In 1800, the population of the island of Sri Lanka was approximately 1.2 million. This figure would begin to grow following the island’s complete annexation into the British Empire with the end of the Second Kandyan War in 1815. Population growth then increased much faster towards the end of the 19th century, as child mortality rates dropped and large numbers of Indian migrants were imported to work on British plantations. These migrants were largely Tamil migrants from southern India, and by 1911, this group would make up almost 13 percent of the island’s population (on top of the existing 13 percent Sri Lankan Tamil population).

Population growth would expand rapidly in the years immediately following the island’s independence from the British Empire in 1948. However, this growth would slow in the 1950s, as legislation passed by the Sinhalese-dominated government immediately following independence resulted in the removal of citizenship for an estimated 700,000 Indian Tamils, and the deportation of over 300,000 to India over the following three decades. Growth would slow even further after the ethnic clashes of Black July in 1983, which marked the beginning of a civil war in Sri Lanka which would last from 1983 to 2009 and result in the death of over 80,000 people, and the displacement of an estimated 800,000. However, since the end of the civil war in 2009, the population of Sri Lanka has continued to grow, and in 2020, the population of Sri Lanka is estimated to be over 21 million.

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

Abstract

The 2006-07 Sri Lanka Demographic and Health Survey (SLDHS) is the fourth in a series of DHS surveys to be held in Sri Lanka-the first three having been implemented in 1987, 1993, and 2000. Teams visited 2,106 sample points across Sri Lanka and collected data from a nationally representative sample of almost 20,000 households and over 14,700 women age 15-49.

A nationally representative sample of 21,600 housing units was selected for the survey and 19,872 households were enumerated to give district level estimates (excluding Northern Province). Detailed information was collected from all ever-married women aged 15-49 years and about their children below five years at the time of the survey. Within the households interviewed, a total of 15,068 eligible women were identified, of whom 14,692 were successfully interviewed.

The Department of Census and Statistics (DCS) carried out the 2006-07 SLDHS for the Health Sector Development Project (HSDP) of the Ministry of Healthcare and Nutrition, a project funded by the World Bank. The objective of the survey is to provide data needed to monitor and evaluate the impact of population, health, and nutrition programmes implemented by different government agencies. Additionally, it also aims to measure the impact of interventions made under the HSDP towards improving the quality and efficiency of health care services as a whole.

All 25 districts of Sri Lanka were included at the design stage. The final sample has only 20 districts, however, after dropping the 5 districts of the Northern Province (Jaffna, Kilinochchi, Mannar, Vavuniya, and Mullativu), due to the security situation there.

OBJECTIVES

The objective of this report is to publish the final findings of the 2006-07 SLDHS. This final report provides information mainly on background characteristics of respondents, fertility, reproductive health and maternal care, child health, nutrition, women's empowerment, and awareness of HIV/AIDS and prevention. It is expected that the content of this report will satisfy the urgent needs of users of this information.

MAIN RESULTS

FERTILITY Survey results indicate that there has been a slight upturn in the total fertility rate since the 2000 SLDHS. The total fertility rate for Sri Lanka is 2.3, meaning that, if current age-specific fertility rates were to remain unchanged in the future, a woman in Sri Lanka would have an average of 2.3 children by the end of her childbearing period. This is somewhat higher than the total fertility rate of 1.9 measured in the 2000 SLDHS.

Fertility is only slightly lower in urban areas than in rural areas (2.2 and 2.3 children per woman, respectively); however, it is higher in the estate areas (2.5 children per woman). Interpretation of variations in fertility by administrative districts is limited by the small samples in some districts. Nevertheless, results indicate that Galle and Puttalam districts have fertility rates of 2.1 or below, which is at what is known as “replacement level” fertility, i.e., the level that is necessary to maintain population size over time. Differences in fertility by level of women's education and a measure of relative wealth status are minimal.

FAMILY PLANNING According to the survey findings, knowledge of any method of family planning is almost universal in Sri Lanka and there are almost no differences between ever-married and currently married women. Over 90 percent of currently married women have heard about pills, injectables, female sterilization, and the IUD. Eight out of ten respondents know about some traditional method of delaying or avoiding pregnancies.

