This statistic shows the total median income of senior citizens in Canada from 2000 to 2020, distinguished by age group. In 2020, the total median income of Canadian senior citizens aged 65 years and over amounted to 32,020 Canadian dollars.

This is a special extract of the 2000 Census 5-Percent Public Use Microdata Samples (PUMS) created by the National Archive of Computerized Data on Aging (NACDA). The file combines the individual 5-percent state files for all 50 states, the District of Columbia, and Puerto Rico as released by the United States Census Bureau into a single analysis file. The file contains information on all households that contain at least one person aged 65 years or more in residence as of the 2000 Census enumeration. The file contains individual records on all persons aged 65 and older living in households as well as individual records for all other members residing in each of these households. Consequently, this file can be used to examine both the characteristics of the elderly in the United States as well as the characteristics of individuals who co-reside with persons aged 65 and older as of the year 2000. All household variables from the household-specific "Household record" of the 2000 PUMS are appended to the end of each individual level record. This file is not a special product of the Census Bureau and is not a resample of the PUMS data specific to the elderly population. While it is comparable to the 1990 release CENSUS OF POPULATION AND HOUSING, 1990: [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE: 3-PERCENT ELDERLY SAMPLE (ICPSR 6219), the sampling procedures and weights for the 2000 file reflect the methodology that applies to the 5-percent PUMS release CENSUS OF POPULATION AND HOUSING, 2000 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE: 5-PERCENT SAMPLE (ICPSR 13568). Person variables cover age, sex, relationship to householder, educational attainment, school enrollment, race, Hispanic origin, ancestry, language spoken at home, citizenship, place of birth, year of immigration, place of residence in 1985, marital status, number of children ever born, military service, mobility and personal care limitation, work limitation status, employment status, occupation, industry, class of worker, hours worked last week, weeks worked in 1989, usual hours worked per week, temporary absence from work, place of work, time of departure for work, travel time to work, means of transportation to work, total earnings, total income, wages and salary income, farm and nonfarm self-employment income, Social Security income, public assistance income, retirement income, and rent, dividends, and net rental income. Housing variables include area type, state and area of residence, farm/nonfarm status, type of structure, year structure was built, vacancy and boarded-up status, number of rooms and bedrooms, presence or absence of a telephone, presence or absence of complete kitchen and plumbing facilities, type of sewage facilities, type of water source, type of heating fuel used, property value, tenure, year moved into house/apartment, type of household/family, type of group quarters, household language, number of persons in the household, number of persons and workers in the family, status of mortgage, second mortgage, and home equity loan, number of vehicles available, household income, sales of agricultural products, payments for rent, mortgage and property tax, condominium fees, mobile home costs, and cost of electricity, water, heating fuel, and flood/fire/hazard insurance.

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 Glen Elder. The dataset can be utilized to gain insights into gender-based income distribution within the Glen Elder population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Glen Elder, among individuals aged 15 years and older with income, there were 166 men and 263 women in the workforce. Among them, 114 men were engaged in full-time, year-round employment, while 117 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 2.63% fell within the income range of under $24,999, while 0.85% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 4.39% of men in full-time roles earned incomes exceeding $100,000, while 4.27% 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 Glen Elder 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 Elder township. The dataset can be utilized to gain insights into gender-based income distribution within the Elder township population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Elder township, among individuals aged 15 years and older with income, there were 410 men and 397 women in the workforce. Among them, 146 men were engaged in full-time, year-round employment, while 124 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 3.42% fell within the income range of under $24,999, while 25.81% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 7.53% of men in full-time roles earned incomes exceeding $100,000, while 3.23% 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 Elder township median household income by race. You can refer the same here

Family characteristics of seniors by total income statistics for Canada, provinces and territories, census metropolitan areas and census agglomerations. Includes age of seniors, housing indicators, tenure including presence of mortgage payments and subsidized housing, and structural type of dwelling.

If you’re a senior with low income, you may qualify for monthly Guaranteed Annual Income System payments.

Maximum payment and allowable private income amounts for the period from July 1, 2025 to June 30, 2026 are:

• $90 monthly for single seniors (maximum monthly payment amount), your annual private income must be less than $4,320
• $180 monthly for senior couples (maximum monthly payment amount), your annual private income must be less than $8,640

The data is organized by private income levels. GAINS payments are provided on top of the Old Age Security (OAS) pension and the Guaranteed Income Supplement (GIS) payments you may receive from the federal government.

Learn more about the Ontario Guaranteed Annual Income System

This data is related to The Retirement Income System in Canada

Join the Ontario Ministry of Finance for a free webinar to help you learn about tax credits, benefits, and other programs available to support Ontario seniors with a low income. Visit ontario.ca/TaxTalk to learn more.

