Historical dataset of population level and growth rate for the Colombo, Sri Lanka metro area from 1950 to 2025.

Sri Lanka Population: Mid Year: Colombo data was reported at 2,439.000 Person th in 2018. This records an increase from the previous number of 2,419.000 Person th for 2017. Sri Lanka Population: Mid Year: Colombo data is updated yearly, averaging 2,334.500 Person th from Jun 1991 (Median) to 2018, with 28 observations. The data reached an all-time high of 2,606.000 Person th in 2011 and a record low of 1,970.000 Person th in 1991. Sri Lanka Population: Mid Year: Colombo data remains active status in CEIC and is reported by Department of Census and Statistics. The data is categorized under Global Database’s Sri Lanka – Table LK.G001: Population: Mid Year.

Sri Lanka Population: Mid Year: Male: Colombo data was reported at 1,197.000 Person th in 2018. This records an increase from the previous number of 1,187.000 Person th for 2017. Sri Lanka Population: Mid Year: Male: Colombo data is updated yearly, averaging 1,192.000 Person th from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 1,333.000 Person th in 2011 and a record low of 1,143.000 Person th in 2012. Sri Lanka Population: Mid Year: Male: Colombo data remains active status in CEIC and is reported by Department of Census and Statistics. The data is categorized under Global Database’s Sri Lanka – Table LK.G001: Population: Mid Year.

amales vs.females p

Sri Lanka Population: Mid Year: Female: Colombo data was reported at 1,242.000 Person th in 2018. This records an increase from the previous number of 1,232.000 Person th for 2017. Sri Lanka Population: Mid Year: Female: Colombo data is updated yearly, averaging 1,203.000 Person th from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 1,273.000 Person th in 2011 and a record low of 1,100.000 Person th in 2001. Sri Lanka Population: Mid Year: Female: Colombo data remains active status in CEIC and is reported by Department of Census and Statistics. The data is categorized under Global Database’s Sri Lanka – Table LK.G001: Population: Mid Year.

Brazil Population: Residents: South: Paraná: Colombo data was reported at 240,840.000 Person in 2018. This records an increase from the previous number of 237,402.000 Person for 2017. Brazil Population: Residents: South: Paraná: Colombo data is updated yearly, averaging 216,104.000 Person from Jun 1992 (Median) to 2018, with 24 observations. The data reached an all-time high of 247,268.000 Person in 2009 and a record low of 122,233.000 Person in 1992. Brazil Population: Residents: South: Paraná: Colombo data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAA053: Population: by Municipality: South: Paraná.

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

Brazil Population Census: South: Paraná: Colombo data was reported at 212,967.000 Person in 2010. This records a decrease from the previous number of 233,916.000 Person for 2007. Brazil Population Census: South: Paraná: Colombo data is updated yearly, averaging 198,148.000 Person from Jul 1996 (Median) to 2010, with 4 observations. The data reached an all-time high of 233,916.000 Person in 2007 and a record low of 153,698.000 Person in 1996. Brazil Population Census: South: Paraná: Colombo data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAC057: Population Census: by Municipality: South: Paraná.

Abstract

The major objective of this survey was to provide up-to-date and accurate information on fertility, contraception, child mortality, child nutrition and health status of children.

This sample survey is further intended to serve as a source of demographic data for comparison with earlier surveys such as Sri Lanka Demographic and Health Survey 1987 (DHS87) and Sri Lanka Contraceptive Prevalence Survey 1982 (CPS82). Such comparisons help to understand the demographic changes over a period of time.

Two types of questionnaires were used in the survey. ie (1) Household and (2) Individual.

Source : Report on Sri Lanka Demographic and Health Survey 1993 published in 1995

Geographic coverage

The country has been stratified into nine zones on the basis of socio economic and ecological criteria for DHS87. The same zones were used without major changes. Although there are nine zones the survey was confined to seven excluding Northern and Eastern provinces; the few areas covered in Amparai district in the Eastern Province during DHS87 had to be excluded due to security reasons of the country.

Analysis unit

(1) Household (2) Eligible women (3) Children

Universe

The survey interviews were designed to obtain responses from all usual residents and any visitors who slept in the household the night before the interview. An eligible respondent was defined as an ever married woman aged 15 - 49 years who slept in the household the night before the interview.

Source : Report on Sri Lanka Demographic and Health Survey 1993 published in 1995

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size - 9230 households 7078 eligible women in 9007 housing units.

