29 datasets found
  1. Poverty rate in Lima, Peru 2012-2023

    • statista.com
    • ai-chatbox.pro
    Updated Jul 10, 2025
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    Statista (2025). Poverty rate in Lima, Peru 2012-2023 [Dataset]. https://www.statista.com/statistics/1473821/poverty-rate-lima/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Peru
    Description

    The share of the population with at least one poverty condition or unmet need in the Peruvian capital of Lima reached its lowest during 2017 with *** percent. In 2023, the share of residents of the metropolitan area was over **** percent.

  2. w

    White poverty in Lima, Ohio (2022)

    • welfareinfo.org
    Updated Sep 12, 2024
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    WelfareInfo.org (2024). White poverty in Lima, Ohio (2022) [Dataset]. https://www.welfareinfo.org/poverty-rate/ohio/lima/stat-white-people/
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    Dataset updated
    Sep 12, 2024
    Dataset provided by
    WelfareInfo.org
    License

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

    Area covered
    Lima, Ohio
    Description

    White Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Lima, Ohio by age, education, race, gender, work experience and more.

  3. w

    Dataset of book subjects that contain Poverty and problem-solving under...

    • workwithdata.com
    Updated Nov 7, 2024
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    Work With Data (2024). Dataset of book subjects that contain Poverty and problem-solving under military rule : the urban poor in Lima, Peru [Dataset]. https://www.workwithdata.com/datasets/book-subjects?f=1&fcol0=j0-book&fop0=%3D&fval0=Poverty+and+problem-solving+under+military+rule+%3A+the+urban+poor+in+Lima%2C+Peru&j=1&j0=books
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Work With Data
    License

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

    Area covered
    Peru
    Description

    This dataset is about book subjects. It has 1 row and is filtered where the books is Poverty and problem-solving under military rule : the urban poor in Lima, Peru. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

  4. F

    Percent of Population Below the Poverty Level (5-year estimate) in Allen...

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
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    (2024). Percent of Population Below the Poverty Level (5-year estimate) in Allen County, OH [Dataset]. https://fred.stlouisfed.org/series/S1701ACS039003
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    jsonAvailable download formats
    Dataset updated
    Dec 12, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Allen County, Ohio
    Description

    Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Allen County, OH (S1701ACS039003) from 2012 to 2023 about Allen County, OH; Lima; OH; percent; poverty; 5-year; population; and USA.

  5. F

    90% Confidence Interval Lower Bound of Estimate of People Age 0-17 in...

    • fred.stlouisfed.org
    json
    Updated Dec 20, 2024
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    (2024). 90% Confidence Interval Lower Bound of Estimate of People Age 0-17 in Poverty for Allen County, OH [Dataset]. https://fred.stlouisfed.org/series/PECILBU18OH39003A647NCEN
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    jsonAvailable download formats
    Dataset updated
    Dec 20, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Allen County, Ohio
    Description

    Graph and download economic data for 90% Confidence Interval Lower Bound of Estimate of People Age 0-17 in Poverty for Allen County, OH (PECILBU18OH39003A647NCEN) from 1989 to 2023 about Allen County, OH; Lima; under 18 years; OH; child; poverty; persons; and USA.

  6. Population in Lima 2020-2025

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Population in Lima 2020-2025 [Dataset]. https://www.statista.com/statistics/1473801/population-lima-peru/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Peru
    Description

    There has been an overall increase in the number of people living within the city limits of Lima throughout the time frame displayed. The population in the Peruvian capital growth has been steady since 2020, surpassing the 10 million inhabitants during 2022 and leading to reach its highest peak in 2024 with 10.29 million people. The metropolitan area of Lima also ranked as one of the most populous in Latin America. A crucial part of Peru's economic output The total GDP of Lima reached around 246 billion Peruvian soles, which represents almost half of the total economic output of the country. The industry that contributed the most to Lima's GDP was by far services; nonetheless, the importance of manufacturing makes it the second-largest contributor. Other sectors that are important for the nation, like mining and some agricultural activities, stayed at the bottom part of the list.