United States Avg Hourly Earnings: sa: EH: Homes for Elderly data was reported at 16.190 USD in May 2018. This records an increase from the previous number of 16.150 USD for Apr 2018. United States Avg Hourly Earnings: sa: EH: Homes for Elderly data is updated monthly, averaging 13.740 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 16.190 USD in May 2018 and a record low of 12.520 USD in Jul 2006. United States Avg Hourly Earnings: sa: EH: Homes for Elderly data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G033: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Seasonally Adjusted.

Graph and download economic data for All Employees: Education and Health Services: Continuing Care Retirement Communities and Assisted Living Facilities for the Elderly in New York (SMU36000006562330001A) from 1990 to 2024 about elderly, nursing homes, nursing, assistance, retirement, health, NY, education, services, employment, and USA.

AHE: PW: EH: Community Care Facilities for the Elderly data was reported at 22.380 USD in Mar 2025. This records an increase from the previous number of 22.330 USD for Feb 2025. AHE: PW: EH: Community Care Facilities for the Elderly data is updated monthly, averaging 12.350 USD from Jan 1990 (Median) to Mar 2025, with 423 observations. The data reached an all-time high of 22.720 USD in Jan 2025 and a record low of 6.800 USD in Feb 1990. AHE: PW: EH: Community Care Facilities for the Elderly data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Average Hourly Earnings: Production Workers.

Comprehensive YouTube channel statistics for Elderly Timeless Wisdom, featuring 111,000 subscribers and 9,176,988 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Lifestyle category and is based in US. Track 152 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

These data from the 1990 Census comprise a sample of households with at least one person 60 years and older, plus a sample of persons 60 years and older in group quarters. The data are grouped into housing variables and person variables. Housing variables include area type, state and area of residence, farm/nonfarm status, type of structure, year structure was built, vacancy and boarded-up status, number of rooms and bedrooms, presence or absence of a telephone, presence or absence of complete kitchen and plumbing facilities, type of sewage facilities, type of water source, type of heating fuel used, property value, tenure, year moved into house/apartment, type of household/family, type of group quarters, household language, number of persons in the household, number of persons and workers in the family, status of mortgage, second mortgage, and home equity loan, number of vehicles available, household income, sales of agricultural products, payments for rent, mortgage and property tax, condominium fees, mobile home costs, and cost of electricity, water, heating fuel, and flood/fire/hazard insurance. Person variables cover age, sex, relationship to householder, educational attainment, school enrollment, race, Hispanic origin, ancestry, language spoken at home, citizenship, place of birth, year of immigration, place of residence in 1985, marital status, number of children ever born, military service, mobility and personal care limitation, work limitation status, employment status, occupation, industry, class of worker, hours worked last week, weeks worked in 1989, usual hours worked per week, temporary absence from work, place of work, time of departure for work, travel time to work, means of transportation to work, total earnings, total income, wages and salary income, farm and nonfarm self-employment income, Social Security income, public assistance income, retirement income, and rent, dividends, and net rental income.

United States Avg Hourly Earnings: EH: Homes for Elderly data was reported at 16.210 USD in May 2018. This records a decrease from the previous number of 16.240 USD for Apr 2018. United States Avg Hourly Earnings: EH: Homes for Elderly data is updated monthly, averaging 13.740 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 16.240 USD in Apr 2018 and a record low of 12.470 USD in Jun 2006. United States Avg Hourly Earnings: EH: Homes for Elderly data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G032: Current Employment Statistics Survey: Average Weekly and Hourly Earnings.

View monthly updates and historical trends for US Education and Health Services, Community Care Facilities for the Elderly Real Average Weekly Earnings. f…

Graph and download economic data for All Employees: Education and Health Services: Continuing Care Retirement Communities and Assisted Living Facilities for the Elderly in California (SMU06000006562330001) from Jan 1990 to Aug 2025 about elderly, nursing homes, nursing, assistance, retirement, health, education, CA, services, employment, and USA.

United States Avg Hourly Earnings: sa: EH: Services for Elderly & Disabled data was reported at 15.190 USD in May 2018. This records an increase from the previous number of 15.130 USD for Apr 2018. United States Avg Hourly Earnings: sa: EH: Services for Elderly & Disabled data is updated monthly, averaging 13.880 USD from Mar 2006 (Median) to May 2018, with 147 observations. The data reached an all-time high of 15.190 USD in May 2018 and a record low of 12.700 USD in Aug 2007. United States Avg Hourly Earnings: sa: EH: Services for Elderly & Disabled data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G033: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Seasonally Adjusted.

