Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

This dataset includes a count and rate per 100,000 population for COVID-19 cases, a count of COVID-19 molecular diagnostic tests, and a percent positivity rate for tests among people living in community settings for the previous two-week period. Dates are based on date of specimen collection (cases and positivity).

A person is considered a new case only upon their first COVID-19 testing result because a case is defined as an instance or bout of illness. If they are tested again subsequently and are still positive, it still counts toward the test positivity metric but they are not considered another case.

Percent positivity is calculated as the number of positive tests among community residents conducted during the 14 days divided by the total number of positive and negative tests among community residents during the same period. If someone was tested more than once during that 14 day period, then those multiple test results (regardless of whether they were positive or negative) are included in the calculation.

These case and test counts do not include cases or tests among people residing in congregate settings, such as nursing homes, assisted living facilities, or correctional facilities.

These data are updated weekly and reflect the previous two full Sunday-Saturday (MMWR) weeks (https://wwwn.cdc.gov/nndss/document/MMWR_week_overview.pdf).

DPH note about change from 7-day to 14-day metrics: Prior to 10/15/2020, these metrics were calculated using a 7-day average rather than a 14-day average. The 7-day metrics are no longer being updated as of 10/15/2020 but the archived dataset can be accessed here: https://data.ct.gov/Health-and-Human-Services/COVID-19-case-rate-per-100-000-population-and-perc/s22x-83rd

As you know, we are learning more about COVID-19 all the time, including the best ways to measure COVID-19 activity in our communities. CT DPH has decided to shift to 14-day rates because these are more stable, particularly at the town level, as compared to 7-day rates. In addition, since the school indicators were initially published by DPH last summer, CDC has recommended 14-day rates and other states (e.g., Massachusetts) have started to implement 14-day metrics for monitoring COVID transmission as well.

With respect to geography, we also have learned that many people are looking at the town-level data to inform decision making, despite emphasis on the county-level metrics in the published addenda. This is understandable as there has been variation within counties in COVID-19 activity (for example, rates that are higher in one town than in most other towns in the county).

Additional notes: As of 11/5/2020, CT DPH has added antigen testing for SARS-CoV-2 to reported test counts in this dataset. The tests included in this dataset include both molecular and antigen datasets. Molecular tests reported include polymerase chain reaction (PCR) and nucleic acid amplicfication (NAAT) tests.

The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

Data suppression is applied when the rate is <5 cases per 100,000 or if there are <5 cases within the town. Information on why data suppression rules are applied can be found online here: https://www.cdc.gov/cancer/uscs/technical_notes/stat_methods/suppression.htm

Background

Sarcomas are uncommon cancers that can affect any part of the body. There are many different types of sarcoma and subtypes can be grouped into soft tissue or bone sarcomas. About 15 people are diagnosed every day in the UK. 3 in every 200 people with cancer in the UK have sarcoma.

A highly granular dataset with a confirmed sarcoma event including hospital presentation, serial physiology, demography, treatment prescribed and administered, prescribed and administered drugs. The infographic includes data from 27/12/2004 to 31/12/2021 but data is available from the past 10 years+.

PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.

EHR. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & an expanded 250 ITU bed capacity during COVID. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All hospitalised patients from 2004 onwards, curated to focus on Sarcoma. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to acute care process (timings, staff grades, specialty review, wards and triage). Along with presenting complaints, outpatients admissions, microbiology results, referrals, procedures, therapies, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations and others), and all blood results (urea, albumin, platelets, white blood cells and others). Includes all prescribed & administered treatments and all outcomes. Linked images are also available (radiographs, CT scans, MRI).

Available supplementary data: Matched controls; ambulance, OMOP data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

The National Cancer Registration and Analysis Service (NCRAS) at Public Health England supplies cancer registration data to NHS Digital. This data is available to be linked to other data held by NHS Digital in order to provide notifications on an individual's cancer status, be available to support research studies and to identify potential research participants for clinical trials.

NCRAS is the population-based cancer registry for England. It collects, quality assures and analyses data on all people living in England who are diagnosed with malignant and pre-malignant neoplasms, with national coverage since 1971.

The Cancer Registration dataset comprises England data to the present day, and Welsh data up to April 2017.

Timescales for dissemination of agreed data can be found under 'Our Service Levels' at the following link: https://digital.nhs.uk/services/data-access-request-service-dars/data-access-request-service-dars-process Standard response

BackgroundSedentary behavior is thought to pose different risks to those attributable to physical inactivity. However, few studies have examined the association between physical activity and sitting time with cancer incidence within the same population.MethodsWe followed 38,154 healthy Norwegian adults in the Nord-Trøndelag Health Study (HUNT) for cancer incidence from 1995–97 to 2014. Cox proportional hazards regression was used to estimate risk of site-specific and total cancer incidence by baseline sitting time and physical activity.ResultsDuring the 16-years follow-up, 4,196 (11%) persons were diagnosed with cancer. We found no evidence that people who had prolonged sitting per day or had low levels of physical activity had an increased risk of total cancer incidence, compared to those who had low sitting time and were physically active. In the multivariate model, sitting ≥8 h/day was associated with 22% (95% CI, 1.05–1.42) higher risk of prostate cancer compared to sitting 16.6 MET-h/week). The joint effects of physical activity and sitting time the indicated that prolonged sitting time increased the risk of CRC independent of physical activity in men.ConclusionsOur findings suggest that prolonged sitting and low physical activity are positively associated with colorectal-, prostate- and lung cancer among men. Sitting time and physical activity were not associated with cancer incidence among women. The findings emphasizing the importance of reducing sitting time and increasing physical activity.

