39 datasets found
  1. Population in China 2014-2024, by gender

    • statista.com
    Updated Jan 15, 2025
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    Statista (2025). Population in China 2014-2024, by gender [Dataset]. https://www.statista.com/statistics/251129/population-in-china-by-gender/
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    Dataset updated
    Jan 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2024, there were around 719 million male inhabitants and 689 million female inhabitants living in China, amounting to around 1.41 billion people in total. China's total population decreased for the first time in decades in 2022, and population decline is expected to accelerate in the upcoming years. Birth control in China From the beginning of the 1970s on, having many children was no longer encouraged in mainland China. The one-child policy was then introduced in 1979 to control the total size of the Chinese population. According to the one-child policy, a married couple was only allowed to have one child. With the time, modifications were added to the policy, for example parents living in rural areas were allowed to have a second child if the first was a daughter, and most ethnic minorities were excepted from the policy. Population ageing The birth control led to a decreasing birth rate in China and a more skewed gender ratio of new births due to boy preference. Since the negative economic and social effects of an aging population were more and more felt in China, the one-child policy was considered an obstacle for the country’s further economic development. Since 2014, the one-child policy has been gradually relaxed and fully eliminated at the end of 2015. However, many young Chinese people are not willing to have more children due to high costs of raising a child, especially in urban areas.

  2. Sex ratio in China 2023, by age group

    • statista.com
    Updated Nov 27, 2024
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    Statista (2024). Sex ratio in China 2023, by age group [Dataset]. https://www.statista.com/statistics/282119/china-sex-ratio-by-age-group/
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    Dataset updated
    Nov 27, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    The gender or sex ratio in China has been a contentious issue since the introduction of the one-child policy in 1979, intended to limit the population of the country. Although the policy is no longer in place, the population gender difference throughout the country is still evident. In 2023, fifteen to nineteen-year-old children had the largest gender disparity of 115.3 males to every 100 females. Gender imbalance While the difference of gender at birth has been decreasing in the country over the past decade, China still boasts the world’s most skewed sex ratio at birth at around 110 males born for every 100 females as of 2023. That means there are about 31 million more men in the country than women. This imbalance likely came from the country’s traditional preference for male children to continue the family lineage, in combination with the population control policies enforced. Where does that leave the population? The surplus of young, single men across the country poses a risk for China in many different socio-economic areas. Some of the roll-on effects include males overrepresenting specific labor markets, savings rates increasing, consumption reducing and violent crime increasing across the country. However, the adult mortality rate in China, that is, the probability of a 15-year-old dying before reaching age 60, was significantly higher for men than for women. For the Chinese population over 60 years of age, the gender ratio is in favor of women, with more females outliving their male counterparts.

  3. N

    China, TX Population Breakdown by Gender and Age Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 19, 2024
    + more versions
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    Neilsberg Research (2024). China, TX Population Breakdown by Gender and Age Dataset: Male and Female Population Distribution Across 18 Age Groups // 2024 Edition [Dataset]. https://www.neilsberg.com/research/datasets/8da912ae-c989-11ee-9145-3860777c1fe6/
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    csv, jsonAvailable download formats
    Dataset updated
    Feb 19, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China, Texas
    Variables measured
    Male and Female Population Under 5 Years, Male and Female Population over 85 years, Male and Female Population Between 5 and 9 years, Male and Female Population Between 10 and 14 years, Male and Female Population Between 15 and 19 years, Male and Female Population Between 20 and 24 years, Male and Female Population Between 25 and 29 years, Male and Female Population Between 30 and 34 years, Male and Female Population Between 35 and 39 years, Male and Female Population Between 40 and 44 years, and 8 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. To measure the three variables, namely (a) Population (Male), (b) Population (Female), and (c) Gender Ratio (Males per 100 Females), we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau across 18 age groups, ranging from under 5 years to 85 years and above. These age groups are described above in the variables section. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of China by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for China. The dataset can be utilized to understand the population distribution of China by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in China. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for China.

