In 2024, the share of the population in Taiwan aged 65 and older accounted for approximately 19.2 percent of the total population. While the share of old people on the island increased gradually over recent years, the percentage of the working-age population and the children have both declined. Taiwan’s aging population With one of the lowest fertility rates in the world and a steadily growing life expectancy, the average age of Taiwan’s population is increasing quickly, and the share of people aged 65 and above is expected to reach around 38.4 percent of the total population in 2050. This development is also reflected in Taiwan’s population pyramid, which shows that the size of the youngest age group is only half of the size of age groups between 40 and 60 years. The rapid aging of the populations puts a heavy burden on the social insurance system. Old-age dependency is expected to reach more than 70 percent by 2050, meaning that by then three people of working age will have to support two elders, compared to only one elder supported by four working people today. Aging societies in East Asia Today, many countries in East Asia have very low fertility rates and face the challenges of aging societies. This is especially true among those countries that experienced high economic growth in the past, which often resulted in quickly receding birth rates. Japan was one of the first East Asian countries witnessing this demographic change, as is reflected in its high median age. South Korea had the lowest fertility rate of all Asian countries in recent years, and with China, one of the largest populations on earth joined the ranks of quickly aging societies.

The Gulf Cooperation Council (GCC) countries namely, Bahrain, Kuwait, Oman, Qatar, United Arab Emirates (UAE), and Saudi Arabia, have experienced unique demographic changes. The major population growth contributor in these countries is young migrants, which has led to a shift in the population age pyramid. Migrants constitute the vast proportion of GCC countries’ population reaching >80% in Qatar and UAE. Using Global Burden of Disease Study 2015 (GBD 2015) and United Nations data, for the GCC countries, we assessed the association between age-standardized mortality and population size trends with linear and polynomial regressions. In 1990–2015, all-cause age-standardized mortality was inversely proportional to national population size (p-values: 0.0001–0.0457). In Bahrain, Qatar, Oman, and Saudi Arabia, the highest annual decrease in mortality was observed when the annual population growth was the highest. In Qatar, all-cause age-specific mortality was inversely proportional to age-specific population size. This association was statistically significant among the 5–14 and 15–49 age groups, which have the largest population size. Cause-specific age-standardized mortality was also inversely proportional to population size. This association was statistically significant for half of the GBD 2015-defined causes of death such as “cirrhosis and other chronic liver diseases” and “HIV/AIDS and tuberculosis”. Remarkably, incoming migrants to Qatar have to be negative for HIV, hepatitis B and C, and tuberculosis. These results show that decline in mortality can be partly attributed to the increase in GCC countries’ population suggesting a healthy migrant effect that influences mortality rates. Consequently, benefits of health interventions and healthcare improvement are likely to be exaggerated in such countries hosting a substantial proportion of migrants compared with countries where migration is low. Researchers and policymakers should be cautious to not exclusively attribute decline in mortality within the GCC countries as a result of the positive effects of health interventions or healthcare improvement.

In 2024, approximately 965.65 million people in China were of working age between 15 and 64 years. This was equal to a 68.3 percent share of the total population. Age groups between 30 and 59 years represented the largest age cohorts in the Chinese population pyramid. Age demographics in China The change in China’s age distribution over time displayed in the given statistic illustrates the unfolding of an aging population. As the fertility rate in China declined and life expectancy increased, the only age groups that have been growing over the last three decades were those of old people. In contrast, the number of children decreased gradually between 1995 and 2010 and remained comparatively low thereafter. According to the data provided by the National Bureau of Statistics of China, which has not been revised for years before the 2020 census, the size of the working age population declined in 2014 for the first time and entered a downward trajectory thereafter. This development has extended itself into the total population, which has shrunk in 2022 for the first time in decades. Future age development As the fertility rate in China is expected to remain below the reproductive level, the Chinese society will very likely age rapidly. According to UN data, which is based on figures slightly different from the Chinese official numbers, the share of the population above 60 years of age is projected to reach nearly 40 percent in 2050, while the share of children is expected to remain stable. This will lead to an increased burden of the old-age population on the social security system, illustrated by an old-age dependency ratio peaking at nearly 106 percent in 2090. This means that by then, ten working-age adults would have to support nine elderly people.

Abstract

The 2022 Philippines National Demographic and Health Survey (NDHS) was implemented by the Philippine Statistics Authority (PSA). Data collection took place from May 2 to June 22, 2022.

The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, fertility preferences, family planning practices, childhood mortality, maternal and child health, nutrition, knowledge and attitudes regarding HIV/AIDS, violence against women, child discipline, early childhood development, and other health issues.

The information collected through the NDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The 2022 NDHS also provides indicators anchored to the attainment of the Sustainable Development Goals (SDGs) and the new Philippine Development Plan for 2023 to 2028.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the 2022 NDHS was based on a two-stage stratified sample design using the Master Sample Frame (MSF) designed and compiled by the PSA. The MSF was constructed based on the listing of households from the 2010 Census of Population and Housing and updated based on the listing of households from the 2015 Census of Population. The first stage involved a systematic selection of 1,247 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

In the second stage, an equal take of either 22 or 29 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the preselected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

All women age 15–49 who were either usual residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on women’s safety.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two questionnaires were used for the 2022 NDHS: the Household Questionnaire and the Woman’s Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, academe, and international agencies. The survey protocol was reviewed by the ICF Institutional Review Board.

After all questionnaires were finalized in English, they were translated into six major languages: Tagalog, Cebuano, Ilocano, Bikol, Hiligaynon, and Waray. The Household and Woman’s Questionnaires were programmed into tablet computers to allow for computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the languages for each questionnaire.

