@article {9797, title = {Religion, Life Expectancy and Disability-Free Life Expectancy Among Older Women and Men in the United States}, journal = {The Journals of Gerontology: Series B}, volume = {74}, year = {2019}, pages = {e107{\textendash}e118}, type = {Journal}, abstract = {OBJECTIVES Existing literature shows religion is associated with health and survival separately. We extend this literature by considering health and survival together using a multi-state life table approach to estimate total, disability-free and disabled life expectancy, separately for women and men, for two disability measures, and by two indicators of religion. METHOD Data come from the Health and Retirement Study (1998-2014 waves). Predictors include importance of religion and attendance at religious services. The disability measures are defined by ADLs and IADLs. Models control for sociodemographic and health covariates. RESULTS Attendance at religious services shows a strong and consistent association with life and health expectancy. Men and women who attend services at least once a week (compared to those who attend less frequently or never) have between 1.1 and 5.1 years longer total life expectancy and between 1.0 and 4.3 years longer ADL disability-free life expectancy. Findings for IADL disability are similar. Importance of religion is related to total and disabled life expectancy (both ADL and IADL), but the differentials are smaller and less consistent. Controlling for sociodemographic and health factors does not explain these associations. DISCUSSION By estimating total, disability-free and disabled life expectancy we are able to quantify the advantage of religion for health. Results are consistent with previous studies that have focused on health and mortality separately.}, keywords = {Disabilities, Gender Differences, Mortality, Religion}, issn = {1079-5014}, doi = {10.1093/geronb/gby098}, url = {https://academic.oup.com/psychsocgerontology/article-abstract/74/8/e107/5078835?redirectedFrom=fulltext}, author = {Mary Beth Ofstedal and Chi-Tsun Chiu and Jagger, Carol and Saito, Yasuhiko} } @article {9606, title = {Measuring Cognition in a Multi-mode Context}, year = {2018}, month = {05-2018}, pages = {1-48}, institution = {Survey Research Center, Institute for Social Research, University of Michigan}, address = {Ann Arbor, MI}, keywords = {Cognitive Ability, Mode effects, Survey Methodology}, author = {McClain, Colleen A. and Mary Beth Ofstedal and Mick P. Couper} } @article {9023, title = {The Benefits and Challenges of Collecting Physical Measures and Biomarkers in Cross-National Studies}, year = {2017}, month = {04/2017}, institution = {Survey Research Center, Institute for Social Research, University of Michigan}, address = {Ann Arbor, Michigan}, author = {Heidi M Guyer and Mary Beth Ofstedal and Lessof, Carli and Cox, Kate} } @article {8942, title = {Estimation of Mode Effects in the Health and Retirement Study Using Measurement Models}, journal = {Journal of Survey Statistics and Methodology}, volume = {4}, year = {2016}, month = {May-12-2018}, pages = {501 - 524}, abstract = {Using multiple modes to collect data is becoming a standard practice in surveys. While this should lower costs and reduce nonresponse error, it may have detrimental effects on measurement quality. This is of special concern in panel surveys where a key focus is on measuring change over time and where changing modes may have an effect on key measures. In this paper, we use a quasi-experimental design from the Health and Retirement Study to compare the measurement quality of two scales between face-to-face, telephone, and Web modes. Panel members were randomly assigned to receive a telephone survey or enhanced face-to-face survey in the 2010 core wave, while this was reversed in the 2012 core wave. In 2011, panelists with Internet access completed a Web survey containing selected questions from the core waves. We examine the responses from 3,251 respondents who participated in all three waves, using latent variable models to identify measurement mode effects. The two scales, depression and physical activity, show systematic differences between interviewer-administered modes (i.e., face-to-face and telephone) and the self-administered one (i.e., Web). Possible explanations are discussed.