Documentation of Biomarkers in the Health and Retirement Study

Crimmins, Ellen; Guyer, Heidi; Langa, Kenneth M.; Ofstedal, Mary Beth; Wallace, Robert B.

doi:10.7826/isr-um.06.585031.001.05.0018.2009

Cited by 90 publications

(151 citation statements)

References 0 publications

Supporting

Mentioning

151

Contrasting

Order By: Relevance

“…Data for this analysis is from the 2006 and 2008 interviews, when direct biomarker assessments in randomly selected subsamples of the study population were collected. Respondents were excluded if they were unable or unwilling to participate in the blood pressure assessment [11]. Our analyses include individuals with direct assessments of blood pressure (n = 13,451), which comprised 62% of the eligible sample.…”

Section: Study Populationmentioning

confidence: 99%

Self-Reported and Measured Hypertension Among Older US- and Foreign-Born Adults

White

Avendaño

Capistrant

et al. 2011

J Immigrant Minority Health

View full text Add to dashboard Cite

Self-reported hypertension is frequently used for health surveillance. However, little is known about the validity of self-reported hypertension among older Americans by nativity status. This study compared self-reported and measured hypertension among older black, white, and Hispanic Americans by nativity using the 2006 and 2008 Health and Retirement Study (n = 13,451). Sensitivity and specificity of self-reported hypertension were calculated using the Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure definition. Sensitivity was high among older blacks (88.9%), whites (82.8%), and Hispanics (84.0%), and both foreign-born (83.2%) and US-born (84.0%). Specificity was above 90% for both US-born and foreign-born, but higher for whites (92.8%) than blacks (86.0%). Despite the potential vulnerability of older foreign-born Americans, self-reported hypertension may be considered a reasonable estimate of hypertension status. Future research should confirm these findings in samples with a larger and more ethnically diverse foreign-born population.

show abstract

Section: Study Populationmentioning

confidence: 99%

Self-Reported and Measured Hypertension Among Older US- and Foreign-Born Adults

White

Avendaño

Capistrant

et al. 2011

J Immigrant Minority Health

View full text Add to dashboard Cite

show abstract

“…Although all measures in HRS were adjusted to reflect levels equivalent to markers t a k e n f r o m v e n o u s b l o o d ( C r i m m i n s e t a l . 2 0 1 4 ) , t h e l e v e l s o f t o t a l a n d H D L cholesterol deviate strongly from those in reference studies like NHANES (Crimmins et al 2013). The distortion is proportional for total and HDL cholesterol, so that the ratio is comparable to other studies.…”

Section: Methodsmentioning

confidence: 77%

“…The cut-off for hbA1c conforms to both a common recommendation (American Diabetes Association 2011; World Health Organization 2011) and to previous studies (Delpierre et al 2016b;Goldman et al 2011;Rosero-Bixby and Dow 2009). The CRP cut-off has also been used in previous studies (Crimmins et al 2013(Crimmins et al , 2014Osman et al 2006) and follows standard recommendations (Pearson et al 2003). The systolic blood pressure cut-off has been used in previous studies (Rosero-Bixby and Dow 2009;Seeman et al 2004) and has been tested in a randomized control trial (The SPRINT Research Group 2015).…”

Section: Methodsmentioning

confidence: 99%

“…All analyses are weighted by weights provided by the HRS survey team (Crimmins et al 2013). These weights are meant to account for non-random sampling and selective non-response to participation in the biomarker measurement.…”

Section: Methodsmentioning

confidence: 99%

“…Many biosocial surveys give explicit guidelines to users on how to construct such risk factors, which makes them easy to use even without prior experience in this field (Benzeval et al 2014;Crimmins et al 2013). Our analyses are therefore of an explanatory nature, and are designed to determine whether mortality prediction is best achieved by using a simple risk factor index, binary risk factors, continuous biomarkers, risk profiles, or risk groups based on a combination of risk factors.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The association between CVD-related biomarkers and mortality in the Health and Retirement Survey