Although the link between sugar-sweetened beverages (SSB) and pancreatic cancer has been suggested for its insulin-stimulating connection, most epidemiological studies showed inconclusive relationship. Whether the result was limited by sample size is explored. This prospective study followed 491,929 adults, consisting of 235,427 men and 256,502 women (mean age: 39.9, standard deviation: 13.2), from a health surveillance program and there were 523 pancreatic cancer deaths between 1994 and 2017. The individual identification numbers of the cohort were matched with the National Death file for mortality, and Cox models were used to assess the risk. The amount of SSB intake was recorded based on the average consumption in the month before interview by a structured questionnaire. We classified the amount of SSB intake into 4 categories: 0–<0.5 serving/day, ≥0.5–<1 serving per day, ≥1–<2 servings per day, and ≥2 servings per day. One serving was defined as equivalent to 12 oz and contained 35 g added sugar. We used the age and the variables at cohort enrolment as the reported risks of pancreatic cancers. The cohort was divided into 3 age groups, 20–39, 40–59, and ≥60. We found young people (age <40) had higher prevalence and frequency of sugar-sweetened beverages than the elderly. Those consuming 2 servings/day had a 50% increase in pancreatic cancer mortality (HR = 1.55, 95% CI: 1.08–2.24) for the total cohort, but a 3-fold increase (HR: 3.09, 95% CI: 1.44–6.62) for the young. The risk started at 1 serving every other day, with a dose–response relationship. The association of SSB intake of ≥2 servings/day with pancreatic cancer mortality among the total cohort remained significant after excluding those who smoke or have diabetes (HR: 2.12, 97% CI: 1.26–3.57), are obese (HR: 1.57, 95% CI: 1.08–2.30), have hypertension (HR: 1.90, 95% CI: 1.20–3.00), or excluding who died within 3 years after enrollment (HR: 1.67, 95% CI: 1.15–2.45). Risks remained in the sensitivity analyses, implying its independent nature. We concluded that frequent drinking of SSB increased pancreatic cancer in adults, with highest risk among young people.

To describe the last year in the lives of a random sample of adults dying in 1987. 2. To make comparisons with an earlier study and identify change in the nature and availability of care and in the attitudes and expectations of lay and professional carers. 3. To make some assessment of the influence of the hospice movement on these changes. 4. To describe in more detail than the previous 1969 study, the institutional care of people in the year preceeding their death. 5. To determine the experience and views of the doctors and nurses involved in the care of these people in the last year of their lives. 6. To describe the care and support given to close relatives both after and before the death. An earlier study Life Before Death, 1969 is held at the Data Archive as Study No. 393. Main Topics: Methodological issues in studying life before death; the roles of professionals, hospitals, hospices, residential and nursing homes, and day centres in caring for the dying; the balance of care; hospice deaths and cancer deaths; experiences of those who died and those who cared for them; changes since 1969. Characteristics of the general practitioners were obtained from DHSS data. One-stage stratified or systematic random sample Local authority areas (or combinations for small numbers of deaths) chosen after stratification into 3 groups: (1) with no hospice or hospice service (2) hospice service but no beds (3) hospice service with beds. For further details see documentation. Face-to-face interview Telephone interview Postal survey Questionnaire interview with person who knew most about those who died; postal questionnaire to general practitioners and consultants about views and experiences; Face to face, postal and telephone interviewing was used for community nurses.

Content

The hospital readmission rate PUF presents nation-wide information about inpatient hospital stays that occurred within 30 days of a previous inpatient hospital stay (readmissions) for Medicare fee-for-service beneficiaries. The readmission rate equals the number of inpatient hospital stays classified as readmissions divided by the number of index stays for a given month. Index stays include all inpatient hospital stays except those where the primary diagnosis was cancer treatment or rehabilitation. Readmissions include stays where a beneficiary was admitted as an inpatient within 30 days of the discharge date following a previous index stay, except cases where a stay is considered always planned or potentially planned. Planned readmissions include admissions for organ transplant surgery, maintenance chemotherapy/immunotherapy, and rehabilitation.

This dataset has several limitations. Readmissions rates are unadjusted for age, health status or other factors. In addition, this dataset reports data for some months where claims are not yet final. Data published for the most recent six months is preliminary and subject to change. Final data will be published as they become available, although the difference between preliminary and final readmission rates for a given month is likely to be less than 0.1 percentage point.

Data Source: The primary data source for these data is the CMS Chronic Condition Data Warehouse (CCW), a database with 100% of Medicare enrollment and fee-for-service claims data. For complete information regarding data in the CCW, visit http://ccwdata.org/index.php. Study Population: Medicare fee-for-service beneficiaries with inpatient hospital stays.

Context

This is a dataset hosted by the Centers for Medicare & Medicaid Services (CMS). The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore CMS's Data using Kaggle and all of the data sources available through the CMS organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Justyn Warner on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

