Population: Census: Guangdong: Guangzhou data was reported at 18,676.605 Person th in 12-01-2020. This records an increase from the previous number of 12,701.900 Person th for 12-01-2010. Population: Census: Guangdong: Guangzhou data is updated decadal, averaging 12,701.900 Person th from Dec 2000 (Median) to 12-01-2020, with 3 observations. The data reached an all-time high of 18,676.605 Person th in 12-01-2020 and a record low of 9,942.022 Person th in 12-01-2000. Population: Census: Guangdong: Guangzhou data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: By Census.

By 2035, nearly ** million people are predicted to call Guangzhou home. As one of the key cities in the Guangdong-Hong Kong-Macao Greater Bay Area, Guangzhou’s vibrancy is very attractive to people searching for their opportunities there.

Megacity – Guangzhou

As China’s cities become increasingly urbanized, the demographic of this megacity has also changed considerably over the years, with more and more Chinese locals and foreigners opting to dwell in Guangzhou for work and cultural opportunities. Together with Beijing, Shanghai and Shenzhen, Guangzhou is listed as one of China’s first-tier cities, indicating its great economic power and developing potential. Guangzhou has been a large port of China for over *** thousand years and has contributed significantly to the economic and cultural exchange between China and the world. Today, the Guangzhou Port is one of the largest in the world.

Multicultural hub

The traces of immigrants from different times to this city can be easily found in Guangzhou’s architecture. In the former colonial area, there are still plenty of old western style buildings. Today’s Guangzhou is one of the Chinese cities with the highest density of skyscrapers in some business areas. The Canton Tower, landmark of Guangzhou, is *** meters tall and the second tallest tower in the world after Tokyo Skytree. In this capital city of the Guangdong province, Cantonese culture is highly respected and well developed. Guangzhou is also one of the Chinese cities with the largest foreign population. Cantonese, Mandarin and English are the widely used languages of the residents in Guangzhou.

This statistic illustrates the population of the Guangdong - Hong Kong - Macao Greater Bay Area cities in 2024. That year, the population of Guangzhou amounted to approximately ***** million people, making it the largest city by population in the region.

Historical dataset of population level and growth rate for the Guangzhou, Guangdong, China metro area from 1950 to 2025.

Population: Guangdong: Guangzhou: Household Registration data was reported at 10,566.070 Person th in 2023. This records an increase from the previous number of 10,349.074 Person th for 2022. Population: Guangdong: Guangzhou: Household Registration data is updated yearly, averaging 7,066.438 Person th from Dec 1978 (Median) to 2023, with 46 observations. The data reached an all-time high of 10,566.070 Person th in 2023 and a record low of 4,828.961 Person th in 1978. Population: Guangdong: Guangzhou: Household Registration data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

Population: Household Registration: Birth Rate: Guangdong: Guangzhou data was reported at 11.070 ‰ in 2023. This records an increase from the previous number of 10.720 ‰ for 2022. Population: Household Registration: Birth Rate: Guangdong: Guangzhou data is updated yearly, averaging 10.905 ‰ from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 22.730 ‰ in 2017 and a record low of 7.920 ‰ in 2003. Population: Household Registration: Birth Rate: Guangdong: Guangzhou data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Growth Rate.

Population: Usual Residence: Urbanization Rate: Guangdong: Guangzhou data was reported at 86.760 % in 2023. This records an increase from the previous number of 86.480 % for 2022. Population: Usual Residence: Urbanization Rate: Guangdong: Guangzhou data is updated yearly, averaging 84.380 % from Dec 2010 (Median) to 2023, with 14 observations. The data reached an all-time high of 86.760 % in 2023 and a record low of 83.790 % in 2010. Population: Usual Residence: Urbanization Rate: Guangdong: Guangzhou data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Urbanization Rate.

As of 2025, Guangzhou had the largest metropolitan population in the Asia-Pacific region, with approximately **** million inhabitants. Tokyo had the second-largest metropolitan population of around **** million inhabitants. There were a total of ** megacities with a population of over 10 million inhabitants in the Asia-Pacific region as of 2025.

As of 2023, around **** percent of the total population of Guangdong province in China were 65 years old or older. Guangdong is the most populous province in China, and its population density is higher than in many countries in the world.

Guangzhou is a city with a population of 15,273,343 and lies in the 5000 and above (Very High) density category. The city has an area of 2378.88 km² with a total green space of 34% and a tree coverage of 25%. The city lies in the Torrid Zone of the world. The city has improved its Urban green space per capita when compared to Global Average and also improved its Urban green space per capita when compared to previous year. Within Central East Asia, 38.9% of cities are ranked lower than Guangzhou.

