This statistic shows the biggest cities in Bangladesh in 2022. In 2022, approximately ***** million people lived in Dhaka, making it the biggest city in Bangladesh.

Bangladesh BD: Population in Largest City data was reported at 23,935,652.000 Person in 2024. This records an increase from the previous number of 23,209,616.000 Person for 2023. Bangladesh BD: Population in Largest City data is updated yearly, averaging 7,344,419.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 23,935,652.000 Person in 2024 and a record low of 507,921.000 Person in 1960. Bangladesh BD: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.;United Nations, World Urbanization Prospects.;;

Actual value and historical data chart for Bangladesh Population In Largest City

Bangladesh BD: Population in Largest City: as % of Urban Population data was reported at 33.448 % in 2024. This records an increase from the previous number of 33.444 % for 2023. Bangladesh BD: Population in Largest City: as % of Urban Population data is updated yearly, averaging 30.733 % from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 33.448 % in 2024 and a record low of 19.085 % in 1960. Bangladesh BD: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.;United Nations, World Urbanization Prospects.;Weighted average;

The below dataset shows the top 800 biggest cities in the world and their populations in the year 2024. It also tells us which country and continent each city is in, and their rank based on population size. Here are the top ten cities:

• Tokyo, Japan - in Asia, with 37,115,035 people.
• Delhi, India - in Asia, with 33,807,403 people.
• Shanghai, China - in Asia, with 29,867,918 people.
• Dhaka, Bangladesh - in Asia, with 23,935,652 people.
• Sao Paulo, Brazil - in South America, with 22,806,704 people.
• Cairo, Egypt - in Africa, with 22,623,874 people.
• Mexico City, Mexico - in North America, with 22,505,315 people.
• Beijing, China - in Asia, with 22,189,082 people.
• Mumbai, India - in Asia, with 21,673,149 people.
• Osaka, Japan - in Asia, with 18,967,459 people.

The population density in Bangladesh reached its highest in 2020, amounting to approximately 1.27 thousand people per square kilometer. The South Asian country was the tenth most densely populated country in the world in 2019. Within the Asia Pacific region, Bangladesh’s population density was only exceeded by Macao, Singapore, Hong Kong, and the Maldives. Overall, Asia had the highest population density in the world in 2018.

Population growth in Bangladesh

In 1971, Bangladesh gained its independence from Pakistan. Bangladesh’s birth rate and mortality rate had declined significantly in the past years with a life expectancy of 72.59 years in 2019. In general, the population in Bangladesh had been growing at a slow pace, slightly fluctuating around an annual rate of one percent. This growth was forecasted to continue, although it was estimated to halve by 2040. As of today, Dhaka is the largest city in Bangladesh.

Population density explained

According to the source, “population density is the mid-year population divided by land area in square kilometers.” Further, “population is based on the de facto definition of population, which counts all residents.” Bangladesh’s population reached an estimated number of 164.69 million inhabitants in 2020. In 2018, the country’s land area amounted 130.2 thousand square kilometers.

This horizontal bar chart displays population (people) by cities using the aggregation sum in Bangladesh. The data is about cities.

Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Other Deposit Takers for Bangladesh (BGDFCBODDLNUM) from 2004 to 2015 about branches and Bangladesh.

This horizontal bar chart displays land area (km²) by capital city using the aggregation sum in Bangladesh. The data is filtered where the date is 2021. The data is about countries per year.

This horizontal bar chart displays median age (year) by capital city using the aggregation average, weighted by population in Bangladesh. The data is filtered where the date is 2021. The data is about countries per year.

Graph and download economic data for Geographical Outreach: Number of Branches in 3 Largest Cities, Excluding Headquarters, for Deposit Taking Microfinance Institutions (MFIs) for Bangladesh (BGDFCBODMFLNUM) from 2004 to 2015 about microfinance, branches, Bangladesh, and deposits.

最大城市人口占城市总人口的百分比在12-01-2024达33.448%，相较于12-01-2023的33.444%有所增长。最大城市人口占城市总人口的百分比数据按年更新，12-01-1960至12-01-2024期间平均值为30.733%，共65份观测结果。该数据的历史最高值出现于12-01-2024，达33.448%，而历史最低值则出现于12-01-1960，为19.085%。CEIC提供的最大城市人口占城市总人口的百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的孟加拉 – Table BD.World Bank.WDI: Population and Urbanization Statistics。

This horizontal bar chart displays countries yearly by capital city using the aggregation count in Bangladesh. The data is filtered where the date is 2021. The data is about countries per year.