This dataset is distributed under NA

BackgroundStrategies to increase physical activity (PA) and improve nutrition would contribute to substantial health benefits in the population, including reducing the risk of several types of cancers. The increasing accessibility of digital technologies mean that these tools could potentially facilitate the improvement of health behaviours among young people.ObjectiveWe conducted a review of systematic reviews to assess the available evidence on digital interventions aimed at increasing physical activity and good nutrition in sub-populations of young people (school-aged children, college/university students, young adults only (over 18 years) and both adolescent and young adults (<25 years)).MethodsSearches for systematic reviews were conducted across relevant databases including KSR Evidence (www.ksrevidence.com), Cochrane Database of Systematic Reviews (CDSR) and Database of Abstracts of Reviews of Effects (DARE; CRD). Records were independently screened by title and abstract by two reviewers and those deemed eligible were obtained for full text screening. Risk of bias (RoB) was assessed with the Risk of Bias Assessment Tool for Systematic Reviews (ROBIS) tool. We employed a narrative analysis and developed evidence gap maps.ResultsTwenty-four reviews were included with at least one for each sub-population and employing a range of digital interventions. The quality of evidence was limited with only one of the 24 of reviews overall judged as low RoB. Definitions of “digital intervention” greatly varied across systematic reviews with some reported interventions fitting into more than one category (i.e., an internet intervention could also be a mobile phone or computer intervention), however definitions as reported in the relevant reviews were used. No reviews reported cancer incidence or related outcomes. Available evidence was limited both by sub-population and type of intervention, but evidence was most pronounced in school-aged children. In school-aged children eHealth interventions, defined as school-based programmes delivered by the internet, computers, tablets, mobile technology, or tele-health methods, improved outcomes. Accelerometer-measured (Standardised Mean Difference [SMD] 0.33, 95% Confidence Interval [CI]: 0.05 to 0.61) and self-reported (SMD: 0.14, 95% CI: 0.05 to 0.23) PA increased, as did fruit and vegetable intake (SMD: 0.11, 95% CI: 0.03 to 0.19) (review rated as low RoB, minimal to considerable heterogeneity across results). No difference was reported for consumption of fat post-intervention (SMD: −0.06, 95% CI: −0.15 to 0.03) or sugar sweetened beverages(SSB) and snack consumption combined post-intervention (SMD: −0.02, 95% CI:–0.10 to 0.06),or at the follow up (studies reported 2 weeks to 36 months follow-up) after the intervention (SMD:–0.06, 95% CI: −0.15 to 0.03) (review rated low ROB, minimal to substantial heterogeneity across results). Smartphone based interventions utilising Short Messaging Service (SMS), app or combined approaches also improved PA measured using objective and subjective methods (SMD: 0.44, 95% CI: 0.11 to 0.77) when compared to controls, with increases in total PA [weighted mean difference (WMD) 32.35 min per day, 95% CI: 10.36 to 54.33] and in daily steps (WMD: 1,185, 95% CI: 303 to 2,068) (review rated as high RoB, moderate to substantial heterogeneity across results). For all results, interpretation has limitations in terms of RoB and presence of unexplained heterogeneity.ConclusionsThis review of reviews has identified limited evidence that suggests some potential for digital interventions to increase PA and, to lesser extent, improve nutrition in school-aged children. However, effects can be small and based on less robust evidence. The body of evidence is characterised by a considerable level of heterogeneity, unclear/overlapping populations and intervention definitions, and a low methodological quality of systematic reviews. The heterogeneity across studies is further complicated when the age (older vs. more recent), interactivity (feedback/survey vs. no/less feedback/surveys), and accessibility (type of device) of the digital intervention is considered. This underscores the difficulty in synthesising evidence in a field with rapidly evolving technology and the resulting challenges in recommending the use of digital technology in public health. There is an urgent need for further research using contemporary technology and appropriate methods.

These data are being released in BETA version to facilitate early access to the study for research purposes. This collection has not been fully processed by NACDA or ICPSR at this time; the original materials provided by the principal investigator were minimally processed and converted to other file types for ease of use. As the study is further processed and given enhanced features by ICPSR, users will be able to access the updated versions of the study. Please report any data errors or problems to user support and we will work with you to resolve any data related issues. The National Health Interview Survey (NHIS) is conducted annually and sponsored by the National Center for Health Statistics (NCHS), which is part of the U.S. Public Health Service. The purpose of the NHIS is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive across the United States population through the collection and analysis of data on a broad range of health topics. The redesigned NHIS questionnaire introduced in 1997 (see National Health Interview Survey, 1997 [ICPSR 2954]) consists of a core that remains largely unchanged from year to year, plus an assortment of supplements varying from year to year. The 2010 NHIS Core consists of three modules: Family, Sample Adult, and Sample Child. The datasets derived from these modules include Household Level, Family Level, Person Level, Injury/Poison Episode Level, Injury/Poison Verbatim Level, Sample Adult Level, and Sample Child level. The 2010 NHIS supplements consist of stand alone datasets for Cancer Level and Quality of Life data derived from the Sample Adult core and Disability Questions Tests 2010 Level derived from the Family core questionnaire. Additional supplementary questions can be found in the Sample Child dataset on the topics of cancer, immunization, mental health, and mental health services and in the Sample Adult dataset on the topics of epilepsy, immunization, and occupational health. Part 1, Household Level, contains data on type of living quarters, number of families in the household responding and not responding, and the month and year of the interview for each sampling unit. Parts 2-5 are based on the Family Core questionnaire. Part 2, Family Level, provides information on all family members with respect to family size, family structure, health status, limitation of daily activities, cognitive impairment, health conditions, doctor visits, hospital stays, health care access and utilization, employment, income, participation in government assistance programs, and basic demographic information. Part 3, Person Level, includes information on sex, age, race, marital status, education, family income, major activities, health status, health care costs, activity limits, and employment status. Parts 4 and 5, Injury/Poisoning Episode Level and Injury/Poisoning Verbatim Level, consist of questions about injuries and poisonings that resulted in medical consultations for any family members and contains information about the external cause and nature of the injury or poisoning episode and what the person was doing at the time of the injury or poisoning episode, in addition to the date and place of occurrence. A randomly-selected adult in each family was interviewed for Part 6, Sample Adult Level, regarding specific health issues, the relation between employment and health, health status, health care and doctor visits, limitation of daily activities, immunizations, and behaviors such as smoking, alcohol consumption, and physical activity. Demographic information, including occupation and industry, also was collected. The respondents to Part 6 also completed Part 7, Cancer Level, which consists of a set of supplemental questions about diet and nutrition, physical activity, tobacco, cancer screening, genetic testing, family history, and survivorship. Part 8, Sample Child Level, provides information from an adult in the household on medical conditions of one child in the household, such as developmental or intellectual disabilities, respiratory problems, seizures, allergies, and use of special equipment like hearing aids, braces, or wheelchairs. Parts 9 through 13 comprise the additional Supplements and Paradata for the 2010 NHIS. Part 9, Disability Questions Tests 2010 Level

• 'normal day-to-day activities' include everyday things like eating, washing, walking and going shopping There are additional provisions relating to people with progressive conditions. People with HIV, cancer or multiple sclerosis are protected by the Act from the point of diagnosis. People with some visual impairments are automatically deemed to be disabled. 18/03/2015 Data has been reweighted in line with the latest ONS estimates. 2013 data is not available for disability measures from this survey. Due to changes in the health questions on the Annual Population Survey there is quite a large discontinuity in the estimates from the Apr 2012 to Mar 2013 period onwards. These became available again from the Apr 2013 to March 2014 period as new variables. 95% confidence interval of percent figure (+/-).

