The dietary changes during Ramadan and their impact on anthropometry, blood pressure, and metabolic profile

BackgroundThe effect of Ramadan intermittent fasting (RIF) on the metabolic profile, anthropometry and blood pressure has been investigated in multiple studies. However, it is still unknown to what extent changes in nutrient intakes contribute to these changes.MethodsThis observational study was conducted in London (UK) in 2019. The study collected diverse data from a community-based sample in London before and during/after Ramadan. Collected data included a 3-day food diary (before and during Ramadan), as well as blood samples, anthropometric measurements and blood pressure (before and after Ramadan). The food diary was translated into nutritional data using nutrition software “Nutritics.” The changes in nutrient intakes were investigated using a mixed-effects regression model. The impact of adjusting for nutrient intake change was investigated on the absolute difference of metabolites (Nightingale platform), systolic/diastolic blood pressure and anthropometric measures.ResultsThe study collected data on food intake before and during Ramadan from 56 participants; the mean age was 44.7 ± 17.3, and 51.8% (n = 29) were females. We found a change in the intake of 11 nutritional factors, glucose, fructose, betaine, sugars, sugars as monosaccharide equivalents, lutein/zeaxanthin, starch, starch as monosaccharide equivalents, proline, glutamic acid and lycopene. No changes in quantities or proportions of macronutrients, carbohydrates, protein and fat. Mainly, the changes in diet during Ramadan are characterized by more consumption of sugars (62%, p < 0.001) and a lower intake of starch (−21%, p = 0.012). The changes in 14 metabolite levels (two glycolysis-related metabolites, one amino acid, two ketone bodies, two triglyceride, six lipoprotein subclasses, and an inflammation marker) after Ramadan were partially associated with some changes in nutrient intakes during Ramadan, especially betaine, fructose, glucose, starches and sugars. The lutein/zeaxanthin intake change explained inversely 14% of systolic blood pressure changes. Moreover, BMI and weight changes were partially explained by changes in intake of fat (7%; 9%), monounsaturated fat (6%; 7%), starch (8%; 9%), and starch as monosaccharide equivalents (8%; 9%) intakes in a direct relationship.ConclusionDiet changes during Ramadan were associated partially with the observed changes in the metabolic profile, blood pressure and anthropometry. This confirms the changes associated with RIF in the metabolic profile, blood pressure and anthropometry are not an absolute physiological response to the diet transition occurring during Ramadan

Validity of observational evidence on putative risk and protective factors:appraisal of 3744 meta-analyses on 57 topics

BACKGROUND: The validity of observational studies and their meta-analyses is contested. Here, we aimed to appraise thousands of meta-analyses of observational studies using a pre-specified set of quantitative criteria that assess the significance, amount, consistency, and bias of the evidence. We also aimed to compare results from meta-analyses of observational studies against meta-analyses of randomized controlled trials (RCTs) and Mendelian randomization (MR) studies. METHODS: We retrieved from PubMed (last update, November 19, 2020) umbrella reviews including meta-analyses of observational studies assessing putative risk or protective factors, regardless of the nature of the exposure and health outcome. We extracted information on 7 quantitative criteria that reflect the level of statistical support, the amount of data, the consistency across different studies, and hints pointing to potential bias. These criteria were level of statistical significance (pre-categorized according to 10-6, 0.001, and 0.05 p-value thresholds), sample size, statistical significance for the largest study, 95% prediction intervals, between-study heterogeneity, and the results of tests for small study effects and for excess significance. RESULTS: 3744 associations (in 57 umbrella reviews) assessed by a median number of 7 (interquartile range 4 to 11) observational studies were eligible. Most associations were statistically significant at P < 0.05 (61.1%, 2289/3744). Only 2.6% of associations had P < 10-6, ≥1000 cases (or ≥20,000 participants for continuous factors), P < 0.05 in the largest study, 95% prediction interval excluding the null, and no large between-study heterogeneity, small study effects, or excess significance. Across the 57 topics, large heterogeneity was observed in the proportion of associations fulfilling various quantitative criteria. The quantitative criteria were mostly independent from one another. Across 62 associations assessed in both RCTs and in observational studies, 37.1% had effect estimates in opposite directions and 43.5% had effect estimates differing beyond chance in the two designs. Across 94 comparisons assessed in both MR and observational studies, such discrepancies occurred in 30.8% and 54.7%, respectively. CONCLUSIONS: Acknowledging that no gold-standard exists to judge whether an observational association is genuine, statistically significant results are common in observational studies, but they are rarely convincing or corroborated by randomized evidence

