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The Annual Health Survey (AHS), conducted by the Government of India between July 2010 and May 2013, investigates maternal and child health in nine states: Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttarakhand, and Uttar Pradesh. These states constitute about 70 percent of neonatal deaths in India and about one-in-five neonatal deaths globally. The AHS consists of a three-round panel that interviewed over 4 million households in each round, as well as a one-time Clinical, Anthropometric, and Bio-Chemical Survey (CAB). The data were originally released to the public in 2015 as a set of 45 .csv files. The .csv files are included in a restricted-use zipped package as part of the ICPSR release (see dataset 21).

The survey focused on topics such as household composition, caste, fertility, family planning, pre- and post-natal care, breastfeeding, infant mortality, illness, disease, disability, and health care practices. Demographic information includes sex, age, education, occupation, marital status, household size, and religion. The CAB files contain biometric data including but not limited to height, weight, blood pressure, hemoglobin, pulse, and blood glucose.

Potential data users should note that the public-use and restricted-use versions of the datasets are the same except for the masking of day component variables for certain dates in the public-use versions of the files (please see the Description of Variables section for full details). Therefore, only researchers with a limited set of research questions that require full birth, marriage, and death dates will need to apply for the restricted-use versions of the data files.

Additionally, because the final data files are very large and potentially very time consuming to analyze on personal computers, researchers have the option to download ten-percent samples of each file (see datasets 3, 4, 7, 8, 11, 12, 15, 16, 19, and 20). These samples contain the same variables as the original files but only ten percent of the records. The samples were determined by taking a randomly selected ten percent of households in each district. P.I. codebooks were not produced for these samples. Please note that the ten-percent samples for each dataset were selected independently, so it is not advised to merge across datasets within the AHS using these samples, as the match rates will be very low.

Asthma is one of the nation's most common and costly chronic conditions, affecting over 38 million Americans at some time in their lives. Managing asthma requires a long term, multifaceted approach, including patient education, behavior changes, asthma trigger avoidance, pharmacological therapy, and frequent medical follow-up. This study provides asthma data available at the state and local level to direct and evaluate interventions undertaken by asthma control programs located in the state health departments. Improved tracking for asthma is critical for planning and evaluating efforts to reduce the health burden from the disease.

The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based system of health surveys that collects information on health risk behaviors, preventive health practices, and health care access primarily related to chronic disease and injury. For many states, the BRFSS is the only available source of timely, accurate data on health-related behaviors. BRFSS was established in 1984 by the Centers for Disease Control and Prevention (CDC); currently data are collected monthly in all 50 states, the District of Columbia, Puerto Rico, the United States Virgin Islands, and Guam. More than 350,000 adults are interviewed each year, making the BRFSS the largest telephone health survey in the world. States use BRFSS data to identify emerging health problems, establish and track health objectives, and develop and evaluate public health policies and programs. The BRFSS is a cross-sectional telephone survey conducted by state health departments with technical and methodological assistance provided by CDC. States conduct monthly telephone surveillance using a standardized questionnaire to determine the distribution of risk behaviors and health practices among adults. Responses are forwarded to CDC, where the monthly data are aggregated for each state, returned with standard tabulations, and published at the year's end by each state. The BRFSS questionnaire was developed jointly by CDC's Behavioral Surveillance Branch (BSB) and the states. Data derived from the questionnaire provide health departments, public health officials, and policymakers with necessary behavioral information. When combined with mortality and morbidity statistics, these data enable public health officials to establish policies and priorities and to initiate and assess health promotion strategies. Demographic variables include race, age, sex, education level, marital status, employment status, and income level.

CCPC's long term vision is to use pragmatic comparative effectiveness methods, linked to an extensive primary care practice data repository, to establish evidence about best practices for complex real world patients and deliver appropriate, real-time decision support at point of service for primary care practitioners (PCPs) in a way that will account for individualized management of conditions and choice of treatments in order to provide optimal care.

The primary aim of BICEP was to advance analytical methods of observational Comparative Effectiveness Research (CER) to support evidentiary needs of primary care practitioners in answering important questions related to care of patient populations with Multiple Complex Conditions (MCCs).

The secondary aim of BICEP was to conduct a pilot study to demonstrate the feasibility and value of using the analytic methods for conducting CER among complex patients.

