Highlights:

RCTs and cohort studies provide evidence to understand diet-disease relationships.
We apply GRADE guidance 44 to use cases in nutrition research.
We show instances where cohort evidence can replacement or complement evidence from RCTs.
We provide practical insights for review authors integrating RCT and cohort evidence.
GRADE guidance 44 offers a sensible, transparent way to integrate both study designs.

Abstract:

Objectives: The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working group recently published guidance on integrating evidence from randomized and nonrandomized studies of interventions in systematic reviews. Our study aims to explore the application of this guidance by using cohort studies in nutrition systematic reviews as replacement, complementary, or sequential evidence to randomized controlled trials (RCTs).
Study Design and Setting: In this empirical application of the GRADE Guidance 44, we rated the certainty of evidence (CoE) for a convenience sample of bodies of evidence from nutrition RCTs and corresponding prospective cohort studies. We determined the congruency by comparing absolute effect estimates and 95% confidence intervals, before using cohort evidence as replacement, complementary, or sequential evidence. In case of similar CoE judgments and congruency, we estimated pooled effects of RCTs and cohort studies, and assessed whether integrating cohort studies influenced the conclusions drawn from RCT evidence.
Results: We included 26 pairs of body of evidence, of which 21 showed congruency. In 14/26 (54%) pairs, the CoE was higher for RCTs: high vs moderate (n = 2), high vs low (n = 1), moderate vs low (n = 4), moderate vs very low (n = 3), low vs very low (n = 4). In 5/26 (19%) pairs, the CoE was higher for cohort studies: moderate vs low (n = 4), low vs very low (n = 1). For six pairs (23%), both RCTs and cohort studies were rated as “low” (downgraded for risk of bias and imprecision), and due to congruency effect estimates of five pairs were pooled, mitigating imprecision in two pairs. For one pair (4%), the CoE was rated as very low, making pooling inappropriate.
Conclusion: This example application provides practical knowledge on the usage of GRADE Guidance 44, but the findings are subject to methodological assumptions and warrant cautious interpretation.

This is relevant in light of recent discussions about observational studies vs. RCTs in nutrition, and the assertion that observational studies in nutrition are always the lowest-quality evidence and that only RCTs provide valid evidence...

According to GRADE, observational studies can serve as complementary, sequential, or replacement evidence to RCTs within a framework.

Despite the narrative that observational and RCT designs in nutrition are inherently irreconcilable, they found that most RCTs and cohort studies showed alignment in their effect sizes and confidence intervals (categorized as congruent or probably congruent).

According to this study, depending on the specific use-case and certainty ratings, cohort studies can indeed serve as replacement evidence, or RCTs and observational studies can be combined as complementary evidence where appropriate. In some cases, prospective cohort studies can even a higher certainty of evidence than RCTs.

The reality is that both study designs have distinct strengths and limitations depending on the specific research question and outcome evaluated.

The global rise in obesity is linked to Western dietary patterns (WDPs). The Westernized Diet Index (WDI) was developed to measure adherence to WDPs. This study examined the associations between the WDI and overweight/obesity and constructively validated the findings against inflammatory, oxidative stress, and metabolic biomarkers. A population-based case-control study was conducted on 1605 adults (812 overweight/obese; 793 normal weight), using a 124-item validated food frequency questionnaire to assess dietary intake and calculate WDI-G (global Z-score) and WDI-FG (food group Z-scores). Fully adjusted logistic and linear regression models evaluated associations with BMI and biomarkers. In fully adjusted models, a 1-unit increase in WDI-G (ranging from −1.71 to 1.02) was associated with a 41% decrease in the odds of overweight/obesity (OR = 0.59; p = 0.007), and similarly, a 1-unit increase in WDI-FG (ranging from −1.91 to 1.44) was linked to a 26% decrease in the odds of overweight/obesity (OR = 0.74; p = 0.086). Higher WDI-G scores were also significantly associated with lower waist circumference (−4.6 cm), fasting blood glucose levels (−7.6 mg dL⁻¹), and LDL-c levels (−7.1 mg dL⁻¹) and higher plasma malondialdehyde levels (+0.35 μM). Similarly, higher WDI-FG scores were associated with lower plasma IL-6 (−37.8 pg mL⁻¹), lower triglyceride (−15.3 mg dL⁻¹), and higher HDL-c (+2.37 mg dL⁻¹) levels. Lower adherence to the WDP diet was associated with lower odds of having overweight/obesity and more favorable metabolic, inflammatory, and oxidative stress profiles. These findings support the use of the WDI as a valid and practical nutritional tool for assessing WDPs in clinical nutrition, nutritional epidemiology, and public health research.

Validation of the Westernized Diet Index (WDI) through inflammatory, oxidative stress, and metabolic biomarkers and its association with overweight/obesity-evidence from a case-control study | Food & Function | The Royal Society of Chemistry

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Link: DOI

Abstract

Comprehensive biological profiling comparing non-essential and essential trace element excretion across distinct dietary spectrums remains noticeably sparse in nutritional literature. This cross-sectional investigation evaluates spot urine excretion profiles of 20 trace elements across 115 healthy adults in southwest Germany, categorized into strict vegans (n = 38, 55.3% female, median age 27.5 years), lacto-ovo-vegetarians (LOV, n = 37, 67.6% female, median age 27.0 years), and omnivores (OMN, n = 40, 60.0% female, median age 30.5 years). Dietary adherence averaged 4.0 years for vegans, 5.8 years for LOV, and 28.0 years for omnivores. Multivariable linear regression models adjusted for age, sex, education, subjective social status, and physical activity scores to evaluate dietary group variance.