Selection process : The sample is a multi-stage stratified probability sample representative of the entire country excluding Northern and Eastern Provinces. The country has been stratified into nine zones on the basis of socio-economic and ecological criteria for DHS87. The same zones were used without major changes. Although there are nine zones the survey was confined to seven, excluding Northern and Eastern Provinces. The seven zones are:

Zone 1 - Colombo Metro consisting some urban areas in Colombo and Gampaha District Zone 2 - Colombo feeder areas Zone 3 - South Western coastal low lands Zone 4 - Lower South Central hill country excluding Districts with a concentration of estates Zone 5 - South Central hill country with a concentration of estates Zone 6 - Irrigated dry zone with major or minor irrigation schemes Zone 7 - Rain-fed Dry zone

Each zone was further stratified into three strata - urban, rural and estate sectors. The number of stages of the design and the Primary Sampling Units (PSU) vary according to the sector.

In urban areas PSU is the ward and generally two census blocks have been selected per ward as the second stage unit. The selections were carried out with probability proportional to size(PPS). The number of housing units was taken as the measure of size.

The PSU's were mostly selected from a specially organized frame consisting of wards and Grama Niladhari divisions organized by zone, sector and within sector geographically. The organization provided a better basis for stratification as it is arranged on a geographical basis.

The census blocks were selected from the only frame available from 1981 Census of Population and Housing. The ever married women aged 15-49 found in the selected housing units were interviewed.

In rural areas, Grama Niladhari (GN) division was taken as PSU and generally a single village has been selected per sample GN division with PPS. As such in rural areas villages form effective PSU's. However special steps were taken to merge and divide the villages to deal with areas which are too small or too large.

Unlike the GN divisions and wards, the selection in the estate sector has to take into account the fact that many estates are very small in size to form proper units for first stage of selection. To avoid the need to group estates in the whole frame special procedure was applied to select estates depending on the relative size of the estate compared to the nearby estates.

Sampling deviation

The target sample size was 6500 ever married women in the age group 15-49. This includes an over-sampling of around 500 women in five less developed areas in zones 6 and 7. The latter addition to the sample is needed to provide Policy relevant information and permit comparative analysis of these areas. In order to get that target sample, a total of 9007 housing units were selected for the survey.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire - listed all usual residents any visitors who slept in the household the night before the interview and some basic information was collected on the characteristics of each person listed such as age, sex, marital status, relationship to head of household. The household questionnaire was used to identify women who were eligible for the individual questionnaire.

Individual questionnaire - Administered to each eligible woman who was defined as one who is an ever married female aged between 15 - 49 who slept in the household the night before the interview. This questionnaire had eight sections such as Respondent's background, Reproduction, Contraception, Health of children, Marriage, Fertility, Husband's background, length and weight of infants.

Source : Report on Sri Lanka Demographic and Health Survey 1993 published in 1995

Cleaning operations

Manual editing covered basic investigations such as checking of identification details, completeness of the questionnaire, coding, age and birth history, checking of certain internal consistencies, checking the information recorded in filter questions and coding of few items.

Response rate

Sample size - 9230 households 7078 eligible women in 9007 housing units. Completed - 8918 households 6983 eligible women

Household response rate - 98.9% Eligible women response rate - 98.7% Overall response rate - 97.6%

Household interviews

Completed 96.6% other(vacant, incompetent responder, refused etc) 3.4% Un-weighted number 9230

Eligible women interviews

Completed 98.7% Other(not in, refused, partly complete etc) 1.3% Un-weighted number 7078

Sampling error estimates

The sample of women had been selected as a simple sample, it would have been possible to use straightforward formulas for calculating sampling errors. However the sample design for this survey depended on stratification, stages and clusters. The computer package CLUSTERS developed by the International Statistical Institute for the World Fertility Survey was used to assist in computing the sampling errors with the proper statistical methodology.

In general, the sampling errors are small, which implies that the results are reliable.

Data appraisal

Pl refer to the Source : Report on Sri Lanka Demographic and Health Survey 1993 published in 1995

Demographic characteristic of study population.

OLS regression analysis (Colombo).