Although the proportion of currently married women who have heard of at least one method of family planning has been high for some time, knowledge of some specific methods has increased recently. Since 1993, knowledge of implants has increased five-fold-from about 10 percent in 1993 to over 50 percent in 2006-07. Awareness about pill, IUD, injectables, implants, and withdrawal has also increased. On the other hand, awareness of male sterilization has dropped by 14 percentage points.

CHILD HEALTH The study of infant and child mortality is critical for assessment of population and health policies and programmes. Infant and child mortality rates are also regarded as indices reflecting the degree of poverty and deprivation of a population. Survey data show that for the most recent five-year period before the survey, the infant mortality rate is 15 deaths per 1,000 live births and under-five mortality is 21 deaths per 1,000 live births. Thus, one in every 48 Sri Lankan children dies before reaching age five. The neonatal mortality rate is 11 deaths per 1,000 live births and the postneonatal mortality rate is 5 deaths per 1,000 live births. The child mortality rate is 5 deaths per 1,000 children surviving to age one year.

REPRODUCTIVE HEALTH The survey shows that virtually all mothers (99 percent) in Sri Lanka receive antenatal care from a health professional (doctor specialist, doctor, or midwife). The proportion receiving care from a skilled provider is remarkably uniform across all categories for age, residence, district, woman's education, and household wealth quintile. Even in the estate sector, antenatal care usage is at the same high level. Although doctors are the most frequently seen provider (96 percent), women also go to public health midwives often for prenatal care (44 percent).

BREASTFEEDING AND NUTRITION Poor nutritional status is one of the most important health and welfare problems facing Sri Lanka today and particularly affects women and children. The survey data show that 17 percent of children under five are stunted or short for their age, while 15 percent of children under five are wasted or too thin for their height. Overall, 21 percent of children are underweight, which may reflect stunting, wasting, or both. As for women, at the national level, 16 percent of women are considered to be thin (with a body mass index < 18.5); however, only 6 percent of women are considered to be moderately or severely thin.

Poor breastfeeding and infant feeding practices can have adverse consequences for the health and nutritional status of children. Fortunately, breastfeeding in Sri Lanka is universal and generally of fairly long duration; 97 percent of newborns are breastfed within one day after delivery and 76 percent of infants under 6 months are exclusively breastfed, lower than the recommended 100 percent exclusive breastfeeding for children under 6 months. The median duration of any breastfeeding is 33 months in Sri Lanka and the median duration of exclusive breastfeeding is 5 months.

HIV/AIDS The HIV/AIDS pandemic is a serious health concern in the world today because of its high case fatality rate and the lack of a cure. Awareness of AIDS is almost universal among Sri Lankan adults, with 92 percent of ever-married women saying that they have heard about AIDS. Nevertheless, only 22 percent of ever-married women are classified as having “comprehensive knowledge” about AIDS, i.e., knowing that consistent use of condoms and having just one faithful partner can reduce the chance of getting infected, knowing that a healthy-looking person can be infected, and knowing that AIDS cannot be transmitted by sharing food or by mosquito bites. Such a low level of knowledge about AIDS implies that a concerted effort is needed to address misconceptions about HIV transmission. Programs might be focused in the estate sector and especially in Batticaloa, Ampara, and Nuwara Eliya districts where comprehensive knowledge is lowest.

Moreover, a composite indicator on stigma towards HIV-infected people shows that only 8 percent of ever-married women expressed accepting attitudes toward persons living with HIV/AIDS. Overall, only about one- half of ever-married women age 15-49 years know where to get an HIV test.

WOMEN'S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES The 2006-07 SLDHS collected data on women's empowerment, their participation in decisionmaking, and attitudes towards wife beating. Survey results show that more than 90 percent of currently married women, either alone or jointly with their husband, make decisions on how their income is used. However, husbands' control over women's earnings is higher among women with no education (15 percent) than among women with higher education (4 percent).

In Sri Lanka, the husband is usually the main source of household income; two-thirds of women earn less than their husband. Although the majority of women earn less than their husband, almost half have autonomy in decisions about how to spend their earnings.

The survey also collected information on who decides how the husband's cash earnings are spent. The majority of couples (60 percent) make joint decisions on how the husband's cash income is used. More than 1 in 5 women (23 percent) reported that they decide how their husband's earnings are used; another 16 percent of the women reported that their husband mainly decides how his earnings are spent.

Geographic coverage

A nationally representative sample of 21,600 housing units was selected for the survey and 19,872 households were enumerated to give district level estimates (excluding Northern Province).