    Key observations

    Largest age group (population): Male # 15-19 years (53) | Female # 30-34 years (103). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

    Age groups:

    • Under 5 years
    • 5 to 9 years
    • 10 to 14 years
    • 15 to 19 years
    • 20 to 24 years
    • 25 to 29 years
    • 30 to 34 years
    • 35 to 39 years
    • 40 to 44 years
    • 45 to 49 years
    • 50 to 54 years
    • 55 to 59 years
    • 60 to 64 years
    • 65 to 69 years
    • 70 to 74 years
    • 75 to 79 years
    • 80 to 84 years
    • 85 years and over

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

    Variables / Data Columns

    • Age Group: This column displays the age group for the China population analysis. Total expected values are 18 and are define above in the age groups section.
    • Population (Male): The male population in the China is shown in the following column.
    • Population (Female): The female population in the China is shown in the following column.
    • Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in China for each age group.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for China Population by Gender. You can refer the same here

  4. China's sex ratio at birth 1990-2015, by urban-rural area

    • statista.com
    Updated Oct 12, 2015
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    Statista (2015). China's sex ratio at birth 1990-2015, by urban-rural area [Dataset]. https://www.statista.com/statistics/1051004/china-sex-ratio-at-birth-urban-rural-area/
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    Dataset updated
    Oct 12, 2015
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1990 - 2015
    Area covered
    China
    Description

    In 2015, China's sex ratio at birth dropped to ***** boys to 100 girls in rural regions, approximately *** boys more than the urban area. As Chinese families generally favored sons over daughters, aborting female infants was common under the one-child policy. The policy was replaced by a universal two-child policy in 2015. The sex ratio in China remained stable at around *** males to 100 females.

  5. Sex ratio in the age group 0 to 4 years in China 2013-2023

    • statista.com
    Updated Mar 17, 2006
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    Statista (2006). Sex ratio in the age group 0 to 4 years in China 2013-2023 [Dataset]. https://www.statista.com/statistics/251468/sex-ratio-at-birth-in-china/
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    Dataset updated
    Mar 17, 2006
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    The graph shows the sex ratio in the age group of 0 to 4 years in China from 2013 to 2023. In 2023, the ratio in that group was more than *** boys to 100 girls. The sex ratio of the total population in China was ****** males to 100 females in 2023.

  6. Gender distribution in China 2023, by region

    • statista.com
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    Statista, Gender distribution in China 2023, by region [Dataset]. https://www.statista.com/statistics/1087836/china-gender-distribution-by-region-province/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    In 2023, the gender ratio in different regions in China varied greatly, from around 113.2 men per 100 women in Hainan province to only 97.1 men per 100 women in Liaoning. In most provinces in China, there are living more men than women, leading to a national gender ratio of around 104.2 men to 100 women in 2023.

  7. N

    China, Maine Population Breakdown by Gender Dataset: Male and Female...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). China, Maine Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/china-me-population-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China, Maine
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of China town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of China town across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a slight majority of male population, with 51.44% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the China town is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of China town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for China town Population by Race & Ethnicity. You can refer the same here

  8. Population distribution by five-year age group and gender in China 2023

    • statista.com
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    Statista, Population distribution by five-year age group and gender in China 2023 [Dataset]. https://www.statista.com/statistics/1244036/population-distribution-by-five-year-age-group-and-gender-in-china/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    The age distribution of China's population by five-year age groups in 2023 demonstrates that there are more females than males in the population for all age groups below 60 to 64 years. The largest gender difference exists for the younger age groups born between 2000 and 2010 when the one-child policy had been enforced most strictly.

