The influence of reliability and variability of objectively measured physical activity on associations with lower body muscle strength in young children.

It is not known how extended or multiple monitoring periods affect associations between accelerometer-measured physical activity and outcomes. The aim of this study was to examine how accelerometer monitoring length influenced cross-sectional and prospective associations for physical activity with lower body muscle strength in young children. 176 Norwegian 2-6-year-old children had 3 valid 14-day periods of accelerometer monitoring (ActiGraph GT3×+) between September 2015 and May 2016 (baseline) as well as baseline and 4-year follow-up measurements of standing long jump. We analysed physical activity using a descriptor with 4 intensities using 6 different monitoring lengths both within and across monitoring periods (1 day, 3 days, 1 week, 2 weeks, 3 weeks, 6 weeks) and determined associations with lower body muscle strength using multivariate pattern analysis. We found that the strength of cross-sectional associations with lower body muscle strength improved for longer monitoring periods (explained variances = 7.7%, 9.8%, 11.8%, 15.8%, 18.4% and 22.9% for 1 day, 3 days, 1 week, 2 weeks, 3 weeks and 6 weeks of measurement). Longitudinal associations were weaker and less clear. Our findings suggest that multiple extended physical activity monitoring periods improve the validity of the study findings regarding associations between physical activity and relevant outcomes.

Plasma lipopolysaccharide-binding protein is a biomarker for future venous thromboembolism: Results from discovery and validation studies.

BACKGROUND: Effect-size underestimation impedes biomarker identification. Long follow-up time in prospective studies attenuates effect-size estimates for transient biomarkers, while disease category-specific biomarkers are affected by merging of categories. Venous thromboembolism (VTE) encompasses deep vein thrombosis (DVT) and pulmonary embolism (PE). OBJECTIVES: (i) To re-analyze untargeted proteomic data to identify biomarker candidates for future VTE that differ between DVT and PE and are attenuated by extended time between sampling and VTE. (ii) To perform targeted candidate validation. PATIENTS/METHODS: A VTE case-control discovery study and a nested case-control validation study were derived from the general population surveyed in 1994-95. Plasma was obtained at study enrollment, and VTE events were registered until 2007. Untargeted proteomic data were re-analyzed for candidate discovery. Lipopolysaccharide-binding protein (LBP) was validated by enzyme-linked immunosorbent assay. RESULTS: Elevated LBP was discovered as a candidate DVT biomarker in women with less than 3 years between blood sampling and DVT. In the validation study, the odds ratio (OR) for DVT was 2.03 (95% confidence intervals [CI]: 1.53-2.74) per standard deviation (SD) increase in LBP for women with less than 3 years between blood sampling and DVT. Adjustment for age, body mass index, and C-reactive protein attenuated the OR to 1.79 (95% CI: 1.25-2.62) per SD. In the validation study, we observed an OR for VTE of 0.47 (95% CI: 0.28-0.77) for men in the 25th to 50th percentiles when compared to the lowest quartile. CONCLUSIONS: We discovered and validated increased LBP as a predictive biomarker for DVT in women. We found an increased VTE risk for men in the lowest quartile of LBP.

Hierarchical models that address measurement error are needed to evaluate the correlation between treatment effect and control group event rate.

OBJECTIVES: To apply a hierarchical model (HM) that addresses measurement error in regression of the treatment effect on the control group event rate (CR). We compare HM to weighted linear regression (WLR) which is subject to measurement error and mathematical coupling. STUDY DESIGN AND SETTING: We reviewed published HMs that address measurement error and implemented a Bayesian version in open-source code to facilitate adoption by meta-analysts. We compared WLR and HM across a very large convenience sample of meta-analyses published in the Cochrane Database of Systematic Reviews. RESULTS: We applied both approaches (WLR and an HM that addresses measurement error) to 3193 meta-analyses that included 33,071 studies (average 10.28 studies per meta-analysis). A statistically significant slope suggesting an association between the treatment effect and CR was demonstrated with both approaches in 568 (17.19%) meta-analyses, with neither approach in 2036 (63.77%) meta-analyses, only with WLS in 229 (7.17%) and only with HM in 360 (11.28%) meta-analyses. The majority of slopes was negative (WLR 85%, HM 83%). In the majority of cases, HM had wider confidence intervals (72.53%) and slopes farther from the null (64.77%). CONCLUSION: Approximately 28% of meta-analyses demonstrate a significant association between the treatment effect and CR when HM is used to address measurement error, which can suggest frequent lack of portability of the relative effect across baseline risks. User-friendly open-source code is provided to meta-analysts interested in exploring this association.

Cystatin C-based estimated glomerular filtration rate and risk of stroke in the general population: a prospective cohort study.

