Supporting Online Material for



Supplemental Online Materials forPerceived Physical Activity and Mortality: Evidence from Three Nationally Representative U.S. SamplesOctavia H. ZahrtAlia J. CrumStanford UniversityAuthor NoteOctavia H. Zahrt, Department of Organizational Behavior, Stanford Graduate School of Business, Stanford University; Alia J. Crum, Department of Psychology, Stanford University.Correspondence concerning this article should be addressed to Octavia H. Zahrt, Stanford Graduate School of Business, 655 Knight Way, Stanford, CA 94305. E-mail: zahrt@stanford.edu; or Alia J. Crum, Stanford University, 450 Serra Mall, Stanford, CA 94305, Email: crum@stanford.eduContents:Materials and MethodsResultsTable S1Table S2Table S3Supplemental ReferencesMaterials and MethodsData Source and Study SamplesThe data originate from the National Health Interview Survey (NHIS) and the National Health and Nutrition Examination Survey (NHANES), two cross-sectional surveys conducted by the National Center for Health Statistics (NCHS). This study used the 1990 wave of NHIS, the 1999-2002 waves and the 2003-2006 waves of NHANES. The main report includes further details.MeasuresOutcome Measure: Mortality. Mortality was measured as death from any cause between the respondent’s interview date and December 31, 2011. Information on deaths among respondents was obtained from the National Death Index (NDI). Data from the NHIS and NHANES samples were linked to 2011 NDI mortality data by the NCHS, using respondent identifying information (social security number, first name, middle initial, last name, month of birth, day of birth, year of birth, sex, father’s surname, state of birth, race, state of residence, marital status) ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "accessed" : { "date-parts" : [ [ "2015", "1", "1" ] ] }, "author" : [ { "dropping-particle" : "", "family" : "National Center for Health Statistics", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2016" ] ] }, "title" : "NCHS Data Linked to NDI Mortality Files", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(National Center for Health Statistics, 2016b)", "plainTextFormattedCitation" : "(National Center for Health Statistics, 2016b)", "previouslyFormattedCitation" : "(National Center for Health Statistics, 2016b)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(National Center for Health Statistics, 2016b). Respondents in the NHIS and NHANES samples were then linked to mortality information using their NHIS public-use ID or NHANES Respondent Sequence Number, respectively.Independent Measures. The main independent measure of interest was perceived physical activity compared to others. Additionally, covariates measuring actual physical activity and other health behaviors, health status, socioeconomic and demographic factors were included. Tables S1a, S1b, and S1c show the distribution of these characteristics in the 1990 NHIS, 1999-2002 NHANES, and 2003-2006 NHANES samples, respectively. In a few instances, the operationalization of a construct varies between the three samples, due to differences in survey design, as described below.Physical Activity and Fitness. Perceived physical activity relative to peers. This measure is the critical independent variable of this study. NHIS: Respondents were asked to evaluate their level of physical activity relative to other persons their age: “Would you say that you are physically more active, less active, or about as active as other persons your age?” Depending on their response, NHIS respondents were then asked if they were “a lot more or a little more”, or “a lot less or a little less” physically active. We combined these two questions into one measure of relative perceived physical activity (levels: a lot more active/ a little more active/ about as active/ a little less active/ a lot less active). NHANES: Respondents were asked: “Compared with most [men/ women] your age, would you say that you are more active/ less active/ or about the same?”, resulting in a three-level factor.Actual physical activity level. Respondents indicated which of 24 (NHIS) or 48 (1999-2002 NHANES) leisure-time sports, exercises, and physically active hobbies they had done in the recent past (NHIS: past 14 days: NHANES: past 30 days). For each activity they had done, respondents also reported frequency, average duration in minutes, and intensity (NHIS: small, moderate, large, or no increase in heart rate and breathing; NHANES: moderate or vigorous intensity). From this information, actual physical activity level was determined following a procedure recommended by the National Center for Health Statistics ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "accessed" : { "date-parts" : [ [ "2016", "6", "18" ] ] }, "author" : [ { "dropping-particle" : "", "family" : "National Center for Health Statistics", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2016" ] ] }, "title" : "Leisure-time Physical Activity Recodes", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(National Center for Health Statistics, 2016a)", "plainTextFormattedCitation" : "(National Center for Health Statistics, 2016a)", "previouslyFormattedCitation" : "(National Center for Health Statistics, 2016a)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(National Center for Health Statistics, 2016a) and used in prior research ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1249/MSS.0b013e31821ece12", "ISSN" : "0195-9131", "author" : [ { "dropping-particle" : "", "family" : "Ainsworth", "given" : "Barbara E.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Haskell", "given" : "William L.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Herrmann", "given" : "Stephen D.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Meckes", "given" : "Nathanael", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Bassett", "given" : "David R.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Tudor-Locke", "given" : "Catrine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Greer", "given" : "Jennifer L.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Vezina", "given" : "Jesse", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Whitt-Glover", "given" : "Melicia C.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Leon", "given" : "Arthur S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Medicine & Science in Sports & Exercise", "id" : "ITEM-1", "issue" : "8", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "1575-1581", "title" : "2011 Compendium of Physical Activities", "type" : "article-journal", "volume" : "43" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Stephens", "given" : "T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Craig", "given" : "C L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Assessing Physical Fitness and Physical Activity in Population-Based Surveys", "editor" : [ { "dropping-particle" : "", "family" : "Drury", "given" : "Thomas F.