    Unemployment and poverty The unemployment rate of the Peruvian capital exceeded the 7.5 percent mark during March 2024. While the figure appears as quite an improvement over 2020 and 2021 data, when it reached over 16 percent, it still hasn't fully recovered to the figures before the COVID-19 pandemic. Likewise, the poverty rate presented a growing trend from 2017 to 2023, reaching 9.5 percent of Lima's residents living under the poverty line.

  7. I

    Indonesia Average Monthly Poverty Line per Capita: West Sumatera: Lima Puluh...

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Indonesia Average Monthly Poverty Line per Capita: West Sumatera: Lima Puluh Kota Regency [Dataset]. https://www.ceicdata.com/en/indonesia/poverty-line-by-regency/average-monthly-poverty-line-per-capita-west-sumatera-lima-puluh-kota-regency
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2007 - Dec 1, 2018
    Area covered
    Indonesia
    Description

    Indonesia Average Monthly Poverty Line per Capita: West Sumatera: Lima Puluh Kota Regency data was reported at 388,689.000 IDR in 2018. This records an increase from the previous number of 370,506.000 IDR for 2017. Indonesia Average Monthly Poverty Line per Capita: West Sumatera: Lima Puluh Kota Regency data is updated yearly, averaging 274,152.500 IDR from Dec 2005 (Median) to 2018, with 14 observations. The data reached an all-time high of 388,689.000 IDR in 2018 and a record low of 153,436.000 IDR in 2005. Indonesia Average Monthly Poverty Line per Capita: West Sumatera: Lima Puluh Kota Regency data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Socio and Demographic – Table ID.GAE015: Poverty Line: by Regency.

  8. QuickFacts: Lima city, Ohio

    • census.gov
    csv
    Updated Feb 25, 2022
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    United States Census Bureau > Communications Directorate - Center for New Media and Promotion (2022). QuickFacts: Lima city, Ohio [Dataset]. https://www.census.gov/quickfacts/fact/faq/limacityohio/POP060210
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    csvAvailable download formats
    Dataset updated
    Feb 25, 2022
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United States Census Bureau > Communications Directorate - Center for New Media and Promotion
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Lima, Ohio
    Description

    U.S. Census Bureau QuickFacts statistics for Lima city, Ohio. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

  9. I

    Indonesia Poverty Gap Index: West Sumatera: Lima Puluh Kota Regency

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). Indonesia Poverty Gap Index: West Sumatera: Lima Puluh Kota Regency [Dataset]. https://www.ceicdata.com/en/indonesia/poverty-gap-index-by-regency/poverty-gap-index-west-sumatera-lima-puluh-kota-regency
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2007 - Dec 1, 2018
    Area covered
    Indonesia
    Description

    Indonesia Poverty Gap Index: West Sumatera: Lima Puluh Kota Regency data was reported at 1.090 % in 2018. This stayed constant from the previous number of 1.090 % for 2017. Indonesia Poverty Gap Index: West Sumatera: Lima Puluh Kota Regency data is updated yearly, averaging 1.130 % from Dec 2005 (Median) to 2018, with 14 observations. The data reached an all-time high of 2.630 % in 2006 and a record low of 0.820 % in 2014. Indonesia Poverty Gap Index: West Sumatera: Lima Puluh Kota Regency data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Socio and Demographic – Table ID.GAE007: Poverty Gap Index: by Regency.