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 Box Elder. The dataset can be utilized to gain insights into gender-based income distribution within the Box Elder population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Box Elder, among individuals aged 15 years and older with income, there were 4,710 men and 3,613 women in the workforce. Among them, 3,505 men were engaged in full-time, year-round employment, while 1,752 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 12.47% fell within the income range of under $24,999, while 17.98% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 14.18% of men in full-time roles earned incomes exceeding $100,000, while 4.17% 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 Box Elder median household income by race. You can refer the same here

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 Glen Elder. 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 Glen Elder, the median income for all workers aged 15 years and older, regardless of work hours, was $53,357 for males and $35,972 for females.

These income figures highlight a substantial gender-based income gap in Glen Elder. Women, regardless of work hours, earn 67 cents for each dollar earned by men. This significant gender pay gap, approximately 33%, underscores concerning gender-based income inequality in the city of Glen Elder.

- Full-time workers, aged 15 years and older: In Glen Elder, among full-time, year-round workers aged 15 years and older, males earned a median income of $54,545, while females earned $41,425, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Glen Elder.

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

In 2019, the annual salary of senior financial analysts in South Korea ranged from ** million to ** million South Korean won. This was the same as in the previous year, and the annual salary range is expected to stay the same in 2020.

Graph and download economic data for All Employees: Education and Health Services: Continuing Care Retirement Communities and Assisted Living Facilities for the Elderly in Florida (SMU12000006562330001) from Jan 1990 to Aug 2025 about elderly, nursing homes, nursing, assistance, retirement, health, education, FL, services, employment, and USA.

This round of Euro-Barometer surveys queried respondents on standard Euro-Barometer measures such as public awareness of and attitudes toward the Common Market and the European Community (EC), and also focused on consumer goods, Social Security, health care and health care benefits, the elderly, retirement, and alcohol and drug use. Questions concerning consumer goods asked whether respondents read product information before purchasing, what additional product information they would like to see, what three things other than price were most important in deciding whether to purchase an item, and whether it was necessary to have the same type of product information available for all members of the European Community (EC). Respondents' attitudes and opinions on Social Security were probed with questions that asked whether they agreed that Social Security properly protects the unemployed, the elderly, the sick or disabled, those with work-related injuries or illness, and the poor. Respondents were also asked whether policies on pensions, minimum income, and unemployment should be decided by national governments or by the EC, and whether foreigners should have the same Social Security benefits as citizens. The general health of respondents and their health care benefits were assessed through questions that asked whether they had a long-standing illness, disability, or infirmity, whether they had cut down their activity due to illness or injury, and whether they had taken medicine or talked to a doctor within the last 30 days. Respondents were also queried about which conditions they would see a doctor for and what type of examinations they had had in the past three years. Respondents were asked to rate what they paid for various medical services, the general quality of their health care, and the nature and availability of health insurance. The main problems facing the elderly and the role the elderly play in society were also topics of investigation in this survey. Questions elicited respondents' views toward possible changes in pension terms, whether retirement should occur at a fixed age, what types of discrimination affect the elderly who are working, whether the government should introduce laws to try to stop age discrimination, whether a minimum level of income should be provided to the elderly, and whether the elderly needing personal care should go into residential/nursing homes or should have social services help them remain in their homes for as long as possible. Respondents were also asked whether they provided long-term care to anyone either living with them or not living with them, who was in the best position to decide which services are most important for the elderly, what the best method of financing long-term care for the elderly was, and whether the EC was doing enough with regard to the elderly. Questions on retirement dealt with what ages respondents retired/planned to retire, whether the retired felt their pensions to be adequate, whether working people looked forward to retiring, whether pensions should be extended to widows and dependent children, whether pensions should be reduced for those who work for earned income beyond retirement, and whether pensions should be provided through government taxation, employer/employee contributions, or private contracts between workers and pension companies. Queries about alcohol and drug usage probed the use of beer, wine, spirits, and other forms of alcohol, age at which the respondent began drinking, familiarity with major forms of drugs, age at which drugs were first offered, how difficult it was to get drugs, and the means available for getting drugs. Additional questions focused on how the respondent viewed the drug problem, the top priority in eliminating the drug problem, diminishing the effects of drug use, whether drug use leads to AIDS, prostitution, health problems, social problems, violence, suicide, personality breakdowns, and problems with the law, and the major reasons for alcohol and drug use. Demographic and other background information was gathered on life satisfaction, number of people residing in the home, size of locality, home ownership, trade union membership, region of residence, and occupation of the head of household, as well as the respondent's age, sex, marital status, educa