Background: Previous results on the association between the estimated glomerular filtration rate (eGFR) and stroke are mixed. Most studies derived the eGFR from serum creatinine, which is affected by non-kidney determinants and thus has possibly biased the association with stroke risk. Methods: In this cohort study, we included 429 566 UK Biobank participants (94.5% white, 54% women, age 56 ± 8 years) free of stroke at enrollment. The eGFRcys and eGFRcr were calculated with serum cystatin C and creatinine, respectively. Outcomes of interest were risk of total stroke and subtypes. We investigated the linear and nonlinear associations using Cox proportional hazards models and restricted cubic splines, corrected for regression dilution bias. Results: During an average follow-up of 10.11 years, 4427 incident strokes occurred, among which 3447 were ischemic and 1163 were hemorrhagic. After adjustment for confounders, the regression dilution-corrected hazard ratios (95% confidence intervals) for every 10 mL/min/1.73 m2 decrement in eGFRcys were 1.10 (1.05-1.14) for total stroke and 1.11 (1.08-1.15) for ischemic stroke. A similar pattern was observed with eGFRcr, although the association was weaker. When either type of eGFR was below 75 mL/min/1.73 m2, the risks of total and ischemic stroke increased exponentially as eGFR decreased. A U-shaped relationship was witnessed if eGFRcr was used instead. There was a null association between eGFR and hemorrhagic stroke. Conclusions: The risks of total stroke and ischemic stroke increased exponentially when the eGFRcys fell below 75 mL/min/1.73 m2.

Exploring regression dilution bias using repeat measurements of 2858 variables in ≤49 000 UK Biobank participants.

BACKGROUND: Measurement error in exposures and confounders can bias exposure-outcome associations but is rarely considered. We aimed to assess random measurement error of all continuous variables in UK Biobank and explore approaches to mitigate its impact on exposure-outcome associations. METHODS: Random measurement error was assessed using intraclass correlation coefficients (ICCs) for all continuous variables with repeat measures. Regression calibration was used to correct for random error in exposures and confounders, using the associations of red blood cell distribution width (RDW), C-reactive protein (CRP) and 25-hydroxyvitamin D [25(OH)D] with mortality as illustrative examples. RESULTS: The 2858 continuous variables with repeat measures varied in sample size from 109 to 49 121. They fell into three groups: (i) baseline visit [529 variables; median (interquartile range) ICC = 0.64 (0.57, 0.83)]; (ii) online diet by 24-h recall [22 variables; 0.35 (0.30, 0.40)] and (iii) imaging measures [2307 variables; 0.85 (0.73, 0.94)]. Highest ICCs were for anthropometric and medical history measures, and lowest for dietary and heart magnetic resonance imaging.The ICCs (95% confidence interval) for RDW, CRP and 25(OH)D were 0.52 (0.51, 0.53), 0.29 (0.27, 0.30) and 0.55 (0.54, 0.56), respectively. Higher RDW and levels of CRP were associated with higher risk of all-cause mortality, and higher concentration of 25(OH)D with lower risk. After correction for random measurement error in the main exposure, the associations all strengthened. Confounder correction did not influence estimates. CONCLUSIONS: Random measurement error varies widely and is often non-negligible. For UK Biobank we provide relevant statistics and adaptable code to help other researchers explore and correct for this.

Low High-Density Lipoprotein Cholesterol to Monitor Long-Term Average Increased Triglycerides.

CONTEXT: Increased triglyceride-rich remnants represent a causal risk factor for ischemic cardiovascular disease. OBJECTIVE: We tested the hypothesis that low high-density lipoprotein (HDL) cholesterol can be used to monitor long-term high triglycerides/remnant cholesterol, just as high hemoglobin A1c (HbA1c) can be used to monitor long-term high glucose levels. DESIGN, SETTING, PARTICIPANTS, AND INTERVENTIONS: We studied cross-sectionally 108 731 individuals, dynamically 1313 individuals with lipid measurement at 10 repeated visits, short-term 305 individuals during a fat load, and long-term 10 479 individuals with 2 lipid measurements 10 years apart. MAIN OUTCOME MEASURES: Levels of HDL cholesterol and triglycerides. RESULTS: Cross-sectionally, HDL cholesterol was inversely associated with triglycerides (R2 = 0.26) and remnant cholesterol (R2 = 0.26). Dynamically, major changes in triglyceride levels from measurement to measurement were mimicked by corresponding modest changes in HDL cholesterol. In the short-term after a fat load, median triglycerides increased 96% while HDL cholesterol decreased only 1%. Long-term, in individuals with measurements 10 years apart, those who initially had the highest triglycerides and corresponding lowest HDL cholesterol, still had highest triglycerides and lowest HDL cholesterol 10 years later. Prospectively, individuals with increased triglycerides/remnant cholesterol had increased risk of myocardial infarction; however, when the HDL cholesterol monitoring was removed, increased triglycerides/remnant cholesterol were largely no longer associated with increased risk of myocardial infarction. CONCLUSIONS: Low HDL cholesterol is a stable marker of average high triglycerides/remnant cholesterol. This suggests that low HDL cholesterol can be used to monitor long-term average high triglycerides and remnant cholesterol, analogous to high HbA1c as a long-term monitor of average high glucose levels.

