Processed foods are also technically off limits due to an emphasis on fresh foods, but some Paleo diets allow frozen fruits and vegetables because the freezing process preserves most nutrients. Overall, the diet is high in protein , moderate in fat mainly from unsaturated fats , low-moderate in carbohydrate specifically restricting high glycemic index carbohydrates , high in fiber , and low in sodium and refined sugars.

Grass-fed beef is often highlighted on the diet, which is promoted to contain more omega-3 fats than conventional beef due to being fed grass instead of grain.

It does contain small amounts of alpha-linolenic acid ALA , a precursor to EPA and DHA. However, only a small proportion of ALA can be converted in the body to long-chain omega-3 fatty acids EPA and DHA.

The amount of omega-3 is also highly variable depending on the exact feeding regimen and differences in fat metabolism among cattle breeds.

Some randomized controlled trials have shown the Paleo diet to produce greater short-term benefits than diets based on national nutrition guidelines, including greater weight loss, reduced waist circumference, decreased blood pressure, increased insulin sensitivity, and improved cholesterol.

However these studies were of short duration 6 months or less with a small number of participants less than One larger randomized controlled trial followed 70 post-menopausal Swedish women with obesity for two years, who were placed on either a Paleo diet or a Nordic Nutrition Recommendations NNR diet.

It included lean meats, fish, eggs, vegetables, fruits, berries, nuts, avocado, and olive oil. Both groups significantly decreased fat mass and weight circumference at 6 and 24 months, with the Paleo diet producing greater fat loss at 6 months but not at 24 months. Triglyceride levels decreased more significantly with the Paleo diet at 6 and 24 months than the NNR diet.

The Paleo diet includes nutrient-dense whole fresh foods and encourages participants to steer away from highly processed foods containing added salt, sugar, and unhealthy fats. However, the omission of whole grains, dairy, and legumes could lead to suboptimal intake of important nutrients.

The restrictive nature of the diet may also make it difficult for people to adhere to such a diet in the long run. More high-quality studies including randomized controlled trials with follow-up of greater than one year that compare the Paleo diet with other weight-reducing diets are needed to show a direct health benefit of the Paleo diet.

Strong recommendations for the Paleo diet for weight loss cannot be made at this time. The contents of this website are for educational purposes and are not intended to offer personal medical advice. You should seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition.

Never disregard professional medical advice or delay in seeking it because of something you have read on this website.

Together, these two scores can help researchers and clinicians evaluate the impact of the Paleolithic diet and lifestyle on health outcomes. In fact, many studies have used the PD score alone or in combination with lifestyle factors i.

In particular, Whalen et al. found that higher adherence to PD was associated with a lower incidence of colorectal adenomas [ 6 ]. Given that colorectal adenomas are often considered to be precursors of CRC [ 12 ], there may be a potential association between PD and CRC risk.

To our knowledge, no observational studies have examined the potential association between PD and PLL and the risk of CRC. Hence, to fill this gap, the present study comprehensively analyzed the potential association of PD and PLL with the risk of CRC and its different anatomical subsites in a large population-based cohort.

Our study population was derived from the Prostate, Lung, Colorectal, and Ovarian PLCO Cancer Screening Trial, a randomized controlled study of screening exams or tests for PLCO cancers. The aim of this trial was to test whether these screening exams or tests could lower the risk of death from these cancers.

Study design of the PLCO Cancer Screening Trial has been reported previously [ 13 ]. Briefly, between and , a total of , men and women between 55 and 74 years of age were finally enrolled in this trial from 10 screening centers across the US [ 14 ].

All participants in the PLCO Cancer Screening Trial provided written informed consent, and the study was approved by the US National Cancer Institute and the Institutional Review Board of each screening center. Ultimately, a total of 74, individuals, including 35, males and 39, females, were included in this study, as presented in Fig.

All individuals involved in the trial provided explicit, informed, and written consent. Additionally, our study Project ID: PLCO has received approval from the the United States NCI. The flow chart of identifying eligible subjects. PLCO Prostate, Lung, Colorectal, and Ovarian, BQ baseline questionnaire, DHQ diet history questionnaire.

In this study, baseline data were collected using a self-administered baseline questionnaire that is, BQ , which included age, sex, race, education level, smoking status, BMI at baseline, diabetes, diverticulitis or diverticulosis, colon comorbidity, colorectal polyp, aspirin use, and a family history of colorectal cancer.

