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

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.

Mogadishu in Somalia led the ranking of cities with the highest population density in 2025, with ****** residents per square kilometer. When it comes to countries, Monaco is the most densely populated state worldwide.

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.

Local weather influences the transmission of the dengue virus. Most studies analyzing the relationship between dengue and climate are based on relatively coarse aggregate measures such as mean temperature. Here, we include both mean temperature and daily fluctuations in temperature in modelling dengue transmission in Dhaka, the capital of Bangladesh. We used a negative binomial generalized linear model, adjusted for rainfall, anomalies in sea surface temperature (an index for El Niño-Southern Oscillation), population density, the number of dengue cases in the previous month, and the long term temporal trend in dengue incidence. In addition to the significant associations of mean temperature and temperature fluctuation with dengue incidence, we found interaction of mean and temperature fluctuation significantly influences disease transmission at a lag of one month. High mean temperature with low fluctuation increases dengue incidence one month later. Besides temperature, dengue incidence was also influenced by sea surface temperature anomalies in the current and previous month, presumably as a consequence of concomitant anomalies in the annual rainfall cycle. Population density exerted a significant positive influence on dengue incidence indicating increasing risk of dengue in over-populated Dhaka. Understanding these complex relationships between climate, population, and dengue incidence will help inform outbreak prediction and control.

The data set is a 2015 heat wave hazard, exposure and vulnerability data set in Dhaka, Bangladesh, with a spatial resolution of 30m and a temporal resolution of yearly. Heat wave hazard is an index to measure the severity of heat wave event, which is expressed by surface temperature; heat wave exposure refers to the degree that human, livelihood and economy may be adversely affected, which is expressed by nighttime lighting data, and population density. The population older than 65 and younger than 5 years old constitute vulnerable groups; heat wave vulnerability is a measure of increased / reduced risk in the environment. The distance from road / hospital and ambulance station / water body, NDVI, impervious layer and slum area are used to represent the vulnerability of high temperature heat wave. The data set has been proved by experts, which can provide support for regional high temperature heat wave risk assessment.

n1: total number of animals sighted and marked on the first samplen2: total number of animals sighted on the second samplem: number of marked animals on the first sample that were re-sighted on the second sampleN is the estimated total population of dogs using Chapman estimates with 95% confidence interval (see Eqs 1 and 2 in the text).*Total estimated population is the sum of the estimate in each wardEstimation of the number of free-roaming dogs and dog density in Dhaka City, Bangladesh during January and March 2011.

The Bangladesh construction market, valued at $32.33 million in 2025, is projected to experience robust growth, driven by significant government investment in infrastructure development, rapid urbanization, and a burgeoning population. A Compound Annual Growth Rate (CAGR) of 6.42% is anticipated from 2025 to 2033, indicating a substantial market expansion. Key growth drivers include the government's focus on improving transportation networks (roads, railways, ports), the rising demand for residential housing fueled by population growth and economic development, and increasing investment in energy and utility infrastructure to support industrial expansion. The market is segmented into residential, commercial, industrial, infrastructure (transportation), and energy and utilities sectors, each contributing to the overall growth trajectory. While challenges such as land acquisition complexities and potential material price fluctuations exist, the long-term outlook for the Bangladesh construction market remains positive. The strong government support and continuous economic growth are expected to offset these challenges, ensuring sustained market expansion over the forecast period. Leading companies like Mir Akhter Hossain Limited, Mazid Sons Constructions Ltd, and others play a significant role in shaping the market landscape through their project execution capabilities and market expertise. The competitive landscape is dynamic, with both large multinational corporations and local players vying for market share. The increasing adoption of advanced construction technologies and sustainable building practices is also expected to further enhance the market's efficiency and growth potential. The focus on improving infrastructure will be a key driver in the coming years, attracting both domestic and international investment. This growth is likely to be distributed across all market segments, with residential construction possibly witnessing the highest growth rate due to increasing urbanization and population density. Recent developments include: March 2023: Japan was to provide USD 1.27 billion to Bangladesh for 3 infrastructure projects, including the building of Matarbari commercial port in Southeast, according to Bangladesh's Finance Ministry., October 2022: Construction of Dhaka's 31.24 km MRT Line 1, Bangladesh's first metro, was due to start in December 2022. A contract for project construction monitoring services was signed by the Dhaka Mass Rapid Transit Business (DMTCL), the metro project's executing agency, and a Japanese joint venture company led by Nippon Koei. The consortium also includes Oriental Consultants Global, Systra, Delhi Metro Rail, Nippon Koei India, Katahira and Engineers International, Development Design Consultants, and Nippon Koei Bangladesh.. Key drivers for this market are: 4., Rapid Urbanization is driving the market4.; Government Initiatives Actively promoting the Construction Activities. Potential restraints include: 4., Rapid Urbanization is driving the market4.; Government Initiatives Actively promoting the Construction Activities. Notable trends are: Growth in Infrastructure Activities is driving the market.

Bangladesh BD: Population Living in Slums: % of Urban Population data was reported at 51.869 % in 2020. This records a decrease from the previous number of 52.513 % for 2018. Bangladesh BD: Population Living in Slums: % of Urban Population data is updated yearly, averaging 55.090 % from Dec 2000 (Median) to 2020, with 11 observations. The data reached an all-time high of 58.311 % in 2000 and a record low of 51.869 % in 2020. Bangladesh BD: Population Living in Slums: % 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 living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, housing durability, and security of tenure, as adopted in the Millennium Development Goal Target 7.D. The successor, the Sustainable Development Goal 11.1.1, considers inadequate housing (housing affordability) to complement the above definition of slums/informal settlements.;United Nations Human Settlements Programme (UN-HABITAT);Weighted average;

aSD and IQR denoted standard deviation and interquartile range, respectively.bP-values from Fisher's exact test for sex, marital status, education attainment, BMI, cigarette smoking, and skin lesion; or from Wilcoxon rank sum test with continuity correction for age, and arsenic in drinking water. 1 participant was missing for education and 8 participants were missing for smoking status.

In 2024, Bangladesh's capital Dhaka had a pollution index score of ****, the highest among megacities in the Asia-Pacific region. In contrast, Japan's capital Tokyo had a pollution index score of **** that year. Megacities on course for growth The United Nations defines megacities as cities with over ten million inhabitants. The population living in megacities has doubled in size in the last twenty years and is expected to rise even more until 2035. Today, the Asia-Pacific region is home to the highest number of megacities, with China and India alone accounting for around half of all megacities worldwide. At the same time, only half of the population in Asia is living in cities. This figure is also expected to rise exponentially over the next years, especially with much of the younger population migrating to larger cities. The growth of megacities and their higher population densities bring along several environmental problems. Exposure to pollution in India The most populated cities in APAC are located in Japan, China and India. As seen above, India's capital also falls among the top three most polluted megacities in the region and ranks second among the most polluted capital cities worldwide with an average PM2.5 concentration. As one of the fastest emerging economies in the world, India's rapid urbanization and industrialization have led to high pollution rates in different areas. The volume of emissions from coal-fired power plants has led to electricity and heat accounting for the largest share of greenhouse gas emissions in India. The country is also among the nations with the highest population share exposed to hazardous concentrations of air pollution worldwide.

Total migrants, population, migration rate (%), and relative change (%) by division.