}, keywords = {Meta-analyses, Mixed models, Mode effects, Survey Methodology}, issn = {2325-0984}, doi = {10.1093/jssam/smw021}, url = {https://academic.oup.com/jssam/article-lookup/doi/10.1093/jssam/smw021https://academic.oup.com/jssam/article/2670256/Estimation-of-Mode-Effects-in-the-Health-and}, author = {Cernat, Alexandru and Mick P. Couper and Mary Beth Ofstedal} } @article {5879, title = {Estimation of Mode Effects in the Health and Retirement Study using Measurement Models}, year = {2015}, institution = {Essex, UK, Institute for Social and Economic Research}, abstract = {Using multiple modes to collect data is becoming a standard practice in survey agencies. While this should save costs and decrease non-response error it may have detrimental effects on measurement quality. This can happen because different modes have distinct measurement biases which, when combined with selection effects, can increase the total survey error of a mixed-mode survey relative to a single mode approach. In this paper we use a quasi-experimental design from the Health and Retirement Study to compare the measurement quality of a number of scales between face-to-face, telephone and Web modes. Panel members were randomly assigned to receive a telephone survey or enhanced face-to-face survey in the 2010 core wave, while this was reversed in the 2012 core wave. In 2011, panelists with Internet access completed a Web survey containing selected questions from the core waves. We examine the responses from 3251 respondents who participated in all three waves, using latent models to identify measurement mode effects. Two of the scales, depression and physical activity, show systematic differences between interviewer administered modes (i.e., face-to-face and telephone) and the self-administered one (i.e., Web) while religiosity shows no differences of measurement between modes. Possible explanations are discussed.}, author = {Cernat, Alexandru and Mick P. Couper and Mary Beth Ofstedal} } @article {5954, title = {Documentation of Biomarkers in the 2006 and 2008 Health and Retirement Study}, year = {2013}, institution = {Institute for Social Research, University of Michigan}, address = {Ann Arbor, Michigan}, abstract = {Biomarkers refer to the general range of physiological, metabolic, biochemical, endocrine and genetic measures that can be obtained in living organisms. The term is most commonly used to refer to one-time biochemical or hematological measures made on blood or other available bodily fluids, but perhaps the term should be used for a broader range of measures. In 2006 and 2008, HRS included the following biomarkers measurements, administered in this order: Saliva collection for DNA extraction; Blood spot collection for cholesterol, hemoglobin A1C, CRP and cystatin C analysis (results for C-reactive protein and cystatin C are forthcoming). This report describes the following for each of the measures listed above: Rationale and key citations; Sample description; Measure description; Equipment; Protocol description; Special instructions.}, keywords = {Health Conditions and Status, Healthcare, Methodology}, author = {Eileen M. Crimmins and Jessica Faul and Jung K Kim and Heidi M Guyer and Kenneth M. Langa and Mary Beth Ofstedal and Amanda Sonnega and Robert B Wallace and David R Weir} } @article {7946, title = {ENCOURAGING RECORD USE FOR FINANCIAL ASSET QUESTIONS IN AWEB SURVEY.}, journal = {J Surv Stat Methodol}, volume = {1}, year = {2013}, month = {2013 Nov}, pages = {171-182}, publisher = {1}, abstract = {

