Sara Mutikainen

In this study self-reported ability to walk 2 km and six-minute walking test (6MWT) performance were examined as predictors of all-cause mortality in 434 women, aged 63–76 years. The primary outcome measure was all-cause mortality (follow-up: 8 years). Predictors were self-reported difficulties in walking 2 km and 6-min walking distance tertiles of ≤495, 496–560 and ≥561 m, and no test result due to refusal by the physician to grant permission to perform the test or participant's inability or unwillingness to perform the test. During the follow-up, 39 participants died. Participants reporting minor (age- and body mass index-adjusted hazard ratio 2.53, 95% confidence interval 1.12–5.69) or major (7.93, 3.49–18.05) difficulties in walking 2 km had increased risk of death compared with those reporting no difficulties. Participants with no 6MWT result (6.99, 2.46–19.86) were at an increased risk of death when compared with participants who walked ≥561 m. A similar trend (2.47, 0.81–7.56) was found for participants with walking distance of ≤495 m during the 6MWT. The trends remained similar after adjustments for other confounders. In conclusion, self-reported difficulties in walking 2 km are associated with an increased risk of death in older community-dwelling women. Objectively measured walking ability gives similar results.

Both left ventricular hypertrophy (LVH) and repolarization phase (RP) are known to be attributable to genetic influences, but less is known whether they share same genetic influences. The aim of this study was to investigate to what extent individual differences in electrocardiographic (ECG) LVH and RP are explained by genetic and environmental influences and whether these influences are shared between these two traits. Resting ECG recordings were obtained from 186 monozygotic and 203 dizygotic female twin individuals, aged 63 to 76 years. Latent factors, called LVH and RP, were formed to condense the information obtained from LVH indices (Cornell voltage and Cornell product) and T-wave amplitudes (leads V(5) and II), respectively. Multivariate quantitative genetic modeling was used both to decompose the phenotypic variances into additive genetic, common environmental, and unique environmental influences, and for the calculation of genetic and environmental correlations between LVH and RP. Additive genetic influences explained 16% of individual differences in LVH and 74% in RP. The remaining individual differences were explained by both common and unique environmental influences. The genetic correlation and unique environmental correlation between LVH and RP were -0.93 and -0.05, respectively. In older women without overt cardiac diseases, RP is under stronger genetic control than LVH. The majority of genetic influences are shared between LVH and RP whereas environmental influences are mainly specific to each.

Background: Previous studies in young and middle‐aged men and women have shown that resting electrocardiographic (ECG) variables are influenced by genetic factors. However, the extent to which resting ECG variables are influenced by genetic factors in older women is unknown. Thus, the aim of this study was to estimate the relative contribution of genetic and environmental influences to individual differences in resting ECG variables among older female twins without overt cardiac diseases. Methods: Resting ECG recordings were obtained from 186 monozygotic and 203 dizygotic twin individuals, aged 63–76 years. Quantitative genetic modeling was used to decompose the phenotypic variance in each resting ECG variable into additive genetic, dominance genetic, shared environmental, and unique environmental influences. Results: The results showed that individual differences in the majority of the resting ECG variables were moderately to highly explained by additive genetic influences, ranging from 32% for T axis to 72% for TV₅. The results also suggested dominance genetic influences on QRS duration, TV₁, and Sokolow–Lyon voltage (36%, 53%, and 57%, respectively). Unique environmental influences were important for each resting ECG variable, whereas shared environmental influences were detected only for QT interval and QTc. Conclusion: In older women without overt cardiac diseases, genetic influences explain a moderate to high proportion of individual differences in the majority of the resting ECG variables. Genetic influences are especially strong for T‐wave amplitudes, left ventricular mass, and hypertrophy indices, whereas other variables, including heart rate, intervals, and axes, are more affected by environmental influences.