This horizontal bar chart displays net migration (people) by capital city using the aggregation sum in Bangladesh. The data is filtered where the date is 2023. The data is about countries per year.

The main objective of the 2019 Chattogram for Low Income Area Gender, Inclusion, and Poverty (CITY) study is to collect primary data from male and female residents in slum and non-slum poor neighborhoods in Chattogram, the second largest city of Bangladesh, and build the evidence base about their constraints to access more and better jobs. The CITY survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh as well as to identify key constraints and solutions for low-income women trying to obtain better jobs.

A broad array of information was collected on issues related to women's economic empowerment, ranging from demographic and socioeconomic characteristics to detailed work history, time use, attitudes about work, and perceptions of work. The key feature of this survey is to collect economic data directly from the main household members, generally the main couples, unlike traditional surveys which only interviewed the heads of households (who tend to be men in most cases); thus, failed to gather valuable information from the female population.

The SHAHAR (Supporting Household Activities for Health, Assets and Revenue) project aims to increase incomes and improve unhygienic environments and sanitation conditions in poor urban communities, including slums, in major selected secondary cities in Bangladesh. Using relevant indicators namely socioeconomic; health and hygiene; nutrition and diet; and governance and social institutions the project provides insight into the livelihood conditions and the livelihood security of these slum households. The SHAHAR baseline survey was conducted in July to August, 2002 in slum (basti) communities in Dinajpur. The SHAHAR census survey suggested that only 52 percent of households had children under 5 years of age; doubling the sample size would ensure that the final sample would have at least this many households with children under 5 years of age. This gave an estimated sample size of 271 * 2 = 542. As slum dwellers are assumed to be highly mobile, and the losses would increase over the year between round I in July – August, 2002 and round III a year later, a substantial reserve was added to the sample, as well as some allowance for refusal or other non-response, for a final total of 614 households. The field survey was carried out by two teams, each consisting of three male and female pairs and a supervisor. One pair interviewed one household at a time, with the female interviewer interviewing the main female member of the household and collecting information on household composition, migration and education; training; savings; loans; food consumption; household food security; health; anthropometry and childcare; environment, water and sanitation; shocks and coping strategies; social capital; crime, violence, physical security; governance; and women’s status. The male interviewer interviewed the main male member of the household asking questions on language, religion, and migration; training; employment; transfers, social assistance and other income; household assets; land own ership and tenure; urban agriculture; savings; loans; housing; non food expenditure; shocks and coping strategies; social capital; crime, violence and physical security; and governance. The pairs on each team worked together to cover three households per day and the 614 households surveyed in approximately 39 days in July to August, 2002 in Dinajpur. The SHAHAR (Supporting Household Activities for Health, Assets and Revenue) Dinajpur baseline survey was conducted in collaboration with Data Analysis and Technical Assistance (DATA), Dhaka, Bangladesh; and CARE-Bangladesh. The questionnaires were developed by the International Food Policy Research Institute. The funding for the survey was provided by CARE-Bangladesh; and US Agency for International Development (USAID).

This horizontal bar chart displays forest area (km²) by capital city using the aggregation sum in Bangladesh. The data is filtered where the date is 2021. The data is about countries per year.

Abstract

The 2018 Dhaka Low Income Area Gender, Inclusion, and Poverty (DIGNITY) survey attempts to fill in the data and knowledge gaps on women's economic empowerment in urban areas, specifically the factors that constrain women in slums and low-income neighborhoods from engaging in the labor market and supplying their labor to wage earning or self-employment. While an array of national-level datasets has collected a wide spectrum of information, they rarely comprise all of the information needed to study the drivers of Female Labor Force Participation (FLFP). This data gap is being filled by the primary data collection of the specialized DIGNITY survey; it is representative of poor urban areas and is specifically designed to address these limitations. The DIGNITY survey collected information from 1,300 urban households living in poor areas of Dhaka in 2018 on a range of issues that affect FLFP as identified through the literature. These range from household composition and demographic characteristics to socioeconomic characteristics such as detailed employment history and income (including locational data and travel details); and from technical and educational attributes to issues of time use, migration history, and attitudes and perceptions.