This data set illustrates the protected and total are of global non tropical forests. They are further defined as "Tropical forests included all forests located between the Tropics of Cancer and Capricorn. All other forests were put into the non-tropical categories. Montane forests within the tropics that were classified in the source maps as "temperate" were registered in the "tropical forests" categories in this study" (Earth Trends). http://earthtrends.wri.org/searchable_db/index.php?step=countries&ccID%5B%5D=0&allcountries=checkbox&theme=9&variable_ID=321&action=select_years http://earthtrends.wri.org/searchable_db/index.php?step=countries&ccID%5B%5D=0&allcountries=checkbox&theme=9&variable_ID=320&action=select_years September 25, 2007

Abstract (en): The purpose of the National Health Interview Survey (NHIS) is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. Implementation of a redesigned NHIS, consisting of a basic module, a periodic module, and a topical module, began in 1997 (See NATIONAL HEALTH INTERVIEW SURVEY, 1997 [ICPSR 2954]). This final release of the 2000 NHIS contains the Household, Family, Person, Sample Adult, Sample Child, and Immunization, and Injury and Poison data files from the basic module. The 2000 NHIS also contains the Cancer Control Module (included in the Sample Adult File, Part 4), which corresponds to the Cancer Supplements of 1987 and 1992 and examines such items as diet and nutrition, use of herbal supplements, Hispanic acculturation, genetic testing, and family history. Each record in the Household-Level File (Part 1) of the basic module contains data on the type of living quarters, number of families in the household responding and not responding, and the month and year of the interview for each eligible sampling unit. The Family-Level File (Part 2) is made up of reconstructed variables from the person-level data of the basic module and includes information on sex, age, race, marital status, Hispanic origin, education, veteran status, family income, family size, major activities, health status, activity limits, and employment status, along with industry and occupation. As part of the basic module, the Person-Level File (Part 3) provides information on all family members with respect to health status, limitation of daily activities, cognitive impairment, and health conditions. Also included are data on years at current residence, region variables, height, weight, bed days, doctor visits, hospital stays, and health care access and utilization. A randomly-selected adult in each family was interviewed for the Sample Adult File (Part 4) regarding respiratory conditions, renal conditions, AIDS, joint symptoms, health status, limitation of daily activities, and behaviors such as smoking, alcohol consumption, and physical activity. The Sample Child File (Part 5) provides information from a knowledgeable adult in the household on medical conditions of one child in the household, such as respiratory problems, seizures, allergies, and use of special equipment such as hearing aids, braces, or wheelchairs. Also included are questions regarding child behavior, the use of mental health services, and Attention Deficit Hyperactivity Disorder (ADHD). The Child Immunization File (Part 6) presents information from shot records and supplies vaccination status, along with the number and dates of shots, and information about the chicken pox vaccine. The Injury and Poison Data File (Part 7) contains episode-level data for injuries and poisonings and the Injury and Poison Verbatim File (Part 8) contains verbatim comments for both injuries and poisonings. Civilian, noninstitutionalized population of the 50 United States and the District of Columbia. The NHIS uses a stratified multistage probability design. The sample for the NHIS is redesigned every decade using population data from the most recent decennial census. A redesigned sample was implemented in 1995. This new design includes a greater number of primary sampling units (PSUs) (from 198 in 1994 to 358), and a more complicated nonresponse adjustment based on household screening and oversampling of Black and Hispanic persons, for more reliable estimates of these groups. 2006-03-30 File cb03381-all_volume_2 was removed from dataset 10 and flagged as a study-level file, so that it will accompany all downloads. Dataset 10 was then empty, and was deleted.2006-03-30 File cb03381-all_volume_1 was removed from dataset 9 and flagged as a study-level file, so that it will accompany all downloads. Dataset 9 was then empty, and was deleted.2006-03-30 File MAN3381.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File QU3381.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revis...