We report on two experiments to encourage record use by respondents in an Internet survey. The experiments were conducted in the 2009 Health and Retirement Study (HRS) Internet Survey, administered to those in the HRS panel with Internet access, and in the 2011 HRS Internet Survey. Encouraging respondents to consult records at the relevant point in the questionnaire significantly increased reported record use (from 39 percent to 47 percent), but was insufficient to produce significant changes in the precision (amount of rounding) of the information reported. Including the encouragement in the mailed invitation to the Web survey in 2011 resulted in a lower response rate (77 percent with encouragement, 80 percent without), but increased reported record use among respondents (from 46 percent to 55 percent). In neither case was the increase in reported record use large enough to produce significant differences in the precision of the information reported between the groups with and without encouragement.

}, issn = {2325-0984}, doi = {10.1093/jssam/smt007}, url = {http://jssam.oxfordjournals.org/content/1/2/171.abstract}, author = {Mick P. Couper and Mary Beth Ofstedal and Lee, Sunghee} } @article {8943, title = {Linking Survey and Administrative Records: Mechanisms of Consent}, journal = {Sociological Methods \& Research}, volume = {41}, year = {2012}, month = {2012 Nov}, pages = {535-569}, abstract = {

Survey records are increasingly being linked to administrative databases to enhance the survey data and increase research opportunities for data users. A necessary prerequisite to linking survey and administrative records is obtaining informed consent from respondents. Obtaining consent from all respondents is a difficult challenge and one that faces significant resistance. Consequently, data linkage consent rates vary widely from study-to-study. Several studies have found significant differences between consenters and non-consenters on socio-demographic variables, but no study has investigated the underlying mechanisms of consent from a theory-driven perspective. In this study, we describe and test several hypotheses related to respondents{\textquoteright} willingness to consent to an earnings and benefit data linkage request based on mechanisms related to financial uncertainty, privacy concerns, resistance towards the survey interview, level of attentiveness during the interview, the respondents{\textquoteright} preexisting relationship with the administrative data agency, and matching respondents and interviewers on observable characteristics. The results point to several implications for survey practice and suggestions for future research.

}, keywords = {Consent, Meta-analyses, Survey Methodology}, issn = {0049-1241}, doi = {10.1177/0049124112460381}, author = {Joseph W Sakshaug and Mick P. Couper and Mary Beth Ofstedal and David R Weir} } @article {7630, title = {A comparison of response rates in the English Longitudinal Study of Ageing and the Health and Retirement Study.}, journal = {Longit Life Course Stud}, volume = {2}, year = {2011}, month = {2011 May 01}, pages = {127-144}, publisher = {2}, abstract = {

Survey response rates are an important measure of the quality of a survey; this is true for both longitudinal and cross-sectional surveys. However, the concept of a response rate in the context of a panel survey is more complex than is the case for a cross-sectional survey. There are typically many different response rates that can be calculated for a panel survey, each of which may be relevant for a specific purpose. The main objective of our paper is to document and compare response rates for two long-term panel studies of ageing, the English Longitudinal Study of Ageing (ELSA) and the Health and Retirement Study (HRS) in the United States. To guide our selection and calculation of response rates for the two studies, we use a framework that was developed by Peter Lynn (2005) and present several different types of longitudinal response rates for the two surveys. We discuss similarities and differences in the study designs and protocols and how some of the differences affect comparisons of response rates across the two studies.

}, issn = {1757-9597}, doi = {10.14301/llcs.v2i2.118}, author = {Hayley Cheshire and Mary Beth Ofstedal and Shaun Scholes and Mathis Schroeder} } @article {5917, title = {Updates to HRS Sample Weights}, year = {2011}, institution = {Institute for Social Research, University of Michigan}, address = {Ann Arbor, Michigan}, keywords = {Methodology}, author = {Mary Beth Ofstedal and David R Weir and Chen, K.T. and James Wagner} } @article {7436, title = {Characteristics of physical measurement consent in a population-based survey of older adults.}, journal = {Med Care}, volume = {48}, year = {2010}, month = {2010 Jan}, pages = {64-71}, publisher = {48}, abstract = {

BACKGROUND: Collecting physical measurements in population-based health surveys has increased in recent years, yet little is known about the characteristics of those who consent to these measurements.

OBJECTIVE: To examine the characteristics of persons who consent to physical measurements across several domains, including one{\textquoteright}s demographic background, health status, resistance behavior toward the survey interview, and interviewer characteristics.

RESEARCH DESIGN, SUBJECTS, AND MEASURES: We conducted a secondary data analysis of the 2006 Health and Retirement Study, a nationally-representative panel survey of older adults aged 51 and older. We performed multilevel logistic regressions on a sample of 7457 respondents who were eligible for physical measurements. The primary outcome measure was consent to all physical measurements.

RESULTS: Seventy-nine percent (unweighted) of eligible respondents consented to all physical measurements. In weighted multilevel logistic regressions controlling for respondent demographics, current health status, survey resistance indicators, and interviewer characteristics, the propensity to consent was significantly greater among Hispanic respondents matched with bilingual Hispanic interviewers, patients with diabetes, and those who visited a doctor in the past 2 years. The propensity to consent was significantly lower among younger respondents, those who have several Nagi functional limitations and infrequently participate in "mildly vigorous" activities, and those interviewed by black interviewers. Survey resistance indicators, such as number of contact attempts and interviewer observations of resistant behavior in prior wave iterations of the Health and Retirement Study were also negatively associated with physical measurement consent. The propensity to consent was unrelated to prior medical diagnoses, including high blood pressure, cancer (excluding skin), lung disease, heart abnormalities, stroke, and arthritis, and matching of interviewer and respondent on race and gender.