Reliability of Office, Home, and Ambulatory Blood Pressure Measurements and Correlation With Left Ventricular Mass.

BACKGROUND: Determining the reliability and predictive validity of office blood pressure (OBP), ambulatory BP (ABP), and home BP (HBP) can inform which is best for diagnosing hypertension and estimating risk of cardiovascular disease. OBJECTIVES: This study aimed to assess the reliability of OBP, HBP, and ABP and evaluate their associations with left ventricular mass index (LVMI) in untreated persons. METHODS: The Improving the Detection of Hypertension (IDH) study, a community-based observational study, enrolled 408 participants who had OBP assessed at 3 visits, and completed 3 weeks of HBP, 2 24-h ABP recordings, and a 2-dimensional echocardiogram. Mean age was 41.2 ± 13.1 years, 59.5% were women, 25.5% African American, and 64.0% Hispanic. RESULTS: The reliability of 1 week of HBP, 3 office visits with mercury sphygmomanometry, and 24-h ABP were 0.938, 0.894, and 0.846 for systolic and 0.918, 0.847, and 0.843 for diastolic BP, respectively. The correlations among OBP, HBP, and ABP, corrected for regression dilution bias, were 0.74 to 0.89. After multivariable adjustment including OBP and 24-h ABP, 10 mm Hg higher systolic and diastolic HBP were associated with 5.07 (standard error [SE]: 1.48) and 3.92 (SE: 2.14) g/m2 higher LVMI, respectively. After adjustment for HBP, neither systolic or diastolic OBP nor ABP was associated with LVMI. CONCLUSIONS: OBP, HBP, and ABP assess somewhat distinct parameters. Compared with OBP (3 visits) or 24-h ABP, systolic and diastolic HBP (1 week) were more reliable and more strongly associated with LVMI. These data suggest that 1 week of HBP monitoring may be the best approach for diagnosing hypertension.

Reflection on modern methods: calculating a sample size for a repeatability sub-study to correct for measurement error in a single continuous exposure.

Using a continuous exposure variable that is measured with random error in a univariable linear regression model leads to regression dilution bias: the observed association between the exposure and outcome is smaller than it would be if the true value of the exposure could be used. A repeatability sub-study, where a sample of study participants have their data measured again, can be used to correct for this bias. It is important to perform a sample size calculation for such a sub-study, to ensure that correction factors can be estimated with sufficient precision. We describe how a previously published method can be used to calculate the sample size from the anticipated size of the correction factor and its desired precision, and demonstrate this approach using the example of the cross-sectional studies conducted as part of the International Project on Cardiovascular Disease in Russia study. We also provide correction factors calculated from repeat data from the UK Biobank study, which can be used to help plan future repeatability studies.

Usual Blood Pressure and Risk of New-Onset Diabetes: Evidence From 4.1 Million Adults and a Meta-Analysis of Prospective Studies.

BACKGROUND: Reliable quantification of the association between blood pressure (BP) and risk of type 2 diabetes is lacking. OBJECTIVES: This study sought to determine the association between usual BP and risk of diabetes, overall and by participant characteristics. METHODS: A cohort of 4.1 million adults, free of diabetes and cardiovascular disease, was identified using validated linked electronic health records. Analyses were complemented by a meta-analysis of prospective studies that reported relative risks of new-onset diabetes per unit of systolic blood pressure (SBP). RESULTS: Among the overall cohort, 20 mm Hg higher SBP and 10 mm Hg higher diastolic BP were associated with a 58% and a 52% higher risk of new-onset diabetes (hazard ratio: 1.58; 95% confidence interval [CI]: 1.56 to 1.59; and hazard ratio: 1.52; 95% confidence interval: 1.51 to 1.54), respectively. There was no evidence of a nadir to a baseline BP of 110/70 mm Hg. The strength of the association per 20 mm Hg higher SBP declined with age and with increasing body mass index. Estimates were similar even after excluding individuals prescribed antihypertensive or lipid-lowering therapies. Systematic review identified 30 studies with 285,664 participants and 17,388 incident diabetes events. The pooled relative risk of diabetes for a 20 mm Hg higher usual SBP across these studies was 1.77 (1.53 to 2.05). CONCLUSIONS: People with elevated BP are at increased risk of diabetes. The strength of the association declined with increasing body mass index and age. Further research should determine if the observed risk is modifiable.

Regression dilution bias in blood pressure and body mass index in a longitudinal population-based cohort study.