Adiposity and cancer at major anatomical sites: umbrella review of the literature

Objective To evaluate the strength and validity of the evidence for the association between adiposity and risk of developing or dying from cancer. Design Umbrella review of systematic reviews and metaanalyses. Data sources PubMed, Embase, Cochrane Database of Systematic Reviews, and manual screening of retrieved references. Eligibility criteria Systematic reviews or meta-analyses of observational studies that evaluated the association between indices of adiposity and risk of developing or dying from cancer. Data synthesis Primary analysis focused on cohort studies exploring associations for continuous measures of adiposity. The evidence was graded into strong, highly suggestive, suggestive, or weak after applying criteria that included the statistical significance of the random effects summary estimate and of the largest study in a meta-analysis, the number of cancer cases, heterogeneity between studies, 95% prediction intervals, small study effects, excess significance bias, and sensitivity analysis with credibility ceilings. Results 204 meta-analyses investigated associations between seven indices of adiposity and developing or dying from 36 primary cancers and their subtypes. Of the 95 meta-analyses that included cohort studies and used a continuous scale to measure adiposity, only 12 (13%) associations for nine cancers were supported by strong evidence. An increase in body mass index was associated with a higher risk of developing oesophageal adenocarcinoma; colon and rectal cancer in men; biliary tract system and pancreatic cancer; endometrial cancer in premenopausal women; kidney cancer; and multiple myeloma. Weight gain and waist to hip circumference ratio were associated with higher risks of postmenopausal breast cancer in women who have never used hormone replacement therapy and endometrial cancer, respectively. The increase in the risk of developing cancer for every 5 kg/m2 increase in body mass index ranged from 9% (relative risk 1.09, 95% confidence interval 1.06 to 1.13) for rectal cancer among men to 56% (1.56, 1.34 to 1.81) for biliary tract system cancer. The risk of postmenopausal breast cancer among women who have never used HRT increased by 11% for each 5 kg of weight gain in adulthood (1.11, 1.09 to 1.13), and the risk of endometrial cancer increased by 21% for each 0.1 increase in waist to hip ratio (1.21, 1.13 to 1.29). Five additional associations were supported by strong evidence when categorical measures of adiposity were included: weight gain with colorectal cancer; body mass index with gallbladder, gastric cardia, and ovarian cancer; and multiple myeloma mortality. Conclusions Although the association of adiposity with cancer risk has been extensively studied, associations for only 11 cancers (oesophageal adenocarcinoma, multiple myeloma, and cancers of the gastric cardia, colon, rectum, biliary tract system, pancreas, breast, endometrium, ovary, and kidney) were supported by strong evidence. Other associations could be genuine, but substantial uncertainty remains. Obesity is becoming one of the biggest problems in public health; evidence on the strength of the associated risks may allow finer selection of those at higher risk of cancer, who could be targeted for personalised prevention strategies

The relationship between lipoprotein A and other lipids with prostate cancer risk:A multivariable Mendelian randomisation study

BACKGROUND: Numerous epidemiological studies have investigated the role of blood lipids in prostate cancer (PCa) risk, though findings remain inconclusive to date. The ongoing research has mainly involved observational studies, which are often prone to confounding. This study aimed to identify the relationship between genetically predicted blood lipid concentrations and PCa. METHODS AND FINDINGS: Data for low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides (TG), apolipoprotein A (apoA) and B (apoB), lipoprotein A (Lp(a)), and PCa were acquired from genome-wide association studies in UK Biobank and the PRACTICAL consortium, respectively. We used a two-sample summary-level Mendelian randomisation (MR) approach with both univariable and multivariable (MVMR) models and utilised a variety of robust methods and sensitivity analyses to assess the possibility of MR assumptions violation. No association was observed between genetically predicted concentrations of HDL, TG, apoA and apoB, and PCa risk. Genetically predicted LDL concentration was positively associated with total PCa in the univariable analysis, but adjustment for HDL, TG, and Lp(a) led to a null association. Genetically predicted concentration of Lp(a) was associated with higher total PCa risk in the univariable (OR(weighted median) per standard deviation (SD) = 1.091; 95% CI 1.028 to 1.157; P = 0.004) and MVMR analyses after adjustment for the other lipid traits (OR(IVW) per SD = 1.068; 95% CI 1.005 to 1.134; P = 0.034). Genetically predicted Lp(a) was also associated with advanced (MVMR OR(IVW) per SD = 1.078; 95% CI 0.999 to 1.163; P = 0.055) and early age onset PCa (MVMR OR(IVW) per SD = 1.150; 95% CI 1.015,1.303; P = 0.028). Although multiple estimation methods were utilised to minimise the effect of pleiotropy, the presence of any unmeasured pleiotropy cannot be excluded and may limit our findings. CONCLUSIONS: We observed that genetically predicted Lp(a) concentrations were associated with an increased PCa risk. Future studies are required to understand the underlying biological pathways of this finding, as it may inform PCa prevention through Lp(a)-lowering strategies

