****************** and ****** are the top two answers among U.S. consumers in our survey on the subject of "Most popular hobbies & activities".The survey was conducted online among 67,079 respondents in the United States, in 2025.

This statistic shows the share of adults in United States who participated in a craft or hobby in the last month, by activity. During the survey, ** percent of the respondents stated that they had participated in paper arts in the last month.

This statistic shows the share of adults in United States who participated in a craft or hobby in the last year, by activity. During the survey, ** percent of the respondents stated that they had participated in edible arts in the last year.

This statistic shows the mean annual expenditure on toys, hobbies, and playground equipment per consumer unit in the United States in 2023. In 2023, the 35 to 44 age group was the highest spender on this category, with an annual expenditure mean of *** U.S. dollars.

This statistic shows the most popular leisure activities among men in the United States as of September 2013. During the survey, 43 percent of the male respondents named watching TV as their most preferred activity during leisure time.

Financial overview and grant giving statistics of Pike County Adult Activities Center

Daily average time and proportion of day spent on various activities, by age group and gender, 15 years and over, Canada, Geographical region of Canada, province or territory, 2022.

This dataset contains a listing of events and activities offered by NYC Aging funded Older Adult Centers. There are more than 300 older adult centers (OACs) and affiliated sites throughout the five boroughs that provide healthy meals, fun activities, classes, fitness programs and social services. For more information, please refer to https://www.nyc.gov/site/dfta/services/older-adult-center.page

Daily average time in hours and proportion of day spent on various activities by age group and sex, 15 years and over, Canada and provinces.

Explore the booming adult craft subscription box market, driven by creativity and self-care. Discover key trends, market size, CAGR, and leading companies shaping this engaging industry.

Financial overview and grant giving statistics of Fun Family Activities Assoc Of Berlin Businesses

The coronavirus (COVID-19) pandemic made it significantly more difficult for consumers in the United States to spend disposable income on travel, dining out, and other in-person experiences. Subsequently, many consumers turned their attention to other hobbies to fill the entertainment void. In 2021, the degree to which U.S. consumers collected physical items as a hobby or investment varied by gender. Men were the most likely to collect physical items, with ** percent of respondents stating that this was the case. Meanwhile, ** percent of women stated that they collected physical items.

China Participants’ Average Daily Time Use: Primary Activity Domain: Male: Discretionary Personal Activities data was reported at 217.000 min in 2024. China Participants’ Average Daily Time Use: Primary Activity Domain: Male: Discretionary Personal Activities data is updated yearly, averaging 217.000 min from Dec 2024 (Median) to 2024, with 1 observations. The data reached an all-time high of 217.000 min in 2024 and a record low of 217.000 min in 2024. China Participants’ Average Daily Time Use: Primary Activity Domain: Male: Discretionary Personal Activities data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OT: Participants’ Average Daily Time Use: By Sex.

China Participants’ Average Daily Time Use: Primary Activity Domain: Male: Essential Personal Physiological Activities data was reported at 743.000 min in 2024. China Participants’ Average Daily Time Use: Primary Activity Domain: Male: Essential Personal Physiological Activities data is updated yearly, averaging 743.000 min from Dec 2024 (Median) to 2024, with 1 observations. The data reached an all-time high of 743.000 min in 2024 and a record low of 743.000 min in 2024. China Participants’ Average Daily Time Use: Primary Activity Domain: Male: Essential Personal Physiological Activities data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OT: Participants’ Average Daily Time Use: By Sex.

Jordan Employment: Male: Activities of Extraterritorial Organizations and Bodies data was reported at 25.000 Person in 2016. This records an increase from the previous number of 15.000 Person for 2015. Jordan Employment: Male: Activities of Extraterritorial Organizations and Bodies data is updated yearly, averaging 37.500 Person from Dec 2011 (Median) to 2016, with 6 observations. The data reached an all-time high of 61.000 Person in 2011 and a record low of 15.000 Person in 2015. Jordan Employment: Male: Activities of Extraterritorial Organizations and Bodies data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Jordan – Table JO.G010: Employment: by Industry.