Abstract

The survey provides comprehensive information on household income, individual income, household expenditure, per capita expenditure etc. which are required to study the living conditions and nutritional status of the different segments of population. Key objectives of the survey - To identify the income patterns in Urban, Rural and Estate Sectors & provinces - To identify the income patterns by income levels - Average consumption of food items and non food items - Expenditure patterns by sector and by differnt income levels

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design A multi-stage stratified random sample design was used in this survey. Sectors of the district are the domains for stratification. Master sample frame prepared for Demographic Survey 1994 was used in this survey. There were about 4000 Primary Sampling Units (PSUs) in this frame. From thus frames, sample of 1061 PSU's were drawn for Income and Expenditure Survey 1995/96. From each sampled PSU, 20 numbers of housing units (final sampling units) were drawn to reach a sample of 21,220 housing units. Therefore the weighting factors calculated for Income and Expenditure Survey 1995/96 were based on the corresponding factors of the Demographic Survey 1994.

Sample Allocation The district and sector allocation of the number of housing units to be surveyed was done proportionate to the square root of the total number of housing units in the district and sector. However selected areas under the urban sector of the Colombo district and the Gampaha district were over sampled to obtain a better representative sample and to obtain weighting factors for computation of Consumer Price Indices.

(Refer Section 1.3 of the Final Report)

Mode of data collection

Face-to-face [f2f]

Research instrument

The data was collected by direct interviews based on a special schedule which had three sections:-
(1) Demographic characteristics (2) Household expenditure (Food and Non-food items) (3) Household income (Monetary and Non-monetary income)

The demographic characteristics and usual activities of the inmates belonging to the household are reported in the Demographic section of the schedule and close relatives temporarily living away are also listed in the section. Expenditure section has two sub sections to report food and non-food consumption data separately. Expenditure incurred on their own decisions by boarders and servants are recorded in the sub section under the expenditure section. The income has seven sub sections categorized according to the main sources of income.

Sampling error estimates

Refer Section 1.4 of the Final Report regarding Estimation Procedures

UNOSAT code: FL20240603LKA, GDACS ID: 1102660 This map illustrates satellite-detected water extent in Gampaha, Colombo and Kalutara Districts, Western Province, Sri Lanka as observed from a Sentinel-1 image acquired on 04 June 2024 at 00:25 UTC. Within the analysed areas of about 8,000 km², a total of about 124 km² of lands appear to be affected with flood waters. Based on WorldPop population data and the flood extent about 100,000 people are potentially exposed.
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).
Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Population Census: South: Paraná: Colombo在2010达212,967.000 人口，相较于2007的233,916.000 人口有所下降。Population Census: South: Paraná: Colombo数据按每年更新，1996至2010期间平均值为198,148.000 人口，共4份观测结果。该数据的历史最高值出现于2007，达233,916.000 人口，而历史最低值则出现于1996，为153,698.000 人口。CEIC提供的Population Census: South: Paraná: Colombo数据处于定期更新的状态，数据来源于Brazilian Institute of Geography and Statistics，数据归类于Brazil Premium Database的Socio and Demographic – Table BR.GAC057: Population Census: by Municipality: South: Paraná。

Violence, including interpersonal violence, is a significant public health concern (Krug et al., 2002). The WHO defines interpersonal violence as “intentional use of physical force or power, threatened or actual, against another person, which either results in or has a high likelihood of resulting in injury, death, psychological harm, maldevelopment, or deprivation (Butchart, 2015).” Exposure to interpersonal violence is related to physical health problems, reproductive problems, risky health behaviours, as well as mental health problems (Krug et al., 2002). Interpersonal violence can take many forms including, bullying, intimate partner violence, as well as physical and sexual assault. Understanding the antecedents of interpersonal violence (e.g., risk factors for exposure) and the mechanisms through which it influences mental health (e.g., influence of genetics and environment) is key for developing interventions. However, research methodologies which allow us to study developmental mechanisms, such as longitudinal and twin studies, are overrepresented in the global north. The social and economic context in some global south countries is significantly different. Here we focus on Sri Lanka because of the under-representation of the Global South in this research area and the opportunity for developing such research further provided by an existing twin study in District Colombo. Sri Lanka also represents a particular context for population mental health research, as the country experienced a major tsunami in 2004 and a civil war which lasted between 1983 and 2009. These significant events were connected to ethnic divisions and economic instability. They acted as stressors on a population level, impacting population mental health. Researching interpersonal violence and mental health in Sri Lanka means that interventions can be developed with local and/or regional context in mind.

