In 2023, the Faroe Islands was the European country estimated to have the highest fertility rate. The small Atlantic island state had a fertility rate of 2.71 children per woman. Other small countries such as Monaco and Gibraltar also came towards the top of the list for 2023, while the large country with the highest fertility rate was France, with 1.79 children per woman. On the other hand, Andorra, San Marino, and Malta had the lowest fertility rates in Europe, with Ukraine, Spain, and Italy being the largest countries with low fertility rates in that year, averaging around 1.3 children per woman.

Between 2010 and 2023, the fertility rate in Sweden decreased steadily, dropping to 1.5. The fertility rate is defined as the number of children that would be born or are likely to be born to a woman if she lives to the end of her reproductive years. A similar decline was visible for the crude birth rate, which in 2022 was down at 10 births per 1,000 inhabitants.

More immigrants than emigrants

Despite the decreasing fertility- and crude birth rate in Sweden, the population in Sweden continues to grow. More babies are born each year than people dying, which contributes to a growing population. However, the major reason behind the continued population growth is the positive inflow of immigrants. Few people are leaving the country, while many more migrants are arriving in Sweden.

Fertility rate in Europe

Even though the fertility rate in the country decreased over the last 10 years, Sweden had a higher fertility rate than many other countries in Europe in 2023. The Faroe Islands had the highest fertility rate, whereas Andorra had the lowest.

In 2023, the average total fertility rate in Taiwan ranged at around 0.87 children per woman over lifetime. This extremely low figure is not expected to increase over the coming years. Taiwan’s demographic development Taiwan was once known for its strong population growth. After the retreat of the Republican government to the island in 1949, the population grew quickly. However, during Taiwan’s rapid economic development thereafter, the fertility rate dropped substantially. This drastic change occurred in most East Asian countries as well, of which many have some of the lowest fertility rates in the world today. As a result, populations in many East Asian regions are already shrinking or are expected to do so soon.In Taiwan, population decreased in 2020 for the first time, and the declining trend is expected to accelerate in the years ahead. At the same time, life expectancy has increased considerably, and Taiwan’s population is now aging at fast pace, posing a huge challenge to the island’s social security net. Addressing challenges of an aging society Most east Asian countries could, until recently, afford generous public pensions and health care systems, but now need to adjust to their changing reality. Besides providing incentives to raise children, the Taiwanese government also tries to attract more immigrants by lowering requirements for permanent residency. As both strategies have been met with limited success, the focus remains on reforming the pension system. This is being done mainly by raising the retirement age, promoting late-age employment, increasing pension contributions, and lowering pension payments.

In 2023, Murcia ranked as the Spanish region with the highest fertility rate in Spain, with an average of roughly 1.36 children per woman. That year, Melilla ranked first as the region with the highest birth rate, with an average of 8.99 newborns every 1,000 inhabitants.

Over the past 10 years, the highest number of babies born in Sweden was in 2016, when over 117,000 births occurred. In 2023, the number of new-born babies dropped to 100,000. Within the last decade, there were yearly more boys than girls born in the country.

Lowest fertility rate in a ten-year period

In Sweden, the fertility rate reached the lowest point in a ten-year period in 2022. The fertility rate is defined as the number of children that would be born or are likely to be born to a woman if she lives to the end of her reproductive years, and in 2022 it was down to 1.52 children per woman in Sweden. By comparison, the Faroe Islands had the highest fertility rate in Europe at 2.71.

Lowest crude rate of birth in thirteen years

As with the fertility rate, the crude birth rate in Sweden was at its lowest point for several years in 2022. It is defined as the number of live births in a given geographical area in a given time period, per thousand mid-year population, and it was down to 10 in 2022, which was the lowest number in the past decade.

Abstract

The principal objective of the SIDHS was to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, the use of maternal and child health services, and knowledge of HIV and AIDS. Specific survey objectives were to: - collect data at the national level, which will allow the calculation of key demographic rates; - analyse the direct and indirect factors that determine the level and trends of fertility; - measure the level of contraceptive knowledge and practice among women and men by method, urban-rural residence and region; - collect high-quality data on family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under 5 years, and maternity care indicators, including antenatal visits, assistance at delivery, and postnatal care; - collect data on infant and child mortality; - obtain data on child feeding practices, including breastfeeding, and collect ‘observation’ information to use in assessing the nutritional status of women and children; - collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV and AIDS, and evaluate patterns of recent behaviour regarding condom use; and - collect data on support to mentally ill people as well as information on the incidence of suicides.

This information is essential for informed policy decisions, planning, monitoring, and evaluating programmes on health in general, and reproductive health in particular, at both the national level as well as in urban and rural areas. A long-term objective of the survey is to strengthen the technical capacity of government organisations to plan, conduct, process, and analyse data from complex national population and health surveys. Moreover, the 2006/2007 SIDHS provides national, rural and urban estimates on population and health that are comparable with data collected in similar surveys in other Pacific DHS pilot countries and other developing countries.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design The sample SIDHS was designed to provide reliable estimates of total fertility and infant mortality rates at the national level, with urban and rural breakdown and relatively stable estimates for selected provinces. Although the design considered an urban-rural split, this was not carried out during the sample selection of the enumeration area (EA). The sample was not spread out geographically in proportion to the population; as a result, the SIDHS sample is not self-weighting at the national level and sample weighting factors have been applied to survey records in order to bring them into proportion.