BICEP sought to answer the following clinical research questions: In adults with Type 2 Diabetes Mellitus (T2DM) coupled with additional chronic diseases,

1. What is the comparative effectiveness of T2DM medications in achieving glycemic control?
2. What is the comparative effectiveness of T2DM medications on intermediate outcomes, adverse events, side effects, tolerability?
3. Does the effectiveness and safety of the diabetic treatment options differ across subgroups of patients based on patient demographic characteristics, complex co-morbidities, or the use of other concurrent therapies?

The Common Cold Project began in 2011 with the aim of creating, documenting, and archiving a database that combines final research data from 5 prospective viral-challenge studies that were conducted over the preceding 25 years. The data collection includes the British Cold Study (BCS), which focused on psychological stress; the Pittsburgh Cold Study 1 (PCS1), which built on the BCS; the Pittsburgh Cold Study 2 (PCS2), which examined childhood socioeconomic status and personality; the Pittsburgh Mind-Body Center Cold Study (PMBC), which recorded detailed mood and behavior data over 14 days; the Pittsburgh Cold Study 3, which focused on childhood environment; the Pittsburg Cold Study 3 Social Rhythm Data (PCS3-SRM), which recorded daily interview data of mood, health behavior, and social interaction; and finally the 5 Study Aggregate, which was designed to facilitate analysis across studies. These studies assessed predictor (and hypothesized mediating) variables in healthy adults aged 18 to 55 years, experimentally exposed them to a virus that causes the common cold, and then monitored them for development of infection and signs and symptoms of illness. Standard control variables (covariates) included age, sex, socioeconomic status (SES), race/ethnicity, body mass index (BMI), season of the year, and specific antibody (Ab) titer to the challenge virus (specific immunity). Three of the studies also include daily evening interviews (conducted for 6 or 14 days before exposure to a virus and assessing daily social interactions, mood, health behaviors, and physical symptoms; and daily diaries collected during the quarantine period (1 day before and 5-6 days after viral exposure), including cold-specific and nonspecific symptoms, mood, and health behaviors. These data accompany datasets four, five, and seven.

Many common variables were collected across 2 or more studies, and all 5 studies include measures of upper respiratory infectious illness (URI) (e.g., infection, signs and symptoms of a cold, local [nasal mucosa] release of pro- and anti-inflammatory cytokines). Data were also collected on a broad assortment of health-related outcomes not specific to URI including anthropomorphic measures (such as body mass index and waist circumference), complete blood cell counts and differentials, measures of functional immunity, self-reported and objectively assessed health behaviors (smoking, alcohol consumption, physical activity, diet, and sleep), measures of functional physiology across several biological systems (such as pulmonary function, resting cardiovascular function, endocrine, and metabolic activity), and self-reported assessments of physical and psychological health and well-being. In addition, the 5 studies collected data on an extensive range of demographic, health behavior, psychological and social variables including adult SES and subjective social standing, childhood SES, major stressful life events and perceived stress, personality, psychological expectations and beliefs, social relationships, and state and trait affect.

For people with serious chronic conditions, healthcare that defaults to all available treatments without considering patient preferences risks harms that may exceed benefits. Advance care planning (ACP) has the potential to align healthcare with what is important to patients and maximize quality of life. While primary care is where most people receive most of their care, engaging patients in ACP is not routine in primary care given competing demands and limited resources. Primary care clinicians, patients, and families agree that it is preferred to make plans before there is a medical crisis. The research team's goal was to make ACP routine in primary care and to "move it upstream" so that it included improving the quality of the last years of life as well as respecting wishes for end of life care.

This study included a comparative effectiveness trial of team-based versus individual clinician-focused ACP in primary care practices. The research team adapted Ariadne Labs' Serious Illness Care Program (SICP) and aimed to determine if a team approach produces better patient outcomes and explore factors influencing implementation of ACP across practices.

Seven practice-based research networks (PBRNs) in the United States and Canada randomized their primary care practices to team-based or individual clinician-focused versions of SICP. Team members and clinicians completed training, and implementation was supported through practice facilitation. Consented patient participants completed a baseline survey after initial conversations and follow-up surveys at 6 and 12 months later. Forty practices (21 team, 19 clinician) completed training and referred patients to the study. Half of the practices were rural, 80 percent were family medicine, and 33 percent were medical residency training sites. 535 healthcare staff completed training. Both arms trained primary care providers; the team arm also trained nurses, medical assistants, and other roles. 1,321 patients and care partners were referred; and 917 consented and were enrolled (455 from team practices, 462 from clinician). Data from 802 patients were included in the primary analyses. Qualitative implementation data was collected during practice facilitation and from practice interviews.

