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Fermented foods and fibre may lower stress levels – new study

Our latest study adds further evidence that diet and mental health are closely connected.

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Foods such as kimchi are great to include in a psychobiotic diet. Nungning20/ Shutterstock

When it comes to dealing with stress, we’re often told the best things we can do are exercise, make time for our favourite activities or try meditation or mindfulness.

But the kinds of foods we eat may also be an effective way of dealing with stress, according to research published by me and other members of APC Microbiome Ireland. Our latest study has shown that eating more fermented foods and fibre daily for just four weeks had a significant effect on lowering perceived stress levels.

Over the last decade, a growing body of research has shown that diet can have a huge impact on our mental health. In fact, a healthy diet may even reduce the risk of many common mental illnesses.

The mechanisms underpinning the effect of diet on mental health are still not fully understood. But one explanation for this link could be via the relationship between our brain and our microbiome (the trillions of bacteria that live in our gut). Known as the gut-brain axis, this allows the brain and gut to be in constant communication with each other, allowing essential body functions such as digestion and appetite to happen. It also means that the emotional and cognitive centres in our brain are closely connected to our gut.

While previous research has shown stress and behaviour are also linked to our microbiome, it has been unclear until now whether changing diet (and therefore our microbiome) could have a distinct effect on stress levels.

This is what our study set out to do. To test this, we recruited 45 healthy people with relatively low-fibre diets, aged 18–59 years. More than half were women. The participants were split into two groups and randomly assigned a diet to follow for the four-week duration of the study.

A bowl of slices apples.
Participants were told to eat foods high in prebiotic fibres, such as apples. gowithstock/ Shutterstock

Around half were assigned a diet designed by nutritionist Dr Kirsten Berding, which would increase the amount of prebiotic and fermented foods they ate. This is known as a “psychobiotic” diet, as it included foods that have been linked to better mental health.

This group was given a one-on-one education session with a dietitian at both the start and halfway through the study. They were told they should aim to include 6-8 servings daily of fruits and vegetables high in prebiotic fibres (such as onions, leeks, cabbage, apples, bananas and oats), 5-8 servings of grains per day, and 3-4 servings of legumes per week. They were also told to include 2-3 servings of fermented foods daily (such as sauerkraut, kefir and kombucha). Participants on the control diet only received general dietary advice, based on the healthy eating food pyramid.

Less stress

Intriguingly, those who followed the psychobiotic diet reported they felt less stressed compared with those who followed the control diet. There was also a direct correlation between how strictly participants followed the diet and their perceived stress levels, with those who ate more psychobiotic foods during the four-week period reporting the greatest reduction in perceived stress levels.

Interestingly, the quality of sleep improved in both groups – though those on the psychobiotic diet reported greater improvements in sleep. Other studies have also shown that gut microbes are implicated in sleep processes, which may explain this link.

The psychobiotic diet only caused subtle changes in the composition and function of microbes in the gut. However, we observed significant changes in the level of certain key chemicals produced by these gut microbes. Some of these chemicals have been linked to mental health, which could potentially explain why participants on the diet reported feeling less stressed.

Our results suggest specific diets can be used to reduce perceived stress levels. This kind of diet may also help to protect mental health in the long run as it targets the microbes in the gut.

While these results are encouraging, our study is not without its limitations. First, the sample size is small due to the pandemic restricting recruitment. Second, the short duration of the study could have limited the changes we observed – and it’s unclear how long they would last. As such, long-term studies will be needed.

Third, while participants recorded their daily diet, this form of measurement can be susceptible to error and bias, especially when estimating food intake. And while we did our best to ensure participants didn’t know what group they’d been assigned to, they may have been able to guess based on the nutrition advice they were given. This may have affected the responses they gave at the end of the study. Finally, our study only looked at people who were already healthy. This means we don’t understand what effect this diet could have on someone who may not be as healthy.

Still, our study offers exciting evidence that an effective way to reduce stress may be through diet. It will be interesting to know if these results can also be replicated in people suffering from stress-related disorders, such as anxiety and depression. It also adds further evidence to this field of research, showing evidence of an association between diet, our microbiome and our mental health.

So the next time you’re feeling particularly stressed, perhaps you’ll want to think more carefully about what you plan on eating for lunch or dinner. Including more fibre and fermented foods for a few weeks may just help you feel a little less stressed out.

John Cryan receives funding from Science Foundation Ireland (SFI), Irish Research Council and the Health Research Board. He also receives funding from the Saks-Kavanaugh Foundation. The author receives research funding, has been a consultant and been on the Speakers Bureau of food and pharmaceutical companies in the microbiome, food and neuroscience arena.

