southern region of Andalusia featuring the highest number at over four million female residents.