Non-exercise equations to estimate fitness in white European and South Asian men

© 2015 American College of Sports Medicine PURPOSE: Cardiorespiratory fitness is a strong, independent predictor of health, whether it is measured in an exercise test or estimated in an equation. The purpose of this study was to develop and validate equations to estimate fitness in middle-aged white European and South Asian men. METHODS: Multiple linear regression models (n=168, including 83 white European and 85 South Asian men) were created using variables that are thought to be important in predicting fitness (VO2 max, mL⋅kg⋅min): age (years); BMI (kg·m); resting heart rate (beats⋅min); smoking status (0=never smoked, 1=ex or current smoker); physical activity expressed as quintiles (0=quintile 1, 1=quintile 2, 2=quintile 3, 3=quintile 4, 4=quintile 5), categories of moderate- to vigorous-intensity physical activity (0=150-225 min⋅wk, 3=>225-300 min⋅wk, 4=>300 min⋅wk), or minutes of moderate- to vigorous-intensity physical activity (min⋅wk); and, ethnicity (0=South Asian, 1=white). The leave-one-out-cross-validation procedure was used to assess the generalizability and the bootstrap and jackknife resampling techniques were used to estimate the variance and bias of the models. RESULTS: Around 70% of the variance in fitness was explained in models with an ethnicity variable, such as: VO2 max = 77.409 - (age*0.374) – (BMI*0.906) – (ex or current smoker*1.976) + (physical activity quintile coefficient) – (resting heart rate*0.066) + (white ethnicity*8.032), where physical activity quintile 1 is 1, 2 is 1.127, 3 is 1.869, 4 is 3.793, and 5 is 3.029. Only around 50% of the variance was explained in models without an ethnicity variable. All models with an ethnicity variable were generalizable and had low variance and bias. CONCLUSION: These data demonstrate the importance of incorporating ethnicity in non-exercise equations to estimate cardiorespiratory fitness in multi-ethnic populations

The Forest Plot for the effect of TNFi on HOMA index.

<p>The Forest Plot for the effect of TNFi on HOMA index.</p

The Forest Plot for the effect of TNFi on QUICKI.

<p>The Forest Plot for the effect of TNFi on QUICKI.</p

Funnel plots (A) for HOMA from 8 selected studies and (B) for QUICKI from 4 selected studies evaluating effects of TNFi on IR/IS.

<p>Funnel plots (A) for HOMA from 8 selected studies and (B) for QUICKI from 4 selected studies evaluating effects of TNFi on IR/IS.</p

Flow chart of studies identification and selection.

<p>Flow chart of studies identification and selection.</p

<strong>Genetic evidence strongly supports managing weight and blood pressure in addition to glycemic control in preventing vascular complications in people with type 2 diabetes </strong>

Objective: To investigate the causal association of type 2 diabetes and its components on the risk of vascular complications independent of shared risk factors obesity and hypertension, and to identify the main driver of this risk.  Study design and method We conducted Mendelian randomization using independent genetic variants previously associated with type 2 diabetes, fasting glucose, HbA1c, fasting insulin, BMI, and systolic blood pressure as instrumental variables. We obtained summary-level data for 18 vascular diseases (15 for type 2 diabetes) from FinnGen and publicly available genome-wide association studies as our outcomes. We conducted univariable and multivariable Mendelian randomization, in addition to sensitivity tests to detect and minimize pleiotropic effects. Results Univariable Mendelian randomization analysis showed that type 2 diabetes was associated with 9 of 15 outcomes, BMI and systolic blood pressure with 13 and 15 of 18 vascular outcomes, fasting insulin with 4, and fasting glucose with 2. No robust association was found for HbA1c instruments. Adjusting for correlated traits in the multivariable test, BMI and systolic blood pressure maintained consistent causal effects, while five associations with type 2 diabetes (chronic kidney disease, ischemic heart disease, heart failure, subarachnoid haemorrhage, and intracerebral haemorrhage) were attenuated to null.  Conclusion Our findings add strong evidence to support the importance of BMI and systolic blood pressure in the development of vascular complications in people with type 2 diabetes. Such findings strongly support the need for better weight and blood pressure management in type 2 diabetes, independent of glucose lowering, to limit important complications.</p

Genetic Evidence Strongly Supports Managing Weight and Blood Pressure in Addition to Glycemic Control in Preventing Vascular Complications in People With Type 2 Diabetes.

OBJECTIVETo investigate the causal association of type 2 diabetes and its components with risk of vascular complications independent of shared risk factors obesity and hypertension and to identify the main driver of this risk.RESEARCH DESIGN AND METHODSWe conducted Mendelian randomization (MR) using independent genetic variants previously associated with type 2 diabetes, fasting glucose, HbA1c, fasting insulin, BMI, and systolic blood pressure as instrumental variables. We obtained summary-level data for 18 vascular diseases (15 for type 2 diabetes) from FinnGen and publicly available genome-wide association studies as our outcomes. We conducted univariable and multivariable MR, in addition to sensitivity tests to detect and minimize pleiotropic effects.RESULTSUnivariable MR analysis showed that type 2 diabetes was associated with 9 of 15 outcomes; BMI and systolic blood pressure were associated with 13 and 15 of 18 vascular outcomes, respectively; and fasting insulin was associated with 4 and fasting glucose with 2. No robust association was found for HbA1c instruments. With adjustment for correlated traits in the multivariable test, BMI and systolic blood pressure, consistent causal effects were maintained, while five associations with type 2 diabetes (chronic kidney disease, ischemic heart disease, heart failure, subarachnoid hemorrhage, and intracerebral hemorrhage) were attenuated to null.CONCLUSIONSOur findings add strong evidence to support the importance of BMI and systolic blood pressure in the development of vascular complications in people with type 2 diabetes. Such findings strongly support the need for better weight and blood pressure management in type 2 diabetes, independent of glucose lowering, to limit important complications.</p

Relationship between measured variables and underlying latent factors.

<p>Numbers in arrows show factor loadings. Relationships between latent factors and measured variables only shown for rotated factor loadings >0.32 (i.e. where observed variable explains >10% of the variance in the latent factor (0.32² = 0.10)). See methods for further details.</p

Additional file 1: Table S1. of Association of maternal diabetes/glycosuria and pre-pregnancy body mass index with offspring indicators of non-alcoholic fatty liver disease

Univariable associations of maternal diabetes status, by maternal existing diabetes, gestational diabetes and glycosuria compared to no diabetes/glycosuria with offspring USS and blood-based markers of non-alcoholic fatty liver disease. Table S2. Results of the multivariable model (model 4) of the association of maternal diabetes/glycosuria with offspring USS determined fatty liver. Table S3. Results of the multivariable model (model 4) of the association of maternal pre-pregnancy obesity status and BMI with offspring USS determined fatty liver. Table S4. Multivariable associations (model 4, with adjustment for offspring concurrent BMI) of maternal diabetes/glycosuria with offspring USS and blood-based markers of non-alcoholic fatty liver disease. (N = 1,215 or 2,358 as indicated). Table S5. Multivariable associations of maternal pre-pregnancy BMI ((model 4, with adjustment for offspring concurrent BMI)) with offspring USS and blood-based markers of non-alcoholic fatty liver disease. (N = 1,215 or 2,358 as indicated). (DOCX 26 kb