Indonesia Avg Weekly Hour Worked: Male: Real Estate Activities data was reported at 49.000 Hour in 2018. This records a decrease from the previous number of 51.000 Hour for 2017. Indonesia Avg Weekly Hour Worked: Male: Real Estate Activities data is updated yearly, averaging 50.000 Hour from Aug 2015 (Median) to 2018, with 4 observations. The data reached an all-time high of 51.000 Hour in 2017 and a record low of 49.000 Hour in 2018. Indonesia Avg Weekly Hour Worked: Male: Real Estate Activities data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Indonesia – Table ID.GBB016: Average Weekly Hour Worked: by Industry.

Average daily time spent by adults on activities including paid work, unpaid household work, unpaid care, travel and entertainment. These are official statistics in development.

Abstract

Statistics South Africa (Stats SA) was commissioned by the South African Department of Labour (DoL) to conduct the first Survey of Activities of Young People in 1999. Stats SA was responsible for data collection and processing, while the analysis and report writing was the responsibility of DoL. In thethird quarter of 2010 (Q3:2010) Stats SA conducted the second Survey of Activities of Young People (SAYP) as a supplement to the Quarterly Labour Force Survey (QLFS). However differences in methodologies followed in the two surveys make comparisons difficult. SAYP is a household-based sample survey that collects data on the activities of children aged 7 to 17 years who live in South Africa. This information is gathered from respondents who are members of households living in dwellings that have been selected to take part in the QLFS and have children aged 7–17 years. The survey covers market production activities, production for own final consumption, household chores as well as activities that children engaged in at school. The reference period for some activities is the week preceding the survey interview and for others it is the past twelve months. The specific objectives of SAYP are: • To understand the extent of children’s involvement in economic activities; • To provide users with statistics on the number of working children; • To supply information for the formulation of informed policy to combat child labour within the country; and • To monitor the Child Labour Action Plan of the Department of Labour based on the findings.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the study were households and individuals

Universe

The sampled population was household members in South Africa. The survey excluded all people in prison, patients in hospitals, people residing in boarding houses and hotels, and boarding schools. Any single person households were screened out in all areas before the sample was drawn. Families living in hostels were treated as households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Survey of Activities of Young People (SAYP) involved two stages. The first stage involved identifying households with children aged 7–17 years during the Quarterly Labour Force Survey (QLFS) data collection that took place in the third quarter of 2010 (Q3:2010). The second stage involved a follow-up interview with children in those households to establish what kind of activities they were involved in and several other aspects related to the activities they engaged in. In Q3:2010, all the QLFS questionnaires were checked for any children aged 7–17 years using the question on age in the first part of the QLFS questionnaire. The screening process for the SAYP was performed to ensure that only households with eligible children were revisited.

Sampling deviation

The non-response adjustment is done through the creation of adjustment classes. The adjustment classes are created using Response Homogeneity Groups (RHGs), where respondents have the same characteristics with non-respondents in the group. The response rate (which is the ratio of responses to all eligible units in the sample) is calculated within each class. The inverse of the response rate (adjustment factor) is calculated within each class, and the result is multiplied by the QLFS 2010 person's weights of the responding units to get the adjusted SAYP person weights for responding units. Children identified as ineligible for SAYP were not considered when calculating weights adjustment. In short, the weights of responding children are inflated to account for eligible children that did not respond during SAYP data collection.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Phase one questionnaire covered the following topics: Living conditions of the household, including the type of dwelling, fuels used for cooking, lighting and heating,water source for domestic use, land ownership,tenure and cultivation; demographic information on members of the household, both adults and children. Questions covered the age, gender and population group of each household member, their marital status, their relationships to each other, and their levels of education; migration details; household income; school attendance of children aged 5 -17 years; information on economic and non-economic activities of children aged 5-17 years in the 12 months prior to the survey

Phase two questionnaire The second phase questionnaire was administered to the sampled sub-set of households in which at least one child was involved in some form of work in the year prior to the interview. It covered activities of children in much more detail than in phase one, and the work situation of related adults in the household. Both adults and children were asked to respond.