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-2", "issued" : { "date-parts" : [ [ "1989" ] ] }, "page" : "401-432", "publisher" : "National Center for Health Statistics", "publisher-place" : "Hyattsville, MD", "title" : "Fitness and Activity Measurement in the 1981 Canada Fitness Survey", "type" : "chapter" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Ainsworth et al., 2011; Stephens & Craig, 1989)", "plainTextFormattedCitation" : "(Ainsworth et al., 2011; Stephens & Craig, 1989)", "previouslyFormattedCitation" : "(Ainsworth et al., 2011; Stephens & Craig, 1989)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Ainsworth et al., 2011; Stephens & Craig, 1989): First, the metabolic equivalent of task (MET) was assigned to each activity at each intensity level. The MET is a physiological measure expressing the rate of energy consumption, defined as the ratio of work metabolic rate during a specific physical activity to a reference metabolic rate. The reference metabolic rate, 1 MET, is considered as the resting metabolic rate (RMR) or the energy cost of a person at rest, and is set by convention to 1 MET≡1kcal(kg × h) ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1249/MSS.0b013e31821ece12", "ISSN" : "0195-9131", "author" : [ { "dropping-particle" : "", "family" : "Ainsworth", "given" : "Barbara E.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Haskell", "given" : "William L.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Herrmann", "given" : "Stephen D.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Meckes", "given" : "Nathanael", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Bassett", "given" : "David R.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Tudor-Locke", "given" : "Catrine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Greer", "given" : "Jennifer L.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Vezina", "given" : "Jesse", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Whitt-Glover", "given" : "Melicia C.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Leon", "given" : "Arthur S.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Medicine & Science in Sports & Exercise", "id" : "ITEM-1", "issue" : "8", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "1575-1581", "title" : "2011 Compendium of Physical Activities", "type" : "article-journal", "volume" : "43" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Ainsworth et al., 2011)", "plainTextFormattedCitation" : "(Ainsworth et al., 2011)", "previouslyFormattedCitation" : "(Ainsworth et al., 2011)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Ainsworth et al., 2011). Then, combining the number of times (n) a respondent had engaged in each activity in the past 14 days (30 days for NHANES), average duration (min) of the activity, and each activity’s MET value, average total energy expenditure in kilocalories per kilogram of body weight per day was computed: kcalkg × day =all activities n# of days × min60h × MET Finally, participants were classified as “inactive” [0 – 1.5 kcalkg × day], “moderately active” [1.5 – 3.0 kcalkg × day], or “very active” [≥ 3.0 kcalkg × day].In the 2003-2006 NHANES, actual physical activity was assessed by accelerometry data, as outlined in the main report.Amount of hard physical work required on job or in main daily activity (NHIS only). Two items assessed how much hard physical work was required on respondents’ job, or if they did not work a job, in their main daily activity (1 = a great deal – 4 = none). Health and health behavior factors. Perceived health. Respondents rated their general health on a 5-point scale (1 = excellent, 2 = very good, 3 = good, 4 = fair, 5 = poor).Disease burden. A detailed medical history was used to calculate disease burden as the sum of 5 diagnoses in NHIS (hypertension, diabetes, heart condition, stroke, high blood cholesterol) or 12 diagnoses in NHANES (heart attack, angina, coronary heart disease, congestive heart failure, high blood pressure, stroke, emphysema, chronic bronchitis, thyroid disease, liver condition, cancer or malignancy of any kind, diabetes). Smoking status. Respondents were classified by the NCHS as “current smokers” (smoked more than 100 cigarettes in life and still smoked at time of survey), “former smokers” (smoked more than 100 cigarettes in life, but did not smoke anymore at time of survey), or “never smokers” (smoked fewer than 100 cigarettes in life).Stress (NHIS only). Amount of stress experienced in the past year (a lot/ a moderate amount/ relatively little/ almost none).Mental health (NHANES only). NHANES respondents indicated whether they had seen mental health professional in the past 12 months.Illness bed days in past 12 months (NHIS only). Respondents indicated on how many days during the past 12 months illness or injury kept them in bed more than half of the day (none/1-7 days/ 8-30 days/ 31-180 days/ 181-365 days).Disability. Respondents reported if they were limited in any major activity (such as working or doing housework) by any disability or long-term health problem (NHIS: unable to perform major activity, limited in kind or amount of major activity, limited in other activities, not limited; NHANES: yes, no). Body Mass Index (BMI). BMI was calculated using the formula weight kgheight (m)2 for each respondent. Weight and height measurements were self-reported (NHIS) or recorded in person by trained examiners (NHANES). To account for the curvilinear relationship between BMI and mortality, BMI was coded into the standard categories ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1177/0956797615601103", "ISBN" : "10.1177/0956797615601103", "ISSN" : "1467-9280", "PMID" : "26420442", "abstract" : "Discrimination based on weight is a stressful social experience linked to declines in physical and mental health. We examined whether this harmful association extends to risk of mortality. Participants in the Health and Retirement Study (HRS; N = 13,692) and the Midlife in the United States Study (MIDUS; N = 5,079) reported on perceived discriminatory experiences and attributed those experiences to a number of personal characteristics, including weight. Weight discrimination was associated with an increase in mortality risk of nearly 60% in both HRS participants (hazard ratio = 1.57, 95% confidence interval = [1.34, 1.84]) and MIDUS participants (hazard ratio = 1.59, 95% confidence interval = [1.09, 2.31]). This increased risk was not accounted for by common physical and psychological risk factors. The association between mortality and weight discrimination was generally stronger than that between mortality and other