  10. I

    Indonesia Poverty Severity Index: West Sumatera: Lima Puluh Kota Regency

    • ceicdata.com
    Updated Jun 4, 2017
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    CEICdata.com (2017). Indonesia Poverty Severity Index: West Sumatera: Lima Puluh Kota Regency [Dataset]. https://www.ceicdata.com/en/indonesia/poverty-severity-index-by-regency/poverty-severity-index-west-sumatera-lima-puluh-kota-regency
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    Dataset updated
    Jun 4, 2017
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2007 - Dec 1, 2018
    Area covered
    Indonesia
    Description

    Indonesia Poverty Severity Index: West Sumatera: Lima Puluh Kota Regency data was reported at 0.240 % in 2018. This records a decrease from the previous number of 0.310 % for 2017. Indonesia Poverty Severity Index: West Sumatera: Lima Puluh Kota Regency data is updated yearly, averaging 0.245 % from Dec 2005 (Median) to 2018, with 14 observations. The data reached an all-time high of 0.720 % in 2006 and a record low of 0.160 % in 2014. Indonesia Poverty Severity Index: West Sumatera: Lima Puluh Kota Regency data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Socio and Demographic – Table ID.GAE011: Poverty Severity Index: by Regency.

  11. F

    Poverty Universe, Age 0-17 for Allen County, OH

    • fred.stlouisfed.org
    json
    Updated Dec 20, 2024
    + more versions
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    (2024). Poverty Universe, Age 0-17 for Allen County, OH [Dataset]. https://fred.stlouisfed.org/series/PUA0T17OH39003A647NCEN
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    jsonAvailable download formats
    Dataset updated
    Dec 20, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Allen County, Ohio
    Description

    Graph and download economic data for Poverty Universe, Age 0-17 for Allen County, OH (PUA0T17OH39003A647NCEN) from 1998 to 2023 about Allen County, OH; Lima; OH; child; poverty; and USA.

  12. F

    Estimated Percent of People of All Ages in Poverty for Allen County, OH

    • fred.stlouisfed.org
    json
    Updated Dec 20, 2024
    + more versions
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    (2024). Estimated Percent of People of All Ages in Poverty for Allen County, OH [Dataset]. https://fred.stlouisfed.org/series/PPAAOH39003A156NCEN
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    jsonAvailable download formats
    Dataset updated
    Dec 20, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Allen County, Ohio
    Description

    Graph and download economic data for Estimated Percent of People of All Ages in Poverty for Allen County, OH (PPAAOH39003A156NCEN) from 1989 to 2023 about Allen County, OH; Lima; OH; percent; child; poverty; and USA.

  13. l

    Supplementary files for "Changes and correlates of household food insecurity...

    • repository.lboro.ac.uk
    docx
    Updated Jan 28, 2025
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    Rebecca Pradeilles; Sabrina Eymard-Duvernay; Rossina Pareja; Michelle Holdsworth; Edwige Landais; Hilary M Creed-Kanashiro; Emily Rousham (2025). Supplementary files for "Changes and correlates of household food insecurity during COVID-19: a repeated cross-sectional survey of low-income households in peri-urban Peru" [Dataset]. http://doi.org/10.17028/rd.lboro.28296809.v1
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    docxAvailable download formats
    Dataset updated
    Jan 28, 2025
    Dataset provided by
    Loughborough University
    Authors
    Rebecca Pradeilles; Sabrina Eymard-Duvernay; Rossina Pareja; Michelle Holdsworth; Edwige Landais; Hilary M Creed-Kanashiro; Emily Rousham
    License