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Televisions (Module 177): this module was asked on behalf of the Department of National Heritage, to ascertain how many households have a television that did not work at the time and did not have another TV set that did work, and whether they intended to get the broken television set repaired in the next seven days after the interview took place. ACAS awareness (Module 187): this module was asked on behalf of ACAS, the Advisory, Conciliation and Arbitration Service, who wished to know how many people had heard of them and how many had a realistic idea of what sort of organisation they are and what they do. The module was asked of all respondents in paid employment. Second homes (Module 4): this module was asked on behalf of the Department of Environment, Transport and the Regions (DETR). It has appeared in previous Omnibus surveys in a slightly different form. The module queried respondents on ownership of a second home by any member of the household and reasons for having the second home. Expectation of house price changes (Module 137): this module asks respondents' views on changes to house prices in the next year and next five years. Fire safety (Module 33): this module covers fire safety and was asked in connection with Fire Safety Week. Questions assess awareness of fire risks and fire safety measures the respondent has taken. Lone mothers (Module 184): this module was asked on behalf of the Department of Social Security. The questions were taken from a British attitudes survey and compare attitudes towards mothers living in couples with children of varying ages with attitudes towards lone mothers. Smoking (Module 130): this module assesses people's smoking habits, past and present, attitudes to smoking in different scenarios, and awareness of cigarette advertising. Unemployment risk (Module 183): this module was asked on behalf of the Centre for Research in Social Policy at Loughborough University. The questions were designed to investigate respondents' assessment of the risks of being unemployed, their attitude towards unemployment insurance and their recent experience of unemployment. Contraception (Module 170): the Special Licence version of this module is held under SN 6475. PEPs and TESSAs (Module 185): this module was asked on behalf of the Inland Revenue, to gain more information about the distribution of PEPs and TESSAs and in particular the extent to which the two groups overlap. Multi-stage stratified random sample Face-to-face interview 1997 ACCIDENTS ADULTS ADVERTISING ADVICE AGE ARBITRATION ASTHMA ATTITUDES BANK ACCOUNTS CANCER CARDIOVASCULAR DISE... CAUSES OF DEATH CHILD BENEFITS CHILD CARE CHILD DAY CARE CHILDREN CINEMA COHABITATION COLOUR TELEVISION R... COMPANIES CONFLICT RESOLUTION COOKING EQUIPMENT COSTS COT DEATHS COURTS CREDIT CARD USE CULTURAL EVENTS Consumption and con... DIABETES DISEASES ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATIONAL BACKGROUND ELECTRICAL EQUIPMENT EMPLOYEES EMPLOYMENT EMPLOYMENT CONTRACTS EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS EXPENDITURE Economic conditions... FAMILY MEMBERS FINANCIAL SERVICES FIRE PROTECTION EQU... FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... Family life and mar... GENDER GENERAL PRACTITIONERS GRANTS HEADS OF HOUSEHOLD HEALTH HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEARING HEATING SYSTEMS HOLIDAYS HOME CONTENTS INSUR... HOME OWNERSHIP HOME SELLING HOSPITAL SERVICES HOURS OF WORK HOUSEHOLDS HOUSES HOUSING TENURE HUMAN SETTLEMENT Health behaviour Housing ILL HEALTH INCOME INCOME TAX INDUSTRIES INFLATION INFORMATION MATERIALS INFORMATION SOURCES INHERITANCE INSURANCE INTEREST FINANCE INVESTMENT Income JOB HUNTING JUDGMENTS LAW LABOUR RELATIONS LANDLORDS Labour relations co... MANAGERS MARITAL STATUS MARRIAGE DISSOLUTION MASS MEDIA MEDICAL CENTRES MEDICAL INSURANCE MEDICAL PRESCRIPTIONS MORTGAGES MOTHERS MOTOR VEHICLES ONE PARENT FAMILIES ORGANIZATIONS PARENTS PART TIME EMPLOYMENT PASSIVE SMOKING PENSIONS PERSONNEL PLACE OF RESIDENCE PRESCHOOL CHILDREN PRICES PRIVATE SECTOR PUBLIC HOUSES PUBLIC INFORMATION PUBLIC SERVICE BUIL... RADIO RECRUITMENT RENTED ACCOMMODATION RESPIRATORY TRACT D... RESTAURANTS RETIREMENT SAVINGS SCHOOLCHILDREN SCHOOLS SECOND HOMES SELF EMPLOYED SHOPS SICK LEAVE SMOKING SMOKING CESSATION SMOKING RESTRICTIONS SOCIAL HOUSING SOCIAL SECURITY BEN... SPORTING EVENTS SPOUSE S ECONOMIC A... SPOUSE S EMPLOYMENT SPOUSES STATE AID SUPERVISORS Social behaviour an... TELEPHONE HELP LINES TELEVISION ADVERTISING TELEVISION RECEIVERS TERMINATION OF SERVICE TIED HOUSING TOBACCO TRAINING TRAVEL UNEMPLOYMENT UNFURNISHED ACCOMMO... UNMARRIED MOTHERS UNWAGED WORKERS Unemployment VOCATIONAL EDUCATIO... WAGES WORKERS RIGHTS WORKING MOTHERS WORKPLACE property and invest...

This round of Euro-Barometer surveys queried respondents on standard Euro-Barometer measures, such as how satisfied they were with their present life, whether they attempted to persuade others close to them to share their views on subjects they held strong opinions about, whether they discussed political matters, what their country's goals should be for the next ten or fifteen years, and how they viewed the need for societal change. The surveys also focused on health problems. Questions about smoking examined whether the respondent had heard of the European Code Against Cancer and whether the respondent smoked. Smokers were asked what tobacco products they used, how many cigarettes they smoked in a day, and whether they planned to cut down on their tobacco consumption. Queries focusing on other health issues included respondents' subjective ratings of their health and diet, the basis for their foodstuff selections, the extent and impact of alcohol consumption on their driving, the extent of the problem of drinking and driving, how the problem of drinking and driving would be best addressed, and respondents' own use of alcohol. Opinions on alcohol and drug abuse were elicited through questions such as what type of problem the respondent considered alcohol and drug use to be, whether current measures were enough to solve abuse, what measures should be taken to solve the problems, the respondent's knowledge of drugs and the use of drugs, drug use among acquaintances, and how drug testing should be implemented. AIDS-related items focused on how the respondent thought AIDS could be contracted and which manner of transmission the respondent most feared, which interventions should be used to eliminate or to slow the spread of AIDS, which interventions should be undertaken by the European Community, how best to handle those who had AIDS or were HIV-positive, whether the respondent personally knew anyone with AIDS/HIV+, how the emergence and spread of AIDS had changed the respondent's personal habits, and what precautions were effective against contracting AIDS. Questions concerning the respondent's work history asked whether there had been periods without work lasting more than a year. A series of items focused on the longest period without pay: how long the period was, the age of the respondent during this period, the main reason for leaving the previous job, what the previous occupation was and whether it was part-time, what the new occupation was and whether it was part-time, and how the level of the new occupation compared to the previous occupation. The interaction of raising children and pursuing a career was investigated through questions including how many children the respondent had, what effect changes in family life had on working life, whether the respondent worked full- or part-time while raising children, and whether the respondent would prefer to care for children full-time, care for children part-time and work part-time, or work full-time. A series of questions pertained to the period prior to the respondent's first three children attending school: whether the respondent worked during this period, what the respondent's occupation was, the attributes of the occupation that concerned the family, the attributes of the partner's occupation that concerned the family, who the primary caregivers were, whether the partner was the primary caregiver, and whether there were difficulties making last-minute arrangements for child care. Additional information was gathered on family income, number of people residing in the home, size of locality, home ownership, region of residence, occupation of the head of household, and the respondent's age, sex, occupation, education, religion, religiosity, subjective social class standing, political party and union membership, and left-right political self-placement. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR09577.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The steering group for Malmö Offspring Study: Peter Nilsson, Lund University, Department of Clinical Sciences, Malmö, Internal Medicine Research Unit Olle Melander, Lund University, Faculty of Medicine Jan Nilsson, Lund university, Department of Clinical Sciences Gunnar Engström, Lund University, Department of Clinical Sciences, Malmö Margaretha Persson, Skåne University Hospital, Department of Clinical Sciences, Malmö Marju Orho-Melander, Lund University, Department of Clinical Sciences, Malmö, Division of Diabetes and cardiovascular disease - genetic epidemiology

In Malmö Offspring Study, children and grandchildren to participants from the previous population study Malmö Diet Cancer are invited to participate. The children are today in the ages 50-55 while the grandchildren are 20-30 years old. The objective is to examine 5,000-6,000 individuals by the year 2020.