Analysis unit

• Household
• Women age 15-49
• Children under five

Universe

In principle, the sample was designed to cover private households in the areas sampled. The population residing in institutions and institutional households was excluded. For the detailed individual interview, the eligibility criteria wereall ever-married women aged 15-49 years who slept in the household the previous night and about their children below five years at the

Abstract

The Demographic and Health Survey (DHS) is an important link in a chain of surveys carried out in Sri Lanka in the past decade or so. Having been designed as part of an international survey program and modelled on the lines of the well renowned World Fertility Survey (WFS) program, the DHS provides an exceptionally valuable source of data for the estimation of trends over time within Sri Lanka as well as for cross national comparison.

The survey focussed primarily on fertility, contraception and child mortality as did WFS but. also measured several indicators of child health, particularly immunization coverage and nutrition status. The inclusion of health sector information has been welcome and fruitful, for improve- ment of nutrition status is a subject to which the Government of Sri Lanka has accorded high priority.

The Sri Lanka Demographic and Health Survey has the following objectives: 1. To provide policymakers and administrators with current and accurate data on fertility, morbidity, family planning and selected indicators of health status which could be used for planning new strategies for the wellbeing of the population; etc. 2. To provide data which can be used to analyze trends over time. The SLDHS examines many of the same fertility, mortality, and health issues that were addressed in earlier surveys, most notably the SLWFS and the more recent SLCPS; and 3. To add to the international body of data which can be used for comparative studies.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49

Universe

In principle, the sample was designed to cover private households in the areas sampled. The population residing in institutions and institutional households was excluded. For the detailed individual interview, the eligibility criteria were: ever-married women aged 15 through 49 who slept in the household the previous night.

Kind of data

Sample survey data

Sampling procedure

SURVEY SAMPLE DESIGN

On the basis of socio-economic and ecological criteria, and the experience of the SLWFS, nine zones were created. It was felt that some of the six SLWFS zones were too heterogeneous and should be redrawn as shown in Figure i.i and described below:

Zone 1 - Colombo Metropolitan area consisting of SLWFS zone 1 and parts of zone 2. Zone 2 - Colombo feeder areas and Northern part of SLWFS zone 2. Zone 3 - South Western coastal low lands corresponding to Southern part of SLWFS zone 2. Zone 4 - Lower South Central hill country corresponding to Western and Southern part of SLWFS zone 6, excluding districts with a concentration of estates. Zone 5 - South Central hill country corresponding to part of SLWFS zone 5 with a concentration of estates. Zone 6 - Irrigated Dry Zone corresponding to SLWFS zone 3, with major or minor irrigation schemes. Zone 7 - Rain fed Dry Zone covering the rest of SLWFS zone 3. Zone 8 - Eastern Coastal Belt, corresponding to SLWFS zone 4 (not included in SLDNS). Zone 9 - Northern Province corresponding to SLWFS zone 5 (not included in SLDHS).

The changes SLDHS made to the SLWFS zones were designed: a) to separate the Colombo urban feeder areas from rural hinterlands; b) to separate rural areas with predominantly estate populations from other rural areas; and c) to distinguish between irrigated dry zone areas which are new settlements under development projects from those areas which rely primarily on rains for cultivation.

Although the survey originally planned to conduct interviews in all nine zones, Civil disturbances in zones 9 and 8 (the Northern and Eastern provinces) prevented interviews from being conducted there. These zones, which contain approximately 14 percent of the 1986 estimated population of Sri Lanka, have been excluded from the SLDHS.

With the exception of zone 5, the sample was allocated equally between zones with an estimated target 900 completed individual interviews per zone. Zone 5 was given a larger target sample size of 1,350 to permit over sampling of the estate plantation workers.

In principle, the sample was designed to cover private households in the areas sampled. The population residing in institutions and institutional households was excluded. For the detailed individual interview, the eligibility criteria were: ever-married women aged 15 through 49 who slept in the household the previous night.

For the selection of area units, the sample frame was based on block statistics from the 1981 Census of Population and Housing. However, these figures were updated where possible on the basis of the work done in connection with a 1985-86 labour force survey. This applied in particular to newly settled areas with the development of irrigation schemes in the dry zone. For the final selection of housing units within ultimate area units, a special operation was undertaken before the survey to update household lists within selected census blocks.

