2 datasets found
  1. Drug Use By Age

    • kaggle.com
    Updated Apr 23, 2021
    + more versions
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    Bojan Tunguz (2021). Drug Use By Age [Dataset]. https://www.kaggle.com/datasets/tunguz/drug-use-by-age/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 23, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Bojan Tunguz
    License

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

    Description

    Drug Use By Age

    This directory contains data behind the story How Baby Boomers Get High. It covers 13 drugs across 17 age groups.

    Source: National Survey on Drug Use and Health from the Substance Abuse and Mental Health Data Archive.

    HeaderDefinition
    alcohol-usePercentage of those in an age group who used alcohol in the past 12 months
    alcohol-frequencyMedian number of times a user in an age group used alcohol in the past 12 months
    marijuana-usePercentage of those in an age group who used marijuana in the past 12 months
    marijuana-frequencyMedian number of times a user in an age group used marijuana in the past 12 months
    cocaine-usePercentage of those in an age group who used cocaine in the past 12 months
    cocaine-frequencyMedian number of times a user in an age group used cocaine in the past 12 months
    crack-usePercentage of those in an age group who used crack in the past 12 months
    crack-frequencyMedian number of times a user in an age group used crack in the past 12 months
    heroin-usePercentage of those in an age group who used heroin in the past 12 months
    heroin-frequencyMedian number of times a user in an age group used heroin in the past 12 months
    hallucinogen-usePercentage of those in an age group who used hallucinogens in the past 12 months
    hallucinogen-frequencyMedian number of times a user in an age group used hallucinogens in the past 12 months
    inhalant-usePercentage of those in an age group who used inhalants in the past 12 months
    inhalant-frequencyMedian number of times a user in an age group used inhalants in the past 12 months
    pain-releiver-usePercentage of those in an age group who used pain relievers in the past 12 months
    pain-releiver-frequencyMedian number of times a user in an age group used pain relievers in the past 12 months
    oxycontin-usePercentage of those in an age group who used oxycontin in the past 12 months
    oxycontin-frequencyMedian number of times a user in an age group used oxycontin in the past 12 months
    tranquilizer-usePercentage of those in an age group who used tranquilizer in the past 12 months
    tranquilizer-frequencyMedian number of times a user in an age group used tranquilizer in the past 12 months
    stimulant-usePercentage of those in an age group who used stimulants in the past 12 months
    stimulant-frequencyMedian number of times a user in an age group used stimulants in the past 12 months
    meth-usePercentage of those in an age group who used meth in the past 12 months
    meth-frequencyMedian number of times a user in an age group used meth in the past 12 months
    sedative-usePercentage of those in an age group who used sedatives in the past 12 months
    sedative-frequencyMedian number of times a user in an age group used sedatives in the past 12 months
  2. 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
    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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Bojan Tunguz (2021). Drug Use By Age [Dataset]. https://www.kaggle.com/datasets/tunguz/drug-use-by-age/discussion
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Drug Use By Age

US Drug Use By Age Dataset

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Apr 23, 2021
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Bojan Tunguz
License

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

Description

Drug Use By Age

This directory contains data behind the story How Baby Boomers Get High. It covers 13 drugs across 17 age groups.

Source: National Survey on Drug Use and Health from the Substance Abuse and Mental Health Data Archive.

HeaderDefinition
alcohol-usePercentage of those in an age group who used alcohol in the past 12 months
alcohol-frequencyMedian number of times a user in an age group used alcohol in the past 12 months
marijuana-usePercentage of those in an age group who used marijuana in the past 12 months
marijuana-frequencyMedian number of times a user in an age group used marijuana in the past 12 months
cocaine-usePercentage of those in an age group who used cocaine in the past 12 months
cocaine-frequencyMedian number of times a user in an age group used cocaine in the past 12 months
crack-usePercentage of those in an age group who used crack in the past 12 months
crack-frequencyMedian number of times a user in an age group used crack in the past 12 months
heroin-usePercentage of those in an age group who used heroin in the past 12 months
heroin-frequencyMedian number of times a user in an age group used heroin in the past 12 months
hallucinogen-usePercentage of those in an age group who used hallucinogens in the past 12 months
hallucinogen-frequencyMedian number of times a user in an age group used hallucinogens in the past 12 months
inhalant-usePercentage of those in an age group who used inhalants in the past 12 months
inhalant-frequencyMedian number of times a user in an age group used inhalants in the past 12 months
pain-releiver-usePercentage of those in an age group who used pain relievers in the past 12 months
pain-releiver-frequencyMedian number of times a user in an age group used pain relievers in the past 12 months
oxycontin-usePercentage of those in an age group who used oxycontin in the past 12 months
oxycontin-frequencyMedian number of times a user in an age group used oxycontin in the past 12 months
tranquilizer-usePercentage of those in an age group who used tranquilizer in the past 12 months
tranquilizer-frequencyMedian number of times a user in an age group used tranquilizer in the past 12 months
stimulant-usePercentage of those in an age group who used stimulants in the past 12 months
stimulant-frequencyMedian number of times a user in an age group used stimulants in the past 12 months
meth-usePercentage of those in an age group who used meth in the past 12 months
meth-frequencyMedian number of times a user in an age group used meth in the past 12 months
sedative-usePercentage of those in an age group who used sedatives in the past 12 months
sedative-frequencyMedian number of times a user in an age group used sedatives in the past 12 months
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