Notably, BMI was calculated as weight in kilograms divided by the square of height in meters. Dietary intake information, including alcohol consumption, dietary energy intake, and dietary foods or nutrients intake, were collected using a item self-administered food frequency questionnaire FFQ called the DHQ over a 3-year period after enrollment.

Daily food intake was estimated by calculating the product of food frequency and portion size. Estimates of daily energy and nutrient intake were based on the United States Department of Agriculture's — Continuing Survey of Food Intakes by Individuals [ 16 ], which was commonly used nutrient database.

In addition to this, DHQ recorded the age of individuals when they completed the DHQ and calculated the Healthy Eating Index HEI as described in the literature [ 17 ], which is used to assess the dietary quality of individuals. Previous research, such as the Eating at America's Table Study, had substantiated the validity of the DHQ in dietary assessment [ 18 ].

Physical activity was assessed using a self-reported supplemental questionnaire SQX , which evaluated the total weekly time spent engaging in moderate to high-intensity exercise.

In this investigation, the PD score and PLL score were formulated according to the method utilized by Sohouli et al. In brief, all food items identified in the DHQ were categorized into 14 predetermined food groups based on their nutrient and culinary similarities.

These food groups were subsequently classified into two overarching categories, namely those with PD characteristics comprising of vegetables, fruits, a score for fruit and vegetable diversity, lean meat, fish, nuts, and calcium and those without PD characteristics including red and processed meat, dairy products, sugar-sweetened beverages, baked goods, grains and starches, sodium, and alcohol , which as presented in Table 1.

The score of fruit and vegetable diversity was defined as the number of components of the fruit and vegetable group consumed by each individual. Furthermore, to consider dietary calcium separately from dairy products, we used the residuals of a linear regression of total calcium intake on total dairy food intake to represent calcium intake independent of dairy consumption since the Paleolithic diet had little dairy food but high amounts of calcium from wild greens [ 5 ].

Ultimately, the PD score for each participant was calculated as the sum of points awarded for each food group, with a possible range of 14 to 70 points, where higher scores indicated a greater adherence to the PD. According to the method used by Sohouli et al. In this study, a score of 5 was assigned to individuals in the highest tertile of physical activity, while scores of 3 and 1 were assigned to those in the middle and lower tertiles, respectively.

The scoring scheme was reversed for BMI. Smoking status was scored as 5, 3, and 1 for non-smokers, ex-smokers, and smokers, respectively.

The scores of the PD and the above three lifestyle factors were then combined to compute the PLL score for each individual. The final score range in our study was from 17 to 85, with higher scores indicating greater adherence to the PLL. In this study, the identification of CRC cases relied mainly on an annual study update form.

The screening centers mailed the annual form to each living participant, requesting information about any cancer diagnosis they received, including the site, type, date, location of diagnosis, and contact information for their healthcare providers.

To ensure the accuracy of the reported cancer cases, relevant medical records were reviewed using a standardized form. Study physicians, who were blinded to participants' risk factors, confirmed the cases and their anatomical locations.

In study, CRC were defined based on the definitions by the International Classification of Diseases for Oncology ICD-O; codes: colon cancer: C18, and rectal cancer: CC Proximal colon cancers including cecum, appendix, ascending colon, hepatic flexure, transverse colon, and splenic flexure colon cancer.

Distal CRC including descending cancer, sigmoid colon cancer, rectosigmoid junction cancer and rectal cancer. It is worth noting that the primary outcome in this study was CRC, and the secondary outcome was proximal colon cancer and distal CRC. We utilized the mode and median methods to impute categorical and continuous variables in the presented study, respectively.

Additional information on the specific types and proportions of missing data can be found in Additional file 1 : Table S1. Here, follow-up length was measured from the DHQ completion date to the date of CRC diagnosis, death, loss, or end of follow-up that is, December 31, , whichever happened first Fig.

To exam whether there was a linear trend between CRC cancer incidence and the quartiles of the two mentioned scores, every individual was assigned a median quartile score within that quartile and subsequently treated as a continuous variable in regression models, using the lowest quartile as the reference group.

The P value representing the significance of linear trends. Subsequently, we identified potential confounding variables on the basis of a comprehensive review of the relevant literature and the clinical expertise of the investigators.

These variables were included in COX regression models to mitigate their potential impact on the study outcomes [ 12 , 19 ]. Main model of the potential association between the PD score and risks of CRC was adjusted for demographic features sex, age, race, and education level , health status personal history of diabetes, diverticulitis or diverticulosis, colon comorbidity, colorectal polyp, and aspirin use, and a family history of CRC cancer , lifestyle factors including smoking status, BMI at baseline, and physical activity level , and energy intake value from diet.