The zones created by the SLDHS, which were designed to capture relatively homogeneous subgroups of the population, served as the primary strata. Each zone was further stratified into (up to) three strata: urban, rural, and estate areas. Further implicit stratification was achieved by ordering the sampling areas according to administrative and geographical location. Similar systematic sampling procedures were followed at all stages up to and including the selection of housing units.

The sampling of housing units was undertaken in two or three stages depending upon the stratum. In densely populated zones i, 2, and 3, and in urban strata of all zones a three stage design was used:

At the first stage, a stratified sample of Gram Savaka or equivalent areas (waras or estates) with probability proportional to size (PPS) was selected. The number of primary sampling units (PSIs) selected was 54 in zones 5 and 36 in each of the other zones. Within a given zone, the number to be selected in a stratum was allocated proportionately to the strata populations.

1.Within each PSU, two census blocks were selected with PPS, systematically without replacement. 2.The final stage consisted of the selection of the housing units in selected blocks with inverse PPS so as to yield a self weighting sample within each stratum.

For the main survey, there was no further sampling as all eligible women in each selected housing unit were taken into the sample. Also, for the anthropometric measurements, all children 3 through 36 months of eligible women were taken.

In the non-urban strata in zones 3 through 7, the only difference in procedures was that generally only one block was selected per PSU. This procedure effectively reduced the number of stages to two: blocks as the first stage and housing units as the second stage.

Since zones were allocated generally uniform sample sizes, the overall sampling fractions varied in inverse proportion to the zone population.

Sampling deviation

It is important to note once again that the districts in the northern and eastern portions of the country were not covered by the SLDHS because of civil disturbances. Whenever comparisons are made between the SLDHS and the earlier SLWFS and SLCPS, the differences in areas covered by the surveys should be kept in mind.

Mode of data collection

Face-to-face

Research instrument

The Sri Lanka Demographic and Health Survey used two questionnaires each of which was pretested.

a) The first, called the Household Questionnaire, was used to list all usual household members and any visitors who slept in the household the preceding night. For each person listed, information on age, sex, and marital status and whether or not he/she slept in the household the previous night was recorded. From this list eligible respondents were selected for interview. An eligible respondent is defined as a woman currently married, divorced, separated, or widowed between the ages of 15 and 49 who slept in the household the previous night.

b) The second or Individual Questionnaire was administered to each eligible respondent. On the average, an individual interview took approximately 35 to 40 minutes. The Individual Questionnaire consisted of nine sections: 1. Respondents background 2. Birth history-dates of all live births and infant and child deaths 3. Contraception-knowledge, ever use, current use and a detailed history of inter birth use in the last 5 years 4. Child health -immunization status, episodes of diarrhea, breastfeeding, the use of supplementary foods, prenatal care, and assistance at delivery 5. Marriage and migration 6. Fertility preferences 7. Husband's background and respondent's work 8. Socio-economic indicators 9. Length and weight-measurements of all children 3 through 36 months.

More than in similar fertility and family planning surveys conducted in the past, the SLDHS devoted considerable time and attention to obtaining information on the health status of mothers and children. In addition to many health related questions, anthropometric length and weight measurements were taken on all children 3 months through 36 months.

Cleaning operations

Data were entered onto microcomputers starting just two weeks after the commencement of field work. The ISSA (Integrated System for Survey Analysis) software package of programs developed by IRD/Westinghouse was used for data entry, machine editing, and tabulation. An especially effective procedure for correcting errors and inconsistencies detected during office editing and data entry was to relay information about problems in a questionnaire to the interviewers while they were still in the field. In most cases the problem could be

Sri Lanka LK: UCB Projection: Population: Mid Year data was reported at 25,166,733.000 Person in 2050. This records a decrease from the previous number of 25,172,152.000 Person for 2049. Sri Lanka LK: UCB Projection: Population: Mid Year data is updated yearly, averaging 19,041,167.000 Person from Jun 1950 (Median) to 2050, with 101 observations. The data reached an all-time high of 25,172,152.000 Person in 2049 and a record low of 7,533,097.000 Person in 1950. Sri Lanka LK: UCB Projection: Population: Mid Year data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Sri Lanka – Table LK.US Census Bureau: Demographic Projection.