Population: Household Registration: Urbanization Rate: Guangdong: Guangzhou data was reported at 81.860 % in 2023. This records an increase from the previous number of 81.160 % for 2022. Population: Household Registration: Urbanization Rate: Guangdong: Guangzhou data is updated yearly, averaging 79.900 % from Dec 2015 (Median) to 2023, with 9 observations. The data reached an all-time high of 81.860 % in 2023 and a record low of 79.690 % in 2017. Population: Household Registration: Urbanization Rate: Guangdong: Guangzhou data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Urbanization Rate.

Population: Guangdong: Guangzhou: Usual Residence data was reported at 18,827.000 Person th in 2023. This records an increase from the previous number of 18,734.100 Person th for 2022. Population: Guangdong: Guangzhou: Usual Residence data is updated yearly, averaging 12,795.150 Person th from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 18,827.000 Person th in 2023 and a record low of 9,496.800 Person th in 2005. Population: Guangdong: Guangzhou: Usual Residence data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GBA: Population: GBA.

The Gross Domestic Product is used as the estimator, see text. The corresponding values are plotted in Fig 6a. It is clear that the true population size of large coastal cities is not well described by the Hukou system count, but better captured by the estimates resulting from the residuals of the scaling relations for GDP.

Population: Guangdong: Guangzhou: Zengcheng data was reported at 860.000 Person th in 2014. This records an increase from the previous number of 850.000 Person th for 2013. Population: Guangdong: Guangzhou: Zengcheng data is updated yearly, averaging 850.000 Person th from Dec 2004 (Median) to 2014, with 11 observations. The data reached an all-time high of 900.000 Person th in 2009 and a record low of 790.000 Person th in 2005. Population: Guangdong: Guangzhou: Zengcheng data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

1 Continuous variables were shown as the means±standard deviation. Categorical variables were shown as numbers (percents). Variables were evaluated in conditional logistic model.2 Variables were scored as yes or no, and numbers (percents) of yes responses were listed. House decoration refers to replacement of floor board, wall, and indoor painting for almost a whole flat or house; new furniture refers to a set of new furniture for living room(s) and bed room(s). 3 Occupation was categorized into 3 levels on the basis of the intensity of occupational physical activity.4 Smoking status was defined as current smoker, ex-smoker or nonsmoker (a smoker was defined as someone smoking at least one cigarette per day for at least six months).5 Passive smoking was designated as exposure to other peoples' tobacco smoke for at least 5 minutes daily in the previous five years.6 Physical activity was defined as occupational, leisure time and household chores activity, and evaluated by metabolic equivalent hours per day (MET∙ h/d).Abbreviations: BMI: body mass index; NPC: Nasopharyngeal carcinoma; MET: metabolic equivalent1 .

Population: Household Registration: Natural Change: Guangdong: Guangzhou data was reported at 38.860 Person th in 2023. This records a decrease from the previous number of 52.234 Person th for 2022. Population: Household Registration: Natural Change: Guangdong: Guangzhou data is updated yearly, averaging 47.069 Person th from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 140.011 Person th in 2017 and a record low of 16.195 Person th in 2003. Population: Household Registration: Natural Change: Guangdong: Guangzhou data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Change.

BackgroundA novel avian-origin influenza A(H7N9) caused a major outbreak in Mainland China in early 2013. Exposure to live poultry was believed to be the major route of infection. There are limited data on how the general public changes their practices regarding live poultry exposure in response to the early outbreak of this novel influenza and the frequency of population exposure to live poultry in different areas of China.MethodologyThis study investigated population exposures to live birds from various sources during the outbreak of H7N9 in Guangzhou city, China in 2013 and compared them with those observed during the 2006 influenza A(H5N1) outbreak. Adults were telephone-interviewed using two-stage sampling, stratified by three residential areas of Guangzhou: urban areas and two semi-rural areas in one of which (Zengcheng) A(H7N9) virus was detected in a chicken from wet markets. Logistic regression models were built to describe practices protecting against avian influenza, weighted by age and gender, and then compare these practices across residential areas in 2013 with those from a comparable 2006 survey.Principal FindingsOf 1196 respondents, 45% visited wet markets at least daily and 22.0% reported buying live birds from wet markets at least weekly in April-May, 2013, after the H7N9 epidemic was officially declared in late March 2013. Of those buying live birds, 32.3% reported touching birds when buying and 13.7% would slaughter the poultry at home. Although only 10.1% of the respondents reported raising backyard birds, 92.1% of those who did so had physical contact with the birds they raised. Zengcheng respondents were less likely to report buying live birds from wet markets, but more likely to buy from other sources when compared to urban respondents. Compared with the 2006 survey, the prevalence of buying live birds from wet markets, touching when buying and slaughtering birds at home had substantially declined in the 2013 survey.Conclusion/SignificanceAlthough population exposures to live poultry were substantially fewer in 2013 compared to 2006, wet markets and backyard poultry remained the two major sources of live bird exposures for the public in Guangzhou in 2013. Zengcheng residents seemed to have reduced buying live birds from wet markets but not from other sources in response to the detection of H7N9 virus in wet markets.