CONCLUSIONS: Physical measurement consent is not strongly associated with one{\textquoteright}s health status, though the findings are somewhat mixed. We recommend that physical measurement results be adjusted for characteristics associated with the likelihood of consent, particularly functional limitations, to reduce potential bias. Otherwise, health researchers should exercise caution when generalizing physical measurement results to the population at large, including persons with functional limitations that may affect their participation.

}, keywords = {Age Factors, Aged, Female, Health Status, Health Surveys, Humans, Male, Middle Aged, Physical Examination, Socioeconomic factors}, issn = {1537-1948}, doi = {10.1097/mlr.0b013e3181adcbd3}, author = {Joseph W Sakshaug and Mick P. Couper and Mary Beth Ofstedal} } @article {7338, title = {Comparing models of frailty: the Health and Retirement Study.}, journal = {J Am Geriatr Soc}, volume = {57}, year = {2009}, month = {2009 May}, pages = {830-9}, publisher = {57}, abstract = {

OBJECTIVES: To operationalize and compare three models of frailty, each representing a distinct theoretical view of frailty: as deficiencies in function (Functional Domains model), as an index of health burden (Burden model), and as a biological syndrome (Biologic Syndrome model).

DESIGN: Cross-sectional analysis.

SETTING: 2004 wave of the Health and Retirement Study, a nationally representative, longitudinal health interview survey.

PARTICIPANTS: Adults aged 65 and older (N=11,113) living in the community and in nursing homes in the United States.

MEASUREMENTS: The outcome measure was the presence of frailty, as defined according to each frailty model. Covariates included chronic diseases and sociodemographic characteristics.

RESULTS: Almost one-third (30.2\%) of respondents were frail according to at least one model; 3.1\% were frail according to all three models. The Functional Domains model showed the least overlap with the other models. In contrast, 76.1\% of those classified as frail according to the Biologic Syndrome model and 72.1\% of those according to the Burden model were also frail according to at least one other model. Older adults identified as frail according to the different models differed in sociodemographic and chronic disease characteristics. For example, the Biologic Syndrome model demonstrated substantial associations with older age (adjusted odds ratio (OR)=10.6, 95\% confidence interval (CI)=6.1-18.5), female sex (OR=1.7, 95\% CI=1.2-2.5), and African-American ethnicity (OR=2.1, \% CI=1.0-4.4).

CONCLUSION: Different models of frailty, based on different theoretical constructs, capture different groups of older adults. The different models may represent different frailty pathways or trajectories to adverse outcomes such as disability and death.