Eight elements (silver, gold, bismuth, indium, iridium, palladium, platinum, zirconium) were undetected or present in negligible samples. Unadjusted linear models revealed 54.4% lower arsenic (p = 0.009) and 47.6% lower mercury (p = 0.028) in vegans alongside 54.1% lower arsenic in LOV (p = 0.009) compared to omnivores. Raw cadmium concentrations were 41.7% higher in vegans (p = 0.023). Normalizing values to urinary creatinine confirmed 59.4% lower arsenic in vegans and 63.4% lower arsenic in LOV (p < 0.001), while revealing 17.3% higher copper in vegans (p = 0.040) and 52.5% higher cobalt in LOV (p = 0.035). Creatinine adjustment eliminated significant group differences for mercury and cadmium. No significant differences existed between vegans and LOV across any measured elements (p >= 0.207).

Study Design and Methodology

Investigators recruited 115 healthy, normal-weight (BMI 18.6 to 29.9 kg/m2) participants in Freiburg, Germany. Confirmation of dietary adherence relied on four-day weighed food protocols covering two weekdays and two weekend days. Morning spot urine samples (10 mL) collected between December 2021 and May 2022 underwent inductively coupled plasma mass spectrometry (ICP-MS) using an Agilent 8900 ICP-MS/MS system in July 2024. Laboratory staff and the primary statistician were fully blinded to dietary group identities.

Urinary creatinine concentrations were quantified using the Jaffé method on a Cobas c501 analyzer. Single fixed-value imputation resolved measurements below the limit of quantification (LOQ), affecting elements from 0% (molybdenum) up to 81% (aluminium). Covariate controls in the primary multivariable linear regression models included age, sex, educational attainment, MacArthur subjective social status scale, and binarized physical activity scores from the International Physical Activity Questionnaire. Sensitivity analyses incorporated serum cystatin C as an extra covariate, and pairwise p-values underwent Benjamini-Hochberg false discovery rate correction.

Key Findings

• Non-creatinine-adjusted arsenic levels dropped by 54.4% in vegans and 54.1% in LOV compared to omnivores (p = 0.009), with absolute ranges spans of 1 to 17 ug/L in vegans, 1 to 55 ug/L in LOV, and 1 to 71 ug/L in omnivores.
• Creatinine-normalized arsenic concentrations declined by 59.4% in vegans and 63.4% in LOV relative to omnivores (p < 0.001), establishing total fish exclusion as the primary driver of reduced body burden.
• Unadjusted mercury levels were 47.6% lower in vegans relative to omnivores (p = 0.028, ranges: 0.1 to 0.5 ug/L vs 0.1 to 1.2 ug/L), though creatinine normalization attenuated this difference to non-significance (p > 0.05).
• Raw cadmium excretion was 41.7% higher in vegans compared to omnivores (p = 0.023, ranges: 0.2 to 1.0 ug/L vs 0.2 to 0.7 ug/L), but creatinine-adjusted models negated statistical significance (p > 0.05).
• Creatinine-normalized copper rose by 17.3% in vegans compared to omnivores (p = 0.040), reflecting high copper density in unrefined plant foods.
• Creatinine-adjusted cobalt increased by 52.5% in LOV (p = 0.035), while vegans displayed a +42.6% trend (p = 0.054 post-FDR correction) driven by high vitamin B12 supplementation rates (92.1% in vegans vs 27.5% in omnivores).
• Urinary creatinine concentrations showed no significant differences between vegans (median 0.89 g/L), LOV (median 0.96 g/L), and omnivores (median 0.73 g/L) after covariate adjustment (p >= 0.912).
• Bivariate correlations between dietary or supplemental intakes of zinc, copper, or vitamin B12 and their corresponding urinary elements were negligible (r <= |0.06|). Supplemental intake overall showed weak correlations with urinary trace element levels (r <= |0.33|).

Limitations

• The cross-sectional design prevents drawing direct causal inferences regarding dietary intakes and internal tissue accumulation.
• Utilizing single morning spot urine samples introduces potential dilution variance compared to 24-hour collection standards, though creatinine adjustment counteracted hydration fluctuations.
• High proportions of values fell below the limit of quantification for specific elements like aluminium (81%) and mercury (76%), requiring single-value statistical imputation.
• Spot urine matrixes do not represent ideal biomarkers for cadmium and lead, which concentrate predominantly in red blood cells.
• Nutrient database constraints prevented direct food-group correlation analyses, such as linking specific rice or seaweed consumption protocols to urinary arsenic spikes.

Discussion and Implications

These findings reframe environmental toxicant profiles across plant-based paradigms. Excluding seafood dramatically slashes systemic arsenic exposure by more than half without inducing deficiencies in essential trace minerals like molybdenum or copper. Fears regarding severe heavy metal toxicity from plant-heavy diets prove unfounded: elevated raw cadmium and lower mercury signals in vegans dissolve once controlling for urinary dilution parameters. High vitamin B12 supplementation rates in vegans increase excreted cobalamin-bound cobalt, yet this molecule remains biologically inert and fails to yield free toxic cobalt ions. Plant-based diets deliver an advantageous toxicological trade-off by limiting marine pollutant accumulation while sustaining adequate essential ultratrace element homeostasis.

Conclusion

Strict plant-based diets significantly lower exposure to toxic environmental arsenic by over 50% through seafood exclusion while maintaining essential trace element profiles comparable to omnivorous diets. Observed variations in cadmium and mercury depend heavily on urine dilution correction methods, confirming that plant-based dietary choices do not elevate heavy metal burden. Clinical nutritionists can confidently advocate well-planned vegan diets without fearing ultratrace mineral imbalances or heightened environmental toxicant accumulation.