  9. Epidemiological profile of dengue in Zhejiang Province, southeast China

    • plos.figshare.com
    docx
    Updated Jun 1, 2023
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    Jiangping Ren; Feng Ling; Jimin Sun; Zhenyu Gong; Ying Liu; Xuguang Shi; Rong Zhang; Yujia Zhai; Enfu Chen; Zhiping Chen (2023). Epidemiological profile of dengue in Zhejiang Province, southeast China [Dataset]. http://doi.org/10.1371/journal.pone.0208810
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jiangping Ren; Feng Ling; Jimin Sun; Zhenyu Gong; Ying Liu; Xuguang Shi; Rong Zhang; Yujia Zhai; Enfu Chen; Zhiping Chen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Zhejiang, China
    Description

    BackgroundDengue is one of the most important vector-bore infectious diseases in China because of its drastic increase in incidence, geographic extension and profound influence on China’s economy. This study aims to retrospectively uncover the epidemiological profile of dengue in Zhejiang, one of the most developed provinces in China, and to find the problem existing in dengue control and prevention.MethodologyDescriptive analyses on the dengue incidence and associated factors were performed. We also identified potential space-time cluster and generated the risk map of dengue.Principal findingsA total of 529 cases were reported in Zhejiang Province from 2005 to 2016, and 44.4% were imported. 67.7% of cases were 25~60 years old and the overall male-to-female sex ratio was 1.09:1. Dengue was reported all year round and 70.7% of cases occurred between August and October. Indigenous cases were only reported in the period between July to November and more than half occurred in September. Geographically, dengue was most distributed in Jinghua (3.62 per million), Shaoxing (1.00 per million) and Taizhou (0.81 per million) prefecture level cities. Outbreaks were confirmed in Yiwu, Keqiao and Huangyan counties in 2009, 2015, and 2016, respectively. 73.9% cases would seek medical advice within two days after onset and be confirmed within 9 days after onset. 75.6% would be recognized as dengue within 8 days after their first visit. The time intervals between onset and confirmation (median 7 vs 6 days; Wilcoxon rank sum test Z = -2.40, P = 0.016), first visit and confirmation (median 7 vs 6 days; Wilcoxon rank sum test Z = -2.59, P = 0.009) of indigenous cases were significantly longer than those of imported ones. However, the time intervals between onset and first visit for indigenous cases was shorter (median 0 vs 1 days; Wilcoxon rank sum test Z = -2.10, P = 0.036). Fever (99.1%), fatigue (81.9), rash (63.7%), headache (67.2%) and myalgia (52.60%) were the most frequently mentioned symptoms.ConclusionsZhejiang has recently witnessed an increase in incidence and geographic extension of dengue. Timely diagnosis is important to stop local transmission and outbreak.

  10. f

    DataSheet_1_Sex differences in metabolically healthy and metabolically...

    • datasetcatalog.nlm.nih.gov
    • figshare.com
    • +1more
    Updated Nov 23, 2022
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    Liu, Yunfei; Shi, Di; Dang, Jiajia; Ma, Jun; Dong, Yanhui; Ma, Ning; Cai, Shan; Zou, Zhiyong; Song, Yi; Zhong, Panliang (2022). DataSheet_1_Sex differences in metabolically healthy and metabolically unhealthy obesity among Chinese children and adolescents.docx [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000276293
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    Dataset updated
    Nov 23, 2022
    Authors
    Liu, Yunfei; Shi, Di; Dang, Jiajia; Ma, Jun; Dong, Yanhui; Ma, Ning; Cai, Shan; Zou, Zhiyong; Song, Yi; Zhong, Panliang
    Description

