This one delves further into the cardiometabolic impact of body fat distribution, finding associations between visceral, abdominal subcutaneous, and gluteofemoral adipose tissue volumes at scale and risk of type 2 diabetes, and coronary artery disease.
This is not the first study of this group in this subject. They have done some previous, related, and very interesting work on the matter:
- The intention was to quantify visceral, abdominal subcutaneous, and gluteofemoral adipose tissue volumes at scale using machine learning and data from the studies mentioned above, in order to determine associations with type 2 diabetes and coronary artery disease.
- To measure specific fat depot volumes at scale, they used BMI-adjusted metrics for each fat depot (visceral, abdominal subcutaneous, and gluteofemoral adipose tissue volumes adjusted for BMI).
The findings were in line with several other studies:
- The study demonstrated a consistent trend of visceral adipose at scale to be associated with increased risk of type 2 diabetes and coronary artery disease.
- Abdominal subcutaneous adipose tissue at scale was found to be largely risk-neutral.
- Gluteofemoral adipose tissue at scale was found to be protective.
Important to note that since the UK biobank is largely consisted of a White, Causasian population that "although our data suggests similar performance of our deep learning models across self-reported ethnicity subgroups...
"...we were underpowered to study disease associations in non-White subgroups."
BMI-adjusted adipose tissue volumes exhibit depot-specific and divergent associations with cardiometabolic diseases (open access)
This one suggests that even though screen-viewing was higher post-lockdown compared to pre-COVID-19 and the high increases reported in previous studies have not, on average, been sustained post-lockdown, not all families were able to break this habit in children.
- The aim of this paper is to examine how screen-viewing changed in 10–11-year-old children over the COVID-19 pandemic in the UK, how this compares to before the pandemic, and what are the influences on screen-viewing behaviour.
- Although screen-viewing was higher post-lockdown compared to pre-COVID-19, the high increases reported during lockdowns were not, on average, sustained post-lockdown.
Here, both metabolically healthy and metabolically unhealthy obesity were associated with higher risk of cancer, although though the risk relationships were weaker in the latter case.
- The combination of obesity and metabolically unhealthy status conveyed the highest risk of any obesity-related cancer, compared to other combinations of BMI and metabolic health status.
- The increased risk was found for most obesity-related cancers, with the highest relative risks found for endometrial, liver, and renal cell cancer.
This one provides further evidence to the notion that that muscle growth does not contribute to the increases in strength that occur after resistance training.
- Often the presence of muscle growth is used as evidence for its causal role in improving strength.
- However, the purported paradigm that muscle growth contributes to strength change became less clear with the emergence of low-load (or no external load) resistance training...
The findings of this one suggest that muscle fatigue per se cannot explain the loss of work efficiency during constant-load exercise above the gas exchange threshold (~50%-60% of VO2max), but muscle activation heterogeneity and metabolism can partially account for both.
- No temporal relationship between loss of work efficiency and the behaviour of muscle force production was observed.
- Loss of torque production, changes in the ratio between muscle V˙O2 kinetics and O2 delivery, a greater rating of perceived exertion, and the loss of work efficiency --mainly during very heavy exercise-- appear to share physiological mechanisms of similar origin.
Contrary to some studies suggesting that time‐restricted eating could improve circadian rhythms and play a role in metabolic regulation, this one found that the frequency and the size, rather than the timing, of meals to be stronger determinants of weight change over time.
- The window of time between first to last meal was not associated with weight change over an average of about 6 years of follow‐up.
- The average daily number of large and medium meals was associated with increased weight over time, suggesting that the meal frequency and meal sizes, rather than the timing of meals, was a stronger determinant of weight gain over time.
The findings of this one suggest that a high adherence to a diet that is rich in protein and unsaturated fatty acids may have beneficial long-term effects on liver fat and lipid metabolism in older subjects.
- An increased intake of protein, total fat, MUFA, PUFA and fiber as well as a decreased consumption of SFAs was achieved in the intervention group.
- Adjusted for baseline intrahepatic lipids, age, sex and BMI change, a reduction of intrahepatic lipids by 33.3% was seen in the intervention group, but the median reduction was not statistically significantly compared to the control group.