6 datasets found
  1. f

    Descriptive statistics of participants.

    • figshare.com
    xls
    Updated Sep 30, 2024
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    Christopher I. Gurguis; Renée A. Duckworth; Nicole M. Bucaro; Consuelo Walss-Bass (2024). Descriptive statistics of participants. [Dataset]. http://doi.org/10.1371/journal.pone.0310598.t001
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    xlsAvailable download formats
    Dataset updated
    Sep 30, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Christopher I. Gurguis; Renée A. Duckworth; Nicole M. Bucaro; Consuelo Walss-Bass
    License

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

    Description

    Depression has strong negative impacts on how individuals function, leading to the assumption that there is strong negative selection on this trait that should deplete genetic variation and decrease its prevalence in human populations. Yet, depressive symptoms remain common. While there has been a large body of work trying to resolve this paradox by mapping genetic variation of this complex trait, there have been few direct empirical tests of the core assumption that there is consistent negative selection on depression in human populations. Here, we use a unique long-term dataset from the National Health and Nutrition Examination Survey that spans four generational cohorts (Silent Generation: 1928–1945, Baby Boomers: 1946–1964, Generation X: 1965–1980, and Millenials: 1981–1996) to measure both depression scores and fitness components (lifetime sexual partners, pregnancies, and live births) of women from the United States born between 1938–1994. We not only assess fitness consequences of depression across multiple generations to determine whether the strength and direction of selection on depression has changed over time, but we also pair these fitness measurements with mixed models to assess how several important covariates, including age, body mass, education, race/ethnicity, and income might influence this relationship. We found that, overall, selection on depression was positive and the strength of selection changed over time–women reporting higher depression had relatively more sexual partners, pregnancies, and births except during the Silent Generation when selection coefficients neared zero. We also found that depression scores and fitness components differed among generations—Baby Boomers showed the highest severity of depression and the most sexual partners. These results were not changed by the inclusion of covariates in our models. A limitation of this study is that for the Millenials, reproduction has not completed and data for this generation is interrupted by right censoring. Most importantly, our results undermine the common belief that there is consistent negative selection on depression and demonstrate that the relationship between depression and fitness changes between generations, which may explain its maintenance in human populations.

  2. Income of individuals by age group, sex and income source, Canada, provinces...

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +2more
    Updated May 1, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas [Dataset]. http://doi.org/10.25318/1110023901-eng
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    Dataset updated
    May 1, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

  3. Adjusted multiple logistic regression of socioeconomic, demographic, and...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 4, 2023
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    Justin Christopher Yang; Andres Roman-Urrestarazu; Carol Brayne (2023). Adjusted multiple logistic regression of socioeconomic, demographic, and health variables associated with past-month substance use and any-use for adults, 2007–16. [Dataset]. http://doi.org/10.1371/journal.pone.0199741.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Justin Christopher Yang; Andres Roman-Urrestarazu; Carol Brayne
    License

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

    Description

    Adjusted multiple logistic regression of socioeconomic, demographic, and health variables associated with past-month substance use and any-use for adults, 2007–16.

  4. Instagram users in the United Kingdom 2019-2028

    • statista.com
    Updated Nov 22, 2024
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    Statista Research Department (2024). Instagram users in the United Kingdom 2019-2028 [Dataset]. https://www.statista.com/topics/3236/social-media-usage-in-the-uk/
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    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United Kingdom
    Description

    The number of Instagram users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 2.1 million users (+7.02 percent). After the ninth consecutive increasing year, the Instagram user base is estimated to reach 32 million users and therefore a new peak in 2028. Notably, the number of Instagram users of was continuously increasing over the past years.User figures, shown here with regards to the platform instagram, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

  5. Pinterest users in the United Kingdom 2019-2028

    • statista.com
    Updated Nov 22, 2024
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    Statista Research Department (2024). Pinterest users in the United Kingdom 2019-2028 [Dataset]. https://www.statista.com/topics/3236/social-media-usage-in-the-uk/
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    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United Kingdom
    Description

    The number of Pinterest users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 0.3 million users (+3.14 percent). After the ninth consecutive increasing year, the Pinterest user base is estimated to reach 9.88 million users and therefore a new peak in 2028. Notably, the number of Pinterest users of was continuously increasing over the past years.User figures, shown here regarding the platform pinterest, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

  6. Number of LinkedIn users in the United Kingdom 2019-2028

    • statista.com
    Updated Nov 22, 2024
    + more versions
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    Statista Research Department (2024). Number of LinkedIn users in the United Kingdom 2019-2028 [Dataset]. https://www.statista.com/topics/3236/social-media-usage-in-the-uk/
    Explore at:
    Dataset updated
    Nov 22, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United Kingdom
    Description

    The number of LinkedIn users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 1.5 million users (+4.51 percent). After the eighth consecutive increasing year, the LinkedIn user base is estimated to reach 34.7 million users and therefore a new peak in 2028. User figures, shown here with regards to the platform LinkedIn, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

  7. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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TwitterTwitter
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Click to copy link
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Christopher I. Gurguis; Renée A. Duckworth; Nicole M. Bucaro; Consuelo Walss-Bass (2024). Descriptive statistics of participants. [Dataset]. http://doi.org/10.1371/journal.pone.0310598.t001

Descriptive statistics of participants.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Sep 30, 2024
Dataset provided by
PLOS ONE
Authors
Christopher I. Gurguis; Renée A. Duckworth; Nicole M. Bucaro; Consuelo Walss-Bass
License

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

Description

Depression has strong negative impacts on how individuals function, leading to the assumption that there is strong negative selection on this trait that should deplete genetic variation and decrease its prevalence in human populations. Yet, depressive symptoms remain common. While there has been a large body of work trying to resolve this paradox by mapping genetic variation of this complex trait, there have been few direct empirical tests of the core assumption that there is consistent negative selection on depression in human populations. Here, we use a unique long-term dataset from the National Health and Nutrition Examination Survey that spans four generational cohorts (Silent Generation: 1928–1945, Baby Boomers: 1946–1964, Generation X: 1965–1980, and Millenials: 1981–1996) to measure both depression scores and fitness components (lifetime sexual partners, pregnancies, and live births) of women from the United States born between 1938–1994. We not only assess fitness consequences of depression across multiple generations to determine whether the strength and direction of selection on depression has changed over time, but we also pair these fitness measurements with mixed models to assess how several important covariates, including age, body mass, education, race/ethnicity, and income might influence this relationship. We found that, overall, selection on depression was positive and the strength of selection changed over time–women reporting higher depression had relatively more sexual partners, pregnancies, and births except during the Silent Generation when selection coefficients neared zero. We also found that depression scores and fitness components differed among generations—Baby Boomers showed the highest severity of depression and the most sexual partners. These results were not changed by the inclusion of covariates in our models. A limitation of this study is that for the Millenials, reproduction has not completed and data for this generation is interrupted by right censoring. Most importantly, our results undermine the common belief that there is consistent negative selection on depression and demonstrate that the relationship between depression and fitness changes between generations, which may explain its maintenance in human populations.

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