    ObjectivesTo analyze sex differences in the prevalence of obesity phenotypes and their risk factors among children and adolescents aged 7-18 years in China.MethodsWe enrolled 15,114 children and adolescents aged 7-18 years into the final analysis. Obesity phenotypes were classified by body mass index (BMI) and metabolic status as metabolically healthy or unhealthy obesity. In addition, we collected four possible influencing factors on obesity phenotypes through questionnaires, including demographic, parental, early life, and lifestyle indicators. Multinomial logistic regression analysis in a generalized linear mixed model (GLMM) was selected to estimate the odds ratio (OR) and 95% confidence interval (95% CI) for identifying risk factors and control the cluster effects of schools. More importantly, the interaction terms of sex and each indicator were established to demonstrate the sex differences.ResultsThe prevalence of metabolically healthy obesity (MHO), metabolically unhealthy obesity (MUO), metabolically healthy overweight and obesity (MHOO), and metabolically unhealthy overweight and obesity (MUOO) were 3.5%, 5.6%, 11.1%, and 13.0% respectively, with higher prevalence in boys (5.3% vs. 1.6%, 7.9% vs. 3.1%, 14.3% vs. 7.7%, 15.6% vs. 10.1%). In addition, younger ages, single children, parental smoking, parental history of diseases (overweight, hypertension, diabetes), caesarean, premature, and delayed delivery time, high birth weight, insufficient sleep time, and excessive screen time were considered as important risk factors of MHO and MUO among children and adolescents (p < 0.05). More notably, boys were at higher risks of MUO when they were single children (boys: OR = 1.56, 95% CI: 1.24-1.96; girls: OR = 1.12, 95% CI: 0.82-1.54), while girls were more sensitive to MUO with parental smoking (girls: OR = 1.34, 95% CI: 1.02-1.76; boys: OR = 1.16, 95% CI: 0.97-1.39), premature delivery (girls: OR = 3.11, 95% CI: 1.59-6.07; boys: OR = 1.22, 95% CI: 0.67-2.22), high birth weight (girls: OR = 2.45, 95% CI: 1.63-3.69; boys: OR = 1.28, 95% CI: 0.96-1.70), and excessive screen time (girls: OR = 1.47, 95% CI: 1.06-2.04; boys: OR = 0.97, 95% CI: 0.79-1.20), with significant interaction term for sex difference (pinteraction < 0.05).ConclusionsMHO and MUO are becoming prevalent among Chinese children and adolescents. Significant sex differences in the prevalence of obesity phenotypes as well as their environmental and genetic risk factors suggest it might be necessary to manage obesity phenotypes problems from a sex perspective.

  11. N

    China, TX Population Breakdown by Gender Dataset: Male and Female Population...

    • neilsberg.com
    csv, json
    Updated Feb 24, 2025
    + more versions
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    Neilsberg Research (2025). China, TX Population Breakdown by Gender Dataset: Male and Female Population Distribution // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/b2276fac-f25d-11ef-8c1b-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 24, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China, Texas
    Variables measured
    Male Population, Female Population, Male Population as Percent of Total Population, Female Population as Percent of Total Population
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the gender classifications (biological sex) reported by the US Census Bureau. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the population of China by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of China across both sexes and to determine which sex constitutes the majority.

    Key observations

    There is a majority of female population, with 62.22% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Scope of gender :

    Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

    Variables / Data Columns

    • Gender: This column displays the Gender (Male / Female)
    • Population: The population of the gender in the China is shown in this column.
    • % of Total Population: This column displays the percentage distribution of each gender as a proportion of China total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for China Population by Race & Ethnicity. You can refer the same here

  12. Female student share in higher education in China 2022, by type

    • statista.com
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    Statista, Female student share in higher education in China 2022, by type [Dataset]. https://www.statista.com/statistics/1324102/china-postgraduate-undergraduate-student-gender-distribution-by-type/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    China
    Description

    In 2022, more than *** million students were enrolled in master's and doctor's degree programs at colleges and universities in China. Female students accounted for almost ** percent of master's degrees enrolment, significantly higher than that of doctor's degrees.

  13. Compromise areas in a romantic relationship in China 2021, by gender

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Compromise areas in a romantic relationship in China 2021, by gender [Dataset]. https://www.statista.com/statistics/1343889/china-compromise-areas-in-romantic-relationship-by-gender/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2021
    Area covered
    China
    Description

    According to a survey conducted on WeChat in China in the end of 2021, not only more female than male respondents had specific deal-breakers in a romantic relationship, but females were also less willing to compromise. Around **** percent of surveyed women said they would not compromise on anything in a relationship. Restraining one's temper for the sake of a better relationship was the most popular compromise area both for male and female respondents.