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

    Area covered
    Peru
    Description

    Supplementary files for article "Changes and correlates of household food insecurity during COVID-19: a repeated cross-sectional survey of low-income households in peri-urban Peru"National lockdowns and containment measures to control the spread of COVID-19 led to increased unemployment, lower household incomes and reduced access to affordable and nutritious foods globally. This study aimed to examine changes and correlates of household food insecurity experience and mitigation strategies adopted in peri-urban Peru during the COVID-19 pandemic. Low income households with children age < 2 years in Lima and Huánuco participated in three repeated cross-sectional surveys from 2020 to 2022 (n = 759). We assessed changes in household food insecurity experience using the Food Insecurity Experience Scale. Correlates of moderate-severe food insecurity were analysed using univariate and multivariable linear mixed-effect regressions. We also assessed perceived impacts of the pandemic on livelihoods, coping strategies and receipt of financial or food assistance. Moderate-severe food insecurity was 47.0% in 2020 (survey 1) decreasing to 31.1% in 2022 (survey 3). In adjusted analyses, food insecurity was higher in households with perceived reduced income (β = 12.69 [6.82; 18.56]); in the lower socio-economic status (SES) tertiles (compared to the relatively highest SES tertile; middle tertile (β = 20.91 [9.89; 31.93]), lowest tertile (β = 39.37 [28.35; 50.40]); in households with ≥ 2 children < 5 years (β = 8.78 [2.05; 15.50]); and in Lima (compared to Huánuco; β = 10.47 [1.27; 19.67]). Food insecurity improved more among the relatively lowest SES compared to the relatively highest SES households between survey 1 and 3 (interaction p = 0.007). In conclusion, almost half of households experienced moderate-severe food insecurity mid-pandemic with greater risk observed in the most socio-economically disadvantaged households. The inequality gap in food insecurity associated with SES narrowed over time likely due to household coping strategies and reduced poverty.©The Authors, CC BY 4.0

  14. f

    Data from: Excess weight among women in a low-income urban community:...

    • scielo.figshare.com
    xls
    Updated Jun 5, 2023
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    Letícia Dinegri; Malaquias Batista Filho; Helânia Virginia Dantas dos Santos; Pedro Israel Cabral de Lira; Poliana Coelho Cabral; Sophie Helena Eickmann; Marilia de Carvalho Lima (2023). Excess weight among women in a low-income urban community: socioeconomic, demographic and reproductive factors [Dataset]. http://doi.org/10.6084/m9.figshare.19904813.v1
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    SciELO journals
    Authors
    Letícia Dinegri; Malaquias Batista Filho; Helânia Virginia Dantas dos Santos; Pedro Israel Cabral de Lira; Poliana Coelho Cabral; Sophie Helena Eickmann; Marilia de Carvalho Lima
    License

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

    Description

    Abstract The aim of the present study was to investigate the prevalence of excess weight and associated factors in women of reproductive age living in a low-income community. A cross-sectional study was conducted with a sample of 663 women 15 to 49 years of age residing in the neighborhood of Coelhos in the city of Recife, Brazil. Body mass index (BMI)-for-age was used to classify the nutritional status of the adolescents (15 to 19 years of age), adopting Z-score of ≥+1 for the definition of overweight. For the adults, BMI≥25.0 kg/m² was considered indicative of overweight. Socioeconomic, demographic and reproductive variables were analyzed as possible factors associated with overweight. The prevalence of excess weight was found in two thirds of the sample. The results of the Poisson multiple regression analysis showed a significantly higher prevalence of excess weight with the advance in age, among those with a younger menarche age, those who had three or more pregnancies, those living with their partner and those self-declared black or white. Multiparity was the only factor associated with excess weight that could be modified, which underscores the importance of prenatal and family planning services to its prevention and control.

  15. i

    World Bank Group Country Survey 2014 - Peru

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
    + more versions
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    Public Opinion Research Group (2019). World Bank Group Country Survey 2014 - Peru [Dataset]. https://datacatalog.ihsn.org/catalog/5444
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    Public Opinion Research Group
    Time period covered
    2014
    Area covered
    Peru
    Description

    Abstract

    The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in Peru or who observe activities related to social and economic development. The following survey will give the World Bank Group's team that works in Peru, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its stakeholders, and to develop more effective strategies that support development in Peru. A local independent firm was hired to oversee the logistics of this survey.

    This survey was designed to achieve the following objectives: - Assist the World Bank Group in gaining a better understanding of how stakeholders in Peru perceive the Bank Group; - Obtain systematic feedback from stakeholders in Peru regarding: · Their views regarding the general environment in Peru; · Their overall attitudes toward the World Bank Group in Peru; · Overall impressions of the World Bank Group's effectiveness and results, knowledge work and activities, and communication and information sharing in Peru; · Perceptions of the World Bank Group's future role in Peru. - Use data to help inform Peru country team's strategy.

