Pew Research Center surveyed 13,122 adults across six countries in Asia about religious identity, beliefs, and practices, using nationally representative methods. Interviews were conducted face-to-face in Cambodia, Indonesia, Sri Lanka, and Thailand. They were conducted on mobile phones in Malaysia and Singapore. Local interviewers administered the survey from June to September 2022, in eight languages.

This survey is part of the Pew-Templeton Global Religious Futures project, a broader effort by Pew Research Center to study religious change and its impact on societies around the world. The Center previously has conducted religion-focused surveys across sub-Saharan Africa; the Middle East-North Africa region and many countries with large Muslim populations; Latin America; Israel; Central and Eastern Europe; Western Europe; India; and the United States.

This survey includes three countries in which Buddhists make up a majority of the population (Cambodia, Sri Lanka, and Thailand); two countries with Muslim majorities (Malaysia and Indonesia); and one country that is religiously diverse, with no single group forming a majority (Singapore). We also are surveying five additional countries and territories in Asia, to be covered in a future report.

Pew Research Center has produced a supplemental syntax file containing SPSS code to generate common analytic variables in the survey's corresponding report and toplines. The ARDA has provided this syntax in a copyable PDF document as an additional download.

Sri Lanka: Christians as percent of the total population: The latest value from 2013 is 0 percent, unchanged from 0 percent in 2012. In comparison, the world average is 51.1 percent, based on data from 145 countries. Historically, the average for Sri Lanka from 1960 to 2013 is 0 percent. The minimum value, 0 percent, was reached in 1960 while the maximum of 0 percent was recorded in 1960.

Abstract

A Census of Population and Housing is the single most extensive statistical undertaking of a country. In order to plan and implement programmes and activities, statistics are needed by the Government administrators of various levels, private users, research organizations and the general public.

The 1971 Census was conducted under the Census Ordinance N0. 9 of 1900. (Chapter 143) According to that it shall be lawful for the Minister from time to time by order published in the Gazette, to direct that a census be taken of the population, agriculture (including animal husbandry ) trade, labour, industry or commerce or such other matters as he may deem necessary for ascertaining the social, civil or economic conditions of the inhabitants of Ceylon. The CPH 1971 has been designed to collect various information about the characteristics of the population and the households in Sri Lanka.

The CHP1971 provides

a. Reliable and detailed benchmark statistics on the size, distribution and composition of population.

b. Information pertaining to the characteristics of the housing units.

c. Information on the characteristics of the households

Geographic coverage

National coverage

Analysis unit

(1) Individuals (2) Households

Universe

CPH 1971 covered all residents in each household and all units in each census block.

Population census did not cover diplomats.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

A main area for the advance preparations for the 1971 Census was the redesigning of Population and Housing schedules in order to minimize the time required for coding the data. One of the reasons for the delay in tabulation of information from the earlier censuses particularly the 1953 and 1963 censuses was the inordinately long time taken at the Head Office to code the information before punching the information on cards. With a view to avoiding such delays it was decided to have as much of the coding as possible done in the field itself by the enumerators. Topics such as Sex, Marital Status, Religion, Ethnic Group etc; which consist of a few well defined categories could be easily entered on the schedules in the form of codes. A schedule designed for the purpose of was tested at the first Pilot Census. In this schedule, however, the codes for each category were shown at the bottom of the schedule and hence the enumerator had to frequently shift his eyes up and down between the cage in which the entry was to be made and the section at the bottom of the schedule showing the codes. This proved to be the somewhat strenuous and time consuming. Some of the codes were easily remembered by the enumerator e.g. Male 1, Female 2. But in the case of other items like Ethnic Group & Marital Status which contain more than 4 or 5 categories, the possibility of some mixing up of codes existed, leading to inaccuracy. On the basis of experience of the first Pilot Census, the schedule was redesigned and the codes were shown against the question in respect of which answers were sought from the respondents and the enumerators required to indicate the answers by circling the appropriate code. This layout of the schedule eliminated errors resulting from marking of a wrong code which was possible in the case of schedules used at the first Pilot Census.

A similar procedure, however, could not be adopted in respect of such topic as educational attainment, occupation and industry, in respect of which the number of possible entries were quite large. In these cases the enumerator wrote down the answers and the coding was done later, in the office, by specially trained coding staff. The Housing schedule was also designed on the same basis.

The schedule which contained the item in respect of which information was collected from all persons in the country was called the Population Schedule (General) and was printed on white paper to distinguish it from the Population Schedule (Special) printed on pink paper. The Population Schedule (Special) contained in addition to those on the Population Schedule (General) items which were to be collected from a sample only. The Housing Schedule was printed on blue paper.

Cleaning operations

The Census Schedules, on receipt in the Head Office, were checked for any possible shortages and then edited and coded where necessary by specially trained staff, prior to being passed on to the Data Processing Division, for punching and tabulation.

Computer Editing Before the punched cards were transferred to the computer room for processing, certain manual checks for control figures and sight checks were carried out administrative regions. A comprehensive editing procedure was done on the computer. The computer program which checked the records comprised of five basic edits. They were : 1. Checking to ensure that all data was numeric 2. Checking the validity of numerical codes entered for descriptive data 3. Checking the range of codes 4. Checking the consistency of related data 5. Checking and imputation of a limited amount of data for omissions.

Editing to ensure that all data was numeric enabled the detection of errors occurring due to punching and verifying machine faults. All the other edits provided a complete check for validity and consistency of the records. Only records which satisfied all edit checks were written on tape while the error records were appropriately printed by districts. These error lists were referred to the appropriate division for correction. The corrected records were re-punched and passed through the edit program again. This procedure was adopted for each district until no errors were printed. At the commencement of processing 4 error lists for each district were referred back, but with experience gained in the correction of error lists, the reference was cut down to two lists

This data set include Sri Lanka census of population and housing 2012 with sex age and religion dis-aggregated data up to GND (4th Admin) level . This data set is shared by Disaster Management Centre of Sri Lanka during the 2016 flood response only for humanitarian response/agency purposes and updated with population projection up to 2022 by WFP and UNOCHA.

Sri Lanka: Shia Muslims as percent of the total population: Pour cet indicateur, The Cline Center for Democracy fournit des données pour la Sri Lanka de à . La valeur moyenne pour Sri Lanka pendant cette période était de pour cent avec un minimum de pour cent en et un maximum de pour cent en .

Sri Lanka LK: Sex Ratio at Birth: Male Births per Female Births data was reported at 1.043 Ratio in 2017. This records an increase from the previous number of 1.042 Ratio for 2016. Sri Lanka LK: Sex Ratio at Birth: Male Births per Female Births data is updated yearly, averaging 1.042 Ratio from Dec 1962 (Median) to 2017, with 21 observations. The data reached an all-time high of 1.046 Ratio in 1987 and a record low of 1.035 Ratio in 1967. Sri Lanka LK: Sex Ratio at Birth: Male Births per Female Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sri Lanka – Table LK.World Bank.WDI: Population and Urbanization Statistics. Sex ratio at birth refers to male births per female births. The data are 5 year averages.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;

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

Interaction of chronic illnesses and religion towards the mean per capita expenditure.