Prevalence and Risk Factors for Interpersonal Violence

Interpersonal violence affects millions of people worldwide (Butchart et al., 2014). The prevalence of bullying victimisation in South Asia (Pakistan, Bangladesh, India and Sri Lanka) has been estimated to be between 39-53% in adolescence (Musharraf and Anis-ul-Haque, 2018; Murshid, 2017; Rahman et al., 2020; Shaikh, 2013; Malhi et al., 2014). Estimates for workplace bullying across South Asia are lacking, but in a study of six Indian cities, 44.3% of over a thousand respondents reported experiencing workplace bullying, including 19.7% reporting moderate or severe bullying (D’Cruz and Rayner, 2013). With regards to intimate partner violence, WHO Global Database on Prevalence of Violence Against Women indicated its lifetime prevalence in South Asia to be 35%, and past year prevalence to be 19% (Saridinha et al., 2022).

In Sri Lanka, the prevalence of intimate partner violence has been estimated between 25 and 35% (Guruge et al., 2015). Furthermore, in a study of twins and singletons in Colombo district of Sri Lanka, some other interpersonal violence experiences were reported including ‘tortured or terrorised’ by 0.9%, ‘physical attack’ by 3.6%, ‘threatened with weapon or kidnapped’ by 2.6% (Dorrington et al., 2014), and ‘sexual assault’ by 1.3% (Zavos et al., 2020). Estimation of the frequency of traumatic events has not been undertaken by many researchers as most studies on the topic focus on the prevalence of post-traumatic stress disorder (PTSD) However, the estimates from Colombo are similar to those in a sample from the Canton of Zurich (Hepp et al., 2005), but dissimilar to a sample from inner-city London (Frissa et al., 2013). This might be because of the unique characteristics of the London sample, which is exclusively urban and focuses on two London boroughs with relatively high crime rates (Lambeth and Southwark). Nonetheless, whatever the sample, it should be considered that self-reporting of traumatic events can lead to underestimation of the actual frequencies, regardless of other sample characteristics.

Several individual antecedent factors for interpersonal violence have been identified, although most of the literature In Sri Lanka and South Asia focuses on intimate partner violence. Women are more likely to experience interpersonal violence than men - 35% of women worldwide are estimated to have experienced intimate partner violence or non-partner sexual assault (WHO, 2013), whereas estimates for men experiencing intimate partner violence vary between 3.4% and 20.3% (Kolbe & Büttner, 2020). In Sri Lanka, younger age, lower educational attainment and socioeconomic status have been linked to higher risk of experiencing intimate partner violence amongst women (Jayasinghe et al., 2009; Jayasuriya et al., 2011). Little to no literature exists on factors associated with experiencing school or workplace bullying in South Asia. In other regions, a number of risk factors have been identified, for example having a disability or an LGBT+ identity, are considered to increase the risk of being bullied (Smith, 2016; Zeedyk et al., 2014; Pinquart, 2017; Birkett et al., 2009). Some other factors that may increase the risk of experiencing interpersonal violence are environmental adversities. Sri Lankans have collectively experienced two significant environmental adversities in recent decades – a civil war, which mainly affected the northern and eastern provinces, and a tsunami in 2004 which affected all coastal areas, especially those on the south and east coasts. The civil war and the tsunami could increase the likelihood of experiencing interpersonal violence. A study in a northern area within the Jaffna District, which was exposed to both the civil war and the tsunami, found high rates of children witnessing violence against another family member, such as their mother, ranging from 4.3% (for sexual violence) to 55.4% for physical violence (Catani et al., 2008). The results of this study also found that socio-economic status, tsunami exposure and previous exposure to war were significant predictors of family violence (Catani et al., 2008). Another study conducted in the areas affected by the civil war and the 2004 tsunami (Northern and Eastern Provinces), found that during the military conflict, intimate partner violence remained a more common form of violence experienced by the local women than violence perpetrated by strangers, such as soldiers (Kottegoda et al., 2008). It is important to understand whether collective traumas, such as civil war and natural disasters, increase the risk of interpersonal violence.

Relationship between Interpersonal Violence and Mental Health

Interpersonal violence is related to mental health outcomes. For instance, bullying victimisation is a well-established risk factor for common mental health disorders in the Global North (e.g., Copeland et al., 2013; Brendgen and Poulin, 2018; Lee and Vaillancourt, 2018; Geoffroy et al., 2015; Islam et al., 2020). In a South Asian setting, cyber-victimisation has been linked to poorer psychological wellbeing and greater psychological distress in Pakistani young adults (Musharraf and Anis-ul-Haque, 2017). Bullying victimisation in childhood and adolescence can have a long-term impact on mental health, including in young adulthood (e.g., Copeland et al., 2013; Klomek et al., 2009; Sourander et al., 2007), as well as later adulthood (Takizawa et al., 2014). Workplace bullying has also been linked to negative mental health outcomes (Verkuil et al., 2015).