attributions for discrimination. In addition to its association with poor health outcomes, weight discrimination may shorten life expectancy. ", "author" : [ { "dropping-particle" : "", "family" : "Sutin", "given" : "Angelina R", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Stephan", "given" : "Yannick", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Terracciano", "given" : "Antonio", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Psychological Science ", "id" : "ITEM-1", "issue" : "11 ", "issued" : { "date-parts" : [ [ "2015" ] ] }, "page" : "1803-1811", "title" : "Weight Discrimination and Risk of Mortality", "type" : "article-journal", "volume" : "26 " }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Sutin, Stephan, & Terracciano, 2015)", "manualFormatting" : "(e.g., Sutin, Stephan, & Terracciano, 2015)", "plainTextFormattedCitation" : "(Sutin, Stephan, & Terracciano, 2015)", "previouslyFormattedCitation" : "(Sutin, Stephan, & Terracciano, 2015)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(e.g., Sutin, Stephan, & Terracciano, 2015): underweight (BMI < 18.50 kg/m2), normal weight (18.50 kg/m2 ≤ BMI < 25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), obese (30 kg/m2 ≤ BMI < 40 kg/m2), morbidly obese (BMI > 40 kg/m2). Sociodemographic characteristics.Gender. Male or female.Age. Respondent’s age at the time of interview. For older adults, age was top coded by the NCHS to reduce the risk of disclosure at 99 years in NHIS and 85 years in NHANES.Race. Respondent’s self-reported race. NHIS: White, Black, Other. NHANES: Non-Hispanic White; Non-Hispanic Black; Other (Mexican American, Other Hispanic, Other Race Including Multi-Racial).Marital status. Respondents reported if they were married/ divorced or separated/ widowed/ never married.Education. Respondent’s self-reported highest grade of school completed or highest degree received. NHIS: Some high school or less/ high school diploma/ some college/ college graduate or more. NHANES: Some high school or less/ high school diploma (including GED)/ more than high school.Employment Status. Coded as employed/ unemployed/ out of labor force.Annual family income. For NHIS, family income with imputed missing values was obtained from the 1990 NHIS Imputed Annual Family Income Public Use File ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "author" : [ { "dropping-particle" : "", "family" : "National Center for Health Statistics", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2015" ] ] }, "title" : "NHIS Data, Questionnaires and Related Documentation", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(National Center for Health Statistics, 2015)", "manualFormatting" : "(S7)", "plainTextFormattedCitation" : "(National Center for Health Statistics, 2015)", "previouslyFormattedCitation" : "(National Center for Health Statistics, 2015)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(S7). Families were categorized into 27 income categories from “Less than $1,000” to “$50,000 and over”. In order to use income information as a continuous variable, we assigned each respondent the middle value of their income category (e.g., $1,500 for the “$1,000 - $2,000” category). For NHANES, family income was obtained from the DEMO survey component. Families were categorized into 11 categories from “$0 - $4,999” to “$75,000 and over”.Urbanicity (NHIS only). Determined from metropolitan statistical area (MSA) status from NHIS master records as urban (i.e., MSA central city or MSA non-central city) vs. rural (i.e., Non-MSA nonfarm or Non-MSA farm).Access to appropriate medical care. NHIS respondents were asked the following questions: “Is there a particular clinic, health center, doctor’s office, or other place that you usually go to when you are sick or need advice about your health?” and if yes, they were asked what kind of place it was—a doctor’s office, a hospital outpatient clinic, respondent’s home, hospital emergency room, company or industry clinic, health center, or other. Individuals who responded that they did not have a usual place of care they went to, or reported the emergency room as their usual place, were classified as not having access to appropriate medical care. The wording of the items in NHANES was slightly different, but the overall procedure and final measure was identical.Data AnalysisAll analyses were conducted using survival models. We investigated the association between respondents’ perceptions of their relative level of physical activity and mortality using Cox proportional hazards regression. Survival time in NHIS was determined using quarter and year of death given in the NCHS 2011 linked mortality files ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "accessed" : { "date-parts" : [ [ "2015", "1", "1" ] ] }, "author" : [ { "dropping-particle" : "", "family" : "National Center for Health Statistics", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2016" ] ] }, "title" : "NCHS Data Linked to NDI Mortality Files", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(National Center for Health Statistics, 2016b)", "plainTextFormattedCitation" : "(National Center for Health Statistics, 2016b)", "previouslyFormattedCitation" : "(National Center for Health Statistics, 2016b)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(National Center for Health Statistics, 2016b). Individuals who were assumed alive (hence not matched to NDI data) were right-censored to 87 quarters (the maximum time from interview quarter in 1990 until December 2011). Survival time in NHANES was determined using the ‘Person Months of Follow-up from Interview Date’ variable given in the NCHS 2011 linked mortality files, indicating the number of months the person survived after being interviewed in 1999-2002 or 2003-2006. Individuals who were assumed alive were right-censored to 153 months (the maximum time from interview quarter in 1999-2002 until December 2011) or to 108 months (the maximum time from interview quarter in 2003-2006 until December 2011). All survival analyses were conducted using the ‘survey’ package in R to account for the complex survey design ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Lumley", "given" : "Thomas", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Journal of Statistical Software", "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "2004" ] ] }, "page" : "1-19", "title" : "Analysis of complex survey samples", "type" : "article-journal", "volume" : "9" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Lumley, 2004)", "plainTextFormattedCitation" : "(Lumley, 2004)", "previouslyFormattedCitation" : "(Lumley, 2004)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Lumley, 2004). Our R script containing all data processing and statistical analyses are available on Open Science