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New research reveals gut microbiota link to colitis: intestinal epithelial axin1 deficiency offers protective effects

A groundbreaking study conducted by Jun Sun’s research team at the University of Illinois Chicago has revealed a new and critical role of Axin1 in regulating…

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A groundbreaking study conducted by Jun Sun’s research team at the University of Illinois Chicago has revealed a new and critical role of Axin1 in regulating intestinal epithelial development and microbial homeostasis. The research, published in the journal Engineering, highlights the potential therapeutic strategies for human inflammatory bowel disease (IBD).

Credit: Shari Garrett et al.

A groundbreaking study conducted by Jun Sun’s research team at the University of Illinois Chicago has revealed a new and critical role of Axin1 in regulating intestinal epithelial development and microbial homeostasis. The research, published in the journal Engineering, highlights the potential therapeutic strategies for human inflammatory bowel disease (IBD).

IBD, a chronic inflammatory disorder affecting the gastrointestinal tract, has been a significant health concern worldwide. The study focused on understanding the role of Axin1, a negative regulator of Wnt/β-catenin signaling, in maintaining gut homeostasis and host response to inflammation.

The research team analyzed Axin1 expression in human inflammatory bowel disease datasets and found increased Axin1 expression in the colonic epithelium of IBD patients. To further investigate the effects and mechanism of intestinal Axin1 in regulating intestinal homeostasis and colitis, the team generated new mouse models with Axin1 conditional knockout in intestinal epithelial cells (Axin1ΔIEC) and Paneth cells (Axin1ΔPC).

The results showed that Axin1ΔIEC mice exhibited altered goblet cell spatial distribution, Paneth cell morphology, reduced lysozyme expression, and an enriched presence of Akkermansia muciniphila (A. muciniphila) in the gut microbiota. Importantly, the absence of intestinal epithelial and Paneth cell Axin1 led to decreased susceptibility to dextran sulfate sodium-induced colitis in vivo.

Furthermore, when Axin1ΔIEC and Axin1ΔPC mice were cohoused with control mice, they became more susceptible to dextran sulfate sodium (DSS)-colitis, suggesting the protective role of Axin1 in the presence of a healthy gut microbiota. Treatment with A. muciniphila further reduced the severity of DSS-colitis, highlighting its potential as a therapeutic target.

Interestingly, antibiotic treatment did not change the proliferation of intestinal epithelial cells in the control mice. However, in Axin1ΔIEC mice with antibiotic treatment, the intestinal proliferative cells were significantly reduced, indicating the non-colitogenic effects driven by the gut microbiome.

These findings demonstrate the novel role of Axin1 in mediating intestinal homeostasis and the microbiota. The loss of intestinal Axin1 protects against colitis, likely through the regulation of epithelial Axin1 and Axin1-associated A. muciniphila. Further mechanistic studies using specific Axin1 mutations will be crucial in elucidating how Axin1 modulates the microbiome and host inflammatory response, paving the way for new therapeutic strategies for human IBD.

Jiaming Wu, editor of the subject of medicine and health of Engineering, commented, “This study provides valuable insights into the development of inflammatory bowel disease and offers potential therapeutic strategies for its treatment. By understanding the intricate interactions between Axin1, the gut microbiota, and host immunity, researchers can develop targeted interventions to restore intestinal homeostasis and alleviate the symptoms of IBD.”

The research team’s findings have significant implications for the field of gastroenterology and hold promise for the development of novel treatments for IBD. As further studies are conducted, the scientific community eagerly awaits the potential therapeutic breakthroughs that may arise from this research.

The paper “Profiling the Antimalarial Mechanism of Artemisinin by Identifying Crucial Target Proteins”, authored by Shari Garrett, Yongguo Zhang, Yinglin Xia, Jun Sun. Full text of the open access paper: https://doi.org/10.1016/j.eng.2023.06.007. For more information about the Engineering, follow us on Twitter (https://twitter.com/EngineeringJrnl) & like us on Facebook (https://www.facebook.com/EngineeringPortfolio).

 

About Engineering

Engineering (ISSN: 2095-8099 IF:12.8) is an international open-access journal that was launched by the Chinese Academy of Engineering (CAE) in 2015. Its aims are to provide a high-level platform where cutting-edge advancements in engineering R&D, current major research outputs, and key achievements can be disseminated and shared; to report progress in engineering science, discuss hot topics, areas of interest, challenges, and prospects in engineering development, and consider human and environmental well-being and ethics in engineering; to encourage engineering breakthroughs and innovations that are of profound economic and social importance, enabling them to reach advanced international standards and to become a new productive force, and thereby changing the world, benefiting humanity, and creating a new future.