The data files contain data from sections of the questionnaires as follows:

PERSON: Data from Section 1, 2 and 3 of the questionnaire HHOLD : Data from Section 4 ADULT : Data from Section 5 YOUNGP: Data from Section 6, 7, 8 and 9

Abstract

Time Use Surveys (TUS) are household-based surveys that measure and analyze time spent by women and men, girls and boys on different activities over a specified period. Unlike data from other surveys, time use results can be specific and comprehensive in revealing the details of a person's daily life. The results of the Time Use Survey enable one to identify what activities are performed, how they are performed and how long it takes to perform such activities. The Department of Census and Statistics (DCS) conducted the first Sri Lanka national survey on time use statistics in 2017. The primary objective of TUS is to measure the participation of men and women in paid and unpaid activities. Moreover, this report contains information on the time spent on unpaid care giving activities, voluntary work, and domestic service of the household members. This also provides information on time spent on learning, socializing, leisure activities and self-care activities of 10 years and above aged Sri Lankans. In this report, statistics were estimated under following three indicators. 1. Participation rate 2. The mean actor time spent on different activities 3. The mean population time spent on different activities

The TUS was conducted in the same households of the fourth quarter Labour Force Survey (LFS) sample in 2017. It was non-independent survey but administered an independent diary and a household module with fourth quarter LFS, 2017. All household members who were age 10 years and above in the sample were provided a diary to record activities done in every 15 minutes within a period of 24 hours (day). The TUS sample covered the household population aged 10 years and above - thus representing an estimated 17.87 million people. Classification of activities Reported activities were coded according to the International Classification of Activities for Time Use Statistics (ICATUS 2016). The ICATUS 2016 has nine broad categories, which aggregate into even broader categories. The categories are consistent with the System of National Accounts (SNA) which underlies the calculation of gross domestic product (GDP). The categories are as follows: 1. Employment and related activities 2. Production of goods for own final use 3. Unpaid domestic services for household and family members 4. Unpaid caregiving services for household and family members 5. Unpaid volunteer, trainee and other unpaid work 6. Learning 7.Socializing and communication, community participation and religious practice 8. Culture, leisure, mass-media and sports practices 9. Self-care and maintenance Activity category number 1 and 2 falls in to SNA production boundary. Therefore, most part be 'counted' in national accounts and the GDP. Activity categories 3 to 5, which cover unpaid household work and unpaid assistance to other households, fall outside the SNA production boundary, although they are recognized as 'productive'. They correspond to what is commonly referred to as unpaid care work. The remaining four activity categories cannot be performed for a person by someone else; people cannot hire someone else to sleep, learn, or eat for them. Hence, they do not qualify as' work 'or' production' in terms of the third-person 'rule'.

Geographic coverage

The survey collects data from a quarterly sample of 6,440 housing units covering the whole country, also this sample enough to provides national estimates on Time use statistics. It covers persons living in housing units and excludes the institutional population.

Analysis unit

Individual,Household

Universe

All household members who were age 10 years and above

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame prepared for 2012 Census of Population and Housing (CPH) is used as sample frame for the sample selection of LFS in 2017. Two stage stratified sampling procedure is adopted to Sri Lanka Time Use Survey Final Report - 2017 1.5 Field Work Select the annual LFS sample of 25,750 housing units. 2,575 Primary Sampling Units (PSU?s) were allocated to each district and to each sector (Urban, Rural and Estate) and equally distributed for 12 months. Housing units are the Secondary Sample Units (SSU). From each selected PSU, 10 housing units (SSU) are selected for the survey using systematic random sampling method. Since, the Time Use survey was planned to disseminate statistics at national level, a quarterly sample of 6,440 housing units of the LFS 4th quarter 2017 sample was selected for the TUS. Also, selected housing units of a PSU were evenly allocated to cover all 7 days of a week including weekends. Sample allocation by sector for TUS - 2017

Number of housing units 

Sri Lanka 6,440
Urban 1,000
Rural 5,140
Estate 300

Mode of data collection

Face-to-face [f2f]

Research instrument

The Survey was conducted in the same households of the fourth quarter Labour Force Survey (LFS) sample in 2017. It was non-independent survey but consists with other two data collection instruments in PAPI method: a) A household questionnaire b) A time diary with fourth quarter LFS 2017 questionnaire in CAPI method. The household questionnaire was designed only for obtain information on the characteristics of the household. Because the LFS questionnaire collects background information about the demographic and socio-economic characteristics of the respondent, such as their labour force status. All household members who were age 10 years and above in the sample were provided a diary to record activities done in every 15 minutes within a period of 24 hours (day). It captures information on spending the time for main activity, simultaneous activity, where the activity takes place and with whom the activity takes place.