Framework ().Preliminary Data Processing.Imputation of missing data. As several variables contained missing data due to item non-response, including complete observations only (i.e., complete-case analysis) entailed exclusion of 3,301 observations (12%) from NHIS, and 3,997 observations (45%) from 2003-2006 NHANES. If observations with missing values differed systematically from completely observed cases, exclusion could create bias and jeopardize representativeness of the sample ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1017/CBO9780511790942.031", "ISBN" : "978-0-521-68689-1", "author" : [ { "dropping-particle" : "", "family" : "Gelman", "given" : "Andrew", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hill", "given" : "Jennifer", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "chapter-number" : "25", "container-title" : "Data Analysis Using Regression and Multilevel/Hierarchical Models", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2006" ] ] }, "page" : "529-544", "publisher" : "Cambridge University Press", "title" : "Missing-data imputation", "type" : "chapter" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Gelman & Hill, 2006)", "plainTextFormattedCitation" : "(Gelman & Hill, 2006)", "previouslyFormattedCitation" : "(Gelman & Hill, 2006)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Gelman & Hill, 2006). Therefore, we performed multiple imputation by chained equations using the R package ‘mice’ ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1177/0962280206074463", "ISBN" : "9067436771", "ISSN" : "15487660", "PMID" : "22289957", "abstract" : "The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice 2.9, which extends the functionality of mice 1.0 in several ways. In mice 2.9, the analysis of imputed data is made completely general, whereas the range ofmodels under which pooling works is substantially extended. mice 2.9 adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs. Imputation of categorical data is improved in order to bypass problems caused by perfect prediction. Special attention is paid to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. mice 2.9 can be downloaded from the Comprehensive R Archive Network. This article provides a hands-on, stepwise approach to solve applied incomplete data problems.", "author" : [ { "dropping-particle" : "", "family" : "Buuren", "given" : "Stef", "non-dropping-particle" : "Van", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Groothuis-Oudshoorn", "given" : "Karin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Journal Of Statistical Software", "id" : "ITEM-1", "issue" : "3", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "1-67", "title" : "Multivariate Imputation by Chained Equations", "type" : "article-journal", "volume" : "45" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Van Buuren & Groothuis-Oudshoorn, 2011)", "plainTextFormattedCitation" : "(Van Buuren & Groothuis-Oudshoorn, 2011)", "previouslyFormattedCitation" : "(Van Buuren & Groothuis-Oudshoorn, 2011)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Van Buuren & Groothuis-Oudshoorn, 2011). We used mice’s built-in imputation methods: predictive mean matching for numeric variables, logistic regression for factors with two levels, and multinomial logit models for factors with more than two levels. For each missing value, ten imputed values were computed using ten iterations of the imputation algorithm, thus creating ten completed datasets. We then used the R packages ‘mitools’ and ‘survey’ to create an object containing a survey design for each imputed data set for further statistical analyses. For completeness, we repeated all analyses with complete-case data (i.e., removing rows with missing values). All results were consistent across imputed and non-imputed data sets.Cox Proportional Hazards Regression. Cox Proportional Hazards Regression was used to formally test the association between our perceived physical activity and mortality. Cox proportional hazards regression fits a semi-parametric model to estimate coefficients. The outcome is represented in terms of the hazard ratio (HR), that is, the ratio between the hazard of the event of interest (death) at one level of an explanatory variable relative to the hazard of the specified reference level of the explanatory variable ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Stevenson", "given" : "Mark", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2009" ] ] }, "publisher-place" : "Palmerston North, NZ", "title" : "An Introduction to Survival Analysis", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Stevenson, 2009)", "plainTextFormattedCitation" : "(Stevenson, 2009)", "previouslyFormattedCitation" : "(Stevenson, 2009)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Stevenson, 2009). For example, a HR equal to 2 associated with smoking would mean that the hazard of death for smokers is two times higher than the hazard of death for non-smokers (the reference group).Models (as reported in main text).Model 1. A Cox proportional hazards model was fit to predict mortality from perceived physical activity and basic demographic characteristics (age, gender, race, education).Model 2. A Cox proportional hazards model was fit to predict mortality from perceived physical activity and all demographic characteristics (age, gender, race, education, employment, income, marital status, access to medical care, urbanicity [NHIS only]).Model 3. A Cox proportional hazards model was fit to predict mortality from perceived physical activity, all demographic characteristics (age, gender, race, education, employment, income, marital status, access to medical care, urbanicity [NHIS only]), and actual physical activity (actual activity measured by self-report [NHIS and 1999-2002 NHANES] or accelerometer [2003-2006 NHANES], activity on the job/ main daily activity [NHIS only]). Model 4. A Cox proportional hazards model was fit to predict mortality from all predictors: perceived physical activity, all demographic characteristics (age, gender, race, education, employment, income, marital status, access to medical care, urbanicity [NHIS only]), actual physical activity (actual activity measured by self-report [NHIS and 1999-2002 NHANES] or accelerometer [2003-2006 NHANES], activity on the job/ main daily activity [NHIS only]), and measures of health status (perceived general health, BMI, disease burden, disability, stress [NHIS only], mental health [NHANES only], illness bed days [NHIS only], smoking). Testing the proportional hazards assumption. We ascertained that the assumption required by Cox proportional hazards regression (i.e., the proportional hazards assumption) held, as recommended by Stevenson ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Stevenson", "given" : "Mark", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2009" ] ] }, "publisher-place" : "Palmerston North, NZ", "title" : "An Introduction to Survival Analysis", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Stevenson, 2009)", "manualFormatting" : "(2009)", "plainTextFormattedCitation" : "(Stevenson, 2009)", "previouslyFormattedCitation" : "(Stevenson, 2009)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(2009). The proportional hazards assumption was tested by plotting the scaled Schoenfeld residuals as a function of time. Schoenfeld residuals for each covariate were scattered around 0 showing no visible trends, indicating that the proportional hazards assumption was not violated. We also formally tested the Pearson product-moment correlation between the scaled Schoenfeld residuals and time, using the cox.zph() function of the ‘survival’ package in R. All correlations were negligible (NHIS: |r|’s ≤ .072, 1999-2002 NHANES: |r|’s ≤ .045, 2003-2006 NHANES: |r|’s ≤ .186). Although Chi squared (χ2) tests indicated some statistically significant (p < .05) departures from the null hypothesis of no correlation, we judge these apparent departures as not practically significant, because (a) all correlations were negligible in size, and (b) even negligible correlations will be highly significant in a sample as large as the current samples, as discussed by Stevenson (2009).ResultsSample characteristicsTables S1a - S1c report population totals and distribution of behavioral, socio-demographic, and health characteristics. Tables S2a - S2c present cross-tabulations of actual and perceived physical activity. Spearman’s correlations between actual and perceived activity were r = .32 (NHIS), r = .24 (1999-2002 NHANES), and r’s = 0.04-0.12 (2003-2006 NHANES).Results of survival analysisTables S3a - S3d report the complete results from the Cox proportional hazard models (Models 1 – 4) estimating risk of death in the 1990 NHIS, 1999-2002 and 2003-2006 NHANES samples.Note on variability of estimates The estimated hazard ratios on perceived physical activity were smaller in the 1990 NHIS sample than in the 1999-2002 and 2003-2006 NHANES samples, though most of the 95% confidence intervals overlapped (Tables S3a - S3d). This variability could be explained by two factors. First, NHIS respondents’ behavior and perceptions are more likely to have changed in the longer follow-up period (e.g., regression to the mean), which might have deflated the estimates. Second, the NHANES samples were collected after the Surgeon General’s report on physical activity and health in 1996 ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Centers for Disease Control and Prevention", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "1996" ] ] }, "publisher-place" : "Atlanta, GA", "title" : "Physical activity and health: A report of the Surgeon General", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Centers for Disease Control and Prevention, 1996)", "manualFormatting" : "(CDC, 1996)", "plainTextFormattedCitation" : "(Centers for Disease Control and Prevention, 1996)", "previouslyFormattedCitation" : "(Centers for Disease Control and Prevention, 1996)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(CDC, 1996), which raised public awareness of the “life-threatening consequences” of physical inactivity and the “obesity epidemic” ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1161/01.CIR.94.9.2045", "ISSN" : "0009-7322", "author" : [ { "dropping-particle" : "", "family" : "Johnson", "given" : "J. M.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Ballin", "given" : "S. D.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Circulation", "id" : "ITEM-1", "issue" : "9", "issued" : { "date-parts" : [ [ "1996", "11", "1" ] ] }, "page" : "2045-2045", "title" : "Surgeon General's Report on Physical Activity and Health Is Hailed as a Historic Step Toward a Healthier Nation", "type" : "article-journal", "volume" : "94" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "White House Task Force on Childhood Obesity", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-2", "issued" : { "date-parts" : [ [ "2010" ] ] }, "title" : "Solving the Problem of Childhood Obesity within a Generation", "type" : "report" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Johnson & Ballin, 1996; White House Task Force on Childhood Obesity, 2010)", "manualFormatting" : "(Johnson & Ballin, 1996; White House Task Force on Childhood Obesity, 2010)", "plainTextFormattedCitation" : "(Johnson & Ballin, 1996; White House Task Force on Childhood Obesity, 2010)", "previouslyFormattedCitation" : "(J. M. Johnson & Ballin, 1996; White House Task Force on Childhood Obesity, 2010)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Johnson & Ballin, 1996; White House Task Force on Childhood Obesity, 2010). NHANES respondents who perceived themselves as inactive relative to others might thus have experienced greater negative affect, stress or depression, and therefore greater health decrements ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1126/stke.2252004re5", "ISBN" : "1525-8882 (Electronic)\\n1525-8882 (Linking)", "ISSN" : "1525-8882", "PMID" : "15039492", "abstract" : "Major depression is a common, severe, chronic, and often life-threatening illness. There is a growing appreciation that, far from being a disease with purely psychological manifestations, major depression is a systemic disease with deleterious effects on multiple organ systems. Stressful life events have a substantial causal association with depression, and there is now compelling evidence that even early life stress constitutes a major risk factor for the subsequent development of depression. The emerging evidence suggests that the combination of genetics, early life stress, and ongoing stress may ultimately determine individual responsiveness to stress and the vulnerability to psychiatric disorders, such as depression. It is likely that genetic factors and life stress contribute not only to neurochemical alterations, but also to the impairments of cellular plasticity and resilience observed in depression. Recent preclinical and clinical studies have shown that signaling pathways involved in regulating cell plasticity and resilience are long-term targets for the actions of antidepressant agents. Agents capable of reversing the hypothesized impairments of cellular resilience, reductions in brain volume, and cell death or atrophy in depression have the potential of becoming new therapeutic classes of antidepressant drugs. Novel cellular targets include agents targeting neurotrophic pathways, glucocorticoid signaling, phosphodiesterase activity, and glutamatergic throughput. The future development of treatments that more directly target molecules in critical CNS (central nervous system) signaling pathways that regulate cellular plasticity thus hold promise as novel, improved long-term treatments for major depression.", "author" : [ { "dropping-particle" : "", "family" : "Charney", "given" : "Dennis S", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Manji", "given" : "Husseini K", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Science's STKE : signal transduction knowledge environment", "id" : "ITEM-1", "issue" : "225", "issued" : { "date-parts" : [ [ "2004" ] ] }, "note" : "313 cites", "page" : "re5", "title" : "Life stress, genes, and depression: multiple pathways lead to increased risk and new opportunities for intervention.", "type" : "article-journal", "volume" : "2004" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Salovey", "given" : "P.