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The New York Fed DSGE Model Forecast— September 2023

This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE)…

This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since June 2023. As usual, we wish to remind our readers that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and variables discussed here, see our DSGE model Q & A.

The New York Fed model forecasts use data released through 2023:Q2, augmented for 2023:Q3 with the median forecasts for real GDP growth and core PCE inflation from the Survey of Professional Forecasters (SPF), as well as the yields on ten-year Treasury securities and Baa-rated corporate bonds based on 2023:Q3 averages up to August 30. Moreover, starting in 2021:Q4, the expected federal funds rate between one and six quarters into the future is restricted to equal the corresponding median point forecast from the latest available Survey of Primary Dealers (SPD) in the corresponding quarter. The current projection can be found here.

The change in the forecast relative to June reflects the fact that the economy remains resilient in spite of the increasingly restrictive stance of monetary policy. Output growth is projected to be almost 1 percentage point higher in 2023 than forecasted in June (1.9 versus 1.0 percent) and somewhat higher than June for the rest of the forecast horizon (1.1, 0.7, and 1.2 percent in 2024, 2025, and 2026, versus 0.7, 0.4, and 0.9 in June, respectively). The probability of a not-so-soft recession, as defined by four-quarter GDP growth dipping below -1 percent by the end of 2023, has become negligible at 4.6 percent, down from 26 percent in June. According to the model, much of the resilience in the economy so far stems from the surprising strength in the financial sector, which counteracts the effects of the tightening in monetary policy. Inflation projections are close to what they were in June: 3.7 percent for 2023 (unchanged from the previous forecast), 2.2 percent for 2024 (down from 2.5 percent), and 2.0 percent for both 2025 and 2026 (down from 2.2 and 2.1 percent, respectively). The model still sees inflation returning close to the FOMC’s longer-run goal by the end of next year.

The output gap is projected to be somewhat higher over the forecast horizon than it was in June, consistent with the fact that the surprising strength of the economy is mainly driven by demand factors such as financial shocks, as opposed to supply factors. As in the June forecast, the gap gradually declines from its current positive value to a slightly negative value by 2025. The real natural rate of interest is estimated at 2.5 percent for 2023 (up from 2.2 percent in June), declining to 2.2 percent in 2024, 1.9 percent in 2025, and 1.6 percent in 2026. 

Forecast Comparison

Forecast Period2023202420252026
Date of ForecastSep 23Jun 23Sep 24Jun 24Sep 25Jun 25Sep 26Jun 26
GDP growth
(Q4/Q4)
1.9
 (0.2, 3.6) 
1.0
 (-1.9, 4.0) 
1.1
 (-4.0, 6.3) 
0.7
 (-4.2, 5.7) 
0.7
 (-4.4, 5.8) 
0.4
 (-4.7, 5.5) 
1.2
 (-4.2, 6.6) 
0.9
 (-4.5, 6.3) 
Core PCE inflation
(Q4/Q4)
3.7
 (3.4, 3.9) 
3.7
 (3.3, 4.2) 
2.2
 (1.5, 3.0) 
2.5
 (1.6, 3.3) 
2.0
 (1.1, 2.9) 
2.2
 (1.2, 3.1) 
2.0
 (1.0, 3.0) 
2.1
 (1.1, 3.2) 
Real natural rate of interest
(Q4)
2.5
 (1.3, 3.7) 
2.2
 (1.0, 3.5) 
2.2
 (0.8, 3.7) 
1.8
 (0.3, 3.2) 
1.9
 (0.3, 3.4) 
1.5
 (-0.1, 3.0) 
1.6
 (-0.0, 3.3) 
1.3
 (-0.4, 3.0) 
Source: Authors’ calculations.
Notes: This table lists the forecasts of output growth, core PCE inflation, and the real natural rate of interest from the September 2023 and June 2023 forecasts. The numbers outside parentheses are the mean forecasts, and the numbers in parentheses are the 68 percent bands.

Forecasts of Output Growth

Source: Authors’ calculations.
Notes: These two panels depict output growth. In the top panel, the black line indicates actual data and the red line shows the model forecasts. The shaded areas mark the uncertainty associated with our forecasts at 50, 60, 70, 80, and 90 percent probability intervals. In the bottom panel, the blue line shows the current forecast (quarter-to-quarter, annualized), and the gray line shows the June 2023 forecast.