    Geographic coverage

    Metropolitan Lima Area, Outside of Metropolitan Lima Area

    Analysis unit

    Stakeholders in Peru

    Universe

    Stakeholders in Peru

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    In February-April 2014, 465 stakeholders of the World Bank Group in Peru were invited to provide their opinions on the WBG's work in the country by participating in a country opinion survey. Participants were drawn from the office of the President; the office of the Prime Minister; office of a minister; office of a parliamentarian; ministries, ministerial departments, or implementation agencies; consultants/contractors working on WBG-supported projects/programs; project management units (PMUs) overseeing implementation of a project; local government officials; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community based organizations; the media; independent government institutions; trade unions; faith-based groups; academia/research institutes/think tanks; judiciary branch; and other organizations.

    Mode of data collection

    Other [oth]

    Research instrument

    The Questionnaire consists of following sections:

    A. General Issues Facing Peru: Respondents were asked to indicate whether Peru is headed in the right direction, what they thought were the top three most important development priorities in the country, which areas would contribute most to reducing poverty and generating economic growth in Peru, and how "shared prosperity" would be best achieved.

    B. Overall Attitudes toward the World Bank Group (WBG): Respondents were asked to rate their familiarity with the WBG and other regional development banks, their effectiveness in Peru, WBG staff preparedness to help Peru solve its development challenges, WBG's local presence, WBG's capacity building in Peru, their agreement with various statements regarding the WBG's work, and the extent to which the WBG is an effective development partner. Respondents were asked to indicate the WBG's greatest values and weaknesses, the most effective instruments in helping reduce poverty in Peru, in which sectoral areas the WBG should focus most of its resources (financial and knowledge services), and to what reasons respondents attributed failed or slow reform efforts. Respondents were also asked to respond to a few questions about capacity building and whether they believe the World Bank Group should have more or less local presence.

    C. World Bank Group's Effectiveness and Results: Respondents were asked to rate the extent to which the WBG's work helps achieve development results in Peru, the extent to which the WBG meets Peru's needs for knowledge services and financial instruments, the importance for the WBG to be involved in thirty one development areas, and the WBG's level of effectiveness across these areas, such as education, public sector governance/reform, water and sanitation, and transport.

    D. The World Bank Group's Knowledge Work and Activities: Respondents were asked to indicate how frequently they consult WBG's knowledge work and activities and to rate the effectiveness and quality of the WBG's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality. Respondents were also asked about the WBG reports, including which of them are the most useful, whether they raised substantive new information, and whether they provided them with useful information in terms of work they do.

    E. Working with the World Bank Group: Respondents were asked to rate WBG's technical assistance/advisory work's contribution to solving development challenges and their level of agreement with a series of statements regarding working with the WBG, such as the WBG's "Safeguard Policy" requirements being reasonable, and disbursing funds promptly.

    F. The Future Role of the World Bank Group in Peru: Respondents were asked to indicate what the WBG should do to make itself of greater value in Peru, and which services the Bank should offer more of in the country. They were asked whether WBG has moved to the right direction, and the future role international development cooperation should play in Peru.

    G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the WBG, and their usage and evaluation of the WBG's websites. Respondents were also asked about their awareness of the WBG's Access to Information policy, were asked to rate WBG's responsiveness to information requests, value of its social media channels, and levels of easiness to find information they needed.

    H. Background Information: Respondents were asked to indicate their current position, specialization, whether they professionally collaborate with the WBG, their exposure to the WBG in Peru, which WBG agencies they work with, whether IFC and the Bank work well together, and their geographic location.

    Response rate

    A total of 197 stakeholders participated in the survey (42% response rate).

  16. f

    Prevalence and socioeconomic determinants of development delay among...