The DIGNITY survey was designed to shed light on poverty, economic empowerment, and livelihood in urban areas of Bangladesh. It has two main modules: the traditional household module (in which the head of household is interviewed on basic information about the household); and the individual module, in which two respondents from each household are interviewed individually. In the second module, two persons - one male and one female from each household, usually the main couple, are selected for the interview. The survey team deployed one male and one female interviewer for each household, so that the gender of the interviewers matched that of the respondents. Collecting economic data directly from a female and male household member, rather than just the head of the household (who tend to be men in most cases), was a key feature of the DIGNITY survey.

Geographic coverage

The DIGNITY survey is representative of low-income areas and slums of the Dhaka City Corporations (North and South, from here on referred to as Dhaka CCs), and an additional low-income site from the Greater Dhaka Statistical Metropolitan Area (SMA).

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling procedure followed a two-stage stratification design. The major features include the following steps (they are discussed in more detail in a copy of the study's report and the sampling document located in "External Resources"):

FIRST STAGE: Selection of the PSUs

Low-income primary sampling units (PSUs) were defined as nonslum census enumeration areas (EAs), in which the small-sample area estimate of the poverty rate is higher than 8 percent (using the 2011 Bangladesh Poverty Map). The sampling frame for these low-income areas in the Dhaka City Corporations (CCs) and Greater Dhaka is based on the population census of 2011. For the Dhaka CCs, all low-income census EAs formed the sampling frame. In the Greater Dhaka area, the frame was formed by all low-income census EAs in specific thanas (i.e. administrative unit in Bangladesh) where World Bank project were located.

Three strata were used for sampling the low-income EAs. These strata were defined based on the poverty head-count ratios. The first stratum encompasses EAs with a poverty headcount ratio between 8 and 10 percent; the second stratum between 11 and 14 percent; and the third stratum, those exceeding 15 percent.

Slums were defined as informal settlements that were listed in the Bangladesh Bureau of Statistics' slum census from 2013/14. This census was used as sampling frame of the slum areas. Only slums in the Dhaka City Corporations are included. Again, three strata were used to sample the slums. This time the strata were based on the size of the slums. The first stratum comprises slums of 50 to 75 households; the second 76 to 99 households; and the third, 100 or more households. Small slums with fewer than 50 households were not included in the sampling frame. Very small slums were included in the low-income neighborhood selection if they are in a low-income area.

Altogether, the DIGNITY survey collected data from 67 PSUs.

SECOND STAGE: Selection of the Households

In each sampled PSU a complete listing of households was done to form the frame for the second stage of sampling: the selection of households. When the number of households in a PSU was very large, smaller sections of the neighborhood were identified, and one section was randomly selected to be listed. The listing data collected information on the demographics of the household to determine whether a household fell into one of the three categories that were used to stratify the household sample:

i) households with both working-age male and female members; ii) households with only a working-age female; iii) households with only a working-age male.

Households were selected from each stratum with the predetermined ratio of 16:3:1. In some cases there were not enough households in categories (ii) and (iii) to stick to this ratio; in this case all of the households in the category were sampled, and additional households were selected from the first category to bring the total number of households sampled in each PSU to 20.

The total sample consisted of 1,300 households (2,378 individuals).

Sampling deviation

The sampling for 1300 households was planned after the listing exercise. During the field work, about 115 households (8.8 percent) could not be interviewed due to household refusal or absence. These households were replaced with reserved households in the sample.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaires for the survey were developed by the World Bank, with assistance from the survey firm, DATA. Comments were incorporated following the pilot tests and practice session/pretest.

Cleaning operations

Collected data was entered into a computer by using the customized MS Access data input software developed by Data Analysis and Technical Assistance (DATA). Once data entry was completed, two different techniques were employed to check consistency and validity of data as follows:

1. Five (5%) percent of the filled-in questionnaire was checked against entered data to measure the transmission error or typos, and;
2. A logical consistency checking technique was employed to identify inconsistencies using SPSS and or STATA software.

Thematic results at a glance.

This horizontal bar chart displays fertility rate (births per woman) by capital city using the aggregation average, weighted by population female in Bangladesh. The data is filtered where the date is 2021. The data is about countries per year.