Forecasts of Inflation

Source: Authors’ calculations.
Notes: These two panels depict core personal consumption expenditures (PCE) inflation. In the top panel, the black line indicates actual data and the red line shows the model forecasts. The shaded areas mark the uncertainty associated with our forecasts at 50, 60, 70, 80, and 90 percent probability intervals. In the bottom panel, the blue line shows the current forecast (quarter-to-quarter, annualized), and the gray line shows the June 2023 forecast.

Real Natural Rate of Interest

Source: Authors’ calculations.
Notes: The black line shows the model’s mean estimate of the real natural rate of interest; the red line shows the model forecast of the real natural rate. The shaded area marks the uncertainty associated with the forecasts at 50, 60, 70, 80, and 90 percent probability intervals.

Marco Del Negro is an economic research advisor in Macroeconomic and Monetary Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.

photo of Gundam Pranay

Pranay Gundam is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

Donggyu Lee is a research economist in Macroeconomic and Monetary Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.

Ramya Nallamotu is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

photo of Brian Pacula

Brian Pacula is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

How to cite this post:
Marco Del Negro, Pranay Gundam, Donggyu Lee, Ramya Nallamotu, and Brian Pacula, “The New York Fed DSGE Model Forecast— September 2023,” Federal Reserve Bank of New York Liberty Street Economics, September 22, 2023, https://libertystreeteconomics.newyorkfed.org/2023/09/the-new-york-fed-dsge-model-forecast-september-2023/.


Disclaimer
The views expressed in this post are those of the author(s) and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author(s).

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The Big Picture of the housing market, and its almost complete bifurcation, in 3 easy graphs

  – by New Deal democratI want to spend some time commenting on the broader issue of why the public perceives that inflation is still rampant, even though…

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 - by New Deal democrat


I want to spend some time commenting on the broader issue of why the public perceives that inflation is still rampant, even though almost all official measures show it rapidly decelerating, and even completely absent on a YoY basis currently by a few measures. A big part of that has to do with housing, and since I’ve discussed several facets of that issue in discussing the data releases this week, I wanted to pull that together into a “Big Picture” summary. I do that in 3 simple graphs below.

Graph #1: Active listing counts of existing homes (red, left scale) vs. new housing under construction (blue, right scale):



The average mortgage on an existing home is something like 3.5%. Huge numbers of people either bought or refinanced when mortgage rates were 3%, and now those people are locked in. For example, a $1000 monthly interest payment at 3% is a $2333 monthly interest payment at 7%. Those people are locked into their existing home for the foreseeable future.

As a result, the existing home market has collapsed. As I showed yesterday, sales are near 25 year lows. The active listing count above, which averaged 1.3 million in the years prior to the pandemic, even with a modest recovery in the past year is still only about 700,000, a -600,000 decline.

Meanwhile the number of new homes under construction has risen from about 1.125 million annualized in the years before the pandemic to about 1.725 annualized, a mirror image +600,000 increase.

In other words, the seizing up of the existing home market has diverted people to the new home market.

Graph #2: median price of existing (red) vs. new (blue) homes:



The NAR only lets FRED publish the last year of their price data, which is not seasonally adjusted, but that is fine for today’s purposes, so the above graph compares it with the not seasonally adjusted price data for new homes.

The lack of inventory of existing homes means that prices got bid up, and remain bid up. Builders responded by building lots of new units, and unlike existing homeowners, they can respond to market conditions by varying their price point, which the above graph shows they have done. The median price for a new home went down -$100,000, or 20%, a few months ago, and is still down about -15% from its peak last year.

Graph #3: Single vs. multi-family units under construction:



The Millennial generation and the first part of Gen Z are well into their home-buying years. But because they have been priced out of large parts of the market, due to both the aforesaid big rise in mortgage rates, but also the post-pandemic increase in prices, they have had to downsize their target from single family homes to the less expensive condos or apartments.

As part of their adjustment described above, apartments and condos are being built hand over fist, and builders are offering price or financing concessions. Single family houses under construction have declined by about 20% from summer 2022, while multi-family units soared to a new all-time record, about 20% higher than their level in summer 2022.

It’s the housing version of shrinkflation, since - although the data isn’t easily available - I think we can take notice of the fact that apartment and condo units are considerably less expensive on average than single family detached houses.

[As an aside, note that a very similar thing happened in the 1970s when the Baby Boom generation was well and truly into their first home-buying years. While the Millennial generation is slightly bigger numerically than the Boomers, since the total US population was only 50% of its current size back in the 1960s, proportionately the Boomers had an even bigger impact on the market.]

That’s the Big Picture of the almost complete bifurcation of the current housing market. The “shrinkflation” I’ve described above is very much a part of why the public continues to believe that inflation remains a big problem. 

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