Whilst other forms of interpersonal violence are defined, most of the literature focuses on the effects of intimate partner violence against women. A review of literature concluded that intimate partner violence had a long-lasting impact on mental health – anxiety, depression, post-traumatic stress disorder (PTSD), and sleep disorders, across different cultures and settings (Dillon et al., 2013). In one study, women in Indian cities who had experienced intimate partner violence were significantly more likely to report suicidal ideation and suicide attempts than women with no history of intimate partner violence (Vachher and Sharma, 2010). A study in Bangladesh reported emotional and physical violence from intimate partners, but not sexual violence, to be related to suicidal ideation in women (Naved and Akhtar, 2008). The authors also found that exposure to more types of intimate partner violence was related to more severe suicidal ideation. Similar relationships were found in South Africa between intimate partner violence and depressive symptoms (Gibbs et al., 2018), and in Paraguay between intimate partner violence and suicidal ideation (Ishida et al., 2010). 34.7% of intimate partner violence disease burden was attributed to depression in women from Victoria, Australia (Vos et al., 2006). A scoping review of research on interpersonal violence in Sri Lanka identified a few studies which found lower self-esteem, suicidal ideation and suicide attempts to be consequences of intimate partner violence (Guruge et al., 2015).

Mental Health Aetiology

Mental health conditions are a result of both environmental and genetic influences. Beyond environmental factors such as interpersonal violence, genetic influences have also been implicated in the aetiology of depression, suicidal ideation and suicidal self-harm in the Global North (Sullivan et al., 2000; Lim et al., 2022; Althoff et al., 2012). Genetically informed research can help to highlight environmental risk factors, while controlling for genetic factors. In Sri Lanka, genetic influences on depression and suicidal ideation appear consistent with those evidenced in the Global North populations – specifically, recent estimates of heritability of depressive symptoms and suicidal ideation were 32% and 57%, respectively, with the rest of the variance attributable to the environment (Badini et al., 2023; Dutta et al., 2017; Zavos et al., 2020).

Genes and environment are

Abstract

The Sri Lanka Contraceptive Prevalence Survey. (CPS) is a national sample survey designed to obtain information on contraceptive use and fertility. This survey was conducted in 1982 by the Department of Census and Statistics, Ministry of Plan Implementation, in collaboration with the Westinghouse Health Systems of Columbia, Maryland, U.S.A.

The Department of Census and Statisties through the CPS has obtained and tabulated data on levels of fertility, knowledge, use and availability of contraceptives for the entire island as well as for urban-rural areas. These data have been obtained by interviewing a nationally representative probability sample of about 4,500 ever-married women in the age group 15-49. The interviews were conducted by rigourously trained female interviewers of the Department of Census and Statistics under careful supervision.

The field work lasted a period of approximately two months from February to March 1982. Findings from the survey on a preliminary analysis were presented and discussed at a seminar held in Colombo on 4th August 1982.

Geographic coverage

1. Western Province Colombo Gampaha Kalutara

2. Central Province Kandy Matale Nuwara Eliya

3. Southern Province Galle Matara Hambantota

4. Northern Province Jaffna Mannar Vavuniya Mullaitivu

5. Eastern Province Batticaloa Trincornalee Amparai

6. North Western Province Kurunegala Puttalam

7. North Central Province Anuradhapura Polonnaruwa

8. Uva Province Badulla Moneragala

9. Sabaragamuwa Province Ratnapura Kegalle

Analysis unit

all ever-married women 15-49 years old living in housing units one of which is defined as a place of residence separate from the other places of residence and with an independent access. (One or more households could occupy one housing units). The population living in places other than housing units such as institutions were excluded.

Universe

All ever-married women 15-49 years old living in housing units.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was a nationally representative probability sample drawn from a two stage design. In the first stage, a sample of Census Blocks was drawn from the predetermined strata. In the second stage a sample of housing units was drawn from each selected Census Block. All ever-married women aged 15-49 who lived in the selected housing units or who spent the previous night in the unit were interviewed in detail.