This collection includes quantitative data collected from primary care practices (DS1) and team members and clinicians (DS2) from study sites located in the United States.

The Comprehensive Post-Acute Stroke Services (COMPASS) Study is a pragmatic cluster-randomized clinical trial that evaluated the real-world effectiveness of the COMPASS transitional care (COMPASS-TC) model compared to usual care among adult stroke and transient ischemic attack (TIA) patients discharged home between 2016 and 2018. In Phase 1, 40 North Carolina hospital units were randomized 1:1 to the COMPASS-TC intervention or usual care, stratified by stroke patient volume and stroke center certification. In Phase 2, hospitals randomized to usual care crossed over to implement COMPASS-TC, and hospitals randomized to the intervention sustained COMPASS-TC. The intervention was patient-centered and assessed social and functional determinates of health to inform individualized care plans for secondary prevention, recovery, and referrals to services and community-based resources. COMPASS-TC was consistent with Centers for Medicare and Medicaid Services (CMS) TC management reimbursement requirements.

The primary outcome was functional status (Stroke Impact Scale-16; SIS-16) at 90 days; secondary outcomes were mortality, disability, medication adherence, depression, cognition, self-rated health, fatigue, care satisfaction, home blood pressure monitoring, falls, and caregiver strain. Telephone interviewers, blinded to treatment assignment, assessed these outcomes at 90 days.

Exposure to traumatic events is a common experience for children and adolescents. Accurate early assessment of acute stress responses can help predict risk for longer term sequelae and can guide secondary prevention to reduce the incidence and severity of post-traumatic stress disorder (PTSD) after trauma exposure.

The goal of this project was to develop a practical self-report measure of acute stress disorder (ASD) for children and adolescents, and to provide initial evidence as to its reliability and validity. The specific aims of the project were to:

• Aim 1: Establish the content validity of a pilot Child ASD measure for ages 8 to 17, based on expert review and youth feedback.
• Aim 2: In a sample of recently injured children (n=176), assess the psychometric properties of the measure: internal consistency, test-retest reliability, convergent and discriminant validity with other measures and other reporters.
• Aim 3: Provide initial data regarding the predictive validity of the Child ASD measure in relation to later PTSD development in the same sample of children.

According to the World Health Organization, palliative care is "an approach that improves the quality of life of patients and their families facing the problems associated with life-threatening illness, through the prevention and relief of suffering by means of early identification and impeccable assessment and treatment of pain and other problems, physical, psycho-social and spiritual." The goal of the study was to generate comparative effectiveness research evidence to support the delivery of coordinated, community-based palliative care that effectively implements care plans consistent with the goals and preferences of older adults with advanced illness and their caregivers.

This study included a pragmatic, two-arm, multi-site randomized controlled trial of older adults (50+ years) with either poor prognosis cancer or end-stage organ failure who were recruited during an emergency department (ED) visit, along with their informal caregivers, to compare nurse-led telephonic case management to facilitated, outpatient specialty palliative care on: 1) quality of life in patients, 2) loneliness, 3) healthcare use in the 12 months following enrollment, 4) symptom burden, 5) caregiver strain, 6) caregiver quality of life, and 7) bereavement.

Patients may respond differently to the same treatment due to differences in personal traits such as age, gender, or the number and type of health problems they have. Researchers use statistical methods to predict how well a treatment may work for patients based on their personal traits. But current methods may not work well if patients have many health problems or are taking other medicines.

In this project, the research team created new methods to figure out which patient traits are related to treatment benefits to help doctors and patients understand the likely treatment benefits for individual patients.