BACKGROUND: Use of single measurement of risk factors can distort their estimated effects, due to random error in measurements. The aim of this study was to examine the extent of underestimation in the estimated effect of common variables in physical exam i.e. systolic and diastolic blood pressure (SBP, DBP) and body mass index (BMI) on cardiovascular diseases in Tehran Lipid and Glucose Study (TLGS). METHODS: A subsample (1167 men and 1786 women) of the original cohort, who had replicate measures of the variables in triennial interval, was used to calculate the regression dilution ratios (RDRs) in men and women. RDRs were determined by parametric and nonparametric methods. Hazard ratios (HR) of risk factors, per one standard deviation change, were corrected for regression dilution bias. RESULTS: The estimated RDRs by parametric method in men and women were 45% and 35% for SBP and 54% and 64% for DBP respectively. There were 26% and 25% underestimation in HR of SBP and 23% and 33% in HR of DBP in men and women. The corresponding underestimation for BMI was about 8%. RDRs of men and women and in age groups by both methods were fairly similar. They were relatively constant during the 10-year follow-up for SBP and BMI. CONCLUSIONS: Using baseline measurements of blood pressure underestimate its real association with CVD events and the estimated HRs. The underestimations are independent of age and sex, and it can be fairly constant in short to moderate time intervals.

The importance of being specific--a meta-analysis evaluating the effect of antibiotics in acute otitis media.

BACKGROUND: Whether acute otitis media (AOM) should be the cause for antibiotic treatment has been a matter of debate during the last decades. Treatment guidelines are based on less than twenty trials that have found the effect of antibiotics on symptomatic outcomes in AOM, such as pain, to be very modest. Two recent trials found a more substantial effect of antibiotics when they looked at treatment failure as the outcome. That the effect varies with the chosen outcome may not only be because the true effect is different but also because different outcomes are more or less specific for the disease in question. OBJECTIVE: The purpose of this study was to perform a meta-analysis to calculate a composite risk ratio for treatment failure in AOM and also to investigate whether the specificity of treatment failure as an outcome differs from that of symptomatic outcomes, such as pain. METHODS: Trials evaluating the effect of antibiotics in AOM and reporting the number of treatment failures were identified and a fixed-effects meta-analysis was performed. In addition, the literature was searched for articles providing direct or indirect figures on the specificity of different outcomes in AOM trials. A hypothetical study was designed to show how differences in sensitivity/specificity of inclusion/outcome criteria affect the results of a trial. RESULTS: The meta-analysis yielded a composite risk ratio of 0.4 (95% CI 0.35-0.48), p<0.001 for the effect of antibiotics on treatment failure. Based on data from the literature, the specificity of treatment failure was estimated to 92-100%. The hypothetical study showed how a non-specific outcome biases the effect estimate towards the null, whereas other kinds of misclassification only decrease precision. CONCLUSION: Future trials should focus on improving diagnostic criteria to increase precision but primarily, they should focus on choosing a specific outcome in order not to get a biased effect estimate.

Within-person variability in calculated risk factors: comparing the aetiological association of adiposity ratios with risk of coronary heart disease.

BACKGROUND: Within-person variability in measured values of a risk factor can bias its association with disease. We investigated the extent of regression dilution bias in calculated variables and its implications for comparing the aetiological associations of risk factors. METHODS: Using a numerical illustration and repeats from 42,300 individuals (12 cohorts), we estimated regression dilution ratios (RDRs) in calculated risk factors [body-mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)] and in their components (height, weight, waist circumference, and hip circumference), assuming the long-term average exposure to be of interest. Error-corrected hazard ratios (HRs) for risk of coronary heart disease (CHD) were compared across adiposity measures per standard-deviation (SD) change in: (i) baseline and (ii) error-corrected levels. RESULTS: RDRs in calculated risk factors depend strongly on the RDRs, correlation, and comparative distributions of the components of these risk factors. For measures of adiposity, the RDR was lower for WHR [RDR: 0.72 (95% confidence interval 0.65-0.80)] than for either of its components [waist circumference: 0.87 (0.85-0.90); hip circumference: 0.90 (0.86-0.93) or for BMI: 0.96 (0.93-0.98) and WHtR: 0.87 (0.85-0.90)], predominantly because of the stronger correlation and more similar distributions observed between waist circumference and hip circumference than between height and weight or between waist circumference and height. Error-corrected HRs for BMI, waist circumference, WHR, and WHtR, were respectively 1.24, 1.30, 1.44, and 1.32 per SD change in baseline levels of these variables, and 1.24, 1.27, 1.35, and 1.30 per SD change in error-corrected levels. CONCLUSIONS: The extent of within-person variability relative to between-person variability in calculated risk factors can be considerably larger (or smaller) than in its components. Aetiological associations of risk factors should be compared through the use of error-corrected HRs per SD change in error-corrected levels of these risk factors.