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rothman", "given" : "a.J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Detweiler", "given" : "J.B.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Steward", "given" : "W.T.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "American Psychologist", "id" : "ITEM-2", "issue" : "1", "issued" : { "date-parts" : [ [ "2000" ] ] }, "note" : "skim", "page" : "110", "title" : "Emotional states and physical health.", "type" : "article-journal", "volume" : "55" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Charney & Manji, 2004; Salovey, Rothman, Detweiler, & Steward, 2000)", "plainTextFormattedCitation" : "(Charney & Manji, 2004; Salovey, Rothman, Detweiler, & Steward, 2000)", "previouslyFormattedCitation" : "(Charney & Manji, 2004; Salovey, Rothman, Detweiler, & Steward, 2000)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Charney & Manji, 2004; Salovey, Rothman, Detweiler, & Steward, 2000). Further research is needed to investigate the heterogeneity of the effects of physical activity perceptions.Table S1. Population totals and distribution of behavioral, socio-demographic, and health characteristics in U.S. adults holding different perceptions of their level of physical activity relative to peers in 1990 NHIS (Table S1a), 1999-2002 NHANES (Table S1b), and 2003-2006 NHANES (Table S1c). Table S1aNHIS (1990)Perceived physical activity relative to peers:A lot more activeA little more activeAbout as activeA little less activeA lot less activeWeighted N (Total = 86,812,447)15,177,22812,882,19040,399,84211,486,9306,866,257Unweighted N(Total = 40,760)7,0355,99318,9985,4763,258 Distribution of Individual CharacteristicsPhysical Activity and Fitness?????Actual activity (self-report)?????Very active51%41%22%14%10%Moderately active15%19%17%13%9%Inactive34%39%61%73%80%Little physical work on job/ daily activity (cont.)1.551.761.851.942.09Health Status and Health Behavior???Perceived Health (cont.)1.851.972.152.383.00Disease burden (cont.)0.330.360.350.380.61Disability?????Not limited88%86%84%77%54%Limited in kind/ amount of major activity5%5%6%8%13%Unable to perform major activity2%2%3%7%24%Limited in other activity6%6%6%8%9%Illness bed days?????None61%59%56%47%41%1-731%33%34%37%29%8-306%7%8%11%15%31-1802%1%2%4%11%181-3650.1%0.1%0.2%1%5%Amount of stress (cont.)2.182.212.272.041.93Smoker?????Never49%51%51%49%40%Former28%27%23%22%24%Current23%22%27%29%36%BMI ?????Normal58%58%52%46%38%Obese7%8%12%17%20%Morbid. obese1%1%2%3%6%Overweight32%30%31%30%31%Underweight3%4%3%4%5%Demographics?????Age (cont.)47.546.144.241.147.0Sex (Female)48%52%58%65%64%Race?????White87%90%86%83%80%Black10%8%11%13%17%Other3%3%3%3%3%Education?????College grad25%25%19%20%14%Some college22%23%20%21%18%High school grad35%36%39%38%37%Some high school or less18%16%22%21%30%Marital status?????Divorced/ separated16%14%13%15%19%Married52%55%57%55%48%Unmarried19%20%20%23%19%Widowed12%11%10%8%13%Employment?????Employed69%66%64%62%46%Out of labor force29%31%33%35%51%Unemployed2%3%3%3%3%Income (cont.)$33,557$33,368$30,430$29,328$24,765Urbanicity (Urban)79%78%76%81%79%Access appropriate health care75%78%78%77%81%Mortality StatusDeceased by Dec 201128%27%25%22%37%Note: The table presents distributions as percentages for factors and means for continuous variables.Table S1bNHANES (1999-2002)Perceived physical activity relative to peers:More activeAbout as activeLess activeWeighted N (Total = 205,796,070)73,759,67690,973,08641,063,309Unweighted N(Total = 11,428)4,0555,1452,228Distribution of Individual CharacteristicsPhysical Activity and FitnessActual activity (self-report)Very active40%22%9%Moderately active14%15%9%Inactive46%64%82%Health Status and Health BehaviorPerceived Health (cont.)2.152.423.01Disease burden (cont.)0.680.621.02Disability5%7%25%Saw mental health prof.6%7%13%SmokerNever50%53%46%Former28%23%23%Current22%25%30%BMI Normal41%33%23%Obese17%26%36%Morbid. obese2%4%12%Overweight39%34%27%Underweight2%2%3%DemographicsAge (cont.)4942.942.9Sex (Female)46%53%61%RaceWhite73%69%68%Black11%11%11%Other16%20%20%EducationMore than high school55%49%51%High school grad26%26%25%Some high school or less19%25%24%Marital statusDivorced/ separated13%10%13%Married62%63%59%Unmarried16%22%23%Widowed8%5%5%EmploymentEmployed66%67%56%Looking for work1%2%2%Not working32%31%42%Income (cont.)$35,000 to $44,999$35,000 to $44,999$25,000 to $34,999Access appropriate health care83%82%84%Mortality StatusDeceased by Dec 201112%10%16%Note: The table presents distributions as percentages for factors and means for continuous variables.Table S1cNHANES (2003-2006)Perceived physical activity relative to peers:More activeAbout as activeLess activeWeighted N (Total = 183,438,224)65,115,20777,800,04340,522,974Unweighted N(Total = 8,953)3,1783,8451,930Distribution of Individual CharacteristicsPhysical Activity and FitnessActual activity (accelerometer)Minutes of moderate/ vigorous activity (cont.)26.7923.9218.02Minutes of light activity (cont.)262.41262.33246.84Health Status and Health BehaviorPerceived health (cont.)2.212.473.06Disease burden (cont.)0.810.711.09Disability6%7%26%Saw mental health prof.7%6%15%SmokerNever51%52%46%Former28%23%24%Current21%26%30%BMI Normal39%31%23%Obese20%30%36%Morbid. obese2%4%14%Overweight37%34%24%Underweight2%2%2%DemographicsAge (cont.)49.0543.7143.03Sex (Female)47%53%61%RaceWhite74%70%71%Black11%11%13%Other14%19%16%EducationMore than high school60%54%53%High school grad25%26%29%Some high school or less15%20%18%Marital statusDivorced/ separated13%10%15%Married64%66%59%Unmarried15%19%21%Widowed8%5%5%EmploymentEmployed68%69%57%Looking for work2%2%2%Not working30%29%41%Income (cont.)