  14. Study on Current Levels of Physical Activity and Sedentary Behavior among...

    • plos.figshare.com
    docx
    Updated Jun 2, 2023
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    Jiali Duan; Huanhuan Hu; Guan Wang; Takashi Arao (2023). Study on Current Levels of Physical Activity and Sedentary Behavior among Middle School Students in Beijing, China [Dataset]. http://doi.org/10.1371/journal.pone.0133544
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    docxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jiali Duan; Huanhuan Hu; Guan Wang; Takashi Arao
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Beijing, China
    Description

    IntroductionThis study aimed to determine current levels of physical activity and sedentary behavior in middle school students on the basis of grade, sex, student attitudes toward physical education, and residence location.MethodsIn 2013, a cross-sectional study of 1793 students aged 12 to 15 years was conducted across eight middle schools in Beijing, China. Four schools were selected from an urban district and another four schools were from a suburban district. Physical activity and sedentary behavior data were collected using the commonly used school-based Chinese version of the China Health and Nutrition Survey.ResultsThe mean age of sampled students was 13.3±1.0 years; 51.5% were boys. Approximately 76.6% of students reported having three 45-minute physical education classes every week. A total of 35.6% students spent ≥1 h/day performing moderate to vigorous physical activity (MVPA) during school, and 34.9% spent ≥1 h/day in MVPA outside school time. Approximately half (49.7%) of the students engaged in reading, writing, or drawing for ≥2 h/day, and 42.9% reported screen time for ≥2 h/day. Although boys spent more time engaged in physical activity than girls did, they also spent more time exhibiting sedentary behavior. Each 10-unit increase in attitudes toward physical education was associated with an increased odds of 1.15 (95%CI: 1.09–1.20) for spending more than 1 h/day on MVPA. Students in suburban schools reported engaging in physical activity less when compared with those in urban schools.ConclusionThe majority of our students did not meet the current physical activity recommendations, and about half of the students spent excessive time engaging in sedentary behaviors. Findings from this study highlight a positive association between student attitudes toward physical education and physical activity. Studies are needed to further explore the role of student attitudes toward physical education in promoting physical activity among Chinese students.

  15. f

    Data_Sheet_1_The association between sedentary behavioral characteristics...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
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    Updated Jun 4, 2023
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    Lin Li; Jinjin Liao; Hui Fu; Boyi Zong (2023). Data_Sheet_1_The association between sedentary behavioral characteristics and poor vision among Chinese children and adolescents.pdf [Dataset]. http://doi.org/10.3389/fpubh.2022.1043977.s001
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    pdfAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    Frontiers
    Authors
    Lin Li; Jinjin Liao; Hui Fu; Boyi Zong
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionTo understand the features of sedentary behavior of Chinese children and adolescents and its relationship with poor visual acuity, a self-administered “Questionnaire on Sedentary Behavior of Children and Adolescents” was used to survey 4,203 students in grades 4–12 in six administrative regions of China.Results(1) The average time spent in sedentary behaviors (SB) of Chinese children and adolescents was about 8.1 h per day, of which the academic sedentary time was the longest, accounting for 79.2% of total sedentary time. The total time spent on SB and the time spent on studying SB were more in the upper grades and less in screen SB and cultural leisure SB, respectively. There were significant sex differences in total SB time (p < 0.05) and weekend sedentary behaviors time (SB-WD) (p < 0.01) among Chinese children and adolescents, with girls being more likely to be higher than boys. There were also significant differences in sedentary time across different regions (p < 0.05), and the longest total sedentary time in East China. (2) Reduction parents' sedentary time and limitation of sedentary behaviors and the use of electronics among children and adolescents can effectively reduce sedentary time among Chinese children and adolescents. (3) Sedentary time was significantly higher in children and adolescents with poor vision than in those with normal vision (p < 0.01), and study SB and screen SB were important independent factors affecting vision. (4) Timing of breaks in SB can play a positive role in promoting vision health.ConclusionThere were significant grade, sex, and regional differences in the SB of Chinese children and adolescents, and sedentary time was strongly related to the prevalence of poor vision detection rate.