Serum uric acid levels and multiple health outcomes: umbrella review of evidence from observational studies, randomised controlled trials, and Mendelian randomisation studies

Objective To map the diverse health outcomes associated with serum uric acid (SUA) levels. Design Umbrella review. Data sources Medline, Embase, Cochrane Database of Systematic Reviews, and screening of citations and references. Eligibility criteria Systematic reviews and meta-analyses of observational studies that examined associations between SUA level and health outcomes, meta-analyses of randomised controlled trials that investigated health outcomes related to SUA lowering treatment, and Mendelian randomisation studies that explored the causal associations of SUA level with health outcomes. Results 57 articles reporting 15 systematic reviews and144 meta-analyses of observational studies (76 unique outcomes), 8 articles reporting 31 meta-analyses of randomised controlled trials (20 unique outcomes), and 36 articles reporting 107 Mendelian randomisation studies (56 unique outcomes) met the eligibility criteria. Across all three study types, 136 unique health outcomes were reported. 16 unique outcomes in meta-analyses of observational studies had P<10-6, 8 unique outcomes in meta-analyses of randomised controlled trials had P<0.001, and 4 unique outcomes in Mendelian randomisation studies had P<0.01. Large between study heterogeneity was common (80% and 45% in meta-analyses of observational studies and of randomised controlled trials, respectively). 42 (55%) meta-analyses of observational studies and 7 (35%) meta-analyses of randomised controlled trials showed evidence of small study effects or excess significance bias. No associations from meta-analyses of observational studies were classified as convincing; five associations were classified as highly suggestive (increased risk of heart failure, hypertension, impaired fasting glucose or diabetes, chronic kidney disease, coronary heart disease mortality with high SUA levels). Only one outcome from randomised controlled trials (decreased risk of nephrolithiasis recurrence with SUA lowering treatment) had P<0.001, a 95% prediction interval excluding the null, and no large heterogeneity or bias. Only one outcome from Mendelian randomisation studies (increased risk of gout with high SUA levels) presented convincing evidence. Hypertension and chronic kidney disease showed concordant evidence in meta-analyses of observational studies, and in some (but not all) meta-analyses of randomised controlled trials with respective intermediate or surrogate outcomes, but they were not statistically significant in Mendelian randomisation studies. Conclusion Despite a few hundred systematic reviews, meta-analyses, and Mendelian randomisation studies exploring 136 unique health outcomes, convincing evidence of a clear role of SUA level only exists for gout and nephrolithiasis

The impact of Ramadan intermittent fasting on anthropometric measurements and body composition: Evidence from LORANS study and a meta-analysis