Given that BMI at baseline, smoking status, and physical activity were used to construct PLL score, these variables were not adjusted in the main model of the association between PLL score and CRC incidence.

The same analytical procedures were repeated for the secondary outcome measures, namely the risk of proximal colon cancer and distal colorectal cancer, to investigate the potential association between the incidence of CRC by anatomical subsites and both the PD score and the PLL score.

A restricted cubic spline model with three knots at the 10th, 50th, and 90th percentiles was used to illustrate the trends of CRC incidence including proximal colon cancer and distal colorectal cancer across the entire range of PD score and PLL score [ 20 ].

The reference value was set at the median of the first quartile of PD score and PLL score, which were 35 and 44, respectively. Additionally, the P-nonlinearity was determined by testing the null hypothesis that the regression coefficient of the second spline was equal to zero.

The timeline and follow-up scheme of our study. Notably, in our study, the baseline point was set at the date of diet history questionnaire completion. female , education levels high-school graduate or less vs. some college or college graduate , family history of CRC cancer no vs. yes , aspirin use regularly no vs.

To prevent false subgroup effects, P -values for interaction were estimated by comparison of models with and without interaction terms before performing the above-mentioned subgroup analyses. In addition, P -values for the trends between quartiles of PD score and CRC incidence were calculated separately for each individual subgroup using the previously described methods.

Additionally, various sensitivity analyses were conducted to assess the robustness of the results. All statistical analyses were performed using R software version 4.

In the whole study population, the mean standard deviation was 42 5 points for PD score, and 51 7 points for PLL score. The baseline characteristics of the study population according to the quartile of PD score and PLL score are presented in Table 2 and Additional file 1 : Table S2, respectively.

Participants in the highest quartiles of the PD and PLL score were less likely to be aspirin users, more likely to be females and never smokers, had higher levels of education and physical activity time than those in the lowest quartiles.

In addition, compared with those in the lowest quartile of PD and PLL score, those in the highest quartile had lower intake of energy, alcohol, total protein, carbohydrate, and total fat, but higher Healthy Eating Index Moreover, the proportion of non-White increased with higher quartiles of PD and PLL score.

Interestingly, the proportion of individuals with diabetes history increased with increasing quartile of PD score Table 2 , but decreased with higher quartiles of PLL score Table S2.

In our study, the overall incidence rate of CRC was 1. The univariable and multivariable Cox regression analyses results of PD score and the incidence of CRC and its subsites were presented in Table 3.

Compared with individuals in the lowest quartile of PD score, those in the highest quartile showed a significantly decreased incidence of CRC, even after adjusting for potential confounders multivariable model: HR quartile 4 versus 1 : 0.

Similar findings were observed in the analysis of the association between PD score and proximal colon cancer incidence multivariable model: HR quartile 4 versus 1 : 0.

An inverse association between PD score and distal CRC incidence was also observed, but the result was not statistically significant multivariable model: HR quartile 4 versus 1 : 0. Furthermore, sensitivity analyses showed that the initial correlation between PD score and CRC incidence did not change substantially Additional file 1 : Table S4.

For PD score, hazard ratio was adjusted for age, sex, race, education levels, family history of colorectal cancer, history of colon comorbidity, history of diverticulitis or diverticulosis, history of colorectal polyp, history of diabetes, history of aspirin use, total energy intake, BMI at baseline, smoking status, and physical activity level.

For PLL score, hazard ratio was adjusted for age, sex, race, education levels, family history of colorectal cancer, history of colon comorbidity, history of diverticulitis or diverticulosis, history of colorectal polyp, history of diabetes, history of aspirin use, total energy intake.

The association between PLL score and the risk of CRC and its subsites were presented in Table 4. We observed a stronger inverse association between CRC and its subsites incidence with PLL score than with PD score in both Model 1 and 2. Likewise, PLL score was inversely associated with the risk of proximal colon cancer HR quartile 4 versus 1 : 0.

Additional file 1 : Table S5 presented the result of subgroup analysis for PLL score and CRC incidence. The significant inverse relationship between PLL score and CRC incidence persisted in sensitivity analyses Additional file 1 : Table S6. In this large prospective study, we found that greater adherence to PD or PLL was associated with a lower risk of overall CRC.

