Effects of data preprocessing on results of the epidemiological analysis of coronary heart disease and behaviour-related risk factors

Voutilainen, Ari; Brester, Christina; Kolehmainen, Mikko; Tuomainen, Tomi‐Pekka

doi:10.1080/07853890.2021.1921838

Cited by 7 publications

(12 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, we used the fasting serum low-density lipoprotein cholesterol (S-LDL-C) concentration instead of the fasting serum total cholesterol (STC) concentration to detect high cholesterol levels. In our previous paper, we had used STC [ 26 ], but preliminary analyses of this study revealed that S-LDL-C could provide even stronger associations with CHD. Based on S-LDL-C concentration we categorised study participants as follows: S-LDL-C < 3.4 mmol/L indicating below borderline concentrations, S-LDL-C 3.4 − 4.1 mmol/L indicating borderline high concentrations, and S-LDL-C > 4.1 mmol/L or cholesterol-lowering medication indicating high concentrations.…”

Section: Methodsmentioning

confidence: 99%

“…We also excluded measures of physical activity since the proportion of physically inactive men in the KIHD cohort is practically zero and, consequently, it is impossible to estimate the impact of sedentary lifestyle on the risk of CHD. Moreover, based on our previous analyses physical activity levels very poorly predict the risk of CHD in this cohort [ 26 ]. Other studies also have found the contradictory nature of physical activity, as in some study populations physical activity, not inactivity, is associated with an increased risk of CHD [ 9 ].…”

Section: Methodsmentioning

confidence: 99%

“…We used the covariates as categorical variables and investigated the Schoenfeld residuals to test the proportional hazards assumption [ 40 ]. Based on our previous study the type of covariate, categorical or continuous, has probably no statistically significant effect on Cox model results [ 26 ] but including continuous covariates in the model requires the assessment of nonlinearity by means of martingale residuals [ 41 ]. Second, we added statistically significant covariate interactions to the Cox model.…”

Section: Methodsmentioning

confidence: 99%

“…On the other hand, this study focussed only on White Finnish males without detailed information regarding their genetic risk for CHD, which limits possibilities to generalise its findings [ 57 ]. Moreover, this study refers specifically to CHD, ICD 10 codes I20 − I25, as an endpoint, and because the main CHD risk factors are to some extent outcome sensitive [ 26 ], i.e. explanatory powers and the order of importance among risk factors slightly differ across endpoints, such as CHD, an acute myocardial infarction (AMI), and a fatal AMI, the present results are not directly generalisable to AMI and sudden cardiac death, although them are typical manifestations of CHD.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

“…explanatory powers and the order of importance among risk factors slightly differ across endpoints, such as CHD, an acute myocardial infarction (AMI), and a fatal AMI, the present results are not directly generalisable to AMI and sudden cardiac death, although them are typical manifestations of CHD. Our previous paper provides analyses to verify this outcome sensitivity [ 26 ]. To control possible bias originated from inaccuracies related to exclusions of study participants based on the ergometer test we executed statistical analyses and reported their results also concerning the dataset without exclusions.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

See 4 more Smart Citations

Epidemiological analysis of coronary heart disease and its main risk factors: are their associations multiplicative, additive, or interactive?

et al. 2022

Self Cite

View full text Add to dashboard Cite

Objective The purpose of this study was to discover how considering multiplicative, additive, and interactive effects modifies results of a prospective cohort study on coronary heart disease (CHD) incidence and its main risk factors. Material and methods The Kuopio Ischaemic Heart Disease Risk Factor (KIHD) Study provided the study material, 2682 Eastern Finnish middle-aged men, followed since the 1980s. We applied multiplicative and additive survival models together with different statistical metrics and confidence intervals for risk ratios and risk differences to estimate the nature of associations. Results The mean (SD) follow-up time among men who were free of CHD at baseline ( n = 1958) was 21.4 (10.4) years, and 717 (37%) of them had the disease and 301 (15%) died for CHD before the end of follow-up. All tested non-modifiable and modifiable risk factors statistically significantly predicted CHD incidence. We detected three interactions: circulating low-density lipoprotein cholesterol (LDL-C) × age, obesity × age, and obesity × smoking of which LDL-C × age was the most evident one. High LDL-C increased the risk of CHD more among men younger than 50 [risk ratio (RR) 2.10] than those older than 50 (RR 1.22). LDL-C status was the only additive covariate. The additive effect of high LDL-C increased almost linearly up to 18 years and then reached a plateau. The simple multiplicative survival model stressed glycemic status as the strongest modifiable risk factor for developing CHD [hazard ratio (HR) for diabetes vs. normoglycemia was 2.69], whereas the model considering interactions and time dependence emphasised the role of LDL-C status (HR for high LDL-C vs. lower than borderline was 4.43). Age was the strongest non-modifiable predictor. Conclusions Including covariate interactions and time dependence in survival models potentially refine results of epidemiological analyses and ease to define the order of importance across CHD risk factors. KEY MESSAGES Including covariate interactions and time dependence in survival models potentially refine results of epidemiological analyses on coronary heart disease. Including covariate interactions and time dependence in survival models potentially ease to define the order of importance across coronary heart disease risk factors.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Strengths and Limitationsmentioning

confidence: 99%

Section: Strengths and Limitationsmentioning

confidence: 99%

See 3 more Smart Citations

Epidemiological analysis of coronary heart disease and its main risk factors: are their associations multiplicative, additive, or interactive?