  16. Workplace performance self-assessment in China 2025, by gender

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Workplace performance self-assessment in China 2025, by gender [Dataset]. https://www.statista.com/statistics/1441334/china-workplace-performance-self-evaluation-by-gender/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    China
    Description

    According to an annual survey about Chinese women's workplace conducted at the beginning of 2025, ** percent of female respondents thought that their performance at work was better than other female employees'. Meanwhile, **** percent thought they were doing a better job than their male colleagues. Male respondents, however, were more confident when comparing their workplace performance to that of the colleagues' of the opposite sex. Almost ** percent of men thought they performed better than their female colleagues.

  17. Frequency of online purchases in China 2022, by gender

    • statista.com
    Updated Jun 30, 2025
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    Statista (2025). Frequency of online purchases in China 2022, by gender [Dataset]. https://www.statista.com/statistics/1127873/china-online-shopping-frequency-by-gender/
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    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 12, 2022 - Jun 30, 2022
    Area covered
    China
    Description

    The coronavirus (COVID-19) pandemic has sped up the shift to online shopping in China. According to a survey on online shopping behavior in China conducted by Rakuten Insight in June 2022, about ** percent of the female respondents said they had made online purchases at least once a week. Rise of the She-economy Along with an increasing income and progress towards gender equality, women in China have become a significant driver of the country’s consumption and economic development. China has nearly *** million female consumers aged between 20 and 60 years, and they are responsible for the majority of household purchasing decisions. Female mobile shoppers Mobile shopping has become the norm for Chinese female internet users. As of February 2020, China recorded nearly *** million female mobile shoppers. Compared to male shoppers, female consumers are more willing to participate in online shopping events and embracing new features like social commerce and live streaming commerce.

  18. Population distribution by five-year age group in China 2023

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Population distribution by five-year age group in China 2023 [Dataset]. https://www.statista.com/statistics/1101677/population-distribution-by-detailed-age-group-in-china/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    As of 2023, the bulk of the Chinese population was aged between 25 and 59 years, amounting to around half of the population. A breakdown of the population by broad age groups reveals that around 61.3 percent of the total population was in working age between 16 and 59 years in 2023. Age cohorts below 25 years were considerably smaller, although there was a slight growth trend in recent years. Population development in China Population development in China over the past decades has been strongly influenced by political and economic factors. After a time of high fertility rates during the Maoist regime, China introduced birth-control measures in the 1970s, including the so-called one-child policy. The fertility rate dropped accordingly from around six children per woman in the 1960s to below two at the end of the 20th century. At the same time, life expectancy increased consistently. In the face of a rapidly aging society, the government gradually lifted the one-child policy after 2012, finally arriving at a three-child policy in 2021. However, like in most other developed countries nowadays, people in China are reluctant to have more than one or two children due to high costs of living and education, as well as changed social norms and private values. China’s top-heavy age pyramid The above-mentioned developments are clearly reflected in the Chinese age pyramid. The age cohorts between 30 and 39 years are the last two larger age cohorts. The cohorts between 15 and 24, which now enter childbearing age, are decisively smaller, which will have a negative effect on the number of births in the coming decade. When looking at a gender distribution of the population pyramid, a considerable gender gap among the younger age cohorts becomes visible, leaving even less room for growth in birth figures.

  19. Data_Sheet_1_What Really Matters for Loneliness Among Left-Behind Children...

    • frontiersin.figshare.com
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    Updated May 31, 2023
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    Xiaoyun Chai; Hongfei Du; Xiaoyan Li; Shaobing Su; Danhua Lin (2023). Data_Sheet_1_What Really Matters for Loneliness Among Left-Behind Children in Rural China: A Meta-Analytic Review.PDF [Dataset]. http://doi.org/10.3389/fpsyg.2019.00774.s001
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    pdfAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Xiaoyun Chai; Hongfei Du; Xiaoyan Li; Shaobing Su; Danhua Lin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    In rural China, left-behind children are likely to suffer chronic loneliness. Research has identified a variety of factors that may be associated with loneliness among these children. A meta-analysis is needed to address the empirical inconsistencies and examine the strength of relations between different factors and loneliness. The current meta-analysis included 51 studies on predictors of loneliness published from 2008 to 2017. Results showed that one individual factor (social anxiety) is a key risk factor for loneliness, whereas eight individual (older age, self-esteem, resilience, extroversion) and contextual factors (family functioning, parent–child relationship, peer relationship, social support) serve as protective factors in predicting loneliness. In addition, boys were more likely to feel lonely than girls. Findings and implications of this study were discussed.