There is a long tradition of larger population studies in Malmö. The main ones are Malmö Preventing Project and Malmö Diet Cancer which together has engaged over 50 000 unique participants. They have created a foundation for future studies and research projects in both Sweden and Internationally. This has resulted in new knowledges about, for example, diabetes, cardiovascular diseases, cancer, alcohol abuse and the importance of nutrition and diet.

Researchers are now hoping to attain more relevant data than in the earlier population studies. This will be carried out through the usage of new methods for function analysis of blood vessels , lungs, brain and body metabolism which will be used at inspections and test. The connection between what people eat daily and the intestinal bacterial flora and how this affects people’s health is of special interest. Inspections and testing takes place at Skåne’s University Hospital in Malmö.

The participants are monitored clinically through tests as well as in records for a long period of time, based on informed consent and in accordance with ethical approval and the Privacy Act (PUL).

Purpose:

The purpose of the study is to provide future research access to new information about how diseases are spread within families, not only through genetic inheritance but also through life style, social patterns and health habits.

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Investment Income (Module 7a): ownership of shares and income from shares, bank accounts and building society accounts. Also question about investments in TESSAs. Fire Safety (Module 33): Awareness of Fire Safety Week, knowledge of facts about fire safety and precautions taken. Alcohol and Tobacco from EU (Module 64): alcohol and/or tobacco products brought back from European Union Countries during previous two months; quantity bought. GP Accidents (Module 78): accidents in previous three months that resulted in seeing a doctor or going to hospital; where accident happened; whether saw a GP or went straight to hospital. For accidents involving either the respondent or other household member, that resulted in a GP being seen, details of items of equipment involved in the accident were recorded. Risk Behaviour (Module 94): perceived risk of, and experience of: heart disease; being mugged; being involved in a road accident; cancer or lung cancer; having home burgled; bronchitis; winning a large sum of money. Perceived risk of a smoker dying of smoking related disease as opposed to being murdered or killed in a road accident. World AIDS Day (Module 98): Awareness of World AIDS Day; sources of information. Contraception (Module 106): method of birth control used and reasons for choice; changes in methods used; views on reliability of methods; the use of Family Planning Clinics; awareness of emergency methods for use after intercourse has taken place; views on contraceptive implants. Workplace Accidents (Module 128): accidents resulting in an injury at work or in the course of work; amount of time not able to work as a result of accident. Smoking (Module 130): whether smokes cigarettes now or has ever smoked; how many cigarettes smoked; type of cigarettes smoked (filter, non-filter or hand-rolled); pipe or cigar smoking; whether would like to give up smoking and reasons; how many times tried to give up smoking, or succeeded in giving up smoking; advice on smoking received from doctor or health worker; whether partner smokes and attitudes to this; attitudes to tobacco advertising, sponsoring by tobacco companies and taxation on cigarettes; perceived risks associated with smoking and passive smoking; attitudes to smoking restrictions in public places.

