In 2023, approximately 988,943 people lived in Stockholm, making it not only the capital, but also the biggest city in Sweden. The second biggest city, Gothenburg (Göteborg) had about half as many inhabitants, with about 596,840 people. Move to the citySweden is a country with a very high urbanization rate, the likes of which is usually only seen in countries with large uninhabitable areas, such as Australia, or in nations with very little rural landscape and agrarian structures, like Cuba. So why do so few Swedes live in rural areas, even though based on total area, the country is one of the largest in Europe? The total population figures are the answer to this question, as Sweden has only about 10.3 million inhabitants as of 2018 – that’s only 25 inhabitants per square kilometer. Rural exodus or just par for the course?It is no mystery why most Swedes flock to the cities: Jobs, of course. Over 65 percent of Sweden’s gross domestic product is generated by the services sector, and agriculture only contributes about one percent to the GDP. Employment mirrors this, with 80 percent of the workforce being deployed in services, namely in foreign trade, telecommunications, and manufacturing, among other industries.

This dataset is about cities in Sweden, featuring 3 columns: city, country, and population. The preview is ordered by population (descending).

Of the total population in Sweden of 10.55 million people, around half resided in the counties Stockholm, Västra Götaland or Skåne. This is also the three counties where the three largest cities in Sweden, Stockholm, Göteborg, and Malmö, are located. In the capital region Stockholm county, there lived nearly 2.5 million inhabitants in 2023. Västra Götaland county had close to 1.8 million inhabitants, while Skåne county, the southernmost region, had roughly 1.4 million inhabitants. The island Gotland had the lowest number of inhabitants with only 60,000.

The highest population density

Stockholm, Skåne and Västra Götaland were also the three counties in Sweden with the highest population density. In 2022, 374.6 inhabitants per square kilometer lived in Stockholm county, while the corresponding figures for Skåne and Västra Götaland were 129 and 73.9, respectively.

The highest rents

Unsurprisingly. Stockholm county is the county in Sweden with the highest rents for rented dwellings, with average prices for one square meter amounting to over 1,400 Swedish kronor in 2022. The lowest average renting prices were in the northwestern region Jämtland, one square meter costing 1,000 Swedish kronor.

Sweden SE: Population in Largest City: as % of Urban Population data was reported at 17.703 % in 2017. This records an increase from the previous number of 17.683 % for 2016. Sweden SE: Population in Largest City: as % of Urban Population data is updated yearly, averaging 15.683 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 17.703 % in 2017 and a record low of 14.346 % in 1981. Sweden SE: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

The share of urban population in Sweden saw no significant changes in 2023 in comparison to the previous year 2022 and remained at around 88.74 percent. Nevertheless, 2023 still represents a peak in the share in Sweden. A population may be defined as urban depending on the size (population or area) or population density of the village, town, or city. The urbanization rate then refers to the share of the total population who live in an urban setting. International comparisons may be inconsistent due to differing parameters for what constitutes an urban center.Find more key insights for the share of urban population in countries like Greenland and Faroe Islands.

The database FOLKNET contains information about the population in Sweden’s parishes, cities and municipalities according to the geographical division around 1990, every ten years during the period 1810–1990. The data has been collected by Christian Svärd, and the Demographic Data Base has digitized the information. The information has mainly been taken from Statistics Sweden’s historical publications. Additional data have been collected from the population forms of the database TABVERK. The database POPULATION is freely available from the home page of the Demographic Data Base.

Stockholm is the Capital of Sweden and in 2023, close to 985,000 people lived in the municipality. Since 2010, the population there has been growing consistently. While more people are moving to Stockholm, the city area is not growing at the same speed, leading the population density to increase as well. Forecasts for the city expect continuous growth of population over the next forty years.

Economy

In Stockholm, the Gross Domestic Product (GDP) per capita was around 734,000 Swedish kronor in 2021. That was much higher than the average GDP per capita in all of Sweden with around 517,000 SEK in 2021. Though it must be noted that living costs are very high in the city and have been increasing in the last years. For example, the average rent per square meter in Stockholm has been rising every single year.