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

Lipid profile, lipid ratios, apolipoproteins, and risk of cardiometabolic multimorbidity in men: The Kuopio Ischaemic Heart Disease Risk Factor Study

Tajik

Voutilainen

Kauhanen

et al. 2022

Lipids

Self Cite

View full text Add to dashboard Cite

The blood level of lipids, apolipoproteins, and lipid ratios are important predictors of some chronic diseases. However, their association with cardiometabolic multimorbidity (CMM) is less known. We evaluated a wide range of lipid profiles and lipid ratios, including low‐density lipoprotein‐cholesterol (LDL‐C), very‐low‐density lipoprotein‐cholesterol (VLDL‐C), high‐density lipoprotein‐cholesterol (HDL‐C), and apoA1 and B, as well triglyceride and total cholesterol with risk of incident CMM. In 1728 men aged 52.5 ± 5.2 years from the Kuopio Ischaemic Heart Disease were included in this study. We defined CMM as coexisting of two or more of stroke, type 2 diabetes mellitus (T2D), coronary heart disease (CHD). A Cox proportional hazard regression method was applied to evaluate the risk of CMM against the exposures. During the mean follow‐up of 22.4 years, 335 men suffered from CMM conditions. Higher serum triglyceride and VLDL concentrations were associated with a higher risk of coexisting T2D‐CHD (HRs 1.99 (95% CI, 1.12–3.53) and HRs 1.79 (95% CI, 1.04–3.11), respectively. Whereas higher HDL was associated with lower incident [HRs 0.49 (95% CI, 0.40–1.00)]. The HRs for coexisting T2D‐CHD was 2.02 (95% CI, 1.01–3.07) for total cholesterol/HDL‐C, 1.85 (95% CI, 1.04–3.29) for triglyceride/HDL‐C, 1.69 (95% CI, 1.01–2.31) for Non‐HDL‐C/HDL‐C, and 1.89 (95% CI, 1.03–2.46) for apoB/apoA1. In contrast, serum LDL‐C/apoB ratios were inversely associated with the risk of coexisting T2D‐CHD [HRs 0.50 (95% CI, 0.28–0.90)]. No associations were observed between our exposures and other CMM conditions. In conclusion, elevated triglyceride, VLDL‐C, total cholesterol/HDL‐C, TG/HDL‐C, apoB/apoA1 as well as lower LDL‐C/apoB were independently associated with the higher risk of T2D‐CHD coexistence.

show abstract

Life’s Essential 8 and the risk of cardiovascular disease death and all-cause mortality in Finnish men

Isiozor

Kunutsor

Voutilainen

et al. 2023

European Journal of Preventive Cardiology

View full text Add to dashboard Cite

Aim To examine the association between Life’s Essential 8 (LE8) and the risk of cardiovascular and all-cause mortality. Methods The LE8 was computed for 1662 men, aged 42 to 60 years, without pre-existing history of CVD at baseline in the Kuopio Ischaemic Heart Disease study. The LE8 factors include diet, physical activity, nicotine exposure, sleep, body mass index, blood pressure, blood glucose and lipids. Each LE8 factor was scored between 0 to 100 points. The summation of all points generated the total LE8 score, which was categorized into quartiles - ≤ 420; > 420 to 485; > 485 to 550; and >550. Multivariable Cox regression models were used to estimate hazard ratios and 95% confidence intervals of LE8 scores for the outcomes. Results During a median follow-up of 30 years, 402 and 987 men died from CVD and any cause, respectively. The total LE8 score among participants ranged from 185 to 750. The higher the LE8 scores, the lower the risk of dying from CVD and all-cause. Following adjustment for age, alcohol consumption and socioeconomic status, every 50-unit increase in LE8 score was associated with 17% and 14% lower risk of CVD and all-cause deaths, respectively. Men within LE8 top quartile had 60% lower risk of CVD mortality when compared with those within the bottom quartile. Conclusion Life’s Essential 8 was strongly and inversely associated with the risk of CVD death and all-cause mortality among ageing men. Measures that promote optimal LE8 scores should be encouraged among the general population.

show abstract

Effects of data preprocessing on results of the epidemiological analysis of coronary heart disease and behaviour-related risk factors

Abstract: Tuomainen (2021) Effects of data preprocessing on results of the epidemiological analysis of coronary heart disease and behaviour-related risk factors,

Cited by 7 publications

References 29 publications

Epidemiological analysis of coronary heart disease and its main risk factors: are their associations multiplicative, additive, or interactive?

Epidemiological analysis of coronary heart disease and its main risk factors: are their associations multiplicative, additive, or interactive?

Lipid profile, lipid ratios, apolipoproteins, and risk of cardiometabolic multimorbidity in men: The Kuopio Ischaemic Heart Disease Risk Factor Study

Life’s Essential 8 and the risk of cardiovascular disease death and all-cause mortality in Finnish men

Contact Info

Product

Resources

About