The survey Epidemiological Survey on Substance Abuse in Germany 2018 (ESA) is a representative survey on the use and abuse of psychoactive substances among adolescents and adults aged 18 to 64 years, which has been conducted regularly nationwide since 1980. The data collection took place between March and July 2018 and was conducted by infas Institut für angewandte Sozialwissenschaft GmbH on behalf of the IFT, Institute for Therapy Research in Munich. The nationwide study was conducted in a mixed-mode design as a standardised telephone survey (CATI: Computer Assisted Telephone Interview), as a written-postal survey (PAPSI: Paper and Pencil Self Interview) and as an online survey. The study is financially supported by the Federal Ministry of Health. The survey covered 30-day, 12-month and lifetime prevalence of tobacco use (tobacco products as well as shisha, heat-not-burn products and e-cigarettes), alcohol, illicit drugs and medicines. For conventional tobacco products, alcohol, selected illicit drugs (cannabis, cocaine and amphetamines) and medications (painkillers, sleeping pills and tranquillisers), additional diagnostic criteria were recorded with the written version of the Munich Composite International Diagnostic Interview (M-CIDI) for the period of the last twelve months. Furthermore, a series of socio-demographic data, the physical and mental state of health, nutritional behaviour, mental disorders as well as modules on the main topics of children from families with addiction problems, reasons for abstinence in the field of alcohol and the perception or knowledge of the health risk posed by alcohol were recorded. Physical and mental health status: self-assessment of health status; self-assessment of mental well-being; chronic illnesses; frequency of physical problems or pain without clear explanation, anxiety attack / panic attack, frequent worries, strong fears in social situations, strong fears of public places, means of transport or shops, strong fears of various situations, e.g. use of lifts, tunnels, aeroplanes as well as severe weather, sadness or low mood, loss of interest, tiredness or lack of energy, unusually happy, over-excited or irritable, stressful traumatic events, psychiatric, psychological or psychotherapeutic treatment in the last 12 months; physical activity and diet in the last three months: frequency of physical activity (moving from place to place, recreational sports, work-related physical activity) per week; duration of physical activity; consumption of selected foods (low-fat dairy products, raw vegetables, fresh salads, herbs, fresh fruit, cereal products, herbal tea or fruit tea); illness caused by excessive alcohol consumption. 2. Medication use: type of medication use (painkillers, sleeping pills, tranquilizers, stimulants, appetite suppressants, antidepressants, neuroleptics and anabolic steroids) in the last 12 months; frequency of use of painkillers, sleeping pills, tranquilizers, stimulants, appetite suppressants, antidepressants and neuroleptics in the last 30 days and respective prescription by a physician; use of painkillers, sleeping pills or tranquilizers in the last 12 months; tendencies towards dependence: In the last 12 months, the following were asked: significant problems related to the use of painkillers, sleeping pills and tranquillisers (neglect of household and children, poor performance, injury-prone situations while under the influence of medication, unintentional injuries such as accidents or falls, legal problems, accusations from family or friends, broken relationship, financial difficulties, physically attacking or hurting someone, use in larger quantities or for longer periods than prescribed or intended by the doctor, discomfort when stopping the medication. discomfort when stopping the medication and then continuing to take the medication to avoid discomfort, higher doses required for desired effect or weakened effect, unsuccessful attempts to reduce or stop medication use, large amount of time required to obtain medication or recover from effects, restriction of activities, taking medication despite knowledge of harmful effects, craving for medication so strong that resisting or thinking otherwise was not possible. 3. Smoking: smoking status; smoking behaviour: smoked more than 100 cigarettes, cigars, cigarillos, pipes in total during lifetime; type of tobacco use (cigarettes, cigars, cigarillos, pipe); age of initiation of tobacco use; time of last tobacco use; specific number of days in the last month on which cigarettes (or cigars, cigarillos or pipes) were smoked and average number smoked per day; average daily consumption of 20 or more cigarettes (or 10 cigarillos, 7 pipes, 5 cigars) in the last 12 months; smoking behaviour in the last 12 months (had to smoke more than before to get the same effect, effect of smoking decreased, smoked much more than intended, tried unsuccessfully to cut down or quit smoking for a few days, chain smoker, gave up important activities because of smoking, continued to smoke during serious illness, smoking interfered with work, school or housework, smoked in situations where there was a high risk of injury, continued to smoke even though it made other people angry or unhappy, unable to resist strong cravings for tobacco, unable to think of anything else because of strong cravings for tobacco); physical or mental health problems in the last 12 months due to smoking; continued to smoke in spite of physical or mental health problems; health problems due to smoking cessation in the last 12 months (low mood, insomnia, irritability/annoyance, restlessness, difficulty concentrating, slow heartbeat, weight gain); started smoking again to avoid complaints; serious attempts to stop smoking in the last 12 months; successful attempt to quit smoking; ever used shisha (hookah), a Neat-Not-Burn product or an e-cigarette, e-shisha, e-pipe, e-cigar and time of last use; age at first use of e-cigarette/e-cigar/e-shisha/e-pipe and frequency of use in the last 30 days; use of e-cigarettes/e-cigars/e-shishas/e-pipes with or without nicotine. 4. Alcohol consumption: age at first glass of alcohol; alcohol consumption at least once a month; age of onset of regular alcohol consumption; alcohol excesses (binge drinking) in the past and frequency of alcohol excesses in the last 12 months; age at first alcohol excess; time of last alcohol consumption; total number of days with alcohol consumption in the last 30 days or 12 months; concrete information on the average amount of beer, wine/sparkling wine and mixed drinks containing alcohol (alcopops, long drinks, cocktails or punch) consumed in the last 30 days or 12 months. 12 months; concrete information on the average amount of beer, wine/sparkling wine, spirits and mixed drinks containing alcohol (alcopops, long drinks, cocktails or punch) consumed in the last 30 days or in the last 12 months; number of days with consumption of at least five glasses of alcohol in the last 30 days or 12 months; problems caused by alcohol in the last 30 days or 12 months; number of days with consumption of at least five glasses of alcohol in the last 30 days or 12 months. 12 months; problems caused by alcohol in the last 12 months (significant difficulties at work, school or home, situations involving risk of injury, trouble with the police, accusations from family or friends, broken relationship, financial difficulties, physically attacking or hurting someone); alcohol consumption behaviour in the last 12 months (had to drink more than before to get the same effect, effect of alcohol consumption decreased, drank much more than intended, tried unsuccessfully to drink less alcohol or to stop drinking altogether, drank a lot of alcohol over several days, been drunk or suffered from the effects of alcohol, gave up important activities because of alcohol, could not resist strong craving for alcohol, could not think of anything else because of strong craving for alcohol); symptoms after alcohol withdrawal (trembling, insomnia, anxiety, sweating, hallucinations (seizure), nausea, vomiting, urge to move, rapid heartbeat); drank alcohol to avoid such complaints; physical illnesses or mental problems related to alcohol in the last 12 months; alcohol consumption despite physical or mental problems; increased cancer incidence in the last 12 months; alcohol consumption in spite of physical or mental problems. increased cancer risk due to alcohol consumption (stomach cancer, ovarian cancer, breast cancer, mouth and oesophagus cancer, brain tumour, bowel cancer, liver cancer, bladder cancer); alcohol consumption in the last 30 days; personal reasons for abstaining from alcohol (alcohol causes people to lose control, condition of illness worsens due to alcohol, parents had an alcohol problem, family is against alcohol consumption, alcohol consumption is against my spiritual/religious attitude, I do not like the taste and/or smell of alcohol, own pregnancy or partner´s pregnancy). 5. Drug use: drug experience with cannabis (hashish, marijuana), stimulants, amphetamines, ecstasy, LSD, heroin, other opiates such as e.g. codeine, methadone, opium, morphine), cocaine, crack, sniffing substances and mushrooms as intoxicants or never tried any of these drugs before; ever used substances that imitate the effect of illegal drugs (legal highs, research chemicals, bath salts, herbal mixtures or new psychoactive substances (NPS); used such legal substances in the last 12 months; form of substances consumed (herbal mixtures for smoking, powders, crystals or tablets as well as liquids); generally tried drugs; frequency of drug use in total, in each case related to cannabis (hashish, marijuana), stimulants, amphetamines, ecstasy, LSD, heroin, other opiates, cocaine, crack cocaine, sniffing substances, mushrooms resp. Legal highs, research chemicals, bath salts, herbal mixtures, NPS; time of last use of any of the above drugs (in the