The sample for the survey is a three-stage stratified, nationally representative sample of households. The sampling frame consisted of the estimated number of households in each EA by province and was prepared by SPC from the 1999 population census data and estimated urban and rural population growth rates. Honiara, which is urban in its entirety and selected enumeration areas of Guadalcanal and other provinces, comprise the country’s urban areas. The rest of Guadalcanal and all other provinces are rural. Five domains were identified: Honiara, remaining Guadalcanal, Western, Malaita, and the combined group of smaller provinces (Choiseul, Isabel, Central, Makira/Ullawa, Rennell/Bellona and Temuto). The primary sampling units, comprising 215 EAs, were selected in each province using systematic random sampling with probability proportional to the estimated number of households in the EA. It was not possible to cover several of the selected sample EAs: 5 EAs were damaged or destroyed during the tsunami of 1 April 2007; 5 EAs were refused permission to survey by village elders or the community; and 23 EAs (11 in Honiara, 7 in Western, 4 in Malaita and 1 in Guadalcanal) were not covered due to poor team leadership or poor field monitoring. In Western Province, 7 EAs were not covered due to internal migration of residents after the tsunami. Thus, the survey covered 182 EAs — 60 urban and 122 rural.

Mapping and listing households in each sample EA were undertaken by the interviewers. In each sample point, 20 households were selected by the team supervisor using systematic random sampling. The sample was designed to cover a target sample of 4,300 households with an expected household response rate of 95%. All women aged 15–49 who slept in the sample household on the night prior to the interview date were eligible to be interviewed for the Women’s Questionnaire, and for the anthropometric (height and weight), blood pressure and haemoglobin measurements. Every second household was sub-selected for the male survey. All men aged 15 or over in the sub-selected households were eligible to be interviewed for the Men’s Questionnaire, and for anthropometric and blood pressure measurements. All children aged 0–5 years were eligible for anthropometric measurement, and those aged 6 months to 5 years, for anaemia testing.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires — a household questionnaire, a women's questionnaire and a men's questionnaire —were used in the SIDHS. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program at Macro International.

In consultation with MOH, SINSO and Macro, staff modified the DHS model questionnaires to reflect relevant issues in population, family planning, HIV and AIDS, and other health issues in the Solomon Islands. The questionnaires were translated into Pidgin and back-translated in order to check accuracy.

The household questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the household questionnaire was to identify women and men who were eligible for the individual interview. The household questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this questionnaire was also used to record height and weight measurements of women aged 15–49, men aged 15 and above, and children under the age of 5 years, as well as consent from women, and children’s parent or guardian to give blood samples for anaemia and blood pressure testing among women and men.

The women's questionnaire was used to collect information from all women aged 15–49 on: • Background characteristics (education, residential history, media exposure, etc.) • Reproductive history and child mortality • Knowledge and use of family planning methods • Fertility preferences • Antenatal and delivery care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Infant and child feeding practices • Awareness and behaviour about AIDS and other sexually transmitted infections.

The men’s questionnaire collected similar information contained in the women's questionnaire, but was shorter because it did not contain questions on reproductive history, contraceptive calendar, and maternal and child health and nutrition.

Both informal and formal pre-tests of the questionnaires were undertaken. In July 2006, an informal pre-test was done through self-administration of the individual women’s and men’s questionnaires, respectively, by six female and four male SINSO staff members.

A more formal three-week pre-test was undertaken for the interviewers from 21 August to 2 September 2006, inclusive of Saturdays. The pre-test training for the nurses/health technicians started a few days later, and went from 25 August to 2 September. Twelve pre-test interviewers (seven males and five females) were expected to become team supervisors and field editors during the main enumeration. Four nurses/health technicians were trained for accuracy and reliability of the various measurements. Most pre-test interviewers had experience as interviewers in the 2006 Household Income and Expenditures Survey. Recruitment was done through radio advertisement and recommendation of SINSO staff.

Pre-test training for the interviewers consisted of classroom lectures, demonstration interviews, front-of-class interviews, mock interviews, quizzes and tests, and three days of field practice. Instructional materials included the household questionnaire, the women’s questionnaire, the men’s questionnaire, four field control forms, and various PowerPoint presentations. A whiteboard, an electronic projector and a laptop computer were also used during the pre-test training. The pre-test resulted in revising the translation of some questions and skip instructions.

Cleaning operations

The computer processing of SIDHS data began a few weeks after the fieldwork began. The Macro Inc data processing consultant held a training from 30 October 30 to 10 November 2006. A data processing specialist from SPC, the data processing head from SINSO, and two data processing staff from the Republic of the Marshall Islands attended. The training included how to set up the data entry system, data entry, and how to run the