About this dataset

Context

The dataset tabulates the population of Italy town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Italy town. The dataset can be utilized to understand the population distribution of Italy town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Italy town. 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 Italy town.

Key observations

Largest age group (population): Male # 65-69 years (80) | Female # 55-59 years (66). 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.

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 Italy town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Italy town is shown in the following column.
• Population (Female): The female population in the Italy town 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 Italy town 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 Italy town Population by Gender. You can refer the same here

About this dataset

Context

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

Key observations

There is a slight majority of female population, with 52.72% 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 Italy is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Italy 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 Italy Population by Race & Ethnicity. You can refer the same here

Italy IT: Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data was reported at 67.758 % in 2017. This records an increase from the previous number of 67.501 % for 2016. Italy IT: Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data is updated yearly, averaging 61.043 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 67.758 % in 2017 and a record low of 52.398 % in 1993. Italy IT: Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank.WDI: Labour Force. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.; ; Derived using data from International Labour Organization, ILOSTAT database. Data retrieved in September 2018.; Weighted average; Data up to 2016 are estimates while data from 2017 are projections. National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

Italy IT: Labour Force Participation Rate: National Estimate: Ratio of Female to Male data was reported at 68.270 % in 2016. This records an increase from the previous number of 67.544 % for 2015. Italy IT: Labour Force Participation Rate: National Estimate: Ratio of Female to Male data is updated yearly, averaging 54.345 % from Dec 1961 (Median) to 2016, with 42 observations. The data reached an all-time high of 68.348 % in 2014 and a record low of 30.519 % in 1961. Italy IT: Labour Force Participation Rate: National Estimate: Ratio of Female to Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Italy – Table IT.World Bank: Labour Force. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.; ; Derived using data from International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average; The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

This is a new dataset containing provincial and yearly data on Italy from 1951 to 1991. In particular, it contains:- female and male workforce divided by sector (total, agriculture, industry and services)- female and male participation rates divided by sector (total, agriculture, industry and services)- migrations data (registrations and cancellations, from/towards foreign countries and other italian provinces, divided by gender)- GDP estimates divided by sector (total, agriculture, industry, services and per capita GDP) both at current and constant prices (2005 euros)- population by class of age and gender

IntroductionIn recent years, the concept of epistemic trust has emerged as a critical factor in understanding psychopathology, particularly within the context of personality disorders. A self-report instrument, the Epistemic Trust, Mistrust, and Credulity Questionnaire (ETMCQ), has demonstrated its validity among English and Italian adult populations. However, extending its applicability to adolescents is essential for comprehending the role of epistemic trust in the development of mental disorders. The aim of this study was to validate the ETMCQ within the Italian adolescent demographic.MethodsData were gathered from a wide selection of middle and high schools across Italy. The data collection started on 01/03/2022 and ended on 30/06/2022. Besides the ETMCQ (Study 1 = 662 participants, 12–18 years old, M = 15.56, SD = 2.20; 324 females, 338 males), we also administered other self-report instruments measuring mentalization, emotional dysregulation, general levels of psychopathology, and interpersonal trust in a smaller groups (Study 2 = 417 participants, aged from 12–19 years old, M = 15.64; SD = 2.08; 249 females, 168 males).ResultsOur findings provide empirical validation for the theoretical framework concerning the role of epistemic trust in psychological functioning and substantiate the validity of ETMCQ as a measure to assess it among teenagers.ConclusionsThe ETMCQ is a valid and promising instrument for adolescent populations; its ease and brevity of administration could make it a valuable tool both in clinical and research contexts, shedding light on the role of epistemic trust in mental health.

About this dataset

Context

The dataset tabulates the data for the Italy, New York population pyramid, which represents the Italy town population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Italy, New York, is 17.6.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Italy, New York, is 46.2.
• Total dependency ratio for Italy, New York is 63.8.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Italy, New York is 2.2.

Content

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

Variables / Data Columns

• Age Group: This column displays the age group for the Italy town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Italy town for the selected age group is shown in the following column.
• Population (Female): The female population in the Italy town for the selected age group is shown in the following column.
• Total Population: The total population of the Italy town for the selected age group is shown in the following column.

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 Italy town Population by Age. You can refer the same here

Anonymized dataset used for the epidemiological analysis of workplace violence in an Italian healthcare setting. (SAV)

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Italy. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Italy, the median income for all workers aged 15 years and older, regardless of work hours, was $37,667 for males and $28,947 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 23% between the median incomes of males and females in Italy. With women, regardless of work hours, earning 77 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Italy.

- Full-time workers, aged 15 years and older: In Italy, among full-time, year-round workers aged 15 years and older, males earned a median income of $58,913, while females earned $50,607, resulting in a 14% gender pay gap among full-time workers. This illustrates that women earn 86 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Italy.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Italy.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Italy median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Italy town. The dataset can be utilized to gain insights into gender-based income distribution within the Italy town population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Italy town, among individuals aged 15 years and older with income, there were 452 men and 362 women in the workforce. Among them, 178 men were engaged in full-time, year-round employment, while 111 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 0.56% fell within the income range of under $24,999, while 5.41% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 7.30% of men in full-time roles earned incomes exceeding $100,000, while 2.70% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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 Italy town median household income by race. You can refer the same here