Employment A high majority of people living in Stockholm have a workplace. The employment rate in Stockholm is at 73.6 percent as of 2021.  The sector with the highest number of employees in Stockholm is professional, scientific, technical, and administrative activities, followed by wholesale and retail trade.

This dataset is about cities in Sweden. It has 7 columns such as city, continent, country, latitude, and longitude. The data is ordered by population (descending).

This dataset is about cities and is filtered where the country includes Sweden, featuring 7 columns including city, continent, country, latitude, and longitude. The preview is ordered by population (descending).

This dataset is about countries in Sweden per year and is filtered where the date is 2,023, featuring 4 columns: capital city, country, date, and urban population. The preview is ordered by date (descending).

Until 2070, the growth of the Swedish-born population in the City of Stockholm is estimated to remain relatively stable, while that of foreign-born citizens is forecast to slow somewhat. By 2070, the Swedish capital is expected to have a total of 1.35 million inhabitants, of which 953,000 were born in Sweden and 406,000 born abroad.

About this dataset

Context

The dataset tabulates the Sweden town median household income by race. The dataset can be utilized to understand the racial distribution of Sweden town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Sweden, Maine median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Sweden, Maine (2021, in 2022 inflation-adjusted dollars)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Sweden town median household income by race. You can refer the same here

Chart and table of population level and growth rate for the Malmo, Sweden metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

Demographic statistics — DESO is a nationwide classification created by Statistics Sweden that entered into force in January 2018. DESO divides Sweden into 5,984 areas with between 700 and 2,700 inhabitants at the start. The division follows the county and municipal boundaries.

DESO does not have names or names, but is described with a code with nine unique positions. The first four consist of the county and municipality code and point out the county and the municipality in which the area is located.

The fifth position indicates the category in which the area belongs to A, B or C. A is areas that are mostly outside larger population concentrations or agglomerations. B are areas that are mostly located in population concentrations or agglomerations but are not a central city. Category C is the areas that are mostly located in the municipality’s central city.

The following three positions consist of a sequential number that sorts the areas geographically. This sorting is based on the categories and starts in the south and continues north. The last position is a reserve location that will be used in case a DESO in the future needs to be split. A DESO can only occur in one place.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education, and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases, as does the strain on the environment and natural resources. Data on urbanization, traffic and congestion, and air pollution are from the United Nations Population Division, World Health Organization, International Road Federation, World Resources Institute, and other sources.

This horizontal bar chart displays death rate (per 1,000 people) by capital city using the aggregation average, weighted by population and is filtered where the country is Sweden. The data is about countries per year.

About this dataset

Context

The dataset tabulates the New Sweden town household income by age. The dataset can be utilized to understand the age-based income distribution of New Sweden town income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• New Sweden, Maine annual median income by age groups dataset (in 2022 inflation-adjusted dollars)
• Age-wise distribution of New Sweden, Maine household incomes: Comparative analysis across 16 income brackets

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of New Sweden town income distribution by age. You can refer the same here

This dataset is about countries in Sweden, featuring 5 columns: capital city, continent, country, currency, and urban land area. The preview is ordered by population (descending).

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 MPP was started in the early 70's as a screening survey in the middle-aged population of Malmö, the third largest city of Sweden. Subjects born in Malmö and residents of the city were invited for a clinical examination, questionnaire and blood sampling. In all 22,444 men and 10,902 women participated during the period 1974-1992. During a later follow-up, the MPP-Re-examination (MPP-RES) in all 17,284 of the original screenes attended in 2002-2006.

Purpose: 1. To screen for cardiovascular risk-factors and alcohol abuse in the local population, and to offer intervention to subjects at risk;

1. To use DNA (at MPP-RES) for analyses of genetic risks of type-2 diabetes and cardiovascular disease, as well as some cancers.