Kröger¹,

Hoffmann²

2018

DemRes

View full text Add to dashboard Cite

BACKGROUNDIt has become increasingly common in multiple purpose general population surveys to integrate different kinds of biomarker in the data collection process. OBJECTIVEIn this article we test the predictive power of five different functional forms of CVDrelated biomarkers for all-cause and CVD mortality in the Health and Retirement Study (HRS). METHODSWe use five different functional forms of biomarker: A risk factor index, risk factors separately, continuous biomarkers, risk groups comprising every possible combination of risk factors, and a cluster analytic approach to identify risk profiles in the sample. We use data from the Health and Retirement Study (HRS) with information on four collected biomarkers (glycated hemoglobin (hbA1c), high-density lipoprotein (HDL), total cholesterol, and C-reactive protein (CRP)) with an eight-year mortality follow-up period. RESULTSThe results show that the additive index has comparatively high predictive power, relative to its simplicity. Risk profiles were identified in the data, with substantial differences in mortality risk between the profiles. The more complex functional forms improve prediction only moderately compared to the simple index, although we can identify groups with an elevated mortality risk that are not identified in more parsimonious approaches.1 Deutsches Institut für Wirtschaftsforschung (DIW), Berlin, Germany. Email: hkroeger@diw.de. 2 Max-Planck-Institut für Demografische Forschung, Rostock, Germany. Email: hoffmann@demogr.mpg.de. Kröger & Hoffmann:The association between CVD-related biomarkers and mortality 1934http://www.demographic-research.org CONCLUSIONSDepending on the specific research question, both a very simple modeling of biomarker information and more detailed examinations of specific complex risk profiles can be appropriate. CONTRIBUTIONThe study provides initial guidelines for the measurement of commonly used biomarkers, which can be a reference for other studies that use biomarkers as health indicators or for mortality prediction.

show abstract

Association of a Genetic Risk Score With Body Mass Index Across Different Birth Cohorts

Walter

Mejía‐Guevara

Estrada

et al. 2016

JAMA

124

114

View full text Add to dashboard Cite

IMPORTANCE Many genetic variants are associated with body mass index (BMI). Associations may have changed with the 20th century obesity epidemic and may differ for black vs white individuals. OBJECTIVE Using birth cohort as an indicator for exposure to obesogenic environment, to evaluate whether genetic predisposition to higher BMI has a larger magnitude of association among adults from more recent birth cohorts, who were exposed to the obesity epidemic at younger ages. DESIGN, SETTING, AND PARTICIPANTS Observational study of 8788 adults in the US national Health and Retirement Study who were aged 50 years and older, born between 1900 and 1958, with as many as 12 BMI assessments from 1992 to 2014. EXPOSURES A multilocus genetic risk score for BMI (GRS-BMI), calculated as the weighted sum of alleles of 29 single nucleotide polymorphisms associated with BMI, with weights equal to the published per-allele effects. The GRS-BMI represents how much each person's BMI is expected to differ, based on genetic background (with respect to these 29 loci), from the BMI of a sample member with median genetic risk. The median-centered GRS-BMI ranged from −1.68 to 2.01. MAIN OUTCOMES AND MEASURES BMI based on self-reported height and weight. RESULTS GRS-BMI was significantly associated with BMI among white participants (n = 7482; mean age at first assessment, 59 years; 3373 [45%] were men; P <.001) and among black participants (n = 1306; mean age at first assessment, 57 years; 505 [39%] were men; P <.001) but accounted for 0.99% of variation in BMI among white participants and 1.37% among black participants. In multilevel models accounting for age, the magnitude of associations of GRS-BMI with BMI were larger for more recent birth cohorts. For example, among white participants, each unit higher GRS-BMI was associated with a difference in BMI of 1.37 (95% CI, 0.93 to 1.80) if born after 1943, and 0.17 (95% CI, −0.55 to 0.89) if born before 1924 (P = .006). For black participants, each unit higher GRS-BMI was associated with a difference in BMI of 3.70 (95% CI, 2.42 to 4.97) if born after 1943, and 1.44 (95% CI, −1.40 to 4.29) if born before 1924. CONCLUSIONS AND RELEVANCE For participants born between 1900 and 1958, the magnitude of association between BMI and a genetic risk score for BMI was larger among persons born in later cohorts. This suggests that associations of known genetic variants with BMI may be modified by obesogenic environments.

show abstract

Documentation of Biomarkers in the Health and Retirement Study

Cited by 90 publications

References 0 publications

Self-Reported and Measured Hypertension Among Older US- and Foreign-Born Adults

Self-Reported and Measured Hypertension Among Older US- and Foreign-Born Adults

The association between CVD-related biomarkers and mortality in the Health and Retirement Survey

Association of a Genetic Risk Score With Body Mass Index Across Different Birth Cohorts

Contact Info

Product

Resources

About