Cleaning operations

The International Classification of Activities for Time Use Statistics (ICATUS 2016) has been developed based on internationally agreed concepts, definitions and principles in order to improve the consistency and international comparability of time use and other social and economic statistics. Reliable time use statistics have been critical for

(a) the measurement and analysis of quality of life or general well-being; (b) a more comprehensive measurement of all forms of work, including unpaid work and non-market production and the development of household production accounts; and (c) producing data for gender analysis for public policies. Hence, the importance of ICATUS link and consistency with the System of National Accounts (SNA) and the International Conference of Labour Statisticians (ICLS) definition and framework for statistics of work. Additionally, ICATUS will serve as an important input for monitoring progress made towards the achievement of the Sustainable Development Goals (SDGs). ICATUS 2016 is a three-level hierarchical classification (composed of major divisions, divisions, and groups) of all possible activities undertaken by the general population during the 24 hours in a day. 1) The first level, one-digit code or "major division" represents the least detailed level or the broadest group of activities. 2) The second level, two-digit code or "division" represents more detailed activities than the preceding one 3) The third level, three-digit code or "group" is considered the most detailed level of the classification detailing specific activities. The purpose of the classification is to provide a framework that can be used to produce meaningful and comparable statistics on time use across countries and over time.

An important aspect of the UN classification system is the fact that it matches the System of National Accounts (SNA), which forms the basis internationally for calculating gross domestic product (GDP). The classification is organized according to nine broad activity categories. These categories can be distinguished by the first digit of the three-digit activity code The nine broad categories are as follows: SNA Production Activities 1. Employment and related activities 2. Production of goods for own final use

Non -SNA Production Activities 3. Unpaid domestic services for household and family members 4. Unpaid caregiving services for household and family members 5. Unpaid volunteer, trainee and other unpaid work

Non-Productive Activities 6. Learning 7. Socializing and communication, community participation and religious practice 8. Culture, leisure, mass-media and sports practices 9. Self-care and maintenance

Activity categories 1-2, which are the two 'work' divisions referred to above, fall in the SNA production boundary. They would thus be 'counted' in national accounts and the GDP. The only exceptions are the codes for looking for work, and time spent on travelling related to SNA-type activity. Activity categories 3-5, which cover unpaid household work and care work for household and family members and assistance to other households, fall outside the SNA general production boundary, although they are recognized as 'productive'. In this report they are referred to as non-SNA production Activities. The remaining activity categories are not covered by the SNA. These activities cannot be performed for a person by someone else - people cannot hire someone else to sleep, learn, or eat for them. They thus do not qualify as'work 'or 'production' terms of the „third-person rule. In this report they are referred to as non-productive activities. Many of the tables in the report are organized according to either the nine categories, or the three SNA-related groupings of these categories.

Response rate

Please refer page number 11 and 12 of annual

Abstract: The study aimed to analyze the association between accessibility to public spaces for leisure activities, availability of equipment for physical exercise in these spaces, and leisure-time physical activity (PA) in adults. A household survey was conducted with 699 adults from 32 census tracts selected according to income and “walkability”. Accessibility to public spaces for leisure activities was determined by geoprocessing according to proximity to public spaces for leisure activities and the amount of such spaces within radiuses of 500 and 1,000 meters around the participants’ homes. Presence of equipment for physical exercise in these public spaces was assessed by the observation method and classified as: (a) without equipment for physical exercise; (b) with equipment for physical exercise; (c) equipment for physical exercise for adults; and (d) with three or more pieces of equipment for physical exercise. PA was self-reported, and walking was analyzed separately from moderate-vigorous PA, classified in two levels (≥ 10 minutes/week and ≥ 150 minutes/week). The amount of public spaces for leisure activities in a 500-meter radius with one or more pieces of equipment for physical exercise was negatively associated with walking (OR = 0.84, based on ≥ 150 minutes/week). The amount of public spaces for leisure activities in a 1,000-meter radius was positively associated with moderate-vigorous PA (OR = 1.03). The distance to a public space for leisure activities with three or more pieces of equipment for physical exercise (OR = 0.95) was inversely associated with moderate-vigorous PA. Proximity and amount of public spaces for leisure activities are associated with higher levels of moderate-vigorous PA in adults. The combination of methods can help reveal the contribution that access to (and quality of) public spaces for leisure activities can make to PA.