  20. Table_1_Sex-Disaggregated Data on Clinical Characteristics and Outcomes of...

    • frontiersin.figshare.com
    • datasetcatalog.nlm.nih.gov
    docx
    Updated May 30, 2023
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    Mengdie Wang; Nan Jiang; Changjun Li; Jing Wang; Heping Yang; Li Liu; Xiangping Tan; Zhenyuan Chen; Yanhong Gong; Xiaoxv Yin; Qiao Zong; Nian Xiong; Guopeng Zhang (2023). Table_1_Sex-Disaggregated Data on Clinical Characteristics and Outcomes of Hospitalized Patients With COVID-19: A Retrospective Study.docx [Dataset]. http://doi.org/10.3389/fcimb.2021.680422.s001
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    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers Mediahttp://www.frontiersin.org/
    Authors
    Mengdie Wang; Nan Jiang; Changjun Li; Jing Wang; Heping Yang; Li Liu; Xiangping Tan; Zhenyuan Chen; Yanhong Gong; Xiaoxv Yin; Qiao Zong; Nian Xiong; Guopeng Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundSex and gender are crucial variables in coronavirus disease 2019 (COVID-19). We sought to provide information on differences in clinical characteristics and outcomes between male and female patients and to explore the effect of estrogen in disease outcomes in patients with COVID-19.MethodIn this retrospective, multi-center study, we included all confirmed cases of COVID-19 admitted to four hospitals in Hubei province, China from Dec 31, 2019 to Mar 31, 2020. Cases were confirmed by real-time RT-PCR and were analyzed for demographic, clinical, laboratory and radiographic parameters. Random-effect logistic regression analysis was used to assess the association between sex and disease outcomes.ResultsA total of 2501 hospitalized patients with COVID-19 were included in the present study. The clinical manifestations of male and female patients with COVID-19 were similar, while male patients have more comorbidities than female patients. In terms of laboratory findings, compared with female patients, male patients were more likely to have lymphopenia, thrombocytopenia, inflammatory response, hypoproteinemia, and extrapulmonary organ damage. Random-effect logistic regression analysis indicated that male patients were more likely to progress into severe type, and prone to ARDS, secondary bacterial infection, and death than females. However, there was no significant difference in disease outcomes between postmenopausal and premenopausal females after propensity score matching (PSM) by age.ConclusionsMale patients, especially those age-matched with postmenopausal females, are more likely to have poor outcomes. Sex-specific differences in clinical characteristics and outcomes do exist in patients with COVID-19, but estrogen may not be the primary cause. Further studies are needed to explore the causes of the differences in disease outcomes between the sexes.

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Statista (2025). Population in China 2014-2024, by gender [Dataset]. https://www.statista.com/statistics/251129/population-in-china-by-gender/
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Population in China 2014-2024, by gender

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11 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 15, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
China
Description

In 2024, there were around 719 million male inhabitants and 689 million female inhabitants living in China, amounting to around 1.41 billion people in total. China's total population decreased for the first time in decades in 2022, and population decline is expected to accelerate in the upcoming years. Birth control in China From the beginning of the 1970s on, having many children was no longer encouraged in mainland China. The one-child policy was then introduced in 1979 to control the total size of the Chinese population. According to the one-child policy, a married couple was only allowed to have one child. With the time, modifications were added to the policy, for example parents living in rural areas were allowed to have a second child if the first was a daughter, and most ethnic minorities were excepted from the policy. Population ageing The birth control led to a decreasing birth rate in China and a more skewed gender ratio of new births due to boy preference. Since the negative economic and social effects of an aging population were more and more felt in China, the one-child policy was considered an obstacle for the country’s further economic development. Since 2014, the one-child policy has been gradually relaxed and fully eliminated at the end of 2015. However, many young Chinese people are not willing to have more children due to high costs of raising a child, especially in urban areas.

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