To access the methods, software, and R package, please visit the personalized CRAN webpage and personalized GitHub

The Mortality in Correctional Institutions (MCI) collection was collected annually by the Bureau of Justice Statistics (BJS) from 2000 to 2019 from the approximately 2,800 local adult jail jurisdictions nationwide, and from 2001 to 2019 from the 50 state departments of corrections. The MCI obtained national, state, and incident-level data on persons who died while in the physical custody of state prisons and local jails. The MCI began in 2000 under the Death in Custody Reporting Act of 2000 (P.L. 106-297), and continued after the law was reauthorized in 2014. BJS used MCI data to track national trends in the number and causes (or manners) of deaths occurring in state prison or local jail custody. The MCI collected data about the characteristics of the decedents as well as circumstances surrounding the death, including the cause, time and location where the death occurred, and information on whether an autopsy was conducted and the availability of results to the respondent. This data collection is comprised of two datasets (one prison, one jail) that contain all deaths from 2000-2019 with the illness (also known as natural) deaths assigned ICD-10 diagnosis codes when possible. Data on executions and deaths of persons in the custody of federal, state, and local law enforcement agencies not acting in a jail capacity were considered out-of-scope for MCI. More details on the collection, survey instruments, and publications using the MCI data can be found at the BJS website: Mortality in Correctional Institutions (MCI) (Formerly Deaths in Custody Reporting Program (DCRP)) | Bureau of Justice Statistics.

The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999 the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The surveys examine a nationally representative sample of approximately 5,000 persons each year. These persons are located in counties across the United States, 15 of which are visited each year.

For NHANES 2003-2004, there were 12,761 persons selected for the sample, 10,122 of those were interviewed (79.3 percent) and 9,643 (75.6 percent) were examined in the mobile examination centers (MEC). Many of the NHANES 2003-2004 questions were also asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2002. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. As in past health examination surveys, data were collected on the prevalence of chronic conditions in the population. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey. Risk factors, those aspects of a person's lifestyle, constitution, heredity, or environment that may increase the chances of developing a certain disease or condition, were examined. Data on smoking, alcohol consumption, sexual practices, drug use, physical fitness and activity, weight, and dietary intake were collected. Information on certain aspects of reproductive health, such as use of oral contraceptives and breastfeeding practices, were also collected. The diseases, medical conditions, and health indicators that were studied include: anemia, cardiovascular disease, diabetes and lower extremity disease, environmental exposures, equilibrium, hearing loss, infectious diseases and immunization, kidney disease, mental health and cognitive functioning, nutrition, obesity, oral health, osteoporosis, physical fitness and physical functioning, reproductive history and sexual behavior, respiratory disease (asthma, chronic bronchitis, emphysema), sexually transmitted diseases, skin diseases, and vision. The sample for the survey was selected to represent the United States population of all ages. Special emphasis in the 2003-2004 NHANES was on adolescent health and the health of older Americans. To produce reliable statistics for these groups, adolescents aged 15-19 years and persons aged 60 years and older were over-sampled for the survey. African Americans and Mexican Americans were also over-sampled to enable accurate estimates for these groups. Several important areas in adolescent health, including nutrition and fitness and other aspects of growth and development, were addressed. Since the United States has experienced dramatic growth in the number of older people during the twentieth century, the aging population has major implications for health care needs, public policy, and research priorities. NCHS is working with public health agencies to increase the knowledge of the health status of older Americans. NHANES has a primary role in this endeavor. In the examination, all participants visit the physician who takes their pulse or blood pressure. Dietary interviews and body measurements are included for everyone. All but the very young have a blood sample taken and see the dentist. Depending upon the age of the participant, the rest of the examination includes tests and procedures to assess the various aspects of health listed above. Usually, the older the individual, the more extensive the examination. Some persons who are unable or unwilling to come to the examination center may be given a less extensive examination in their homes.

Demographic data file variables are grouped into three broad categories: (1) Status Variables: provide core information on the survey participant. Examples of the core variables include interview status, examination status, and sequence number. (Sequence number is a unique ID assigned to each sample person and is required to match the information on this demographic file to the rest of the NHANES 2003-2004 data). (2) Recoded Demographic Variables: these variables include age (age in months for persons through age 19 years, 11 months; age in years for 1- to 84-year-olds, and a top-coded age group of 85 years of age and older), gender, a race/ethnicity variable, current or highest grade of education completed, (less than high school, high school, and more than high school education), country of birth (United States, Mexico, or other foreign born), Poverty Income Ratio (PIR), income, and a pregnancy status variable (adjudicated from various pregnancy related variables). Some of the groupings were made due to limited sample sizes for the two-year data set. (3) Interview and Examination Sample Weight Variables: sample weights are available for analyzing NHANES 2003-2004 data. For a complete listing of survey contents for all years of the NHANES see the document -- Survey Content -- NHANES 1999-2010.