However, when assessed by anatomical subsites, higher adherence to PD was associated with a lower risk of proximal colon cancer, but not distal CRC. For PLL, the decreased risk in different CRC subsites is similar. To the best of our knowledge, this study is the first to examine the potential association between PD and PLL and the risk of CRC, as well as its various anatomical subsites, in a large, mixed-gender population.

In fact, a previous case—control study has investigated the association between PD and colorectal adenoma, a precursor of CRC [ 6 ]. This study recruited individuals, comprising cases identified through outpatient colonoscopy, colonoscopy-negative controls, and community controls, and collected dietary information using a Willett FFQ.

The study found that the multivariable-adjusted odds ratios OR comparing the highest to the lowest quintiles of the PD score were 0. However, no clear differences in the associations were observed according to adenoma anatomical subsites [ 6 ].

reported that adherence to PD may reduce systemic inflammation and oxidative stress levels in humans [ 23 ]. This finding partially supports our conclusion since the progression of CRC is typically associated with inflammation and oxidative stress [ 24 , 25 , 26 ]. In addition, epidemiological studies have increasingly confirmed the potential association between adherence to the PD and a reduced risk of other cancers.

For instance, Shah et al. The following mechanisms can be speculated by which PD lower risk of CRC. First, the PD limits the intake of sugar sweetened beverages, which increased the risk of CRC through pathways of oxidative stress and inflammation [ 27 , 28 , 29 ].

Second, previous studies have suggested that the PD may improve insulin sensitivity and prevent diabetes [ 9 , 30 , 31 ], which could potentially reduce the risk of CRC [ 12 , 32 ]. Extensive evidence supports a direct association of between low insulinemic dietary pattern and reduced risk of total cancer and CRC [ 33 , 34 ].

Moreover, higher dietary insulin load has been found to be correlated with increased cancer recurrence and poorer survival outcomes among individuals diagnosed with stage III colon cancer [ 35 ].

Third, the consumption of red and processed meat, which has been proposed to increase the risk of CRC by producing genotoxic free radicals and inducing lipid peroxidation [ 36 ], was restricted in the PD. Forth, restricting sodium and alcohol intake may also have beneficial effects on the pathophysiology of cancer [ 37 , 38 , 39 ].

On the other hand, the PD highlights the intake of fruits, vegetables, and nuts, which are abundant sources of dietary fiber and unsaturated fatty acids.

These nutrients have been found to exert beneficial effects on modulating detoxification enzymes and the immune system [ 40 , 41 , 42 , 43 ]. Furthermore, dietary fiber promotes the production of short-chain fatty acids through microbial fermentation, which helps to maintain mucosal integrity and inhibit inflammation and carcinogenesis by affecting immunity and gene expression [ 44 , 45 ].

Additionally, various prospective studies have suggested that higher intake of calcium or fish may lower the risk of colorectal cancer [ 46 , 47 ]. Regarding the other three modifiable lifestyle factors of PLL, epidemiological studies have consistently reported direct positive associations between smoking, obesity, and physical inactivity with CRC risk [ 12 ].

Physical activity can reduce the risk of CRC by decreasing inflammation, intestinal transit time, insulin-like growth factor levels, hyperinsulinemia, and regulating immune function [ 48 ].

The mechanism linking obesity to an increased risk of CRC is that it promotes insulin resistance or hyperinsulinemia, chronic inflammation, oxidative stress, and DNA damage [ 49 ]. Smoking primarily plays a role in the development of colorectal cancer by promoting the growth of colorectal cancer cells through nicotine and stimulating angiogenesis in colon cancer [ 50 ].

As mentioned earlier, adherence to PD has been shown to increase insulin sensitivity and reduce the risk of diabetes [ 30 , 31 ], both of which are directly associated with obesity risk [ 51 ].

Thus, one of the possible explanations for the phenomenon observed in the subgroup analysis is that individuals who adhere to PD are less likely to be obese since their healthy dietary habits, while obese is directly associated with a high risk of CRC [ 49 ].

Another plausible hypothesis is that BMI may mediate the association between adherence to the PD and reduced risk of CRC. Nevertheless, additional investigations are warranted to validate this hypothesis.

In addition, we cannot rule out the possibility that the observed interaction between BMI and PD is accidental, although this phenomenon can be explained. Our study has several notable strengths. First, this study is based on a large-scale prospective cohort of over , participants recruited from 10 screening centers all over the US.

In addition, the follow-up period was calculated from the completion of the DHQ, which ensured an appropriate observation time and for the cohort to obtain enough outcome events.