Cleaning operations

Processing the 2022 NDHS data began almost as soon as fieldwork started, and data security procedures were in place in accordance with confidentiality of information as provided by Philippine laws. As data collection was completed in each PSU or cluster, all electronic data files were transferred securely via SyncCloud to a server maintained by the PSA Central Office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the area of assignment. Timely generation of field check tables allowed for effective monitoring of fieldwork, including tracking questionnaire completion rates. Only the field teams, project managers, and NDHS supervisors in the provincial, regional, and central offices were given access to the CAPI system and the SyncCloud server.

A team of secondary editors in the PSA Central Office carried out secondary editing, which involved resolving inconsistencies and recoding “other” responses; the former was conducted during data collection, and the latter was conducted following the completion of the fieldwork. Data editing was performed using the CSPro software package. The secondary editing of the data was completed in August 2022. The final cleaning of the data set was carried out by data processing specialists from The DHS Program in September 2022.

Response rate

A total of 35,470 households were selected for the 2022 NDHS sample, of which 30,621 were found to be occupied. Of the occupied households, 30,372 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 28,379 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 27,821 women, yielding a response rate of 98%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2022 Philippines National Demographic and Health Survey (2022 NDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Population pyramid
• Five-year mortality rates

See details of the data quality tables in Appendix C of the final report.

According to the age distribution of China's population in 2024, approximately 68.6 percent of the population were in their working age between 15 and 64 years of age. Retirees aged 65 years and above made up about 15.6 percent of the total population. Age distribution in China As can be seen from this statistic, the age pyramid in China has been gradually shifting towards older demographics during the past decade. Mainly due to low birth rates in China, the age group of 0 to 14 year-olds has remained at around 16 to 17 percent since 2010, whereas the age groups 65 years and over have seen growth of nearly seven percentage points. Thus, the median age of the Chinese population has been constantly rising since 1970 and is forecast to reach 52 years by 2050. Accompanied by a slightly growing mortality rate of more than 7 per thousand, China is showing strong signs of an aging population. China's aging society The impact of this severe change in demographics is the subject of an ongoing scientific discussion. Rising standards of living in China contain the demand for better health care and pension insurance for retirees, which will be hard to meet with the social insurance system in China still being in its infancy. Per capita expenditure on medical care and services of urban households has grown more than ninefold since 2000 with a clear and distinctive upward trend for the near future. As for social security spending, public pension expenditure is forecast to take up approximately nine percent of China's GDP by 2050.

Abstract

Population and Housing Census of Bhutan 2005 collected data on demographic, education, health, migration, household and housing characteristics. It covered the entire country irrespective of human habitation or not and counted all structures, census house, households and people whether Bhutanese or non-Bhutanese residing in the country at a specific point of time. The Census was carried out for two days, 30 and 31 May, 2005. A total of 7500 enumerators, supervisors and administrators were involved.

General Objective The 2005 Census seeks to create an inventory of Bhutan's population size, socio-economic information, labour and demographic characteristics.

Specific Objectives: - to obtain an up-to date count of the population size, by age and sex - to obtain geographic distribution of the population by demographic and socio-economic characteristics - to provide frames for surveys and other statistical activities - to gather information about migration and fertility

Salient features of a census: 1. The population census forms an integral part of a country’s National Statistical System. 2. The census provides valuable benchmark data on a wide range of characteristics, a frame for statistical survey and data to compile a variety of social and economic indicators. These indicators must be comparable between areas within as well as with that of other countries. 3. The census provides the demographic, housing, social and economic data not provided by population registers. 4. Most importantly a census provides data at the smallest area level like a village. Extensive and detailed cross-classification is possible. This is not possible in a sample survey. 5. The population census has a legitimate methodology, which is acceptable internationally.

Geographic coverage

National

Analysis unit

Households, household members

Universe

The Census covered all de facto household members. It covered the entire country irrespective of human habitation or not and counted all structures, census house, households and people whether Bhutanese or non-Bhutanese residing in the country at a Census Night (Midnight of 30 May).

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not Applicable

Mode of data collection

Face-to-face [f2f]

Research instrument

To develop the census questionnaires, consultative meetings were conducted with all ministries. This was followed by a workshop for all sector heads to finalise the contents of the census questionnaires. Necessary changes were incorporated into the census questionnaires based on the outcome of the workshops and consultative meetings. The questionnaires were pre-tested in the three regions of the country. After making all necessary changes the forms were printed in adequate numbers.

Form PHCB - 2A - Household List Update: This section collects data on village code, structure number, census house number, use of census house, serial number of household, name of household head, sex and age with geographical codes.

Form PHCB - 2B - Household Members List: This section collects information on household members, relationship, sex, age, member status, members absent and duration absent.

Form PHCB -2C - Individual Member Details: This section has three parts. Part A collects information on general demographic characteristics and migration. Part B collects information on education and employment and Part C collects information on fertility of women age 15-49 years.

Form PHCB - 2D - Household Information: This section has two parts. Part A collects information on housing conditions and facilities. Part B collects information on particulars of the deceased in the past twelve months.

Cleaning operations

Data editing was done in several stages. The first editing of data was done by the field supervisors and then followed by the manual editing at the dzongkhag level immediately after the field operation. The final manual editing was done at the centre by 20 Dzongkhag Statistical Officers, 1 Registration Officer and 28 graduates who were trained and deployed on temporary basis for three months.

Response rate

100% response rate.

Note: The Royal Government of Bhutan declared 30 May - 31 May, 2005, as public holidays.

Sampling error estimates

Since PHCB, 2005 involved complete enumeration of respondents, Sampling procedures were not applicable thus sampling errors were not computed.

Data appraisal

Standard tables and graphs were generated to assess the data reliability. This includes the computation of population pyramid, graphs of male and female population by single years of age, age and sex structure, age distribution of the household population.