Sri Lanka LK: UCB Projection: Population: Mid Year: Growth data was reported at -0.030 % in 2050. This records a decrease from the previous number of -0.010 % for 2049. Sri Lanka LK: UCB Projection: Population: Mid Year: Growth data is updated yearly, averaging 0.730 % from Jun 1981 (Median) to 2050, with 70 observations. The data reached an all-time high of 1.620 % in 1981 and a record low of -0.030 % in 2050. Sri Lanka LK: UCB Projection: Population: Mid Year: Growth data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Sri Lanka – Table LK.US Census Bureau: Demographic Projection.

Abstract

A National Census of Population and Housing could not be ventured due to the disturbances in the Northern and eastern Provinces. Hence the Dept of Census and Statistics has decided to conduct an island-wide large scale demographic survey (excluding the Northern and Eastern Provinces) during the year 1994 to satisfy the urgent needs of the data users, with a view to furnish estimates at Divisional Secretariat, District, Provincial and National levels.

Geographic coverage

National coverage (excluding Northern and Eastern Provinces)

Analysis unit

Housing Unit

A housing unit has been defined as a place of residence:

1. which is separate from other places of residence, ie where there are walls or partitions separating it so that the persons occupying it can live separately from other persons in the building or in the locality and 2. which has independent access.

Living Quarters other than housing units

Building or a group of buildings where a number of persons (generally not related to one another) reside under the supervision of a central authority, eg convents, school, hostels, police barracks, boarding houses etc

Non Housing unit

Every building or part of a building which is not a place of residence and does not form part of a housing unit is regarded as a non-housing unit.

Household

A household may be (a) a one person Household or (b) a multi-person household

A one person household is one where a person lives by himself and makes separate provision for his food (either cooking it himself or purchasing it)

A multi person household is a group of two or more persons live together and have a common arrangement for cooking and partaking of food (in short, living and eating together). The household includes not only members of the family but also others who live with the family and share meals with them such as relatives boarders servants. The members of a household could be unrelated.

In the case of lodgers living with a household and having their own arrangements for meals, each lodger should be treated as a separate household. But boarders who share meals with the household should be treated as members of the household.

a housing unit may consist of one or more households.

Universe

The population living in housing units alone were selected for the survey. Institutional population such as those who are living in barracks, hostels etc has not been encompassed. Accordingly, the estimates reflect a coverage confined to the institutional population who were accounted for 2.3% of the entire population in Sri Lanka in 1981 which could be considerably higher at present. Nontheless the household definition has been modified to incorporate all the households without an upper limit for boarders and lodgers. Therefore the data user should note this distinction of population when comparing with other data.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 92,180 housing units distributed in the island barring Northern and Eastern Provinces was picked for this survey. Stratification was done at sectoral level and all the Divisional Secretary areas were taken as domains. A minimal samples of 300 housing units were selected from each DSD in order to give estimates at these levels. Percentage of Urban housing units in the country was 13% and the balance 87% represented the Rural housing units. When allocating the total sample into these two sectors however Urban (MC UC sector) was over sampled because this sector is more heterogeneous in terms of the characteristics, which were to be collected through this survey. As such at national level 21360 housing units (23%) were allocated to Urban sector and 70820 housing units (77%) were allocated to Rural sector.

A stratified two stage sample design was used with GN Division or part of the GN Division as primary sampling unit (PSU) and housing unit as the secondary sampling unit (SSU) in the rural sector. Rural sector covers about 219 DS Divisions. 3541 PSU's were selected from this sector and 20 housing units selected from each selected PSU.

Urban sector covered all the Municipal Councils and urban Councils in the island (excl North and east). A stratified three stage sample design was adopted with PPS selection of Wards and subsequent selection of a part of Ward as PSU and the housing unit as the final sampling unit were done. About 40% of the wards in each MC/UC was selected as PPS with replacement. Thereafter SSU's were selected from each selected ward. Finally 40 housing unit's were selected from each selected PSU. The Urban Sector represents 10 MCs and 32 UC's in 42 Divisional Secretariat Divisions.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is similar to which is usually administered in the Census of Population and Housing with few exceptions. Housing questions were filled only in the schedule of the main household of the housing unit. The information as collected in the Housing Section (H1-H.13) has been processed in order to tabulate the housing data.