The actual observation time was far greater than the nominal follow-up period of 9 years, as the mean time from randomization to DHQ completion was approximately 3 years. Second, we conducted a comprehensive adjustment for a wide range of potential confounding factors in our analyses.

However, we cannot rule out the possibility that there may be additional unmeasured residual confounders that could affect the observed association. Third, our results were supported by a series of sensitivity analyses, which confirmed the robustness of the association between PD and PLL scores and the risk of CRC.

However, this study has several limitations that should be considered. Firstly, dietary intake was only measured by DHQ at baseline, which did not allow for the assessment of changes in diet over time.

Nevertheless, it has been indicated that baseline diet evaluation generally results in weaker associations with disease incidence than cumulative dietary intake [ 52 ].

Furthermore, self-reported food frequency questionnaires may not be precise enough due to their extensive contents. Secondly, the modern PD may differ in terms of the nutritional value of the diet of our pre-agricultural ancestors.

In addition, as with other dietary pattern analyses, individuals just followed a dietary pattern which was more or less similar to the PD definition, instead of explicitly choosing to adhere to the PD. Finally, the observational design of our study makes it impossible for us to confirm the causal association between PD or PLL and the risk of CRC.

In conclusion, our study suggests that adherence to the PD or PLL may reduce the risk of CRC. The anatomical subsite analyses showed that PD was inversely associated with the risk of proximal colon cancer, but not distal CRC.

However, the reduced risk of different CRC subsites was similar by adhering to PLL. Our results need to be further validated in other populations and settings. Access to the dataset should contact the National Cancer Institute by mail. Dekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB.

Colorectal cancer. Article PubMed Google Scholar. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics CA A Cancer J Clin. A Paleo diet for mental health aims to provide a basis for anti-inflammatory foods, thus calming inflammatory tendencies in the brain and body:. The foundations of the Paleo diet exclude foods that are known to cause inflammation or damage in the body such as grains, legumes, and dairy along with all processed and refined foods.

Many of these foods are deficient in a variety of vitamins and minerals, as well as lacking other vital nutrients and quality fats. Animal foods are rich in quality protein, which is made up of various essential amino acids that form the building blocks of key neurotransmitters such as dopamine, noradrenaline, serotonin and melatonin; these play pivotal roles in mood and sleep.

Eating lots of whole, unprocessed foods potentially provides an abundance of vitamins and minerals; in particular, zinc, magnesium, B6, iron, and Vitamin C which are critical to making those brain chemicals. A Paleo diet encourages eating naturally occurring animal and plant fats which are crucial for good brain function and healthy brain cells.

Read on here for more on Paleo fats. Avoiding refined carbohydrates such as the processed grains found in cereals, baked goods and the like helps the body better manage blood sugar levels which otherwise may impact your moods and energy levels.

Some foods such as gluten, found in all wheat products, can have detrimental effects on brain function as well as elsewhere in the body. These used to be included in the diets of many traditional cultures — not surprising really when you consider the beneficial bacteria and the higher density of many nutrients - sauerkraut may contain up to 20 times the amount of vitamin C than raw cabbage!

Due to the gut-brain link, having diverse and healthy bacteria in your gut may have a positive impact on your brain health. A Paleo diet is very dense in the nutrients needed to support your liver detoxification pathways.

When your liver is functioning better there may be a positive effect on the health of your brain, as toxins are cleared from your body and more nutrients are available to make those uplifting brain chemicals.

The gut is another huge regulator for overall inflammation, and a gut-friendly diet protects your brain by reducing overall inflammation. The gut microbiome also assists in regulating mood and neurological function. Diets that increase gut bacterial diversity are associated with better mental health and cognitive function.

A Paleo diet filled with fresh, organic, seasonal produce encourages a diverse gut microbiome. Mental health has much of its foundation in the gut. Keep your gut and your brain happy by including these nutrients in your diet:. Omega-3 fats are anti-inflammatory and important for brain health, especially at the beginning and end of life.

Studies show a correlation between a deficiency in omega-3 and depression. Clinical trials have revealed taking adequate amounts of omega-3 improves symptoms of ADHD, bipolar disorders, depression, and schizophrenia.

A 1 g daily intake of omega-3 in the form of DHA and EPA was found to support cognitive function. Food sources include: fish, seafood, walnuts and flax. B vitamins include choline, B1, B6, B9 folate , and B B12 is particularly important for brain function in aging. Food sources include : all meats or animal foods, especially organ meat.

Iron, selenium, and magnesium are three important minerals for brain health. Selenium: Brazil nuts, fish and seafood, shiitake mushrooms, asparagus.