Achieving high coverage of HIV testing services is critical in many health systems, especially where HIV testing services remain centralized and inconvenient for many. As a result, planning the optimal spatial distribution of HIV testing sites is increasingly important. We aimed to assess the relationship between geographic distance and uptake of HIV testing services among the general population in Guangzhou, China. Utilizing spatial epidemiological methods and stratified household random sampling, we studied 666 adults aged 18–59. Computer-assisted interviews assessed self-reported HIV testing history. Spatial scan statistic assessed the clustering of participants who have ever been tested for HIV, and two-level logistic regression models assessed the association between uptake of HIV testing and the mean driving distance from the participant’s residence to all HIV testing sites in the research sites. The percentage of participants who have ever been tested for HIV was 25.2% (168/666, 95%CI: 21.9%, 28.5%), and the majority (82.7%) of participants tested for HIV in Centres for Disease Control and Prevention, public hospitals or STIs clinics. None reported using self-testing. Spatial clustering analyses found a hotspot included 48 participants who have ever been tested for HIV and 25.8 expected cases (Rate Ratio = 1.86, P = 0.002). Adjusted two-level logistic regression found an inverse relationship between geographic distance (kilometers) and ever being tested for HIV (aOR = 0.90, 95%CI: 0.84, 0.96). Married or cohabiting participants (aOR = 2.14, 95%CI: 1.09, 4.20) and those with greater social support (aOR = 1.04, 95%CI: 1.01, 1.07) were more likely to be tested for HIV. Our findings underscore the importance of considering the geographical distribution of HIV testing sites to increase testing. In addition, expanding HIV testing coverage by introducing non-facility based HIV testing services and self-testing might be useful to achieve the goal that 90% of people living with HIV knowing their HIV status by the year 2020.

Population: Household Registration: Number of Birth: Guangdong: Guangzhou data was reported at 115.804 Person th in 2023. This records an increase from the previous number of 109.648 Person th for 2022. Population: Household Registration: Number of Birth: Guangdong: Guangzhou data is updated yearly, averaging 100.780 Person th from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 200.958 Person th in 2017 and a record low of 57.277 Person th in 2003. Population: Household Registration: Number of Birth: Guangdong: Guangzhou data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Change.

BackgroundThe cesarean section (CS) rate has risen globally during the last two decades. Effective and feasible strategies are needed to reduce it. The aim of this study was to assess the CS rate change after a two-stage intervention package that was designed to reduce the overall CS rate in Guangzhou, China.Methods and findingsThis intervention package was implemented by the Health Commission of Guangzhou Municipality in 2 stages (October 2010–September 2014 and October 2014–December 2016) and included programs for population health education, skills training for healthcare professionals, equipment and technical support for local healthcare facilities, and capacity building for the maternal near-miss care system. A retrospective repeated cross-sectional study was conducted to evaluate influences of the intervention on CS rates. A pre-intervention period from January 2008 to September 2010 served as the baseline. The primary outcome was the CS rate, and the secondary outcomes included maternal mortality ratio (MMR) and perinatal mortality rate (PMR), all obtained from the Guangzhou Perinatal Health Care and Delivery Surveillance System (GPHCDSS). The Cochran-Armitage test was used to examine the trends of the overall CS rate, MMR, and PMR across different stages. Segmented linear regression analysis was used to assess the change of the CS rate over the intervention period.A total of 1,921,932 records of births and 108 monthly CS rates from 2008 to 2016 were analyzed. The monthly CS rate declined across the intervention stages (Z = 75.067, p < 0.001), with an average rate of 42.4% at baseline, 39.8% at Stage 1, and 35.0% at Stage 2. The CS rate declined substantially among nulliparous women who delivered term singletons, with an accelerating decreasing trend observed across Stage 1 and Stage 2 (the difference in slopes: −0.09 [95% CI −0.16 to −0.02] between Stage 1 and baseline, p = 0.014; −0.11 [95% CI −0.20 to −0.02] between Stage 1 and Stage 2, p = 0.017). The CS rate in the remaining population increased during baseline and Stage 1 and subsequently decreased during Stage 2. The sensitivity analysis suggested no immediate impact of the universal two-child policy on the trend of the CS rate. The MMR (Z = −4.368, p < 0.001) and PMR (Z = −13.142, p < 0.001) declined by stage over the intervention period.One of the main limitations of the study is the lack of a parallel control group. Moreover, the influence of temporal changes in the study population on the CS rate was unknown. Given the observational nature of the present study, causality cannot be confirmed.ConclusionsApparent decline in the overall CS rate was observed in Guangzhou, China, after the implementation of a two-stage intervention package. The decline was most evident among nulliparous women who delivered term singletons. Despite some limitations for causal inference, Guangzhou’s experience in controlling the CS rate by implementing composite interventions with public health education and perinatal healthcare service improvement could have implications for other similar areas with high rates of CS.