    • plos.figshare.com
    docx
    Updated Jun 1, 2023
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    Luciano Lima Correia; Hermano Alexandre Lima Rocha; Christopher Robert Sudfeld; Sabrina Gabriele Maia Oliveira Rocha; Álvaro Jorge Madeiro Leite; Jocileide Sales Campos; Anamaria Cavalcante e Silva (2023). Prevalence and socioeconomic determinants of development delay among children in Ceará, Brazil: A population-based study [Dataset]. http://doi.org/10.1371/journal.pone.0215343
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Luciano Lima Correia; Hermano Alexandre Lima Rocha; Christopher Robert Sudfeld; Sabrina Gabriele Maia Oliveira Rocha; Álvaro Jorge Madeiro Leite; Jocileide Sales Campos; Anamaria Cavalcante e Silva
    License

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

    Area covered
    Brazil, Ceará
    Description

    ObjectiveTo assess the prevalence of child development delay and to identify socioeconomic determinants.Study designWe conducted a population-based cross-sectional study of children 2 to 72 months of age residing in the state of Ceará, Brazil. In total, 3200 households were randomly selected for participation in the study and had child development assessed with the Ages and Stages Questionnaire (ASQ) version 3. Development delay was defined as a score of less than -2 standard deviations below the median of the Brazilian ASQ standard. We present population-level prevalence of delay in five development domains and assess socioeconomic determinants.ResultsA total of 3566 children completed the ASQ development assessment of which 9.2% (95% CI: 8.1–10.5) had at least one domain with development delay. The prevalence of delay increased with age in all domains and males were at higher risk for communication, gross motor and personal-social development delays as compared to females (p-values

  17. f

    Food and Nutrition Surveillance by Life Stages - VIANEV - Children under 36...

    • microdata.fao.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 6, 2023
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    National Institute of Health, Peru (2023). Food and Nutrition Surveillance by Life Stages - VIANEV - Children under 36 months - 2015 - Peru [Dataset]. https://microdata.fao.org/index.php/catalog/2517
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    Dataset updated
    Dec 6, 2023
    Dataset authored and provided by
    National Institute of Health, Peru
    Time period covered
    2015
    Area covered
    Peru
    Description

    Abstract

    The survey was conducted, in order to:

    1. Estimate the energy and nutrient intake in a population aged 6-35 months.
    2. Estimate the population with adequate consumption of energy and nutrients in the population aged 6-35 months.
    3. Report the nutritional status indicators: anemia, chronic malnutrition and overweight/obesity, in the population under 36 months of age.
    4. Report on the quality of water for human consumption in the homes of the study population, in the population under 36 months of age.

    Geographic coverage

    National coverage, both urban and rural areas.

    Analysis unit

    Individuals

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    For the sample selection, 14 strata were built combining areas (Metropolitan Lima and Callao, Urban and Rural Rest) and the district poverty quintile. In each stratum, a multiple of 4 clusters was selected by random sampling without replacement and with probability proportional to the total size of inhabitants. 79 of the 80 selected clusters were executed, each of approximately 50-100 households where eight teams worked for 13 weeks in the last quarter of 2015.

    In order to reduce systematic errors, in each area they were randomly permuted to assign them to the teams and weeks. In each conglomerate, the random selection of the assigned day was prepared for each of the 10 children of the sample quota. Field teams performed a quick enumeration of the total number of eligible children. When the total was greater than 10, the first 10 were selected according to a pre-selected and different random sequence for each cluster. When the total was less than 10, we worked with all of them and it was not necessary to look for replacements.

    The sample size was estimated by stratified and multistage random sampling in three domains (Metropolitan, Urban and Rural Lima). The sampling frame consisted of information on population and housing from the 2007 National Censuses: XI on Population and VI on Housing, available at the National Institute of Statistics and Informatics (INEI).