Cleaning operations

Standard Data editing process of DPD/DCS

Response rate

Estimates given in the publication - Demographic Survey 1994 Sri Lanka - Feb 1996 - are subject to standard sampling errors due to enumeration of only selected housing units representing the population. An account of non sampling error is also not readily available for reference.

an adjustment for non-response and coverage errors have been done while inflating the data.

• provisional 2012 census available results [18]; *15–59 age groups percentage was 62%; above 60 years was 12.2%.Socio-demographic characteristics of the sample n = 719.

Overview: This dataset provides population and migration data for five key South Asian countries: Pakistan, India, Bangladesh, Afghanistan, and Sri Lanka, spanning the years 1960 to 2023. The data, sourced from the World Bank API, sheds light on population growth trends and net migration patterns across these nations, offering rich insights into the region's demographic changes over 63 years.

Key Features: - Total Population: Yearly population data for five countries. - Net Migration: The net effect of immigration and emigration for each year. - Time Span: Covers data from 1960 to 2023. - Source: Extracted from the official World Bank API, ensuring credibility and accuracy.

Use Cases: - Explore regional migration trends and their impact on demographics. - Analyze population growth in South Asia. - Compare migration and population patterns among Pakistan, India, Bangladesh, Afghanistan, and Sri Lanka. - Develop predictive models for demographic and migration forecasts.

About the Data: The dataset is publicly available under the World Bank Open Data License. It can be used freely for educational, research, or commercial purposes with appropriate attribution.

Columns: - Country: Name of the country (Pakistan, India, Bangladesh, Afghanistan, and Sri Lanka). - Year: The year of recorded data. - Total Population: Total population of the country for the given year. - Net Migration: Net migration value (immigration minus emigration).

Key Insights (1960–2023) - Pakistan: Steady growth from 45M (1960) to 240M (2023), with varying migration trends influenced by political and economic changes. - India: Rapid increase from 450M (1960) to 1.43B (2023), with consistently low net migration. - Bangladesh: Population rose from 55M (1960) to 170M (2023), showing negative net migration due to significant emigration. - Afghanistan: Marked by volatile migration due to conflict; population increased from 8M (1960) to 41M (2023). - Sri Lanka: Moderate growth from 10M (1960) to 22M (2023), with net migration losses during periods of civil unrest.

There were 1 943 000 Linkedin users in Sri Lanka in July 2023, which accounted for 8.9% of its entire population. People aged 25 to 34 were the largest user group (1 000 000).

There were 2 428 000 Linkedin users in Sri Lanka in September 2024, which accounted for 11.1% of its entire population. People aged 25 to 34 were the largest user group (1 100 000).

There were 9 106 600 Facebook users in Sri Lanka in January 2024, which accounted for 41.6% of its entire population. The majority of them were men - 59.8%. People aged 25 to 34 were the largest user group (2 900 000). The highest difference between men and women occurs within people aged 25 to 34, where men lead by 1 700 000.

The dataset is based on Statistics Canada census data spanning four census periods (2001, 2006, 2016, and 2021). The dataset captures population statistics disaggregated by ethnicity at the Dissemination Area (DA) level—the smallest standard geographic unit for census data dissemination, covering approximately 400-700 people per unit. For Toronto, this encompasses approximately 3,700 DAs, providing high spatial resolution for analyzing urban dynamics. The dataset includes detailed population counts for the five largest ethnic groups in Toronto: China, India, Philippines, Portugal, and Sri Lanka. The features are also extracted from census datasets and 298 socioeconomic and demographic features from the census data, organized into 12 categories:Demographics: Population age structure, household composition, and family sizeHousing: Dwelling types, ownership status, housing values, and maintenance needsFamily Structure: Marriage patterns, presence of children, household typesIncome: Median household and individual income, income sourcesEmployment: Labor force participation, employment/unemployment ratesMobility & Migration: Internal and external migration patterns, non-permanent residentsVisible Minorities: Population distribution by visible minority statusLanguage: Official language use, mother tongue, and multilingual capabilitiesOccupation: Employment categories across economic sectorsReligion: Religious affiliations and practicesIndustry: Distribution across industry sectorsPlace of Birth: Country of origin information

1 ANOVA; tested difference between categories in each socio-economic variable p

"Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.This dataset includes demographic data of 22 countries from 1960 to 2018, including Sri Lanka, Bangladesh, Pakistan, India, Maldives, etc. Data fields include: country, year, population ratio, male ratio, female ratio, population density (km). Source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision. ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme. Periodicity: Annual Statistical Concept and Methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models. Errors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census. The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data. The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census. The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems. International migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect. Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant."