}, keywords = {Activities of Daily Living, Aged, Aged, 80 and over, Chronic disease, Cross-Sectional Studies, Demography, Disability Evaluation, Frail Elderly, Geriatric Assessment, Health Surveys, Humans, Interviews as Topic, Logistic Models, Models, Theoretical, United States}, issn = {1532-5415}, doi = {10.1111/j.1532-5415.2009.02225.x}, author = {Christine T Cigolle and Mary Beth Ofstedal and Zhiyi Tian and Caroline S Blaum} } @inbook {5242, title = {Keeping in Contact with Mobile Sample Members}, booktitle = {Methodology of Longitudinal Surveys}, year = {2009}, pages = {183-202}, publisher = {Wiley}, organization = {Wiley}, chapter = {11}, address = {New York}, abstract = {In this chapter, we first offer an overview of the location problem, as distinct from other sources of panel attrition or nonresponse. We then offer a framework for understanding the location propensity to guide fieldwork strategies and identify likely sources of bias. Then we briefly describe two cases studies, examining the extent of the location problem and correlates of (non)location. We end with a brief discussion of the changing role of technology in facilitating or impeding the ability to locate sample persons who have moved or changed contact information, and offer some thoughts for research and practice.}, keywords = {Methodology}, doi = {https://doi.org/10.1002/9780470743874.ch11}, author = {Mick P. Couper and Mary Beth Ofstedal}, editor = {Lynn, Peter} } @inbook {5243, title = {Data sources, Later Life: Health and Retirement Study (HRS)}, booktitle = {Encyclopedia of the Life Course and Human Development}, volume = {3}, year = {2008}, publisher = {Gale}, organization = {Gale}, address = {Farmington Hills, MI}, abstract = {This reference is an entry in Volume 3 of the Encyclopedia of the Life Course and Human Development; it discusses the Health and Retirement Study as a data source for research on the Later Life stage of the life course.}, keywords = {Methodology}, isbn = {978-0-02-866162-9}, author = {Mary Beth Ofstedal}, editor = {Deborah Carr and Crosnoe, Robert and Mary Elizabeth Hughes and Pienta, Amy M.} } @article {5734, title = {Documentation of Physical Measures, Anthropometrics and Blood Pressure in the Health and Retirement Study}, year = {2008}, institution = {Institute for Social Research, University of Michigan}, address = {Ann Arbor, Michigan}, abstract = {The assessment of physical performance is an important component of the evaluation of functioning of older persons. The HRS has employed a set of standardized assessments of lung function, grip strength, balance, and walking speed. In addition, HRS collected measures of blood pressure, height, weight, and waist circumference. In 2006, HRS included the following measurements, administered in this order: Blood pressure; Lung function; Hand grip strength; Balance tests; Timed walk; Height; Weight; Waist circumference. This report describes the following for each of the measures listed above: Rationale and key citations; Sample description; Measure description; Equipment; Protocol description; Special instructions}, keywords = {Health Conditions and Status, Healthcare, Methodology}, author = {Eileen M. Crimmins and Heidi M Guyer and Kenneth M. Langa and Mary Beth Ofstedal and Robert B Wallace and David R Weir} } @article {6738, title = {National estimates of the quantity and cost of informal caregiving for the elderly with dementia.}, journal = {J Gen Intern Med}, volume = {16}, year = {2001}, month = {2001 Nov}, pages = {770-8}, publisher = {16}, abstract = {

OBJECTIVE: Caring for the elderly with dementia imposes a substantial burden on family members and likely accounts for more than half of the total cost of dementia for those living in the community. However, most past estimates of this cost were derived from small, nonrepresentative samples. We sought to obtain nationally representative estimates of the time and associated cost of informal caregiving for the elderly with mild, moderate, and severe dementia.

DESIGN: Multivariable regression models using data from the 1993 Asset and Health Dynamics Study, a nationally representative survey of people age 70 years or older (N = 7,443).

SETTING: National population-based sample of the community-dwelling elderly.

MAIN OUTCOME MEASURES: Incremental weekly hours of informal caregiving and incremental cost of caregiver time for those with mild dementia, moderate dementia, and severe dementia, as compared to elderly individuals with normal cognition. Dementia severity was defined using the Telephone Interview for Cognitive Status.

RESULTS: After adjusting for sociodemographics, comorbidities, and potential caregiving network, those with normal cognition received an average of 4.6 hours per week of informal care. Those with mild dementia received an additional 8.5 hours per week of informal care compared to those with normal cognition (P < .001), while those with moderate and severe dementia received an additional 17.4 and 41.5 hours (P < .001), respectively. The associated additional yearly cost of informal care per case was 3,630 dollars for mild dementia, 7,420 dollars for moderate dementia, and 17,700 dollars for severe dementia. This represents a national annual cost of more than 18 billion dollars.

CONCLUSION: The quantity and associated economic cost of informal caregiving for the elderly with dementia are substantial and increase sharply as cognitive impairment worsens. Physicians caring for elderly individuals with dementia should be mindful of the importance of informal care for the well-being of their patients, as well as the potential for significant burden on those (often elderly) individuals providing the care.

}, keywords = {Aged, Aged, 80 and over, Caregivers, Cost of Illness, Dementia, Female, Health Care Costs, Humans, Male, Multivariate Analysis, Regression Analysis, Severity of Illness Index, Time Factors, United States}, issn = {0884-8734}, doi = {10.1111/j.1525-1497.2001.10123.x}, author = {Kenneth M. Langa and M.E. Chernew and Mohammed U Kabeto and A. Regula Herzog and Mary Beth Ofstedal and Robert J. Willis and Robert B Wallace and Mucha, L.M. and Walter L. Straus and A. Mark Fendrick} }