    Mode of data collection

    Face-to-face paper [f2f]

  18. Public Expenditure Tracking Survey in Health 2001 - Peru

    • dev.ihsn.org
    • catalog.ihsn.org
    Updated Apr 25, 2019
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    Inter-American Development Bank (2019). Public Expenditure Tracking Survey in Health 2001 - Peru [Dataset]. https://dev.ihsn.org/nada/catalog/study/PER_2001_PETSH_v01_M
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    Dataset updated
    Apr 25, 2019
    Dataset provided by
    Inter-American Development Bankhttp://www.iadb.org/
    World Bankhttp://worldbank.org/
    Ministry of Health
    Ministry of Economics and Finance
    Vice Ministry of Regional Development
    Time period covered
    2002
    Area covered
    Peru
    Description

    Abstract

    The Government of Peru with the assistance of the World Bank and the Inter-American Development Bank launched a Public Expenditure Tracking Survey (PETS) to study weaknesses of the budget execution system in education and health sectors. The study also aimed to analyze effects of these weaknesses on service delivery and to assist in the generation of policy recommendations.

    Documented here is the Public Expenditure Tracking Survey conducted in Peru health sector. The study focused on Vaso de Leche (Glass of Milk) program, one of the largest food assistance program in Peru. By law, the intended primary beneficiaries of the program are children six years old or less and pregnant and breastfeeding mothers. Priority is given to those showing clear signs of malnutrition or tuberculosis. The products distributed can be milk in any form and/or milk substitutes, and/or other products such as soybean, oatmeal, quinoa, kiwicha or other. The funds for the program are transferred from central to local governments. Unfortunately, organizational hurdles, inefficiencies, leakages, and sometimes low nutritional value of the products chosen for distribution, limit the effectiveness of the Vaso de Leche (VdL) program to accomplish its goals.

    This study analyzed the leakages of funds for Vaso de Leche program from the central government to the municipalities, within municipalities, from municipality to VdL committees, from VdL committees to beneficiaries/households, and inside the household. One hundred twenty municipalities out of 1828 were surveyed. The fieldwork was carried out from February 3, 2002, to February 17, 2002.

    Geographic coverage

    Ancash, Arequipa, Cajamarca, Cusco, Lima, Loreto and Piura regions.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The following regions were chosen for the study: Ancash, Arequipa, Cajamarca, Cusco, Loreto, and Piura. These regions have the broadest range of geography, population density and poverty distribution.

    One hundred municipalities were selected in these regions. Municipalities were chosen based on poverty as a central stratification variable. Investigators employed the following steps:

    • A database consisting of the entire universe of districts in Peru excluding Lima & Callao (total of 1,651 districts) was used as a starting point.

    • The Ministry of Economy and Finance's continuous index of poverty FGT24 was used to calculate poverty population deciles.

    • The deciles were arranged into three groups such that group 1 consisted of deciles 1-3, group 2 contained deciles 4-7 and group 3 had deciles 8-10. These three groups approximate the categories of "not poor", "poor" and "extreme poor" and were used to stratify the districts of our sub-population (Ancash and Piura) into three strata.

    • The three strata represented 14 percent, 41 percent, and 45 percent of the districts in Peru (excluding Lima and Callao).

    • In order for the sample to be self-weighted, 14, 41, and 45 municipalities (total of 100) were chosen from each stratum respectively, (from the sub-population of six departments). The selection within each stratum was done using Probability Proportional to Size (PPS) relative to district population.

    Once the above procedures were carried out, individual municipalities were selected according to PPS criteria, using a complete listing of all districts selected that were ordered within the stratums by geographic order to allow a systematic selection that ensured geographic heterogeneity.

    Within each municipality, from the roster of Vaso de Leche committees using systematic sampling technique, researchers selected four committees. If there were less than four Vaso de Leche committees in a municipality, all were included in the sample. A substitute for a committee was used if travel time to the committee exceeded 24 hours. The sample slightly underrepresented remote areas within the neighborhoods of the selected committees.