First Stage Selection

The country was stratified into 2 strata as urban and rural areas. It was decided to select a sample of about 4,500 respondents spread out in 540 Census Blocks. A Census Block is an area assigned to an enumerator at the 1981 Census of Population and Housing for the purpose of enumeration. The Survey estimates were required at the national level and hence it was decided to allocate the sample proportional to the stratum population which was defind as the female population aged 15-49. This made it necessary to select 90 Census Blocks from the Urban Stratum and 450 from the rural stratum. The required number of blocks within each stratum was then selected from among the 24 administrative districts, the number selected from each district being proportional to the stratum population within the district.

Second Stage Selection The Second' Stage consisted of selecting households from lists of housing units. These lists were obtained from the Pre-listing Forms prepared for the 1981 Census and were updated by the procedure outlined in the next section. The procedure for selection of households was as follows.

In the urban Census Blocks, a systematic sample of 15 housing units was selected from a list of such units. That is, starting from a randomly selected unit every unit at the end of an interval equal to one fifteenth the number of units in the block was selected in to the sample. In the rural Census Blocks, clusters of approximately ten housing units were formed and one cluster was selected at random from each block. All households in every housing unit whenever there was more than one in a unit were selected into the Sample.

Listing of Housing Units

The target population of the survey was all ever-married women 15-49 years old living in housing units. A housing unit was defined as a place of residence and with an independent access. One or more households could occupy one housing unit.

The population living in places other than housing units such as institutions were excluded. The effect of this exclusion the survey estimates was considered to be small as the population living in non-housing units at he 1981 census was a very small proportion of approximately 2 per cent. The sample frame for the survey was the prelisting Forms of the 1981 Census. A prelisting form was prepared for each Census Block and it contained a list of all housing units and non-housing units in the Census Block. The Pre-listing Forms of the selected Census Blocks were updated by the range Statistical Investigators of the Department. These officers were also the ones who prepared and later updated the lists initially for the Census and were quite familiar with the updating procedures. However, they were given specific instructions on updating by asking to delete the demolished and vacant units and to insert in the proper place any new units that had come up since the Census.

While the Survey was going on, it was found that some selected housing units were vacant, some were non-existent, and some could not be located by their addresses. However, the proportion of such units was quite small, only 2.7% and is unlikely to have caused a bias in the selection procedure.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was an adaptation of the core questionnaire developed by the Westinghouse Health System to collect information relating to family planning management. The questionnaire has two main sections:

1. The Household schedule
2. Individual questionnaire

Household Schedule The household schedule was used for listing all females present regardless of their eligibility and for recording their background information. Names of females who usually resided in the household and of female visitors who spent the previous night in the household were recorded in this schedule. For each of these women, age, date of birth, and marital status were entered and based on these information the interviewers decided and recorded the eligibility of each woman for the individual interview. A woman was eligible for the individual interview if she met all of the following three criteria: 1. 15 through 49 years old. 2. Had been or was currently married. 3. Was in the household on the night prior to the interview.

Individual Questionnaire The individual questionnaire consisted of the following five sections:- Section I - Respondent's Background. Section II - Fertility Section III - Fertility Regulation Section IV - Contraceptive Availability Section V - Husband's Status

In adapting the core questionnaire to meet the country's requirements, some additional questions were included. Timing of future births and breast-feeding were added to Section II, motivation to adopt family planning, approval of family planning, and induced abortions were added to Section III, and problems related to family planning services was added to Section IV.

The questionnaire was translated into the two national1anguages, Sinhala and Tamil. The translations were independently re-translated into English and compared with the original to ensure exactness of the translation. The questionnaires and all other survey documents were· printed by the Printing Division of the Department.

Cleaning operations

EDITING, CODING, TABULATION AND ANALYSIS Seventeen of the interviewers and two supervisors were retained for manual editing and coding. These officers were given detailed instructions in editing and coding procedures by two senior officers who were also responsible for the preparation of edit specifications and the coding instructions. A coder was, on average, expected to edit, code and check 20 schedules per day. All responses to questions were given specific numeric, machine readable values. Since all but two questions used pre-coded responses, the work of the coders was fairly simple and it progressed smoothly. Computer processing of the data was carried out by the Data Processing Division of the Department of Census and Statistics.. Data were key punched directly from the schedules. Error printouts were returned to the editors and coders for correction. At the end of each correction, the files were updated and the edit program was re-run until a clean data file was obtained. The specified tabulations were prepared well within the allotted time of 2 ½ months from June to early August. Each tabulation was checked for likely errors and internal consistency and it was possible to make the necessary corrections without much delay. These tabulations were made available to any interested institution in order to enable the data from the survey to be used as early as possible. A preliminary analysis of the data was carried out by a team of 6 staff' members of the Department of Census and Statistics. In this task they were assisted by the Westinghouse representative whose advice and comments were particularly valuable in the presentation of results. These findings were presented

Socio-demographic and anthropometric characteristics of the participants.