$35,000 to $44,999$35,000 to $44,999$35,000 to $44,999Access appropriate health care83%83%85%Mortality StatusDeceased by Dec 20116%5%8%Table S2. Cross-tabulation of actual and perceived physical activity in 1990 NHIS (Table S2a), 1999-2002 NHANES (Table S2b), and 2003-2006 NHANES (Table S2c). Percentages present the proportion of respondents with a given level of actual physical activity who perceived themselves as less, about as, or more active than other people their age (thus columns add up to 100%).Table S2a Actual activity (self-report)Perceived activitycompared to othersInactiveModerately activeVery active A lot less active11.4%4.4%3.0% A little less active17.2%11.1%6.6% About as active50.4%50.1%36.8% A little more active10.4%17.8%22.0% A lot more active10.6%16.6%31.7%Total100%100.0%100.1%Table S2b Actual activity (self-report)Perceived activitycompared to othersInactiveModerately activeVery active Less active26.7%13.2%7.4% About as active 46.1%49.1%37.2% More active27.2%37.7%55.4%Total100%100%100%Table S2c Actual activity (accelerometry)Perceived activitycompared to othersLow tertileModerate tertileHigh tertile Less active28.2%19.3%19.1% About as active 38.4%44.8%43.9% More active33.5%35.9%37.0%Total100.1%100%100%Table S3a. Results of the Cox Proportional Hazards Regression Predicting Mortality in the 1990 NHIS sample (N = 40,760, weighted N = 86,812,447).PredictorModel 1Model 2Model 3Model 4Physical ActivityPerceived activity relative to peers A lot more active1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) A little more active1.17[1.09, 1.26]1.15[1.08, 1.24]1.14[1.06, 1.22]1.08[1.01, 1.16] About as active1.26[1.19, 1.33]1.22[1.16, 1.29]1.18[1.11, 1.25]1.08[1.02, 1.15] A little less active1.48[1.37, 1.60]1.40[1.30, 1.51]1.33[1.23, 1.43]1.08[0.98, 1.18] A lot less active2.00[1.80, 2.22]1.83[1.65, 2.04]1.72[1.54, 1.92]1.18[1.03, 1.35]Actual activity (self-report) Very active––––1.00 (baseline)1.00 (baseline) Moderately active––––1.02[0.96, 1.10]1.02[0.94, 1.10] Inactive––––1.10[1.04, 1.16]1.08[1.02, 1.14]Little physical work on job/ daily activity (cont.)––––1.05[1.02, 1.07]1.03[1.01, 1.06]Health and Health BehaviorPerceived Health (cont.)––––––1.10[1.07, 1.13]Disease burden (cont.)––––––1.27[1.23, 1.31]Disability Not limited––––––1.00 (baseline) Limited in other activity––––––1.09[1.01, 1.17] Limited in kind/ amount of major activity––––––1.13[1.03, 1.24] Unable to perform major activity––––––1.32[1.19, 1.46]Illness bed days None––––––1.00 (baseline) 1-7––––––0.93[0.88, 0.99] 8-30––––––1.12[1.03, 1.22] 31-180––––––1.24[1.08, 1.42] 181-365––––––1.02[0.75, 1.38]Amount of stress (cont.)––––––1.03[1.002, 1.05]Smoker Never––––––1.00 (baseline) Former––––––1.21[1.15, 1.27] Current––––––1.97[1.84, 2.10]BMI Normal–––––––– Underweight––––––1.19[1.01, 1.40] Overweight––––––0.97[0.92, 1.02] Obese––––––1.07[1.004, 1.14] Morbid. obese––––––1.34[1.15, 1.56]DemographicsAge (cont.)1.09[1.09, 1.09]1.08[1.08, 1.09]1.08[1.08, 1.08]1.08[1.08, 1.09]Sex (Female)0.66[0.63, 0.69]0.60[0.56, 0.63]0.59[0.56, 0.62]0.65[0.62, 0.69]Race White1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) Black1.05[0.98, 1.13]0.96[0.89, 1.04]0.96[0.89, 1.04]0.90[0.84, 0.98] Other0.65[0.53, 0.79]0.63[0.52, 0.77]0.63[0.52, 0.77]0.66[0.54, 0.82]Education College grad1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) Some college1.27[1.18, 1.36]1.15[1.07, 1.24]1.16[1.08, 1.25]1.10[1.01, 1.20] High school grad1.37[1.28, 1.47]1.21[1.12, 1.31]1.22[1.13, 1.32]1.13[1.04, 1.23] Some high school or less1.57[1.46, 1.68]1.29[1.19, 1.40]1.30[1.19, 1.41]1.14[1.03, 1.25]Marital status Married––1.00 (baseline)1.00 (baseline)1.00 (baseline) Divorced/ separated––1.33[1.24, 1.42]1.32[1.24, 1.41]1.18[1.10, 1.27] Unmarried––1.22[1.12, 1.33]1.21[1.11, 1.32]1.30[1.19, 1.42] Widowed––1.14[1.07, 1.21]1.13[1.06, 1.20]1.12[1.05, 1.20]Employment Employed––1.00 (baseline)1.00 (baseline)1.00 (baseline) Out of labor force––1.34[1.26, 1.42]1.34[1.26, 1.42]1.19[1.12, 1.27] Unemployed––1.31[1.13, 1.52]1.31[1.13, 1.52]1.24[1.07, 1.44]Urbanicity (Urban)––1.00[0.95, 1.05]1.00[0.95, 1.05]1.02[0.97, 1.07]Income (cont.)––0.999993 [±1.5e-6]0.999994 [±1.6e-6]0.999996 [±1.6e-6]Access appropriate health care––0.97[0.91, 1.03]0.97[0.91, 1.04]1.08[1.01, 1.15]Table S3b. Results of the Cox Proportional Hazards Regression Predicting Mortality in the 1999-2002 NHANES sample (N = 11,428, weighted N = 205,796,070).PredictorModel 1Model 2Model 3Model 4Physical ActivityPerceived activity relative to peers More active1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) About as active1.34[1.19, 1.50]1.32[1.17, 1.48]1.23[1.09, 1.40]1.14[1.01, 1.30] Less active2.94[2.54, 3.39]2.72[2.35, 3.16]2.43[2.08, 2.83]1.71[1.41, 2.07]Actual activity (self-report) Very active––––1.00 (baseline)1.00 (baseline) Moderately active––––1.15[0.80, 1.64]1.11[0.76, 1.63] Inactive––––1.53[1.26, 1.86]1.36[1.11, 1.67]Health and Health BehaviorPerceived Health (cont.)––––––1.25[1.18, 1.33]Disease burden (cont.)––––––1.09[1.06, 1.12]Disability1.31[1.12, 1.53]Saw mental health prof.––––––1.21[1.02, 1.43]Smoker Never––––––1.00 (baseline) Former––––––1.27[1.12, 1.44] Current––––––1.88[1.56, 2.26]BMI Normal––––––1.00 (baseline) Underweight––––––0.85[0.53, 1.39] Overweight––––––0.88[0.78, 0.99] Obese––––––0.82[0.69, 0.98] Morbid. obese––––––0.74[0.52, 1.03]DemographicsAge (cont.)1.09[1.09, 1.10]1.09[1.08, 1.09]1.08[1.08, 1.09]1.09[1.08, 1.10]Sex (Female)0.62[0.56, 0.68]0.54[0.50, 0.59]0.53[0.48, 0.57]0.59[0.54, 0.65]Race White1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) Black1.26[1.01, 1.57]1.10[0.89, 1.37]1.07[0.86, 1.33]1.09[0.89, 1.33] Other0.87[0.60, 1.26]0.80[0.55, 1.17]0.79[0.53, 1.16]0.79[0.55, 1.13]Education More than high school1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) High school grad1.29[1.10, 1.52]1.12[0.96, 1.32]1.10[0.94, 1.30]0.99[0.84, 1.17] Some high school or Less1.57[1.35, 1.83]1.27[1.08, 1.50]1.21[1.02, 1.43]1.02[0.86, 1.20]Marital status Married––1.00 (baseline)1.00 (baseline)1.00 (baseline) Divorced/ separated––1.45[1.18, 1.78]1.45[1.19, 1.78]1.30[1.05, 1.61] Unmarried––1.64[1.10, 2.43]1.63[1.11, 2.40]1.66[1.13, 2.44] Widowed––1.31[1.16, 1.47]1.30[1.16, 1.47]1.27[1.12, 1.45]Employment Employed––1.00 (baseline)1.00 (baseline)1.00 (baseline) Looking for work––0.93[0.27, 3.18]0.93[0.27, 3.27]0.92[0.26, 3.22] Not working––1.46[1.20, 1.77]1.50[1.24, 1.83]1.22[1.00, 1.50]Income (cont.)––0.95[0.92, 0.97]0.95[0.92, 0.98]0.97[0.94, 0.999]Access appropriate health care––1.31[0.96, 1.79]1.30[0.95, 1.79]1.31[0.94, 1.81]Table S3c. Results of the Cox Proportional Hazards Regression Predicting Mortality in the 2003-2006 NHANES sample (N = 8,953, weighted N = 183,438,224), with accelerometer-assessed physical activity (categorical). PredictorModel 1Model 2Model 3Model 4Physical ActivityPerceived activity relative to peers More active1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) About as active1.43[1.19, 1.74]1.42[1.16, 1.73]1.30[1.07, 1.59]1.21[0.98, 1.48] Less active3.02[2.36, 3.87]2.66[2.08, 3.40]2.18[1.70, 2.80]1.40[1.08, 1.81]Moderate/ vigorous activity (accelerometer) High tertile––––1.00 (baseline)1.00 (baseline) Moderate tertile––––1.22[0.68, 2.16]1.23[0.70, 2.16] Low tertile––––2.11[1.10, 4.04]1.98[1.05, 3.72]Light activity (accelerometer) High tertile––––1.00 (baseline)1.00 (baseline) Moderate tertile––––1.07[0.76, 1.50]1.06[0.76, 1.47] Low tertile––––1.55[1.11, 2.17]1.43[1.04, 1.97]Health and Health BehaviorPerceived Health (cont.)