    In each municipality investigators interviewed the mayor and obtained municipal-level data from him/her. They also attained the municipal roster of committees participating in the Vaso de Leche program. By law, Vaso de Leche committees should include a mayor, a municipal employee, a representative from the Ministry of Health, three representatives of the Mother's Associations (elected by the mothers following the rules established in their own statutes), and a representative of the local agriculture/farming association accredited by the Ministry of Agriculture.

    Enumerators interviewed at least one committee member. From the respondents, researchers received a list of beneficiary households and interviewed four households in each committee catchments area, using the survey instrument intended for households in Arequipa, Cusco, Cajamarca, and Loreto.

    Mode of data collection

    Face-to-face [f2f]

  19. F

    Estimated Percent of People Age 0-17 in Poverty for Allen County, OH

    • fred.stlouisfed.org
    json
    Updated Dec 20, 2024
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    (2024). Estimated Percent of People Age 0-17 in Poverty for Allen County, OH [Dataset]. https://fred.stlouisfed.org/series/PPU18OH39003A156NCEN
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    jsonAvailable download formats
    Dataset updated
    Dec 20, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Allen County, Ohio
    Description

    Graph and download economic data for Estimated Percent of People Age 0-17 in Poverty for Allen County, OH (PPU18OH39003A156NCEN) from 1989 to 2023 about Allen County, OH; Lima; under 18 years; OH; percent; child; poverty; and USA.

  20. f

    Woodfuel supply, changes by scenario and type of demand in Peru

    • data.apps.fao.org
    Updated Jun 17, 2024
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    (2024). Woodfuel supply, changes by scenario and type of demand in Peru [Dataset]. https://data.apps.fao.org/map/catalog/srv/search?keyword=wood%20energy%20supply
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    Dataset updated
    Jun 17, 2024
    Area covered
    Peru
    Description

    This map shows that forest biomass is unevenly distributed the Peruvian territory. This heterogeneous distribution of resources is the result of geographical and climatic variability that characterizes this country. The forest ecosystem has the largest amount of forest biomass available, while the coastal area and the mountains in the south have limited supply of biomass. This uneven distribution is the result of the tropical humid climate of the jungle, the desert climate in the coast and the limited availability of water in the southern highlands. This distribution of forest biomass, its relationship with the weather, the population distribution in the country and poverty, deserve studies locally. It is noted that the southern highlands is the part with most poverty in the country and is known as the Andean trapeze. The region with the largest supply of biomass is Loreto 145 Mt per year, other regions such as Amazonas, Cusco and San Martin have about 10 Mt per year. While regions that have a limited supply of woody biomass are: Arequipa, Moquegua and Tacna 15 000 17 700 and 14 000 Mt per annum respectively. Source data: - Dirección General Forestal de Faura Silvestre (DGFF). 2009. Perú forestal en números, ano 2008. Ministerio de Agricultura-DGFF. Lima. - INRENA. 2005. Mapa Forestal del Perú 2000. (No public). - INEI, 2008. Perfil socioeconómico del Perú. 2da. Edición. Census Nacionales 2007. XI de población y VI de vivienda. Lima. This dataset is part of the result of the Bioenergy and Food Security (BEFS) analysis for Perú on land and agro-climatic suitability and availability for crops. All BEFS results have been reported in the FAO publication “Bioenergía y seguridad alimentaria - El análisis de BEFS para el Perú - Compendio técnico Vol I y II†and the final products made available in this catalogue.

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Statista (2025). Poverty rate in Lima, Peru 2012-2023 [Dataset]. https://www.statista.com/statistics/1473821/poverty-rate-lima/
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Poverty rate in Lima, Peru 2012-2023

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Dataset updated
Jul 10, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Peru
Description

The share of the population with at least one poverty condition or unmet need in the Peruvian capital of Lima reached its lowest during 2017 with *** percent. In 2023, the share of residents of the metropolitan area was over **** percent.

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