BackgroundAlthough the effect of Ramadan intermittent fasting (RIF) on anthropometry and body composition has been questioned, none of the previous studies tried to explain the reported changes in these parameters. Also, systematic reviews that investigated the topic were limited to healthy individuals or a specific disease group.MethodsThe London Ramadan Study (LORANS) is an observational study on health effects of RIF. We measured weight, waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-hip ratio (WHR), basal metabolic rate (BMR), fat percentage (FP), free-fat mass (FFM), extremities predicted muscle mass, total body water (TBW), trunk FM, trunk FFM and trunk predicted muscle mass before and immediately after Ramadan. Using mixed-effects regression models, we investigated the effect of RIF with adjustment for potential confounders. We also conducted a meta-analysis of the results of LORANS with other studies that investigated the effect of RIF on anthropometry and body composition. The review protocol is registered with PROSPERO registry (CRD42020186532).ResultsWe recruited 146 participants (Mean ± SD age = 43.3 ± 15 years). Immediately after Ramadan, compared with before Ramadan, the mean difference was−1.6 kg (P&lt;0.01) in weight,−1.95cm (P&lt;0.01) in WC,−2.86cm (P &lt;0.01) in HC, −0.60 kg/m2 (P &lt; 0.01) in BMI and −1.24 kg (P &lt; 0.01) in FM. In the systematic review and meta-analysis, after screening 2,150 titles and abstracts, 66 studies comprising 7,611 participants were included. In the general population, RIF was followed by a reduction of 1.12 Kg in body weight (−1.89– −0.36, I2 = 0), 0.74 kg/m2 reduction in BMI (−0.96– −0.53, I2 = 0), 1.54cm reduction in WC (−2.37– −0.71, I2 = 0) and 1.76cm reduction in HC (−2.69– −0.83, I2 = 0). The effect of fasting on anthropometric and body composition parameters starts to manifest in the second week of Ramadan and starts to diminish 3 weeks after Ramadan.ConclusionRIF is associated with a reduction in body weight, BMI, WC, HC, FM, FP and TBW. Most of these reductions are partially attributed to reduced FM and TBW. The reductions in these parameters appear to reverse after Ramadan

Prevalence and determinants of sex-specific dietary supplement use in a greek cohort

We describe the profile of dietary supplement use and its correlates in the Epirus Health Study cohort, which consists of 1237 adults (60.5% women) residing in urban north-west Greece. The association between dietary supplement use and demographic characteristics, lifestyle behaviors, personal medical history and clinical measurements was assessed using logistic regression models, separately for women and men. The overall prevalence of dietary supplement use was 31.4%, and it was higher in women (37.3%) compared to men (22.4%; p-value = 4.2−08). Based on multivariable logistic regression models, dietary supplement use in women was associated with age (positively until middle-age and slightly negatively afterwards), the presence of a chronic health condition (OR = 1.71; 95% CI, 1.18–2.46), lost/removed teeth (OR = 0.52; 95% CI, 0.35–0.78) and diastolic blood pressure (OR per 5 mmHg increase =0.84; 95% CI, 0.73–0.96); body mass index and worse general health status were borderline inversely associated. In men, dietary supplement use was positively associated with being employed (OR = 2.53; 95% CI, 1.21–5.29). A considerable proportion of our sample used dietary supplements, and the associated factors differed between women and men

Systematic review of Mendelian randomization studies on risk of cancer

Abstract Background We aimed to map and describe the current state of Mendelian randomization (MR) literature on cancer risk and to identify associations supported by robust evidence. Methods We searched PubMed and Scopus up to 06/10/2020 for MR studies investigating the association of any genetically predicted risk factor with cancer risk. We categorized the reported associations based on a priori designed levels of evidence supporting a causal association into four categories, namely robust, probable, suggestive, and insufficient, based on the significance and concordance of the main MR analysis results and at least one of the MR-Egger, weighed median, MRPRESSO, and multivariable MR analyses. Associations not presenting any of the aforementioned sensitivity analyses were not graded. Results We included 190 publications reporting on 4667 MR analyses. Most analyses (3200; 68.6%) were not accompanied by any of the assessed sensitivity analyses. Of the 1467 evaluable analyses, 87 (5.9%) were supported by robust, 275 (18.7%) by probable, and 89 (6.1%) by suggestive evidence. The most prominent robust associations were observed for anthropometric indices with risk of breast, kidney, and endometrial cancers; circulating telomere length with risk of kidney, lung, osteosarcoma, skin, thyroid, and hematological cancers; sex steroid hormones and risk of breast and endometrial cancer; and lipids with risk of breast, endometrial, and ovarian cancer. Conclusions Despite the large amount of research on genetically predicted risk factors for cancer risk, limited associations are supported by robust evidence for causality. Most associations did not present a MR sensitivity analysis and were thus non-evaluable. Future research should focus on more thorough assessment of sensitivity MR analyses and on more transparent reporting. </jats:sec