Estimating the influence of body mass index (BMI) on mortality using offspring BMI as an instrumental variable

Liver at crossroads: unraveling the links between obesity, chronic liver diseases, and the mysterious obesity paradox

Obesity is a global health issue that is intricately linked to the development and progression of chronic liver disease (CLD). This bidirectional connection, coupled with the obesity paradox (OP), presents a management dilemma. The established influence of obesity on the development and progression of chronic liver disease (CLD) is surpassed by the liver's impact on the onset and advancement of obesity. Patients with CLD always experience increased energy expenditure, reduced appetite, and low protein synthesis, all of which might lead to weight loss. However, metabolic disturbances, hormonal imbalances, inflammatory signaling, immobility, drugs, and alterations in nutrient metabolism can contribute to the development and exacerbation of obesity. Despite the propagation of the OP concept, none of the guidelines has changed, recommending being overweight. Research bias and confounders might be the lifebuoy explanation. Additionally, overlooking the lethal morbidities of obesity for survival benefits full of suffering seems to be an illogical idea. Therefore, rather than endorsing an overweight status, emphasis should be placed on improving cardiorespiratory fitness and preventing sarcopenia to achieve better outcomes in patients with CLD. Accordingly, the complex interplay between obesity, CLD, and the concept of OP requires a sophisticated individualized management approach. Maximizing cardiorespiratory fitness and mitigating sarcopenia should be considered essential strategies for attaining the most favourable outcomes in patients with chronic liver disease (CLD).

The healthcare costs of increased body mass index-evidence from The Trøndelag Health Study

BACKGROUND

Earlier studies have estimated the impact of increased body mass index (BMI) on healthcare costs. Various methods have been used to avoid potential biases and inconsistencies. Each of these methods measure different local effects and have different strengths and weaknesses.

METHODS

In the current study we estimate the impact of increased BMI on healthcare costs using nine common methods from the literature: multivariable regression analyses (ordinary least squares, generalized linear models, and two-part models), and instrumental variable models (using previously measured BMI, offspring BMI, and three different weighted genetic risk scores as instruments for BMI). We stratified by sex, investigated the implications of confounder adjustment, and modelled both linear and non-linear associations.

RESULTS

There was a positive effect of increased BMI in both males and females in each approach. The cost of elevated BMI was higher in models that, to a greater extent, account for endogenous relations.

CONCLUSION

The study provides solid evidence that there is an association between BMI and healthcare costs, and demonstrates the importance of triangulation.

Body mass index and all-cause mortality in HUNT and UK biobank studies: revised non-linear Mendelian randomisation analyses

OBJECTIVES

To estimate the shape of the causal relationship between body mass index (BMI) and mortality risk in a Mendelian randomisation framework.

DESIGN

Mendelian randomisation analyses of two prospective population-based cohorts.

SETTING

Individuals of European ancestries living in Norway or the UK.

PARTICIPANTS

56 150 participants from the Trøndelag Health Study (HUNT) in Norway and 366 385 participants from UK Biobank recruited by postal invitation.

OUTCOMES

All-cause mortality and cause-specific mortality (cardiovascular, cancer, non-cardiovascular non-cancer).

RESULTS

A previously published non-linear Mendelian randomisation analysis of these data using the residual stratification method suggested a J-shaped association between genetically predicted BMI and mortality outcomes with the lowest mortality risk at a BMI of around 25 kg/m2. However, the 'constant genetic effect' assumption required by this method is violated. The reanalysis of these data using the more reliable doubly-ranked stratification method provided some indication of a J-shaped relationship, but with much less certainty as there was less precision in estimates at the lower end of the BMI distribution. Evidence for a harmful effect of reducing BMI at low BMI levels was only present in some analyses, and where present, only below 20 kg/m2. A harmful effect of increasing BMI for all-cause mortality was evident above 25 kg/m2, for cardiovascular mortality above 24 kg/m2, for cancer mortality above 30 kg/m2 and for non-cardiovascular non-cancer mortality above 26 kg/m2. In UK Biobank, the association between genetically predicted BMI and mortality at high BMI levels was stronger in women than in men.

CONCLUSION

This research challenges findings from previous conventional observational epidemiology and Mendelian randomisation investigations that the lowest level of mortality risk is at a BMI level of around 25 kg/m2. Our results provide some evidence that reductions in BMI will increase mortality risk for a small proportion of the population, and clear evidence that increases in BMI will increase mortality risk for those with BMI above 25 kg/m2.

Fiber Consumption Mediates Differences in Several Gut Microbes in a Subpopulation of Young Mexican Adults

Diet is a determinant for bodyweight and gut microbiota composition. Changes in dietary patterns are useful for the prevention and management of overweight and obesity. We aim to evaluate diet behavior and its potential association with selected gut bacteria and body weight among Mexican young adults. Mexican college students aged between 18 and 25 (normal-weight, overweight, and obese) were recruited. Anthropometric variables were recorded. A validated food frequency questionnaire was applied to all the participants. The percentages of macronutrients, fiber, and energy were calculated, and fecal samples were analyzed by real-time-qPCR to quantify selected gut bacteria. All the participants showed an unbalanced dietary pattern. However, the consumption of fruits, non-fat cereals, and oils and fats without protein were higher in the normal-weight individuals. In the overweight/obese participants, fiber intake did not correlate with the microbial variables, while Kcal from protein and Clostridium leptum correlated positively with Lactobacillus. Similarly, Clostridium coccoides-Eubacterium rectale correlated with Akkermansia muciniphila. In the normal-weight participants, Clostridium leptum and Lactobacillus correlated positively with Clostridium coccoides-Eubacterium rectale and Bifidobacterium, respectively, and Bacteroidetes negatively with Akkermansia muciniphila. In conclusion, a higher fiber intake had a positive impact on body weight and bacterial gut composition in this Mexican population of college students.