The presence of SARS-CoV-2 specific total antibodies and neutralizing antibodies in COVID-19 patients, their close contacts and non-close contacts in the Colombo Municipality region.

Abstract

The Department of Census and Statistics conducted a Household Survey of Agriculture Sector in 1988/89, with a view of obtaining detail information on Agriculture Households which are required for formulation and evaluation of Agricultural Policies and Programmes, and which cannot be obtained from decennial Agricultural Censuses.

Information collected in this survey were on demographic characteristics of the household member such as age, sex, relationship to head of the household, ..... etc., land utilization and ownership, home-garden cultivation, labour utilization, their wages, in-puts, outputs and sales and finally loans and subsidies taken.

Listing operation was done prior to the survey proper. At the listing stage the households with at least one of its members engaged in cultivation, livestock/poultry keeping or fisheries, either as an employer or an own account worker or a labourer were identified and a list was prepared for the selected block.

Geographic coverage

National coverage except Nothern & Eastern Districts.

Analysis unit

Agricultural Household

Universe

Agricultural Households in Sri Lanka

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified two stage probability sample design was used with Census Blocks (CB) as primary sampling units (PSU's) and Agricultural households as secondary sampling units (SSU's).

It was decided to include 2,500 census blocks in the sample. These 2,500 CBS were proportionately allocated between the 25 districts and the two sectors ( urban and rural ), based on the total of Agricultural personnel as at 1981 Population Census.

It was however noticed that the number of Agricultural Households in certain urban blocks were very few. hence it was decided to double the number of urban blocks and to select 5 households from each urban block and 10 households from each rural block.

ALLOCATION OF FIRST STAGE SAMPLE UNITS BY DISTRICT & SECTOR

 DISTRICTS        URBAN     RURAL      ALL
                                          ISLAND

1. Colombo 20 40 60
2. Gampaha 22 86 108
3. Kalutara 10 122 132
4. Kandy 4 92 96
5. Matale 2 94 96
6. Nuwara-Eliya 6 54 60
7. Galle 12 96 108
8. Matara 8 76 84
9. Hambantota 8 112 120
10. Jaffna 62 106 168
11. Mannar 4 56 60
12. Vavuniya 4 44 48
13. Mullaitivu 6 42 48
14. Batticaloa 16 92 108
15. Ampara 12 108 120
16. Trincomalee 24 60 84
17. Kurunegala 2 178 180
18. Puttalam 18 126 144
19. Anuradhapura 2 178 180
20. Polonnaruwa 4 92 96
21. Badulla 2 118 120
22. Monaragala 2 106 108
23. Ratnapura 4 164 168
24. Kegalle 2 130 132

25. Kilinochchi 4 32 36

      Total              260         2404        2664
    

It was also decided that, the maximum number of blocks allocated to a district to be not more than 180 blocks and minimum to be not less than 36 blocks. The number of blocks within districts were adjusted as above and was readjusted so that in any district, the final number of sample blocks to be a multiple of 12. This enabled distributing the final number of blocks over the 12 rounds (monthly rounds). Finally the number of census blocks (PSU's) selected was 2,664 and the number of households selected (SSU's) was 25, 340.

Mode of data collection

Face-to-face [f2f]

人口：中年人口：女性：科伦坡在06-01-2018达1,242.000千人，相较于06-01-2017的1,232.000千人有所增长。人口：中年人口：女性：科伦坡数据按年更新，06-01-2001至06-01-2018期间平均值为1,203.000千人，共18份观测结果。该数据的历史最高值出现于06-01-2011，达1,273.000千人，而历史最低值则出现于06-01-2001，为1,100.000千人。CEIC提供的人口：中年人口：女性：科伦坡数据处于定期更新的状态，数据来源于Department of Census and Statistics，数据归类于Global Database的斯里兰卡 – 表 LK.G001：人口：中年人口。