––––––1.28[1.17, 1.41]Disease burden (cont.)––––––1.15[1.08, 1.22]Disability1.47[1.14, 1.90]Saw mental health prof.––––––1.03[0.74, 1.43]Smoker Never––––––1.00 (baseline) Former––––––1.25[0.95, 1.63] Current––––––1.74[1.32, 2.28]BMI Normal––––––1.00 (baseline) Underweight––––––1.79[0.96, 3.33] Overweight––––––0.67[0.52, 0.86] Obese––––––0.59[0.47, 0.75] Morbid. obese––––––0.76[0.48, 1.21]DemographicsAge (cont.)1.09[1.09, 1.10]1.08[1.07, 1.09]1.07[1.06, 1.08]1.07[1.06, 1.08]Sex (Female)0.59[0.50, 0.71]0.48[0.40, 0.58]0.51[0.42, 0.62]0.56[0.45, 0.69]Race White1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) Black1.18[0.96, 1.45]1.01[0.83, 1.24]1.00[0.83, 1.22]1.01[0.80, 1.26] Other0.91[0.70, 1.18]0.90[0.69, 1.17]0.94[0.71, 1.23]0.95[0.72, 1.24]Education More than high school1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) High school grad1.23[0.94, 1.61]1.12[0.86, 1.47]1.13[0.87, 1.48]1.02[0.76, 1.36] Some high school or less1.67[1.26, 2.20]1.43[1.08, 1.89]1.49[1.12, 1.99]1.19[0.89, 1.60]Marital status Married––1.00 (baseline)1.00 (baseline)1.00 (baseline) Divorced/ separated––2.10[1.57, 2.80]2.04[1.52, 2.74]1.73[1.27, 2.35] Unmarried––1.36[0.83, 2.24]1.31[0.80, 2.15]1.31[0.82, 2.08] Widowed––1.79[1.42, 2.26]1.74[1.39, 2.18]1.79[1.45, 2.22]Employment Employed––1.00 (baseline)1.00 (baseline)1.00 (baseline) Looking for work––1.07[0.37, 3.07]0.99[0.35, 2.84]0.91[0.34, 2.44] Not working––1.94[1.52, 2.49]1.66[1.28, 2.16]1.24[0.94, 1.62]Income (cont.)––0.98[0.94, 1.02]0.98[0.95, 1.02]1.01[0.97, 1.04]Access appropriate health care––0.96[0.69, 1.35]1.00[0.73, 1.38]1.09[0.77, 1.53]Table S3d. Results of the Cox Proportional Hazards Regression Predicting Mortality in the 2003-2006 NHANES sample (N = 8,953, weighted N = 183,438,224), with accelerometer-assessed physical activity (continuous).PredictorModel 1Model 2Model 3Model 4Physical ActivityPerceived activity relative to peers More active1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) About as active1.43[1.19, 1.74]1.42[1.16, 1.73]1.28[1.05, 1.57]1.19[0.97, 1.46] Less active3.02[2.36, 3.87]2.66[2.08, 3.40]2.09[1.62, 2.70]1.35[1.05, 1.76]Accelerometer-assessed physical activity Moderate/ vigorous (cont., in hours)––––0.31[0.10, 0.93]0.35[0.13, 0.96] Light (cont., in hours)––––0.80[0.71, 0.90]0.83[0.74, 0.93]Health and Health BehaviorPerceived Health (cont.)––––––1.27[1.16, 1.40]Disease burden (cont.)––––––1.16[1.09, 1.23]Disability1.47[1.14, 1.89]Saw mental health prof.––––––1.03[0.74, 1.42]Smoker Never––––––1.00 (baseline) Former––––––1.24[0.95, 1.63] Current––––––1.74[1.33, 2.27]BMI Normal––––––1.00 (baseline) Underweight––––––1.82[0.97, 3.41] Overweight––––––0.67[0.52, 0.87] Obese––––––0.59[0.47, 0.74] Morbid. obese––––––0.74[0.47, 1.19]DemographicsAge (cont.)1.09[1.09, 1.10]1.08[1.07, 1.09]1.07[1.05, 1.08]1.07[1.05, 1.08]Sex (Female)0.59[0.50, 0.71]0.48[0.40, 0.58]0.49[0.40, 0.59]0.54[0.43, 0.66]Race White1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) Black1.18[0.96, 1.45]1.01[0.83, 1.24]1.01[0.83, 1.23]1.02[0.81, 1.28] Other0.91[0.70, 1.18]0.90[0.69, 1.17]0.94[0.71, 1.24]0.95[0.72, 1.25]Education More than high school1.00 (baseline)1.00 (baseline)1.00 (baseline)1.00 (baseline) High school grad1.23[0.94, 1.61]1.12[0.86, 1.47]1.15[0.88, 1.50]1.03[0.77, 1.37] Some high school or less1.67[1.26, 2.20]1.43[1.08, 1.89]1.52[1.15, 2.02]1.21[0.91, 1.63]Marital status Married––1.00 (baseline)1.00 (baseline)1.00 (baseline) Divorced/ separated––2.10[1.57, 2.80]2.03[1.53, 2.69]1.70[1.26, 2.29] Unmarried––1.36[0.83, 2.24]1.31[0.80, 2.14]1.31[0.83, 2.07] Widowed––1.79[1.42, 2.26]1.72[1.37, 2.17]1.79[1.44, 2.21]Employment Employed––1.00 (baseline)1.00 (baseline)1.00 (baseline) Looking for work––1.07[0.37, 3.07]0.97[0.34, 2.73]0.91[0.34, 2.40] Not working––1.94[1.52, 2.49]1.64[1.26, 2.13]1.23[0.94, 1.61]Income (cont.)––0.98[0.94, 1.02]0.98[0.94, 1.02]1.00[0.97, 1.04]Access appropriate health care––0.96[0.69, 1.35]1.03[0.74, 1.43]1.12[0.79, 1.60] Supplemental ReferencesADDIN Mendeley Bibliography CSL_BIBLIOGRAPHY Ainsworth, B. E., Haskell, W. L., Herrmann, S. D., Meckes, N., Bassett, D. R., Tudor-Locke, C., … Leon, A. S. (2011). 2011 Compendium of Physical Activities. Medicine & Science in Sports & Exercise, 43(8), 1575–1581. for Disease Control and Prevention. (1996). Physical activity and health: A report of the Surgeon General. Atlanta, GA.Charney, D. S., & Manji, H. K. (2004). Life stress, genes, and depression: multiple pathways lead to increased risk and new opportunities for intervention. Science’s STKE?: Signal Transduction Knowledge Environment, 2004(225), re5. , A., & Hill, J. (2006). Missing-data imputation. In Data Analysis Using Regression and Multilevel/Hierarchical Models (pp. 529–544). Cambridge University Press. , J. M., & Ballin, S. D. (1996). Surgeon General’s Report on Physical Activity and Health Is Hailed as a Historic Step Toward a Healthier Nation. Circulation, 94(9), 2045–2045. , T. (2004). Analysis of complex survey samples. Journal of Statistical Software, 9(1), 1–19.National Center for Health Statistics. (2015). NHIS Data, Questionnaires and Related Documentation. Retrieved from Center for Health Statistics. (2016a). Leisure-time Physical Activity Recodes. Retrieved June 18, 2016, from Center for Health Statistics. (2016b). NCHS Data Linked to NDI Mortality Files. Retrieved January 1, 2015, from , P., Rothman, a. J., Detweiler, J. B., & Steward, W. T. (2000). Emotional states and physical health. American Psychologist, 55(1), 110. Retrieved from , T., & Craig, C. L. (1989). Fitness and Activity Measurement in the 1981 Canada Fitness Survey. In T. F. Drury (Ed.), Assessing Physical Fitness and Physical Activity in Population-Based Surveys (pp. 401–432). Hyattsville, MD: National Center for Health Statistics.Stevenson, M. (2009). An Introduction to Survival Analysis. Palmerston North, NZ. Retrieved from of Sciences/Epicenter/docs/ASVCS/Stevenson_survival_analysis_195_721.pdfSutin, A. R., Stephan, Y., & Terracciano, A. (2015). Weight Discrimination and Risk of Mortality. Psychological Science , 26(11), 1803–1811. Buuren, S., & Groothuis-Oudshoorn, K. (2011). Multivariate Imputation by Chained Equations. Journal Of Statistical Software, 45(3), 1–67. House Task Force on Childhood Obesity. (2010). Solving the Problem of Childhood Obesity within a Generation. Retrieved from ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download