Erfahrungen beim Kauf ausländischer Produkte, Einstellung zum Rauchen und Möglichkeiten zur Krebsvorsorge. Themen: Registrierung des Befragten im Wahlregister; Politikinteresse; eigene Meinungsführerschaft; Einstellung zur Vereinigung Europas; Beurteilung der Mitgliedschaft deseigenen Landes in der EU. 1. Kauf ausländischer Produkte: Art und Umfang des Erwerbs von Produkten sowie Dienstleistungen aus anderen EU-Ländern; Zufriedenheit mit den gekauften ausländischen Waren; im Falle von Reklamationen: Lösung der aufgetretenen Probleme. 2. Rauchgewohnheiten: Täglicher Zigarettenkonsum; Präferenz von leichten Zigarettenmarken; erhöhter Zigarettenkonsum nach dem Wechsel von normalen auf leichte Zigarettenmarken; Wunsch nach Beendigung des Rauchens bzw. Reduktion des Zigarettenkonsums(Split: im zweiten Falle wurde anstatt nach dem Wunsch nach der Absicht gefragt); Zeitpunkt der Beendigung des Rauchens(bei ehemaligen Rauchern); Inanspruchnahme von Medikamenten, Hypnose oder Akupunktur zur Beendigung des Rauchens; Wiederaufnahme des Zigarettenkonsums und Gründe dafür; Intervalle zwischen den Perioden der Tabakabstinenz; Vermutungen über den Zusammenhang von Werbung sowie Tabakkosten und dem allgemeinen Zigarettenkonsum; Einstellung zu einer Reglementierung der Werbung für Zigaretten und Tabak; vermutete Ausrichtung der Tabakwerbung auf junge Menschen; vermuteter Zusammenhang zwischen dem Tabakkonsum und der Werbung für Produkte, die den gleichen Handelsnamen wie Tabakprodukte tragen; Einstellung zum absoluten Verbot von direkter und indirekter Werbung für Zigaretten und Tabak; Anwesenheit von Rauchern zu Hause, im Freundeskreis, am Arbeitsplatz und an anderen Orten; Einstellung zu einem Rauchverbot in öffentlichen Institutionen; erwartete Respektierung eines solchen Rauchverbots durch die Raucher; Präferenz für Raucherzonen bzw. Nichtraucherzonen am Arbeitsplatz; Einstellung zu einer individuellen Lösung unter Arbeitskollegen oder für eine Managemententscheidung; Existenz von Raucherregelungen am eigenen Arbeitsplatz und perzipierte Einhaltung dieser Regeln; Bekanntheitsgrad von Antiraucherorganisationen; mögliche Aufgaben solcher Antiraucherorganisationen; Kenntnis von Aktionen der EU zur Reduzierung des Tabakkonsums. 3. Krebs: Präferenz für nationale oder europäische Bemühungen beim Kampf gegen Krankheiten; Möglichkeiten zur Krebsvermeidung durch entsprechende Vorsorge; Beurteilung von ausgewählten Konsumgewohnheiten als krebserregend; vermuteter Zusammenhang von Sonnenbaden und Krebs; Einstellung zur Vorsorgeuntersuchung bei Frauen zur Früherkennung von Brustkrebs; eigene Beteiligung an solchen Vorsorgeuntersuchungen; Todesfälle aufgrund von Krebserkrankungen im Bekanntenkreis; Kenntnis des europäischen Krebsbekämpfungsprogramms. 4. Sonstiges: Selbsteinstufung auf einem Links-Rechts-Kontinuum; Religiosität; Selbsteinstufung der Klassenzugehörigkeit. Demographie: Nationalität; Selbsteinschätzung auf einem Links-Rechts-Kontinuum; Familienstand; Alter bei Ende der Ausbildung; Geschlecht; Alter; Anzahl der Personen im Haushalt; Kinder unter 15Jahren; Selbsteinschätzung der sozialen Position; Religionszugehörigkeit; Kirchgangshäufigkeit; Haupteinkommensquelle des Haushalts; berufliche Position; monatliches Haushaltseinkommen. Zusätzlich verkodet wurden: Interviewdatum und Interviewbeginn; Interviewdauer; Anzahl der beim Interview anwesenden Personen; Kooperationsbereitschaft des Befragten; Ortsgröße; Region; Postleitzahl; Intervieweridentifikation; Telefonbesitz. In Luxemburg, Belgien und Finnland: Interviewsprache. Experiences in purchasing foreign products, attitude to smoking and opportunities for cancer check-up. Topics: registration of respondent in election register; interest in politics; personal opinion leadership; attitude to unification of Europe; judgment on membership of one´s own country in the EU. 1. purchase of foreign products: manner and extent of purchase of products as well as services from other EU countries; satisfaction with foreign products purchased; in case of complaints: solving problems encountered. 2. smoking habits: daily use of cigarettes; preference for light brands of cigarettes; increased use of cigarettes after change from normal to light brands of cigarettes; desire to quit smoking or reduce use of cigarettes (split: in the second case the question was about intent rather than desire); time of quitting smoking (for former smokers); utilization of medications, hypnosis or acupuncture to quit smoking; resumption of use of cigarettes and reasons for this; intervals between the periods of tobacco abstinence; assumptions about the connection of advertising as well as tobacco costs and the general use of cigarettes; attitude to regimentation of advertising for cigarettes and tobacco; assumed orientation of tobacco advertising on young people; suspected relationship between use of tobacco and advertising for products that have the same brand name as tobacco products; attitude to absolute prohibition of direct and indirect advertising for cigarettes and tobacco; presence of smokers at home, in one´s circle of friends, at work and at other places; attitude to a smoking ban in public institutions; expected observance of such a smoking ban by smokers; preference for smoking zones or no-smoking zones at work; attitude to an individual solution among colleagues or for management decision; existence of smoking regulations at one´s place of work and perceived observance of these rules; degree of familiarity of no-smoking organizations; possible duties of such no-smoking organizations; knowledge of actions of the EU to reduce use of tobacco. 3. cancer: preference for national European efforts in the fight against illnesses; opportunities to avoid cancer through corresponding precaution; judgment on selected consumer habits as causing cancer; assumed connection between sun-bathing and cancer; attitude to medical check-up for women for early diagnosis of breast cancer; personal participation in such medical check-ups; deaths due to cancer in one´s circle of friends; knowledge about the European program to combat cancer. 4. Miscellaneous: self-classification on a left-right continuum; religiousness; self-classification of class affiliation.