OR =  Odds Ratio; 95% CI =  95% confidence Interval; * – significant at p

Abstract

The employment/unemployment data are required at very short intervals to monitor the program made in the employment generating policies of the government. To satisfy this need, Sri Lanka Labour Force Survey was designed as a quarterly basis survey to measure the levels and trends of employment, unemployment and labour force in Sri Lanka. Thus the survey is repeated four times each year since the first quarter of 1990.

Key objectives of the survey - To study the economically active / inactive population. - To analyze employment by major industry group and employment status. - To determine unemployment rates by level of education and by age group - To study the informal sector employment. - To determine the underemployment rates by sector and by major industries

Geographic coverage

National coverage. ( Excluding Nothern and Eastern provinces )

Analysis unit

Individuals from the population aged 10 years or more

Universe

Working age population (10 years and above) living in the non-institutional households in Sri Lanka

Kind of data

Sample survey data [ssd]

Sampling procedure

The Survey is conducted quarterly to produce estimates of employment, unemployment, labour force participation and basic demographic characteristics. The scope of coverage includes all households in Sri Lanka.

The list of housing units created for Demographic Survey 1994 were taken as sample frame. Sample lists were selected from the above frame taken as Primary Sampling Unit (PSU). A systematic Sample of 15 housing units per PSU was selected on final sampling units.

The total annual sample size is 15915 housing units equaly, distributed as 265 PSUs per each quarter and 15 housing units (SSUs) per PSU. The allocation to the domains aims at ensuring approximately equal of reliability from domain to domain.

The 1061 PSUs were selected by systematic Sampling from the PSUs created for Demographic Survey - 1994. A listing operation was conducted in each selected PSU to provide a frame for the second stage of selection. The selection of housing units within PSU was systematic with random start.

Sampling deviation

The field of survey conducted in year 2000 was confined to seven province of the country excluding the Northern and the Eastern provinces due to the prevailing situation in the above two provinces.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire covered questions under four main headings such as

Identification Information Control data Personal Information Labour force Information Questions common to all employed persons

Current survey concepts and methods are very similar to those introduced at the beginning of the survey in 1990. However, some changes have been made over the years to improve the accuracy and usefulness of the data. [Questionnaire is attached in the External Resources section].

Sri Lanka LK: UCB Projection: Fertility Rate: per Woman data was reported at 1.760 NA in 2050. This stayed constant from the previous number of 1.760 NA for 2049. Sri Lanka LK: UCB Projection: Fertility Rate: per Woman data is updated yearly, averaging 2.095 NA from Jun 1981 (Median) to 2050, with 70 observations. The data reached an all-time high of 3.430 NA in 1981 and a record low of 1.760 NA in 2050. Sri Lanka LK: UCB Projection: Fertility Rate: per Woman data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Sri Lanka – Table LK.US Census Bureau: Demographic Projection.

Sri Lanka LK: UCB Projection: Number of Births data was reported at 269,787.000 Person in 2050. This records a decrease from the previous number of 272,614.000 Person for 2049. Sri Lanka LK: UCB Projection: Number of Births data is updated yearly, averaging 336,315.500 Person from Jun 1981 (Median) to 2050, with 70 observations. The data reached an all-time high of 429,446.000 Person in 1981 and a record low of 269,787.000 Person in 2050. Sri Lanka LK: UCB Projection: Number of Births data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Sri Lanka – Table LK.US Census Bureau: Demographic Projection.

Sri Lanka LK: UCB Projection: Crude Birth Rate: per 1000 Persons data was reported at 10.700 NA in 2050. This records a decrease from the previous number of 10.800 NA for 2049. Sri Lanka LK: UCB Projection: Crude Birth Rate: per 1000 Persons data is updated yearly, averaging 15.700 NA from Jun 1981 (Median) to 2050, with 70 observations. The data reached an all-time high of 28.000 NA in 1981 and a record low of 10.700 NA in 2050. Sri Lanka LK: UCB Projection: Crude Birth Rate: per 1000 Persons data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Sri Lanka – Table LK.US Census Bureau: Demographic Projection.